import csv
import json
import os
from datasets import GeneratorBasedBuilder, Features, Value, Sequence, SplitGenerator, BuilderConfig, DatasetInfo, Split, Image
import logging
import pandas as pd
from typing import Dict

CITATION = ""
_DESCRIPTION = "" 
_HOMEPAGE = "https://huggingface.co/datasets/SarcasmNet/self-annotated_reddit_climate_comment"
_LICENSE = "MIT"

_URL = "https://github.com/catherine-ywang/Reddit-Climate-Environment-Sarcasm-Self-Annotated-Data/raw/main/self_annotated_comments.csv"

class NewDataset(GeneratorBasedBuilder):
    def _info(self):
        return DatasetInfo(
            description=_DESCRIPTION,
            features=Features({
                "id": Value("string"),
                "post_title": Value("string"),
                "post_author": Value("string"),
                "post_body": Value("string"),
                "post_url": Value("string"),
                "post_pic": Image(),
                "subreddit": Value("string"),
                "post_timestamp": Value("string"),
                "post_upvotes": Value("int32"),
                "post_permalink": Value("string"),
                "comments": Sequence({
                    "CommentID": Value("string"),
                    "CommentAuthor": Value("string"),
                    "CommentBody": Value("string"),
                    "CommentTimestamp": Value("string"),
                    "CommentUpvotes": Value("int32"),
                    "CommentPermalink": Value("string"),
                    "Label": Value("int32")
                })
            }),
            homepage=_HOMEPAGE,
        )
    def _split_generators(self, dl_manager):
        return [SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": dl_manager.download(_URL)})]
        
    def _generate_examples(self, filepath):
        df = pd.read_csv(filepath)
        for column in df.columns:
            df[column] = df[column].replace({pd.NA: None})
        # Group the DataFrame by post ID
        grouped_df = df.groupby('PostID')

        for post_id, group in grouped_df:
            post_data = group.iloc[0]  # Get the data for the post

            post_title = post_data['PostTitle']
            post_author = post_data['PostAuthor']
            post_body = post_data['PostBody']
            post_url = post_data['PostUrl']
            post_pic = post_data['PostPic']
            subreddit = post_data['Subreddit']
            post_timestamp = post_data['PostTimestamp']
            post_upvotes = post_data['PostUpvotes']
            post_permalink = post_data['PostPermalink']

            comments = []

            # Iterate over each unique comment ID
            for comment_id in group['CommentID'].unique():
                comment_data = group[group['CommentID'] == comment_id].iloc[0]

                comment_author = comment_data['CommentAuthor']
                comment_body = comment_data['CommentBody']
                comment_timestamp = comment_data['CommentTimestamp']
                comment_upvotes = comment_data['CommentUpvotes']
                comment_permalink = comment_data['CommentPermalink']
                comment_label = comment_data['Label']

                # Add comment with its replies to the list
                comment = {
                    "CommentID": comment_id,
                    "CommentAuthor": comment_author,
                    "CommentBody": comment_body,
                    "CommentTimestamp": comment_timestamp,
                    "CommentUpvotes": comment_upvotes,
                    "CommentPermalink": comment_permalink,
                    "Label": comment_label
                }
                comments.append(comment)
            
            example = {
                "id": post_id,
                "post_title": post_title,
                "post_author": post_author,
                "post_body": post_body,
                "post_url": post_url,
                "post_pic": post_pic,
                "subreddit": subreddit,
                "post_timestamp": post_timestamp,
                "post_upvotes": post_upvotes,
                "post_permalink": post_permalink,
                "comments": comments
            }

            yield post_id, example