hydrate/README.md

Hydrating PluRule

This directory contains the three scripts a user runs to reconstitute the full PluRule benchmark from the released dehydrated dataset.

If you instead want to rebuild PluRule from scratch starting from the raw Pushshift archives, see ../pipeline/README.md.

Why hydration?

The released dataset ships only IDs, metadata, rules, cluster labels, and answer options — every comment body, submission, and media file is replaced with a [NEEDS_HYDRATION] placeholder. This keeps the distribution small and avoids redistributing Reddit content that originates from the Pushshift archives. To run the benchmark you first populate those placeholders from a local Pushshift mirror (which you download from Academic Torrents) and then download the submission media.

Prerequisites

• Python 3.10+
• aria2c on PATH (for torrent download)
• A BitTorrent port open in your firewall
• Disk: plan for several hundred GB to ~1–2 TB for the Pushshift subset. Large subreddits (r/askreddit, r/worldnews, …) contribute most of the volume; small subreddits are tens of MB each.
• Bandwidth: torrent throughput depends on seeders; budget several hours.

Install

The quickest path uses the bundled conda env (pulls aria2 from conda-forge so you don't need root):

conda env create -f ../environment-hydrate.yml
conda activate plurule-hydrate

If you already have a Python environment, install the minimal hydrate deps from the yml's pip: section (zstandard, orjson, tqdm, requests, torf) and make sure aria2c is on PATH:

Debian/Ubuntu:  sudo apt install aria2
macOS:          brew install aria2
Fedora/CentOS:  sudo dnf install aria2
No root:        conda install -c conda-forge aria2

Get the dehydrated dataset

Place the three dehydrated split files under ./data/:

data/
├── train_dehydrated_clustered.json.zst
├── val_dehydrated_clustered.json.zst
└── test_dehydrated_clustered.json.zst

Quick start

Three steps, from repo root:

# 1. Download the Pushshift subset referenced by the dataset (~3,978 files)
python hydrate/0_download.py

# 2. Fill every [NEEDS_HYDRATION] placeholder using the downloaded archives
python hydrate/1_hydrate_dataset.py

# 3. (Optional) Download submission images
python hydrate/2_download_media.py

After step 1 the Pushshift subset lives under the path configured in config.PUSHSHIFT_DATA. After step 2 you have data/{train,val,test}_hydrated_clustered.json.zst. After step 3 those same files have their media_files arrays populated with local paths.

---

0. 0_download.py — fetch the Pushshift subset

Reads the dehydrated splits, computes the set of per-subreddit comment and submission files referenced (~3,978 files across ~1,989 subreddits), fetches only those from the Pushshift academictorrent via aria2c, and reorganizes them into a first-letter bucket layout:

<output-dir>/
├── a/
│   ├── askreddit_comments.zst
│   ├── askreddit_submissions.zst
│   └── …
├── b/
│   └── …
└── hydrate_manifest.json

Common invocations

# Default (reads ./data, writes to config.PUSHSHIFT_DATA)
python hydrate/0_download.py

# Preview torrent match without downloading
python hydrate/0_download.py --dry-run

# Custom output directory
python hydrate/0_download.py --output-dir /mnt/big/pushshift

# Skip the torrent; build manifest from an existing local mirror
python hydrate/0_download.py --from-dir /path/to/pushshift/subreddits

Flags

Flag	Default	Purpose
--dataset-dir	./data	where the three *_dehydrated_clustered.json.zst files live
--output-dir	config.PUSHSHIFT_DATA	destination for Pushshift files
--torrent-file	(fetched)	use a pre-downloaded .torrent instead of the Academic Torrents URL
--dry-run	off	preview match report without downloading
--from-dir	(off)	skip torrent; use an existing local mirror

What it writes

• Downloaded files under <output-dir>/<letter>/
• <output-dir>/hydrate_manifest.json — basename_to_path map consumed by step 1
• <output-dir>/pushshift.torrent — cached .torrent so re-runs don't re-fetch

Resuming

aria2c keeps .aria2 control files next to each download. Re-running the script picks up where it left off. Files already in the letter-bucket layout are detected and not re-downloaded.

Subreddits missing from the torrent

Expect a small tail (<2%) of subreddits in the dataset that aren't in this particular torrent snapshot (renamed, banned, or post-cutoff subs). The script reports them and writes their names to hydrate_manifest.json; step 1 marks those subreddits with hydration_status: source_unavailable.

---

1. 1_hydrate_dataset.py — fill the placeholders

Streams each Pushshift file exactly once across all three splits (most subreddits appear in multiple splits), extracts only the referenced comment and submission IDs, and fills the placeholders in each split's JSON.

Run

# Default (reads ./data + config.PUSHSHIFT_DATA, writes ./data)
python hydrate/1_hydrate_dataset.py

# Only one split
python hydrate/1_hydrate_dataset.py --splits test

# Tune parallelism (default from config.PROCESSES)
python hydrate/1_hydrate_dataset.py --num-workers 16

Flags

Flag	Default	Purpose
--dataset-dir	./data	input dehydrated files
--pushshift-dir	config.PUSHSHIFT_DATA	where hydrate_manifest.json lives
--output-dir	./data	output hydrated files
--splits	all	subset of {train, val, test}
--num-workers	config.PROCESSES	parallel subreddit workers

How it fills things

Placeholder in dehydrated JSON	Filled by step 1 from
submissions[sid].submission_object	{sub}_submissions.zst
thread_pairs[i].mod_comment	{sub}_comments.zst (id = mod_comment_id)
thread_pairs[i].violating_thread	root→leaf walk of violating_thread_ids
thread_pairs[i].compliant_thread	root→leaf walk of compliant_thread_ids
submissions[sid].media_files	not filled — see step 2

Missing IDs (the Pushshift archive doesn't contain them) become {"hydration_status": "missing", "id": ...} instead of aborting the script. Subreddits whose Pushshift files aren't in the manifest have a hydration_status: "source_unavailable" flag set on their sub_data; their thread pairs are left with placeholders in place. Partial hydration is fine for these data-quality cases, and the script records them in the summary instead of aborting.

Output

• ./data/{train,val,test}_hydrated_clustered.json.zst — same schema as pipeline/10_assign_cluster_labels.py's hydrated output
• ./data/hydrate_summary.json — per-split counts + list of source-unavailable subreddits

---

2. 2_download_media.py — submission images (optional)

For each hydrated submission, follows the priority hierarchy (media_metadata → url → oembed → preview), validates Content-Type, caps files at 50 MB, and writes actual local paths into each submission's media_files array in the hydrated JSON.

This step reuses the same extraction + download logic as pipeline/7_collect_media.py via utils/media.py.

Run

# Default
python hydrate/2_download_media.py

# Only test split, more parallelism
python hydrate/2_download_media.py --splits test --num-workers 32

# Skip submissions whose media is already on disk
python hydrate/2_download_media.py --skip-existing

Flags

Flag	Default	Purpose
--dataset-dir	./data	hydrated files from step 1
--media-dir	./data/media	where images land (per-subreddit subdirs)
--splits	all	subset of {train, val, test}
--num-workers	16	HTTP threads (I/O-bound; threads, not processes)
--skip-existing	off	keep existing media_files paths that still exist on disk

What to expect

• Media is best-effort. Many historical Reddit URLs are dead or rate-limit. A 60–80% success rate is typical. The benchmark works fine without 100% media coverage; models that don't consume images are unaffected.
• Videos, crossposts, and NSFW submissions are skipped at the top (same rule as the pipeline).
• Files are named {submission_id}_{media_id}.{ext} or {submission_id}_{index}_{safe_media_id}.{ext} for gallery items.

Output

• ./data/media/<subreddit>/<submission_id>_*.{jpg,png,gif,webp,bmp}
• Each submission.media_files array in the hydrated JSON now holds real paths
• ./data/hydrate_media_summary.json — per-split status / error counts

---

Output format

After all three steps, each {split}_hydrated_clustered.json.zst matches the schema produced by pipeline/10_assign_cluster_labels.py:

{
  "metadata": { /* split-level, hydration dates, version */ },
  "subreddits": [
    {
      "subreddit": "excel",
      "title": "...",
      "description": "...",
      "language": "en",
      "rules": [ /* full rule objects with cluster ids */ ],
      "subreddit_cluster_id":    2,
      "subreddit_cluster_label": "tech communities",
      "submissions": {
        "<submission_id>": {
          "submission_object": { /* full submission JSON */ },
          "num_media": 1,
          "media_files": ["data/media/excel/<id>_direct.png"]
        }
      },
      "thread_pairs": [
        {
          "mod_comment_id": "...",
          "mod_comment":    { /* full comment */ },
          "violating_thread":  [ /* root→leaf comments, each with level */ ],
          "compliant_thread":  [ /* same */ ],
          "violating_answer_options": [ /* shuffled MCQ */ ],
          "violating_correct_answer": "(c)",
          "compliant_answer_options": [ /* shuffled MCQ */ ],
          "compliant_correct_answer": "(b)",
          "metadata": {
            "rule": "No low-effort posts",
            "rule_cluster_id":    5,
            "rule_cluster_label": "spam / self-promotion",
            /* plus similarity score, depths, scores, ancestor IDs, … */
          }
        }
      ]
    }
  ]
}

Re-running

All three scripts are safe to re-run:

• Step 0: aria2c resumes from .aria2 control files. Files already in the letter-bucket layout are detected and skipped.
• Step 1: overwrites *_hydrated_clustered.json.zst each run.
• Step 2: with --skip-existing, submissions whose media already exists on disk are not re-downloaded.

Troubleshooting

Symptom	Likely cause / fix
aria2c not found	install it (see Prerequisites)
Step 0 very slow	few seeders for some files; try again later, or use --from-dir with a local mirror
Step 1 OOMs on a big subreddit	use --num-workers 1; the streaming hydrator caps per-subreddit memory at only the needed IDs, not the full file — if you still OOM, file an issue
Step 1 reports many missing IDs for one sub	that subreddit's Pushshift file is truncated or corrupt; re-download just that pair via aria2c --torrent-file=... --select-file=<idx>
Step 2 dies with 429s	lower --num-workers, the retry logic backs off but heavy parallelism against single hosts (e.g. Imgur) can trip limits
hydration_status: source_unavailable on several subs	those subs aren't in the Pushshift torrent snapshot — expected for a small tail of renamed/banned subreddits