Add Reddit comment-tree sample skeleton; data pending

README.md

@@ -1,3 +1,152 @@
 ---
 license: cc-by-nc-4.0
+language:
+  - en
+task_categories:
+  - text-generation
+  - text-classification
+tags:
+  - reddit
+  - social-media
+  - comments
+  - conversation
+  - conversational-tree
+pretty_name: Reddit Comment Trees Sample — Release in preparation
+configs:
+  - config_name: posts
+    data_files:
+      - split: train
+        path: data/posts/**/*.parquet
+  - config_name: comments
+    data_files:
+      - split: train
+        path: data/comments/**/*.parquet
 ---
+
+# Reddit Comment Trees Sample — Release in preparation
+
+> **Preparing the first release. No Reddit records have been uploaded yet.**
+> The table schemas and loading examples are ready; Dataset Viewer previews become available after real Parquet files are published.
+
+## Overview
+
+A sample of posts and comment trees from **r/LocalLLaMA, r/wallstreetbets, and r/SkincareAddiction**.
+The sample is designed for one agreed three-month release window. Its exact UTC boundaries are **pending confirmation** before the first data upload.
+Actual coverage, post and comment counts, and tree completeness are pending validation of the first release.
+Comment relationships are preserved through `link_id`, `parent_id`, and `depth`.
+
+## Why this dataset exists
+
+Public Reddit archives include data after the 2023 API changes; freshness alone is not a unique feature.
+This sample focuses on documented time coverage, explicit post/comment relationships, typed columns, and reproducible collection snapshots.
+The three communities provide examples of AI discussion, market discussion, and consumer product feedback.
+The release will report observed gaps instead of treating unavailable records as successfully collected data.
+
+## Coverage
+
+| Subreddit | Posts | Comments | Actual post coverage (UTC) | Maximum comment depth |
+|---|---:|---:|---|---:|
+| LocalLLaMA | Pending | Pending | Pending | Pending |
+| wallstreetbets | Pending | Pending | Pending | Pending |
+| SkincareAddiction | Pending | Pending | Pending | Pending |
+
+The planned window selects **posts**. Available comments on those posts form a collection-time snapshot and may be newer than the selected post window.
+Exact comment timestamp ranges and tree completeness will be reported separately after validation.
+Unknown statistics in [stats/summary.json](stats/summary.json) are `null`, not zero.
+No estimated size category is advertised before the record counts are known.
+
+## Schema
+
+Both tables use **Parquet with Zstandard compression**. Text is not truncated; timestamps are Unix seconds in UTC.
+Media files are not included. Preserve source text, except any documented anonymization.
+Record any anonymization policy in the first release's collection notes before uploading the data.
+
+### Posts
+
+| Field | Type | Description |
+|---|---|---|
+| id | string | Post ID without the `t3_` prefix |
+| subreddit | string | One of the three listed communities |
+| author | string | Source author; deleted accounts use `[deleted]` |
+| created_utc | int64 | Post creation time, Unix seconds UTC |
+| title | string | Original post title |
+| selftext | string | Original post text; empty string for a link post |
+| url | string | External URL or post permalink |
+| score | int32 | Score snapshot at collection time |
+| upvote_ratio | float32 | Source upvote ratio |
+| num_comments | int32 | Reddit's displayed count; may differ from collected rows |
+| flair | string | Nullable post flair |
+| is_nsfw | bool | Source NSFW flag |
+| permalink | string | Reddit permalink |
+| crawled_at | int64 | Collection time, Unix seconds UTC |
+| batch_id | string | Collection batch identifier |
+
+### Comments
+
+| Field | Type | Description |
+|---|---|---|
+| id | string | Comment ID without the `t1_` prefix |
+| subreddit | string | Same community as the linked post |
+| link_id | string | Linked post ID without the `t3_` prefix |
+| parent_id | string | Unprefixed parent ID; top-level comments use `link_id` |
+| depth | int16 | Top-level comments have depth 0 |
+| author | string | Source author; deleted accounts use `[deleted]` |
+| created_utc | int64 | Comment creation time, Unix seconds UTC |
+| body | string | Original text; preserve `[deleted]` and `[removed]` markers |
+| score | int32 | Score snapshot at collection time |
+| is_submitter | bool | Whether the author is the post's submitter |
+| permalink | string | Reddit permalink |
+| crawled_at | int64 | Collection time, Unix seconds UTC |
+| batch_id | string | Collection batch identifier |
+
+Resolve a depth-0 parent against **posts**; resolve a deeper parent against **comments**, within the same subreddit and `link_id`.
+Post and comment IDs belong to different namespaces even when their prefixes are removed.
+The two HF configurations are `posts` and `comments`, each with a `train` split used as a storage partition, not a predefined ML training benchmark.
+Subreddit folders group files; they do not automatically become separate HF configurations.
+
+## Collection method and known gaps
+
+The exact collection entry point, pagination coverage, comment expansion method, and crawl interval are **pending verification with the running collection batch**.
+No claim of complete comment trees is made until parent links, depth consistency, and comment-expansion results are checked.
+Scores and `num_comments` are snapshots, not lifetime totals; edits, removals, unavailable replies, timing differences, and incomplete expansion can change the counts.
+`[deleted]` and `[removed]` markers remain visible. Missing data and unresolved parents will be reported rather than silently counted as empty results.
+
+## Load the data
+
+These examples work **after the first real data upload**. There are no placeholder Parquet rows.
+Choose a config explicitly because posts and comments have different schemas.
+See [examples/load.py](examples/load.py) for separate `datasets`, pandas, and DuckDB examples.
+
+```python
+from datasets import load_dataset
+comments = load_dataset("mashu-data/reddit-comments-sample", "comments", split="train", streaming=True)
+print(next(iter(comments)))
+```
+
+```python
+import duckdb
+con = duckdb.connect()
+con.execute("INSTALL httpfs; LOAD httpfs;")
+con.sql("""
+    SELECT id, link_id, parent_id, depth
+    FROM read_parquet(
+      'hf://datasets/mashu-data/reddit-comments-sample/data/comments/subreddit=LocalLLaMA/*.parquet',
+      hive_partitioning=false
+    ) LIMIT 20
+""").show()
+```
+
+## Full dataset and custom delivery
+
+**Need more communities, a longer time range, or specific fields? [Contact Mashu Data](https://mashudata.com/contact.html).**
+The full-dataset offering is being prepared for **20+ communities, a rolling 12-month window, and weekly incremental updates**.
+These are target coverage and delivery terms, not a statement that all data or scheduled updates are already available.
+Ask about verified batch availability and custom subreddit, date-range, or field selection before ordering.
+Website: [mashudata.com](https://mashudata.com).
+
+## License and use
+
+The sample is designated **CC BY-NC 4.0** for non-commercial research use, to the extent Mashu Data holds rights in the released material.
+Reddit users retain rights in their content; the repository license does not replace those rights or grant rights held by third parties.
+For commercial use or delivery terms, [contact Mashu Data](https://mashudata.com/contact.html).
+Cite the dataset repository and the exact revision used in your work; this dataset is not affiliated with or endorsed by Reddit.

examples/load.py

@@ -0,0 +1,31 @@
+"""Run ONE example after the first real Parquet release; dependencies run in Docker."""
+import argparse
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument('library', choices=['datasets', 'pandas', 'duckdb'])
+    parser.add_argument('--repo', required=True, help='HF dataset ID: mashu-data/repository-name')
+    args = parser.parse_args()
+    if args.library == 'datasets':
+        from datasets import load_dataset
+        comments = load_dataset(args.repo, 'comments', split='train', streaming=True)
+        print(next(iter(comments)))
+    elif args.library == 'pandas':
+        import pandas as pd
+        # Read one real shard, not the full dataset, into memory.
+        url = f'https://huggingface.co/datasets/{args.repo}/resolve/main/data/comments/subreddit=LocalLLaMA/part-0.parquet'
+        comments = pd.read_parquet(url)
+        print(comments[['id', 'link_id', 'parent_id', 'depth']].head())
+    else:
+        import duckdb
+        # httpfs handles hf:// paths; run in a Docker environment with network access.
+        conn = duckdb.connect()
+        conn.execute('INSTALL httpfs; LOAD httpfs;')
+        path = f'hf://datasets/{args.repo}/data/comments/subreddit=LocalLLaMA/*.parquet'
+        rows = conn.execute('SELECT id, link_id, parent_id, depth FROM read_parquet(?, hive_partitioning=false) LIMIT 20', [path]).fetchall()
+        print(rows)
+
+
+if __name__ == '__main__':
+    main()

stats/summary.json

@@ -0,0 +1,82 @@
+{
+  "status": "awaiting_data",
+  "repo_id": "mashu-data/reddit-comments-sample",
+  "generated_at": null,
+  "planned_post_date_range_utc": [
+    null,
+    null
+  ],
+  "post_window_end_exclusive": true,
+  "date_range_utc": [
+    null,
+    null
+  ],
+  "comment_date_range_utc": [
+    null,
+    null
+  ],
+  "date_range_convention": "actual ranges are observed minimum and maximum created_utc; planned post range is half-open",
+  "comment_scope": "available comment trees for selected posts at crawl time; comments may be outside the post window",
+  "crawl_method": null,
+  "anonymization_policy": null,
+  "tree_completeness_verified": false,
+  "subreddits": {
+    "LocalLLaMA": {
+      "posts": null,
+      "comments": null,
+      "post_date_range_utc": [
+        null,
+        null
+      ],
+      "comment_date_range_utc": [
+        null,
+        null
+      ],
+      "max_depth": null,
+      "depth_distribution": null,
+      "deleted_ratio": null,
+      "removed_ratio": null,
+      "missing_parent_count": null
+    },
+    "wallstreetbets": {
+      "posts": null,
+      "comments": null,
+      "post_date_range_utc": [
+        null,
+        null
+      ],
+      "comment_date_range_utc": [
+        null,
+        null
+      ],
+      "max_depth": null,
+      "depth_distribution": null,
+      "deleted_ratio": null,
+      "removed_ratio": null,
+      "missing_parent_count": null
+    },
+    "SkincareAddiction": {
+      "posts": null,
+      "comments": null,
+      "post_date_range_utc": [
+        null,
+        null
+      ],
+      "comment_date_range_utc": [
+        null,
+        null
+      ],
+      "max_depth": null,
+      "depth_distribution": null,
+      "deleted_ratio": null,
+      "removed_ratio": null,
+      "missing_parent_count": null
+    }
+  },
+  "statistic_definitions": {
+    "deleted_ratio": "comments whose body is exactly [deleted] / total comments; null if not measured or denominator is zero",
+    "removed_ratio": "comments whose body is exactly [removed] / total comments; null if not measured or denominator is zero",
+    "depth_distribution": "mapping from depth to comment count",
+    "unknown_values": "null means not measured; it is not an empty or successfully collected batch"
+  }
+}