Update README.md

README.md

@@ -1,3 +1,292 @@
----
-license: unlicense
----
+---
+license: unlicense
+---
+
+## Top comments from subbreddits
+
+I picked the subreddits that were the most popular.  I did not pick NSFW but there is probably some NSFW language in here.
+
+Here are the subreddits:
+
+* AskReddit
+* worldnews
+* todayilearned
+* Music
+* movies
+* science
+* Showerthoughts
+* Jokes
+* space
+* books
+* WritingPrompts
+* tifu
+* wallstreetbets
+* explainlikeimfive
+* askscience
+* history
+* technology
+* relationship_advice
+* relationships
+* Damnthatsinteresting
+* CryptoCurrency
+* television
+* politics
+* Parenting
+* Bitcoin
+* creepy
+* nosleep
+
+## Code to download subredditt's
+
+dl_subbreddits.sh:
+```
+#!/bin/bash
+#
+# Directions:
+#./dl_reddit_comments.sh submissions
+# or
+#./dl_reddit_comments.sh comments
+
+# Check if the argument is provided and valid
+if [ "$#" -ne 1 ] || { [ "$1" != "submissions" ] && [ "$1" != "comments" ]; }; then
+  echo "Usage: $0 <submissions|comments>"
+  exit 1
+fi
+
+# Create the reddit_data folder if it doesn't exist
+mkdir -p reddit_data
+
+# Base URL
+base_url="https://the-eye.eu/redarcs/files/"
+
+# Array of subreddit names
+subreddits=(
+  "AskReddit"
+  "worldnews"
+  "todayilearned"
+  "Music"
+  "movies"
+  "science"
+  "Showerthoughts"
+  "Jokes"
+  "space"
+  "books"
+  "WritingPrompts"
+  "tifu"
+  "wallstreetbets"
+  "explainlikeimfive"
+  "askscience"
+  "history"
+  "technology"
+  "relationship_advice"
+  "relationships"
+  "Damnthatsinteresting"
+  "CryptoCurrency"
+  "television"
+  "politics"
+  "Parenting"
+  "Bitcoin"
+  "creepy"
+  "nosleep"
+)
+
+# Export base_url so it can be used by xargs
+export base_url
+
+# Argument to determine whether to download comments or submissions
+type=$1
+
+# Generate file names based on the argument
+file_names=()
+for subreddit in "${subreddits[@]}"; do
+  file_names+=("${subreddit}_${type}.zst")
+done
+
+# Download each file using wget in parallel
+printf "%s\n" "${file_names[@]}" | xargs -n 1 -P 8 -I {} wget -P reddit_data "${base_url}{}"
+```
+
+## Code to process for top comments
+
+This may need some work. There is some chunking that needed to be done because some of the comment files are very large. 
+
+AskReddit subbreddit was 50gb of comments so processing that to a csv was a bit painful.
+
+```
+import zstandard
+import os
+import json
+import sys
+import csv
+from datetime import datetime
+import logging
+from concurrent.futures import ProcessPoolExecutor
+
+log = logging.getLogger("bot")
+log.setLevel(logging.DEBUG)
+log.addHandler(logging.StreamHandler())
+
+def read_and_decode(reader, chunk_size, max_window_size, previous_chunk=None, bytes_read=0):
+    chunk = reader.read(chunk_size)
+    bytes_read += chunk_size
+    if previous_chunk is not None:
+        chunk = previous_chunk + chunk
+    try:
+        return chunk.decode()
+    except UnicodeDecodeError:
+        if bytes_read > max_window_size:
+            raise UnicodeError(f"Unable to decode frame after reading {bytes_read:,} bytes")
+        log.info(f"Decoding error with {bytes_read:,} bytes, reading another chunk")
+        return read_and_decode(reader, chunk_size, max_window_size, chunk, bytes_read)
+
+def read_lines_zst(file_name):
+    with open(file_name, 'rb') as file_handle:
+        buffer = ''
+        reader = zstandard.ZstdDecompressor(max_window_size=2**31).stream_reader(file_handle)
+        while True:
+            chunk = read_and_decode(reader, 2**27, (2**29) * 2)
+            if not chunk:
+                break
+            lines = (buffer + chunk).split("\n")
+            for line in lines[:-1]:
+                yield line, file_handle.tell()
+            buffer = lines[-1]
+        reader.close()
+
+def process_file(input_file, output_folder):
+    output_file_path = os.path.join(output_folder, os.path.splitext(os.path.basename(input_file))[0] + '.csv')
+    log.info(f"Processing {input_file} to {output_file_path}")
+
+    is_submission = "submission" in input_file
+    if is_submission:
+        fields = ["author", "title", "score", "created", "link", "text", "url"]
+    else:
+        fields = ["author", "score", "created", "link", "body"]
+
+    file_size = os.stat(input_file).st_size
+    file_lines, bad_lines = 0, 0
+    line, created = None, None
+
+    # Dictionary to store the top comment for each post
+    top_comments = {}
+
+    with open(output_file_path, "w", encoding='utf-8', newline="") as output_file:
+        writer = csv.DictWriter(output_file, fieldnames=fields, quoting=csv.QUOTE_MINIMAL, quotechar='"', escapechar='\\')
+        writer.writeheader()
+
+        try:
+            for line, file_bytes_processed in read_lines_zst(input_file):
+                try:
+                    obj = json.loads(line)
+                    if is_submission:
+                        # Process submission data
+                        submission = {
+                            'author': f"u/{obj['author']}",
+                            'title': obj.get('title', ''),
+                            'score': obj.get('score', 0),
+                            'created': datetime.fromtimestamp(int(obj['created_utc'])).strftime("%Y-%m-%d %H:%M"),
+                            'link': f"https://www.reddit.com/r/{obj['subreddit']}/comments/{obj['id']}/",
+                            'text': obj.get('selftext', ''),
+                            'url': obj.get('url', ''),
+                        }
+                        writer.writerow(submission)
+                    else:
+                        # Process comment data and look for top comments
+                        post_id = obj['link_id']
+                        score = obj.get('score', 0)
+                        body = obj.get('body', '')
+                        
+                        if "[deleted]" in body or score <= 1:
+                            continue
+                        
+                        comment = {
+                            'author': f"u/{obj['author']}",
+                            'score': score,
+                            'created': datetime.fromtimestamp(int(obj['created_utc'])).strftime("%Y-%m-%d %H:%M"),
+                            'link': f"https://www.reddit.com/r/{obj['subreddit']}/comments/{obj['link_id'][3:]}/_/{obj['id']}/",
+                            'body': body,
+                        }
+                        
+                        if post_id not in top_comments or score > top_comments[post_id]['score']:
+                            top_comments[post_id] = comment
+                            writer.writerow(comment)
+                    
+                    created = datetime.utcfromtimestamp(int(obj['created_utc']))
+                except json.JSONDecodeError as err:
+                    bad_lines += 1
+                file_lines += 1
+                if file_lines % 100000 == 0:
+                    log.info(f"{created.strftime('%Y-%m-%d %H:%M:%S')} : {file_lines:,} : {bad_lines:,} : {(file_bytes_processed / file_size) * 100:.0f}%")
+        except KeyError as err:
+            log.info(f"Object has no key: {err}")
+            log.info(line)
+        except Exception as err:
+            log.info(err)
+            log.info(line)
+
+    log.info(f"Complete : {file_lines:,} : {bad_lines:,}")
+
+def convert_to_csv(input_folder, output_folder):
+    input_files = []
+    for subdir, dirs, files in os.walk(input_folder):
+        for filename in files:
+            input_path = os.path.join(subdir, filename)
+            if input_path.endswith(".zst"):
+                input_files.append(input_path)
+
+    with ProcessPoolExecutor() as executor:
+        futures = [executor.submit(process_file, input_file, output_folder) for input_file in input_files]
+        for future in futures:
+            future.result()
+
+if __name__ == "__main__":
+    if len(sys.argv) < 3:
+        print("Usage: python script.py <input_folder> <output_folder>")
+        sys.exit(1)
+    input_folder = sys.argv[1]
+    output_folder = sys.argv[2]
+    convert_to_csv(input_folder, output_folder)
+```
+
+## Combining into one dataset
+
+Afer finishing, combined into one parquet:
+
+```
+import pandas as pd
+import os
+
+# Define the folder containing the CSV files
+folder_path = 'csv'
+
+# List of files in the folder
+files = os.listdir(folder_path)
+
+# Initialize an empty list to store dataframes
+dfs = []
+
+# Process each file
+for file in files:
+    if file.endswith('.csv'):
+        # Extract subreddit name from the file name
+        subreddit = file.split('_')[0]
+        
+        # Read the CSV file
+        df = pd.read_csv(os.path.join(folder_path, file))
+        
+        # Add the subreddit name as a new column
+        df['subreddit'] = subreddit
+        
+        # Keep only the required columns and rename them
+        df = df[['title', 'selftext', 'top_comment_body', 'subreddit']]
+        df.columns = ['title', 'selftext', 'top_comment', 'subreddit']
+        
+        # Append the dataframe to the list
+        dfs.append(df)
+
+# Concatenate all dataframes
+combined_df = pd.concat(dfs, ignore_index=True)
+
+# Save the combined dataframe to a Parquet file
+combined_df.to_parquet('reddit_top_comments.parquet', index=False)
+```