Publish initial Reddit sample: 43,913 posts and 59,874 comments
Browse files- README.md +30 -25
- data/comments/subreddit=LocalLLaMA/part-0.parquet +3 -0
- data/comments/subreddit=SkincareAddiction/part-0.parquet +3 -0
- data/comments/subreddit=SkincareAddiction/part-1.parquet +3 -0
- data/comments/subreddit=wallstreetbets/part-0.parquet +3 -0
- data/posts/subreddit=LocalLLaMA/part-0.parquet +3 -0
- data/posts/subreddit=SkincareAddiction/part-0.parquet +3 -0
- data/posts/subreddit=SkincareAddiction/part-1.parquet +3 -0
- data/posts/subreddit=wallstreetbets/part-0.parquet +3 -0
- stats/summary.json +180 -53
README.md
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---
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license: cc-by-nc-4.0
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language:
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- en
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task_categories:
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- comments
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- conversation
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- conversational-tree
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pretty_name: Reddit Comment Trees Sample —
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configs:
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- config_name: posts
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data_files:
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path: data/comments/**/*.parquet
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---
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# Reddit Comment Trees Sample —
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> **
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>
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## Overview
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The
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## Why this dataset exists
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## Coverage
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| Subreddit | Posts | Comments |
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|---|---:|---:|---|---:|
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| LocalLLaMA |
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| wallstreetbets |
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| SkincareAddiction |
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## Schema
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Both tables use **Parquet with Zstandard compression**. Text is not truncated; timestamps are Unix seconds in UTC.
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Media files are not included. Preserve source text, except any documented anonymization.
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-
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### Posts
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## Collection method and known gaps
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## Load the data
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-
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Choose a config explicitly because posts and comments have different schemas.
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See [examples/load.py](examples/load.py) for separate `datasets`, pandas, and DuckDB examples.
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## Full dataset and custom delivery
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**Need more communities, a longer time range, or specific fields? [Contact Mashu Data](https://mashudata.com/contact.html).**
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These are target coverage and delivery terms, not a statement that all data or scheduled updates are already available.
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Ask about verified batch availability and custom subreddit, date-range, or field selection before ordering.
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Website: [mashudata.com](https://mashudata.com).
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## License and use
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---
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license: cc-by-nc-4.0
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size_categories:
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- 100K<n<1M
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language:
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- en
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task_categories:
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- comments
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- conversation
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- conversational-tree
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pretty_name: Reddit Comment Trees Sample — Initial snapshot
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configs:
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- config_name: posts
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data_files:
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path: data/comments/**/*.parquet
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---
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# Reddit Comment Trees Sample — Initial snapshot
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> **Initial sample: 43,913 posts and 59,874 comments across three communities.**
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> This is a selected, structurally checked snapshot, with incomplete subreddit coverage. It is not a complete three-month archive.
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## Overview
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Posts and associated comments from **r/LocalLLaMA, r/wallstreetbets, and r/SkincareAddiction**.
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The requested post window is **June 1–August 31, 2026 in Asia/Shanghai**, with UTC bounds **2026-05-31 16:00:00 inclusive to 2026-08-31 16:00:00 exclusive**. This window is not calendar Q2 or Q3.
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Only candidates with resolved stored relationships, no outstanding pagination or review flags, and counts matching the collector's expected count are included. These checks do not prove upstream recall.
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`link_id`, `parent_id`, and recomputed `depth` preserve the relationships in the selected records.
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## Why this dataset exists
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## Coverage
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| Subreddit | Posts | Comments | Observed post timestamps (UTC, inclusive endpoints) | Maximum depth |
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|---|---:|---:|---|---:|
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| LocalLLaMA | 3,778 | 21,850 | 2026-05-31T16:13:21+00:00 to 2026-08-31T15:31:52+00:00 | 15 |
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| wallstreetbets | 10,310 | 12,500 | 2026-05-31T16:17:43+00:00 to 2026-08-31T15:53:36+00:00 | 10 |
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| SkincareAddiction | 29,825 | 25,524 | 2026-05-31T16:04:12+00:00 to 2026-08-31T15:58:30+00:00 | 9 |
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Observed endpoints do not establish gap-free coverage. Historical post discovery remains incomplete.
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The sample includes zero-comment posts and disproportionately small comment trees; it is **not a representative or balanced sample** of these communities.
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The date window selects posts. Associated comments retain their collection-time snapshot, including comments newer than the post window.
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Per-community comment dates, depth distributions, deletion/removal ratios, null counts and file checksums are measured in [stats/summary.json](stats/summary.json).
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## Schema
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Both tables use **Parquet with Zstandard compression**. Text is not truncated; timestamps are Unix seconds in UTC.
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Media files are not included. Preserve source text, except any documented anonymization.
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No additional anonymization is applied. Missing or unsupported scalar fields remain null, including unknown authors; null is not converted to `[deleted]`. Community names are normalized against each linked post. All non-key scalar fields may be null.
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### Posts
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## Collection method and known gaps
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Collected through an existing Reddit business API using multiple third-party providers. Initial and continuation results were merged by post/comment ID. The exported snapshot was prepared at **2026-09-12T14:48:06+00:00**.
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All selected records pass post-scope, unique-ID, parent-resolution, cycle, derived-depth and stored-comment-count checks. Comment text was compared with the source database without truncation. At least 24 randomly selected comments were manually inspected across the three communities. Local Parquet loading was checked with datasets, pandas and DuckDB.
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Full tree completeness and complete subreddit recall are **not asserted**: unavailable posts, source-side omissions, historical search gaps and all unresolved review records are outside this sample. Placeholder comment IDs such as `deleted` are excluded by excluding affected threads; valid IDs with `[deleted]` or `[removed]` text are retained.
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Source usernames and public text are retained when provided. Moderator and bot replies, removed-content notices, informal language and potentially offensive text may be present; this is not a filtered human-only conversation dataset. Media, credentials, private messages and raw API responses are not included.
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Scores, displayed post comment counts and comment rows come from different collection snapshots. The displayed `num_comments` field is not a lifetime total or a completeness guarantee.
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## Load the data
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Choose one of the two real Parquet configurations. The files contain source records, not placeholder rows.
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Choose a config explicitly because posts and comments have different schemas.
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See [examples/load.py](examples/load.py) for separate `datasets`, pandas, and DuckDB examples.
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## Full dataset and custom delivery
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**Need more communities, a longer time range, or specific fields? [Contact Mashu Data](https://mashudata.com/contact.html).**
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Ask about verified batch availability and custom subreddit, date-range or field selection before ordering. This sample does not establish availability of 20 communities, a complete 12-month archive or scheduled weekly updates.
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Website: [mashudata.com](https://mashudata.com).
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## License and use
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data/comments/subreddit=LocalLLaMA/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:1fb31e91c3ab84f14a2dd5695f6516683c2d4754b55ca6996843062552938fee
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size 2762857
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data/comments/subreddit=SkincareAddiction/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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size 2639867
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data/comments/subreddit=SkincareAddiction/part-1.parquet
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version https://git-lfs.github.com/spec/v1
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size 64675
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data/comments/subreddit=wallstreetbets/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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size 928742
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data/posts/subreddit=LocalLLaMA/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:57643e425aad8816c1c566c224db96ff5cd777d40ad8ed28624e8aa00de59146
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size 1528552
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data/posts/subreddit=SkincareAddiction/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:392f4a312b430f5021a5426473d0f3e5114060e08379ca7fa57b5d38349eae40
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size 3166071
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data/posts/subreddit=SkincareAddiction/part-1.parquet
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version https://git-lfs.github.com/spec/v1
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size 655524
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data/posts/subreddit=wallstreetbets/part-0.parquet
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version https://git-lfs.github.com/spec/v1
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size 1641302
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stats/summary.json
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{
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"status": "
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"repo_id": "mashu-data/reddit-comments-sample",
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"generated_at":
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"planned_post_date_range_utc": [
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],
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"post_window_end_exclusive": true,
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"date_range_utc": [
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],
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"comment_date_range_utc": [
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],
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"
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"
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"subreddits": {
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"LocalLLaMA": {
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"posts":
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"comments":
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"post_date_range_utc": [
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],
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"comment_date_range_utc": [
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],
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"max_depth":
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"depth_distribution":
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},
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"wallstreetbets": {
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"posts":
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"comments":
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"post_date_range_utc": [
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],
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"comment_date_range_utc": [
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],
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"max_depth":
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"depth_distribution":
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},
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"SkincareAddiction": {
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"posts":
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"comments":
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"post_date_range_utc": [
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-
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],
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"comment_date_range_utc": [
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],
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"max_depth":
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"depth_distribution":
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-
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}
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"
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| 1 |
{
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| 2 |
+
"status": "validated_snapshot",
|
| 3 |
"repo_id": "mashu-data/reddit-comments-sample",
|
| 4 |
+
"generated_at": "2026-09-12T14:48:06+00:00",
|
| 5 |
+
"snapshot_at": 1789224486,
|
| 6 |
"planned_post_date_range_utc": [
|
| 7 |
+
"2026-05-31T16:00:00+00:00",
|
| 8 |
+
"2026-08-31T16:00:00+00:00"
|
| 9 |
],
|
| 10 |
"post_window_end_exclusive": true,
|
| 11 |
"date_range_utc": [
|
| 12 |
+
"2026-05-31T16:04:12+00:00",
|
| 13 |
+
"2026-08-31T15:58:30+00:00"
|
| 14 |
],
|
| 15 |
"comment_date_range_utc": [
|
| 16 |
+
"2026-05-31T16:14:46+00:00",
|
| 17 |
+
"2026-09-12T03:02:24+00:00"
|
| 18 |
],
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| 19 |
+
"crawl_interval_utc": [
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| 20 |
+
"2026-09-12T05:59:45+00:00",
|
| 21 |
+
"2026-09-12T11:57:26+00:00"
|
| 22 |
+
],
|
| 23 |
+
"posts": 43913,
|
| 24 |
+
"comments": 59874,
|
| 25 |
"subreddits": {
|
| 26 |
"LocalLLaMA": {
|
| 27 |
+
"posts": 3778,
|
| 28 |
+
"comments": 21850,
|
| 29 |
+
"zero_comment_posts": 695,
|
| 30 |
"post_date_range_utc": [
|
| 31 |
+
"2026-05-31T16:13:21+00:00",
|
| 32 |
+
"2026-08-31T15:31:52+00:00"
|
| 33 |
],
|
| 34 |
"comment_date_range_utc": [
|
| 35 |
+
"2026-05-31T16:50:33+00:00",
|
| 36 |
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