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"]
+    #                     ),
+    #                 }