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# Notes
These are general notes of the entire process from processing to semi-final results.
# Filtering Steps
## Unpacking (RedditUnpack.py)
1. Run `python RedditUnpack.py process <submissions/comments> <ZST folder> <Output Prefix>` to process submissions and comments respectively.
- This unpacks submissions and comments into jsonl files. Expanding them to ~8TiB uncompressed. So be sure to have plenty of storage or some sort of disk compression.
## Filtering Subreddits (RedditSubredditIndex.py)
We don't want really empty subreddits so we prune subreddits by subscriber count first.
2. Run `python RedditSubredditIndex.py preindex <Submissions Output Folder>`
- This is a very simple counter to get the subscriber counts for each subreddit for each month.
- This additionally creates a folder called `IndexSubReddit` as a scratch folder for indexing subreddits.
3. Run `python RedditSubredditIndex.py combine`
- Combines the multiple jsonl files created into a seperate process into 1 massive file.
- Deduplication via subreddit name matching.
- Fixes some weird inconsistencies in pushshift dumps.
- Get's the highest subscriber count seen. Ignores a decrease in subscriber counts.
- Could be suspectable to sub manipulation, but you need a lot of user accounts to spam for it.
4. (Optional) `python RedditSubredditIndex.py percentile` to get a printout of percentiles: [95th, 90th, 75th, 50th, 25th, 10th, 5th].
- Not required step but a good way to see which subscriber counts is best suited for your usecase.
5. `python RedditSubredditIndex.py selection <Minimum Subscribers>` to create `sub_selects.jsonl`.
- Writes a file called `sub_selects.jsonl` containing a jsonl list of selected subreddits.
6. `python RedditSubredditIndex.py filter-folder <Comment/Submission Folder> <Output Folder> <"Submission"/"Comments" (Mode)>`
- This is the folder known internally as subreddits_M700 / M700 Folder.
- Point the `<Output Folder>` to the same folder.
- This will raise an exception when a wrong folder is selected (Comments when the Mode is not selected as Comments, etc.)
- Don't open the output folder in vscode since vscode will just die trying to see all the jsonl files.
# Roughly Filtering (RedditSubredditIndex.py)
Even after filtering by subreddit count, we are still left with subreddits which are mostly "Empty" or with a lot of spam.
7. `RedditScoring.py compute-scores <M700 Folder>` computes the some statistics for both submissions:
- QScores such as Engagement, Richness and Diversity
- Unique Submission/Comment Authors and submission/comment counts
8. Run `RedditScoring.py merge-stats <M700 Folder> <Merged Stats Jsonl>`
- Merge jsonl files into 1 bigger consolidated stats file.
9. `RedditScoring.py makefilter StatsM700.jsonl <Selection-OUTPUT> --mode <text/media>`
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# Rewrite and Merge submissions, comments into conversations (RedditThreader.py)
10. Run `RedditThreader.py folder subreddits_M700 <OUTPUT_FOLDER> <Selection-OUTPUT>`
- Rethreads submissions and comments into threads
- Thread & a bit of additional subreddit filtering is applied.
# Uploading to HF
11. Run `RedditChunking.py`
- Very quick script to chunk all subreddits into jsonl chunks of 10GiB each for upload
12. Upload Chunks
- Uploaded the files. |