check , title change

reddit_dataset_loader.py → Pill-Ideologies-New-Test.py

@@ -20,6 +20,7 @@ reddit posts dataset."""
 import csv
 import json
 import os
+import pandas as pd
 
 import datasets
 
@@ -217,6 +218,40 @@ class SubRedditPosts(datasets.GeneratorBasedBuilder):
  "date": data["date"],
  }
 
+ # # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+ # def _generate_examples(self, filepath, split):
+ # # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+ # # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+ # print(filepath, "is the filepath")
+ # with open(filepath, encoding="utf-8") as f:
+ # print(f, "is the file")
+ # for key, row in enumerate(f):
+ # data = json.loads(row)
+ # print(data, "is the data")
+ # if self.config.name == "first_domain":
+ # # Yields examples as (key, example) tuples
+ # yield key, {
+ # "subreddit": data["subreddit"],
+ # "id": data["id"],
+ # "title": data["title"],
+ # "text": data["text"],
+ # "url": data["url"],
+ # "score": data["score"],
+ # "author": data["author"],
+ # "date": data["date"],
+ # }
+ # else:
+ # yield key, {
+ # "subreddit": data["subreddit"],
+ # "id": data["id"],
+ # "title": data["title"],
+ # "text": data["text"],
+ # "url": data["url"],
+ # "score": data["score"],
+ # "author": data["author"],
+ # "date": data["date"],
+ # }
+
  # # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
  # def _generate_examples(self, filepath, split):
  # # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.

reddit_dataset_load.py

@@ -0,0 +1,262 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+# TODO: Address all TODOs and remove all explanatory comments
+
+"""This script's purpose is to re-define the datset loading functions to better suit this specific
+reddit posts dataset."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+# TODO: Add BibTeX citation
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {Pill Ideologies Subreddits Dataset},
+author={Eric Rios},
+year={2024}
+source = {reddit.com}
+}
+
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is designed to aid research in the ongoing study of the pill ideologies subreddits, 
+which have risen in response to the clashes between traditional gender roles and the rise of fourth wave feminism.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://huggingface.co/datasets/steamcyclone/Pill-Ideologies-New-Test"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = "Creative Commons" # cc
+
+# TODO: Add link to the official dataset URLs here
+# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URLS = {
+ "train": "https://huggingface.co/datasets/steamcyclone/Pill-Ideologies-New-Test/blob/main/reddit_posts_fm.csv",
+ "dev": "https://huggingface.co/datasets/steamcyclone/Pill-Ideologies-New-Test/blob/main/reddit_posts_fm.csv",
+}
+
+
+# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
+class SubRedditPosts(datasets.GeneratorBasedBuilder):
+ """This dataset contains data from the pill ideologies subreddits and the feminism subreddit.
+
+ It has the subreddit,post_id, title, text, url, score, author, and date.
+
+ It was fully scraped on February 3rd, 2024."""
+
+ VERSION = datasets.Version("1.1.0")
+
+ # This is an example of a dataset with multiple configurations.
+ # If you don't want/need to define several sub-sets in your dataset,
+ # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
+
+ # If you need to make complex sub-parts in the datasets with configurable options
+ # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
+ # BUILDER_CONFIG_CLASS = MyBuilderConfig
+
+ # You will be able to load one or the other configurations in the following list with
+ # data = datasets.load_dataset('my_dataset', 'first_domain')
+ # data = datasets.load_dataset('my_dataset', 'second_domain')
+ BUILDER_CONFIGS = [
+ datasets.BuilderConfig(
+ name="train",
+ version=VERSION,
+ description="This part of my dataset covers a first domain",
+ ),
+ datasets.BuilderConfig(
+ name="dev",
+ version=VERSION,
+ description="This part of my dataset covers a second domain",
+ ),
+ ]
+
+ DEFAULT_CONFIG_NAME = "first_domain" # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+ def show_me():
+
+ return _DESCRIPTION
+
+ def _info(self):
+ # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
+ # This is the name of the configuration selected in BUILDER_CONFIGS above
+ features = datasets.Features(
+ {
+ "subreddit": datasets.Value("string"),
+ "id": datasets.Value("string"),
+ "title": datasets.Value("string"),
+ "text": datasets.Value("string"),
+ "url": datasets.Value("string"),
+ "score": datasets.Value("int64"),
+ "author": datasets.Value("string"),
+ "date": datasets.Value("string"),
+ # These are the features of your dataset like images, labels ...
+ }
+ )
+
+ return datasets.DatasetInfo(
+ # This is the description that will appear on the datasets page.
+ description=_DESCRIPTION,
+ # This defines the different columns of the dataset and their types
+ features=features, # Here we define them above because they are different between the two configurations
+ # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+ # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+ # supervised_keys=("sentence", "label"),
+ # Homepage of the dataset for documentation
+ supervised_keys=None,
+ homepage=_HOMEPAGE,
+ # License for the dataset if available
+ license=_LICENSE,
+ # Citation for the dataset
+ citation=_CITATION,
+ )
+
+ def _split_generators(self, dl_manager):
+ # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+ # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+ # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+ # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+ # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+ urls = _URLS[self.config.name]
+ data_dir = dl_manager.download_and_extract(urls)
+ print(data_dir, "is the data_dir")
+ return [
+ datasets.SplitGenerator(
+ name=datasets.Split.TRAIN,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, "train.jsonl"),
+ "split": "train",
+ },
+ ),
+ datasets.SplitGenerator(
+ name=datasets.Split.VALIDATION,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, "dev.jsonl"),
+ "split": "dev",
+ },
+ ),
+ datasets.SplitGenerator(
+ name=datasets.Split.TEST,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "filepath": os.path.join(data_dir, "test.jsonl"),
+ "split": "test",
+ },
+ ),
+ ]
+
+ # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+ def _generate_examples(self, filepath, split):
+ # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+ # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+ print(filepath, "is the filepath")
+ with open(filepath, encoding="utf-8") as f:
+ print(f, "is the file")
+ for key, row in enumerate(f):
+ data = json.loads(row)
+ print(data, "is the data")
+ if self.config.name == "first_domain":
+ # Yields examples as (key, example) tuples
+ yield key, {
+ "subreddit": data["subreddit"],
+ "id": data["id"],
+ "title": data["title"],
+ "text": data["text"],
+ "url": data["url"],
+ "score": data["score"],
+ "author": data["author"],
+ "date": data["date"],
+ }
+ else:
+ yield key, {
+ "subreddit": data["subreddit"],
+ "id": data["id"],
+ "title": data["title"],
+ "text": data["text"],
+ "url": data["url"],
+ "score": data["score"],
+ "author": data["author"],
+ "date": data["date"],
+ }
+
+ # # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+ # def _generate_examples(self, filepath, split):
+ # # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+ # # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+ # print(filepath, "is the filepath")
+ # with open(filepath, encoding="utf-8") as f:
+ # print(f, "is the file")
+ # for key, row in enumerate(f):
+ # data = json.loads(row)
+ # print(data, "is the data")
+ # if self.config.name == "first_domain":
+ # # Yields examples as (key, example) tuples
+ # yield key, {
+ # "subreddit": data["subreddit"],
+ # "id": data["id"],
+ # "title": data["title"],
+ # "text": data["text"],
+ # "url": data["url"],
+ # "score": data["score"],
+ # "author": data["author"],
+ # "date": data["date"],
+ # }
+ # else:
+ # yield key, {
+ # "subreddit": data["subreddit"],
+ # "id": data["id"],
+ # "title": data["title"],
+ # "text": data["text"],
+ # "url": data["url"],
+ # "score": data["score"],
+ # "author": data["author"],
+ # "date": data["date"],
+ # }
+
+ # # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+ # def _generate_examples(self, filepath, split):
+ # # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+ # # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+
+ # with open(filepath, encoding="utf-8") as f:
+ # for key, row in enumerate(f):
+ # data = json.loads(row)
+ # if self.config.name == "first_domain":
+ # # Yields examples as (key, example) tuples
+ # yield key, {
+ # "sentence": data["sentence"],
+ # "option1": data["option1"],
+ # "answer": "" if split == "test" else data["answer"],
+ # }
+ # else:
+ # yield key, {
+ # "sentence": data["sentence"],
+ # "option2": data["option2"],
+ # "second_domain_answer": (
+ # "" if split == "test" else data["second_domain_answer"]
+ # ),
+ # }