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Upload 3 files
Browse files- app.py +59 -0
- model.py +120 -0
- requirements.txt +565 -0
app.py
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# -*- coding: utf-8 -*-
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"""app.ipynb
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Automatically generated by Colab.
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Original file is located at
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https://colab.research.google.com/drive/1lKXL4Cdum5DiSbczUsadXc0F8j46NM_m
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# in the name of **allah**
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"""
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import gradio as gr
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from model import process_sentence, process_file # ایمپورت توابع پردازش از model.py
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# تابع اصلی که ورودی متن و فایل را پردازش میکند
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def analyze_text_and_file(input_text, file):
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output_text = ""
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if input_text:
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output_text = process_sentence(input_text) # پردازش متن
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file_output = None
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if file:
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file_output = process_file(file) # پردازش فایل
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return output_text, file_output
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# رابط کاربری Gradio
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interface = gr.Interface(
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fn=analyze_text_and_file,
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inputs=[
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gr.Textbox(lines=3, placeholder="Enter Persian text to process...", label="Text Input"),
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gr.File(label="Upload CSV File"),
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],
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outputs=[
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gr.Textbox(label="Processed Text"),
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gr.HTML(label="File Processing Result"),
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],
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title="Persian Text Processor",
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description="Process Persian text or upload a CSV file with a 'Comment' column.",
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css="""
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.gradio-container {
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background-color: #000000;
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color: #FFFFFF;
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}
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.gr-button {
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background-color: #FF5733;
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color: white;
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}
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.gr-textbox input {
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background-color: #333333;
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color: white;
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}
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.gr-button:hover {
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background-color: #FF4500;
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}
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"""
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)
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interface.launch(share=True, debug=True, inline=False)
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model.py
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# -*- coding: utf-8 -*-
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"""model.ipynb
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Automatically generated by Colab.
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Original file is located at
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https://colab.research.google.com/drive/1lKXL4Cdum5DiSbczUsadXc0F8j46NM_m
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# in the name of **allah**
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"""
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import torch
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from transformers import AutoTokenizer, BertForSequenceClassification
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from datasets import Dataset
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import pandas as pd
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import re
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from hazm import Normalizer, Lemmatizer, word_tokenize, stopwords_list
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# Initialize Hazm components
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normalizer = Normalizer()
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lemmatizer = Lemmatizer()
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stopwords = stopwords_list()
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# Load the BERT model for sentiment analysis
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dataset = Dataset.from_pandas(pd.DataFrame({"Comment": []}))
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tokenizer = AutoTokenizer.from_pretrained("HooshvareLab/bert-fa-base-uncased")
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model = BertForSequenceClassification.from_pretrained("HooshvareLab/bert-fa-base-uncased", num_labels=3)
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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# Tokenization function for sentiment analysis
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def tokenize_function(examples):
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return tokenizer(examples["Comment"], padding="max_length", truncation=True, max_length=256, return_tensors='pt')
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# Sentiment prediction function
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def predict_sentiment(batch):
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input_ids = torch.tensor(batch['input_ids']).to(device)
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attention_mask = torch.tensor(batch['attention_mask']).to(device)
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with torch.no_grad():
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outputs = model(input_ids=input_ids, attention_mask=attention_mask)
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predictions = torch.argmax(outputs.logits, dim=-1)
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return {'sentiment': predictions.cpu()}
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# Mapping sentiment labels
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sentiment_labels_en = {0: 'منفی', 1: 'خنثی', 2: 'مثبت'}
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# Adding sentiment prediction to tokenized dataset
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def predict_sentiment_labels(text):
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dataset = Dataset.from_dict({"Comment": [text]})
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tokenized_dataset = dataset.map(tokenize_function, batched=True)
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predicted_sentiments = tokenized_dataset.map(predict_sentiment, batched=True)
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sentiment = predicted_sentiments[0]['sentiment']
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return sentiment_labels_en.get(sentiment, 'نامشخص')
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# Functions from your original code for classifying sentence type and cleaning
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imperative_verbs = [
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'بیا', 'برو', 'بخواب', 'کن', 'باش', 'بذار', 'فراموش کن', 'بخور',
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'بپوش', 'ببخش', 'بنویس', 'دقت کن', 'دست بردار', 'سکوت کن',
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'اجازه بده', 'نکن', 'پیش برو', 'خواب بمان', 'توجه کن', 'خوش آمدید',
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'حواسجمع باش', 'در نظر بگیر', 'بخشید', 'بکش', 'نگذار', 'سعی کن',
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'تلاش کن', 'ببین', 'نرو', 'بگیر', 'بگو', 'شک نکن', 'فکر کن',
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'عادت کن', 'بیانداز', 'حرکت کن', 'شکایت نکن', 'عاشق شو', 'بخند',
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'برگرد', 'بزن', 'آشپزی کن', 'بپذیر', 'شیرینی بپز', 'درس بخوان',
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'کلاس بگذار', 'کمک کن', 'بمان', 'راهنمایی کن', 'لطفا'
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]
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def classify_sentence(sentence):
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sentence = sentence.strip()
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sentence_type = 'خبری'
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if re.search(r'چرا|چطور|کجا|آیا|چه|چی|چند|کدام|کی|چندم|چیست|چیه|چندمین|چجوری|کی|چیست|چگونه|؟', sentence) or sentence.endswith('?'):
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sentence_type = 'پرسشی'
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elif re.search(r'\b(?:' + '|'.join(imperative_verbs) + r')\b', sentence):
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sentence_type = 'امری'
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return sentence_type
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def clean_text(text):
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text = re.sub(r'https://\S+|www\.\S+', '', text)
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text = re.sub(r'[^ا-ی0-9\s#@_؟]', ' ', text)
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text = re.sub(r'\s+', ' ', text).strip()
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words = word_tokenize(text)
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words = [word for word in words if word not in stopwords]
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words = [lemmatizer.lemmatize(word) for word in words]
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return ' '.join(words)
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def process_sentence(sentence):
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cleaned = clean_text(sentence)
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sentence_type = classify_sentence(cleaned)
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sentiment = predict_sentiment_labels(sentence)
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return f"Type: {sentence_type}\nSentiment: {sentiment}\nCleaned Text: {cleaned}"
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# Function to process file
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def process_file(file):
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try:
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df = pd.read_csv(file.name)
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if 'Comment' not in df.columns:
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return "Error: No 'Comment' column found in the file."
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# Process comments
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df['Cleaned_Comment'] = df['Comment'].apply(clean_text)
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df['Type'] = df['Comment'].apply(classify_sentence)
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df['Sentiment'] = df['Comment'].apply(predict_sentiment_labels)
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output_path = "processed_file.csv"
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df.to_csv(output_path, index=False)
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return f"File processed successfully! Download it [here](./{output_path})"
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except Exception as e:
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return str(e)
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requirements.txt
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
absl-py==1.4.0
|
2 |
+
accelerate==1.2.1
|
3 |
+
aiofiles==23.2.1
|
4 |
+
aiohappyeyeballs==2.4.4
|
5 |
+
aiohttp==3.11.10
|
6 |
+
aiosignal==1.3.2
|
7 |
+
alabaster==1.0.0
|
8 |
+
albucore==0.0.19
|
9 |
+
albumentations==1.4.20
|
10 |
+
altair==5.5.0
|
11 |
+
annotated-types==0.7.0
|
12 |
+
anyio==3.7.1
|
13 |
+
argon2-cffi==23.1.0
|
14 |
+
argon2-cffi-bindings==21.2.0
|
15 |
+
array_record==0.5.1
|
16 |
+
arviz==0.20.0
|
17 |
+
astropy==6.1.7
|
18 |
+
astropy-iers-data==0.2024.12.16.0.35.48
|
19 |
+
astunparse==1.6.3
|
20 |
+
async-timeout==4.0.3
|
21 |
+
atpublic==4.1.0
|
22 |
+
attrs==24.3.0
|
23 |
+
audioread==3.0.1
|
24 |
+
autograd==1.7.0
|
25 |
+
babel==2.16.0
|
26 |
+
backcall==0.2.0
|
27 |
+
beautifulsoup4==4.12.3
|
28 |
+
bigframes==1.29.0
|
29 |
+
bigquery-magics==0.4.0
|
30 |
+
bleach==6.2.0
|
31 |
+
blinker==1.9.0
|
32 |
+
blis==0.7.11
|
33 |
+
blosc2==2.7.1
|
34 |
+
bokeh==3.6.2
|
35 |
+
Bottleneck==1.4.2
|
36 |
+
bqplot==0.12.43
|
37 |
+
branca==0.8.1
|
38 |
+
CacheControl==0.14.1
|
39 |
+
cachetools==5.5.0
|
40 |
+
catalogue==2.0.10
|
41 |
+
certifi==2024.12.14
|
42 |
+
cffi==1.17.1
|
43 |
+
chardet==5.2.0
|
44 |
+
charset-normalizer==3.4.0
|
45 |
+
chex==0.1.88
|
46 |
+
clarabel==0.9.0
|
47 |
+
click==8.1.7
|
48 |
+
cloudpathlib==0.20.0
|
49 |
+
cloudpickle==3.1.0
|
50 |
+
cmake==3.31.2
|
51 |
+
cmdstanpy==1.2.5
|
52 |
+
colorcet==3.1.0
|
53 |
+
colorlover==0.3.0
|
54 |
+
colour==0.1.5
|
55 |
+
community==1.0.0b1
|
56 |
+
confection==0.1.5
|
57 |
+
cons==0.4.6
|
58 |
+
contourpy==1.3.1
|
59 |
+
cryptography==43.0.3
|
60 |
+
cuda-python==12.2.1
|
61 |
+
cudf-cu12 @ https://pypi.nvidia.com/cudf-cu12/cudf_cu12-24.10.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
|
62 |
+
cufflinks==0.17.3
|
63 |
+
cupy-cuda12x==12.2.0
|
64 |
+
cvxopt==1.3.2
|
65 |
+
cvxpy==1.6.0
|
66 |
+
cycler==0.12.1
|
67 |
+
cymem==2.0.10
|
68 |
+
Cython==3.0.11
|
69 |
+
dask==2024.10.0
|
70 |
+
datascience==0.17.6
|
71 |
+
datasets==3.2.0
|
72 |
+
db-dtypes==1.3.1
|
73 |
+
dbus-python==1.2.18
|
74 |
+
debugpy==1.8.0
|
75 |
+
decorator==4.4.2
|
76 |
+
defusedxml==0.7.1
|
77 |
+
Deprecated==1.2.15
|
78 |
+
diffusers==0.31.0
|
79 |
+
dill==0.3.8
|
80 |
+
distro==1.9.0
|
81 |
+
dlib==19.24.2
|
82 |
+
dm-tree==0.1.8
|
83 |
+
docker-pycreds==0.4.0
|
84 |
+
docstring_parser==0.16
|
85 |
+
docutils==0.21.2
|
86 |
+
dopamine_rl==4.1.0
|
87 |
+
duckdb==1.1.3
|
88 |
+
earthengine-api==1.4.3
|
89 |
+
easydict==1.13
|
90 |
+
editdistance==0.8.1
|
91 |
+
eerepr==0.0.4
|
92 |
+
einops==0.8.0
|
93 |
+
en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl#sha256=86cc141f63942d4b2c5fcee06630fd6f904788d2f0ab005cce45aadb8fb73889
|
94 |
+
entrypoints==0.4
|
95 |
+
et_xmlfile==2.0.0
|
96 |
+
etils==1.11.0
|
97 |
+
etuples==0.3.9
|
98 |
+
eval_type_backport==0.2.0
|
99 |
+
exceptiongroup==1.2.2
|
100 |
+
fastai==2.7.18
|
101 |
+
fastapi==0.115.6
|
102 |
+
fastcore==1.7.27
|
103 |
+
fastdownload==0.0.7
|
104 |
+
fastjsonschema==2.21.1
|
105 |
+
fastprogress==1.0.3
|
106 |
+
fastrlock==0.8.3
|
107 |
+
fasttext-wheel==0.9.2
|
108 |
+
ffmpy==0.5.0
|
109 |
+
filelock==3.16.1
|
110 |
+
firebase-admin==6.6.0
|
111 |
+
flashtext==2.7
|
112 |
+
Flask==3.1.0
|
113 |
+
flatbuffers==24.3.25
|
114 |
+
flax==0.8.5
|
115 |
+
folium==0.19.2
|
116 |
+
fonttools==4.55.3
|
117 |
+
frozendict==2.4.6
|
118 |
+
frozenlist==1.5.0
|
119 |
+
fsspec==2024.9.0
|
120 |
+
future==1.0.0
|
121 |
+
gast==0.6.0
|
122 |
+
gcsfs==2024.10.0
|
123 |
+
GDAL==3.6.4
|
124 |
+
gdown==5.2.0
|
125 |
+
geemap==0.35.1
|
126 |
+
gensim==4.3.3
|
127 |
+
geocoder==1.38.1
|
128 |
+
geographiclib==2.0
|
129 |
+
geopandas==1.0.1
|
130 |
+
geopy==2.4.1
|
131 |
+
gin-config==0.5.0
|
132 |
+
gitdb==4.0.11
|
133 |
+
GitPython==3.1.43
|
134 |
+
glob2==0.7
|
135 |
+
google==2.0.3
|
136 |
+
google-ai-generativelanguage==0.6.10
|
137 |
+
google-api-core==2.19.2
|
138 |
+
google-api-python-client==2.155.0
|
139 |
+
google-auth==2.27.0
|
140 |
+
google-auth-httplib2==0.2.0
|
141 |
+
google-auth-oauthlib==1.2.1
|
142 |
+
google-cloud-aiplatform==1.74.0
|
143 |
+
google-cloud-bigquery==3.25.0
|
144 |
+
google-cloud-bigquery-connection==1.17.0
|
145 |
+
google-cloud-bigquery-storage==2.27.0
|
146 |
+
google-cloud-bigtable==2.27.0
|
147 |
+
google-cloud-core==2.4.1
|
148 |
+
google-cloud-datastore==2.20.2
|
149 |
+
google-cloud-firestore==2.19.0
|
150 |
+
google-cloud-functions==1.19.0
|
151 |
+
google-cloud-iam==2.17.0
|
152 |
+
google-cloud-language==2.16.0
|
153 |
+
google-cloud-pubsub==2.27.1
|
154 |
+
google-cloud-resource-manager==1.14.0
|
155 |
+
google-cloud-storage==2.19.0
|
156 |
+
google-cloud-translate==3.19.0
|
157 |
+
google-colab @ file:///colabtools/dist/google_colab-1.0.0.tar.gz
|
158 |
+
google-crc32c==1.6.0
|
159 |
+
google-genai==0.3.0
|
160 |
+
google-generativeai==0.8.3
|
161 |
+
google-pasta==0.2.0
|
162 |
+
google-resumable-media==2.7.2
|
163 |
+
googleapis-common-protos==1.66.0
|
164 |
+
googledrivedownloader==0.4
|
165 |
+
gradio==5.9.1
|
166 |
+
gradio_client==1.5.2
|
167 |
+
graphviz==0.20.3
|
168 |
+
greenlet==3.1.1
|
169 |
+
grpc-google-iam-v1==0.13.1
|
170 |
+
grpcio==1.68.1
|
171 |
+
grpcio-status==1.62.3
|
172 |
+
gspread==6.0.2
|
173 |
+
gspread-dataframe==3.3.1
|
174 |
+
gym==0.25.2
|
175 |
+
gym-notices==0.0.8
|
176 |
+
h11==0.14.0
|
177 |
+
h5netcdf==1.4.1
|
178 |
+
h5py==3.12.1
|
179 |
+
hazm==0.10.0
|
180 |
+
holidays==0.63
|
181 |
+
holoviews==1.20.0
|
182 |
+
html5lib==1.1
|
183 |
+
httpcore==1.0.7
|
184 |
+
httpimport==1.4.0
|
185 |
+
httplib2==0.22.0
|
186 |
+
httpx==0.28.1
|
187 |
+
huggingface-hub==0.27.0
|
188 |
+
humanize==4.11.0
|
189 |
+
hyperopt==0.2.7
|
190 |
+
ibis-framework==9.2.0
|
191 |
+
idna==3.10
|
192 |
+
imageio==2.36.1
|
193 |
+
imageio-ffmpeg==0.5.1
|
194 |
+
imagesize==1.4.1
|
195 |
+
imbalanced-learn==0.12.4
|
196 |
+
imgaug==0.4.0
|
197 |
+
immutabledict==4.2.1
|
198 |
+
importlib_metadata==8.5.0
|
199 |
+
importlib_resources==6.4.5
|
200 |
+
imutils==0.5.4
|
201 |
+
inflect==7.4.0
|
202 |
+
iniconfig==2.0.0
|
203 |
+
intel-cmplr-lib-ur==2025.0.4
|
204 |
+
intel-openmp==2025.0.4
|
205 |
+
ipyevents==2.0.2
|
206 |
+
ipyfilechooser==0.6.0
|
207 |
+
ipykernel==5.5.6
|
208 |
+
ipyleaflet==0.19.2
|
209 |
+
ipyparallel==8.8.0
|
210 |
+
ipython==7.34.0
|
211 |
+
ipython-genutils==0.2.0
|
212 |
+
ipython-sql==0.5.0
|
213 |
+
ipytree==0.2.2
|
214 |
+
ipywidgets==7.7.1
|
215 |
+
itsdangerous==2.2.0
|
216 |
+
jax==0.4.33
|
217 |
+
jax-cuda12-pjrt==0.4.33
|
218 |
+
jax-cuda12-plugin==0.4.33
|
219 |
+
jaxlib==0.4.33
|
220 |
+
jedi==0.19.2
|
221 |
+
jeepney==0.7.1
|
222 |
+
jellyfish==1.1.0
|
223 |
+
jieba==0.42.1
|
224 |
+
Jinja2==3.1.4
|
225 |
+
jiter==0.8.2
|
226 |
+
joblib==1.4.2
|
227 |
+
jsonpatch==1.33
|
228 |
+
jsonpickle==4.0.1
|
229 |
+
jsonpointer==3.0.0
|
230 |
+
jsonschema==4.23.0
|
231 |
+
jsonschema-specifications==2024.10.1
|
232 |
+
jupyter-client==6.1.12
|
233 |
+
jupyter-console==6.1.0
|
234 |
+
jupyter-leaflet==0.19.2
|
235 |
+
jupyter-server==1.24.0
|
236 |
+
jupyter_core==5.7.2
|
237 |
+
jupyterlab_pygments==0.3.0
|
238 |
+
jupyterlab_widgets==3.0.13
|
239 |
+
kaggle==1.6.17
|
240 |
+
kagglehub==0.3.5
|
241 |
+
keras==3.5.0
|
242 |
+
keyring==23.5.0
|
243 |
+
kiwisolver==1.4.7
|
244 |
+
langchain==0.3.12
|
245 |
+
langchain-core==0.3.25
|
246 |
+
langchain-text-splitters==0.3.3
|
247 |
+
langcodes==3.5.0
|
248 |
+
langsmith==0.2.3
|
249 |
+
language_data==1.3.0
|
250 |
+
launchpadlib==1.10.16
|
251 |
+
lazr.restfulclient==0.14.4
|
252 |
+
lazr.uri==1.0.6
|
253 |
+
lazy_loader==0.4
|
254 |
+
libclang==18.1.1
|
255 |
+
libcudf-cu12 @ https://pypi.nvidia.com/libcudf-cu12/libcudf_cu12-24.10.1-py3-none-manylinux_2_28_x86_64.whl
|
256 |
+
librosa==0.10.2.post1
|
257 |
+
lightgbm==4.5.0
|
258 |
+
linkify-it-py==2.0.3
|
259 |
+
llvmlite==0.43.0
|
260 |
+
locket==1.0.0
|
261 |
+
logical-unification==0.4.6
|
262 |
+
lxml==5.3.0
|
263 |
+
marisa-trie==1.2.1
|
264 |
+
Markdown==3.7
|
265 |
+
markdown-it-py==3.0.0
|
266 |
+
MarkupSafe==2.1.5
|
267 |
+
matplotlib==3.8.0
|
268 |
+
matplotlib-inline==0.1.7
|
269 |
+
matplotlib-venn==1.1.1
|
270 |
+
mdit-py-plugins==0.4.2
|
271 |
+
mdurl==0.1.2
|
272 |
+
miniKanren==1.0.3
|
273 |
+
missingno==0.5.2
|
274 |
+
mistune==3.0.2
|
275 |
+
mizani==0.13.1
|
276 |
+
mkl==2025.0.1
|
277 |
+
ml-dtypes==0.4.1
|
278 |
+
mlxtend==0.23.3
|
279 |
+
more-itertools==10.5.0
|
280 |
+
moviepy==1.0.3
|
281 |
+
mpmath==1.3.0
|
282 |
+
msgpack==1.1.0
|
283 |
+
multidict==6.1.0
|
284 |
+
multipledispatch==1.0.0
|
285 |
+
multiprocess==0.70.16
|
286 |
+
multitasking==0.0.11
|
287 |
+
murmurhash==1.0.11
|
288 |
+
music21==9.3.0
|
289 |
+
namex==0.0.8
|
290 |
+
narwhals==1.18.4
|
291 |
+
natsort==8.4.0
|
292 |
+
nbclassic==1.1.0
|
293 |
+
nbclient==0.10.1
|
294 |
+
nbconvert==7.16.4
|
295 |
+
nbformat==5.10.4
|
296 |
+
ndindex==1.9.2
|
297 |
+
nest-asyncio==1.6.0
|
298 |
+
networkx==3.4.2
|
299 |
+
nibabel==5.3.2
|
300 |
+
nltk==3.9.1
|
301 |
+
notebook==6.5.5
|
302 |
+
notebook_shim==0.2.4
|
303 |
+
numba==0.60.0
|
304 |
+
numexpr==2.10.2
|
305 |
+
numpy==1.24.3
|
306 |
+
nvidia-cublas-cu12==12.6.4.1
|
307 |
+
nvidia-cuda-cupti-cu12==12.6.80
|
308 |
+
nvidia-cuda-nvcc-cu12==12.6.85
|
309 |
+
nvidia-cuda-runtime-cu12==12.6.77
|
310 |
+
nvidia-cudnn-cu12==9.6.0.74
|
311 |
+
nvidia-cufft-cu12==11.3.0.4
|
312 |
+
nvidia-curand-cu12==10.3.7.77
|
313 |
+
nvidia-cusolver-cu12==11.7.1.2
|
314 |
+
nvidia-cusparse-cu12==12.5.4.2
|
315 |
+
nvidia-nccl-cu12==2.23.4
|
316 |
+
nvidia-nvjitlink-cu12==12.6.85
|
317 |
+
nvtx==0.2.10
|
318 |
+
nx-cugraph-cu12 @ https://pypi.nvidia.com/nx-cugraph-cu12/nx_cugraph_cu12-24.10.0-py3-none-any.whl
|
319 |
+
oauth2client==4.1.3
|
320 |
+
oauthlib==3.2.2
|
321 |
+
openai==1.57.4
|
322 |
+
opencv-contrib-python==4.10.0.84
|
323 |
+
opencv-python==4.10.0.84
|
324 |
+
opencv-python-headless==4.10.0.84
|
325 |
+
openpyxl==3.1.5
|
326 |
+
opentelemetry-api==1.29.0
|
327 |
+
opentelemetry-sdk==1.29.0
|
328 |
+
opentelemetry-semantic-conventions==0.50b0
|
329 |
+
opt_einsum==3.4.0
|
330 |
+
optax==0.2.4
|
331 |
+
optree==0.13.1
|
332 |
+
orbax-checkpoint==0.6.4
|
333 |
+
orjson==3.10.12
|
334 |
+
osqp==0.6.7.post3
|
335 |
+
packaging==24.2
|
336 |
+
pandas==2.2.2
|
337 |
+
pandas-datareader==0.10.0
|
338 |
+
pandas-gbq==0.25.0
|
339 |
+
pandas-stubs==2.2.2.240909
|
340 |
+
pandocfilters==1.5.1
|
341 |
+
panel==1.5.4
|
342 |
+
param==2.2.0
|
343 |
+
parso==0.8.4
|
344 |
+
parsy==2.1
|
345 |
+
partd==1.4.2
|
346 |
+
pathlib==1.0.1
|
347 |
+
patsy==1.0.1
|
348 |
+
peewee==3.17.8
|
349 |
+
peft==0.14.0
|
350 |
+
pexpect==4.9.0
|
351 |
+
pickleshare==0.7.5
|
352 |
+
pillow==11.0.0
|
353 |
+
platformdirs==4.3.6
|
354 |
+
plotly==5.24.1
|
355 |
+
plotnine==0.14.4
|
356 |
+
pluggy==1.5.0
|
357 |
+
ply==3.11
|
358 |
+
polars==1.9.0
|
359 |
+
pooch==1.8.2
|
360 |
+
portpicker==1.5.2
|
361 |
+
preshed==3.0.9
|
362 |
+
prettytable==3.12.0
|
363 |
+
proglog==0.1.10
|
364 |
+
progressbar2==4.5.0
|
365 |
+
prometheus_client==0.21.1
|
366 |
+
promise==2.3
|
367 |
+
prompt_toolkit==3.0.48
|
368 |
+
propcache==0.2.1
|
369 |
+
prophet==1.1.6
|
370 |
+
proto-plus==1.25.0
|
371 |
+
protobuf==4.25.5
|
372 |
+
psutil==5.9.5
|
373 |
+
psycopg2==2.9.10
|
374 |
+
ptyprocess==0.7.0
|
375 |
+
py-cpuinfo==9.0.0
|
376 |
+
py4j==0.10.9.7
|
377 |
+
pyarrow==17.0.0
|
378 |
+
pyasn1==0.6.1
|
379 |
+
pyasn1_modules==0.4.1
|
380 |
+
pybind11==2.13.6
|
381 |
+
pycocotools==2.0.8
|
382 |
+
pycparser==2.22
|
383 |
+
pydantic==2.10.3
|
384 |
+
pydantic_core==2.27.1
|
385 |
+
pydata-google-auth==1.9.0
|
386 |
+
pydot==3.0.3
|
387 |
+
pydotplus==2.0.2
|
388 |
+
PyDrive==1.3.1
|
389 |
+
PyDrive2==1.21.3
|
390 |
+
pydub==0.25.1
|
391 |
+
pyerfa==2.0.1.5
|
392 |
+
pygame==2.6.1
|
393 |
+
pygit2==1.16.0
|
394 |
+
Pygments==2.18.0
|
395 |
+
PyGObject==3.42.1
|
396 |
+
PyJWT==2.10.1
|
397 |
+
pylibcudf-cu12 @ https://pypi.nvidia.com/pylibcudf-cu12/pylibcudf_cu12-24.10.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
|
398 |
+
pylibcugraph-cu12==24.10.0
|
399 |
+
pylibraft-cu12==24.10.0
|
400 |
+
pymc==5.19.1
|
401 |
+
pymystem3==0.2.0
|
402 |
+
pynvjitlink-cu12==0.4.0
|
403 |
+
pyogrio==0.10.0
|
404 |
+
Pyomo==6.8.2
|
405 |
+
PyOpenGL==3.1.7
|
406 |
+
pyOpenSSL==24.2.1
|
407 |
+
pyparsing==3.2.0
|
408 |
+
pyperclip==1.9.0
|
409 |
+
pyproj==3.7.0
|
410 |
+
pyshp==2.3.1
|
411 |
+
PySocks==1.7.1
|
412 |
+
pyspark==3.5.3
|
413 |
+
pytensor==2.26.4
|
414 |
+
pytest==8.3.4
|
415 |
+
python-apt==0.0.0
|
416 |
+
python-box==7.3.0
|
417 |
+
python-crfsuite==0.9.11
|
418 |
+
python-dateutil==2.8.2
|
419 |
+
python-louvain==0.16
|
420 |
+
python-multipart==0.0.20
|
421 |
+
python-slugify==8.0.4
|
422 |
+
python-utils==3.9.1
|
423 |
+
pytz==2024.2
|
424 |
+
pyviz_comms==3.0.3
|
425 |
+
PyYAML==6.0.2
|
426 |
+
pyzmq==24.0.1
|
427 |
+
qdldl==0.1.7.post4
|
428 |
+
ratelim==0.1.6
|
429 |
+
referencing==0.35.1
|
430 |
+
regex==2024.11.6
|
431 |
+
requests==2.32.3
|
432 |
+
requests-oauthlib==1.3.1
|
433 |
+
requests-toolbelt==1.0.0
|
434 |
+
requirements-parser==0.9.0
|
435 |
+
rich==13.9.4
|
436 |
+
rmm-cu12==24.10.0
|
437 |
+
rpds-py==0.22.3
|
438 |
+
rpy2==3.4.2
|
439 |
+
rsa==4.9
|
440 |
+
ruff==0.8.4
|
441 |
+
safehttpx==0.1.6
|
442 |
+
safetensors==0.4.5
|
443 |
+
scikit-image==0.25.0
|
444 |
+
scikit-learn==1.6.0
|
445 |
+
scipy==1.13.1
|
446 |
+
scooby==0.10.0
|
447 |
+
scs==3.2.7
|
448 |
+
seaborn==0.13.2
|
449 |
+
SecretStorage==3.3.1
|
450 |
+
semantic-version==2.10.0
|
451 |
+
Send2Trash==1.8.3
|
452 |
+
sentence-transformers==3.3.1
|
453 |
+
sentencepiece==0.2.0
|
454 |
+
sentry-sdk==2.19.2
|
455 |
+
setproctitle==1.3.4
|
456 |
+
shap==0.46.0
|
457 |
+
shapely==2.0.6
|
458 |
+
shellingham==1.5.4
|
459 |
+
simple-parsing==0.1.6
|
460 |
+
six==1.17.0
|
461 |
+
sklearn-pandas==2.2.0
|
462 |
+
slicer==0.0.8
|
463 |
+
smart-open==7.1.0
|
464 |
+
smmap==5.0.1
|
465 |
+
sniffio==1.3.1
|
466 |
+
snowballstemmer==2.2.0
|
467 |
+
soundfile==0.12.1
|
468 |
+
soupsieve==2.6
|
469 |
+
soxr==0.5.0.post1
|
470 |
+
spacy==3.7.5
|
471 |
+
spacy-legacy==3.0.12
|
472 |
+
spacy-loggers==1.0.5
|
473 |
+
Sphinx==8.1.3
|
474 |
+
sphinxcontrib-applehelp==2.0.0
|
475 |
+
sphinxcontrib-devhelp==2.0.0
|
476 |
+
sphinxcontrib-htmlhelp==2.1.0
|
477 |
+
sphinxcontrib-jsmath==1.0.1
|
478 |
+
sphinxcontrib-qthelp==2.0.0
|
479 |
+
sphinxcontrib-serializinghtml==2.0.0
|
480 |
+
SQLAlchemy==2.0.36
|
481 |
+
sqlglot==25.1.0
|
482 |
+
sqlparse==0.5.3
|
483 |
+
srsly==2.5.0
|
484 |
+
stanio==0.5.1
|
485 |
+
starlette==0.41.3
|
486 |
+
statsmodels==0.14.4
|
487 |
+
StrEnum==0.4.15
|
488 |
+
stringzilla==3.11.1
|
489 |
+
sympy==1.13.1
|
490 |
+
tables==3.10.1
|
491 |
+
tabulate==0.9.0
|
492 |
+
tbb==2022.0.0
|
493 |
+
tcmlib==1.2.0
|
494 |
+
tenacity==9.0.0
|
495 |
+
tensorboard==2.17.1
|
496 |
+
tensorboard-data-server==0.7.2
|
497 |
+
tensorflow==2.17.1
|
498 |
+
tensorflow-datasets==4.9.7
|
499 |
+
tensorflow-hub==0.16.1
|
500 |
+
tensorflow-io-gcs-filesystem==0.37.1
|
501 |
+
tensorflow-metadata==1.13.1
|
502 |
+
tensorflow-probability==0.24.0
|
503 |
+
tensorstore==0.1.71
|
504 |
+
termcolor==2.5.0
|
505 |
+
terminado==0.18.1
|
506 |
+
text-unidecode==1.3
|
507 |
+
textblob==0.17.1
|
508 |
+
tf-slim==1.1.0
|
509 |
+
tf_keras==2.17.0
|
510 |
+
thinc==8.2.5
|
511 |
+
threadpoolctl==3.5.0
|
512 |
+
tifffile==2024.12.12
|
513 |
+
timm==1.0.12
|
514 |
+
tinycss2==1.4.0
|
515 |
+
tokenizers==0.21.0
|
516 |
+
toml==0.10.2
|
517 |
+
tomli==2.2.1
|
518 |
+
tomlkit==0.13.2
|
519 |
+
toolz==0.12.1
|
520 |
+
torch @ https://download.pytorch.org/whl/cu121_full/torch-2.5.1%2Bcu121-cp310-cp310-linux_x86_64.whl
|
521 |
+
torchaudio @ https://download.pytorch.org/whl/cu121/torchaudio-2.5.1%2Bcu121-cp310-cp310-linux_x86_64.whl
|
522 |
+
torchsummary==1.5.1
|
523 |
+
torchvision @ https://download.pytorch.org/whl/cu121/torchvision-0.20.1%2Bcu121-cp310-cp310-linux_x86_64.whl
|
524 |
+
tornado==6.3.3
|
525 |
+
tqdm==4.67.1
|
526 |
+
traitlets==5.7.1
|
527 |
+
traittypes==0.2.1
|
528 |
+
transformers==4.47.1
|
529 |
+
tweepy==4.14.0
|
530 |
+
typeguard==4.4.1
|
531 |
+
typer==0.15.1
|
532 |
+
types-pytz==2024.2.0.20241003
|
533 |
+
types-setuptools==75.6.0.20241126
|
534 |
+
typing_extensions==4.12.2
|
535 |
+
tzdata==2024.2
|
536 |
+
tzlocal==5.2
|
537 |
+
uc-micro-py==1.0.3
|
538 |
+
umf==0.9.1
|
539 |
+
uritemplate==4.1.1
|
540 |
+
urllib3==2.2.3
|
541 |
+
uvicorn==0.34.0
|
542 |
+
vega-datasets==0.9.0
|
543 |
+
wadllib==1.3.6
|
544 |
+
wandb==0.19.1
|
545 |
+
wasabi==1.1.3
|
546 |
+
wcwidth==0.2.13
|
547 |
+
weasel==0.4.1
|
548 |
+
webcolors==24.11.1
|
549 |
+
webencodings==0.5.1
|
550 |
+
websocket-client==1.8.0
|
551 |
+
websockets==14.1
|
552 |
+
Werkzeug==3.1.3
|
553 |
+
widgetsnbextension==3.6.10
|
554 |
+
wordcloud==1.9.4
|
555 |
+
wrapt==1.17.0
|
556 |
+
xarray==2024.11.0
|
557 |
+
xarray-einstats==0.8.0
|
558 |
+
xgboost==2.1.3
|
559 |
+
xlrd==2.0.1
|
560 |
+
xxhash==3.5.0
|
561 |
+
xyzservices==2024.9.0
|
562 |
+
yarl==1.18.3
|
563 |
+
yellowbrick==1.5
|
564 |
+
yfinance==0.2.50
|
565 |
+
zipp==3.21.0
|