Add 2014-06-21 — 202.3K events, 11 files

README.md

@@ -61,9 +61,9 @@ configs:
 
 This dataset contains every public event on GitHub: every push, pull request, issue, star, fork, code review, release, and discussion across all public repositories. GitHub is the world's largest software development platform, home to over 200 million repositories and the daily work of tens of millions of developers, from individual open-source contributors to the engineering teams behind the most widely used software on earth.
 
-The archive currently spans from **2011-02-12** to **2015-01-03** (1,047 days), totaling **177,559,411 events** across 16 fully structured Parquet tables. New events are fetched directly from the GitHub Events API every few seconds and committed as 5-minute Parquet blocks through an automated live pipeline, so the dataset stays current with GitHub itself.
+The archive currently spans from **2011-02-12** to **2015-01-03** (1,048 days), totaling **177,761,730 events** across 16 fully structured Parquet tables. New events are fetched directly from the GitHub Events API every few seconds and committed as 5-minute Parquet blocks through an automated live pipeline, so the dataset stays current with GitHub itself.
 
-We believe this is the most complete and regularly updated structured mirror of public GitHub activity available on Hugging Face. The original 51.3 GB of raw GH Archive NDJSON has been parsed, flattened, and compressed into 16.6 GB of Zstd-compressed Parquet. Every nested JSON field is expanded into typed columns — no JSON parsing needed downstream. The data is partitioned as `data/TABLE/YYYY/MM/DD.parquet`, making it straightforward to query with DuckDB, load with the `datasets` library, or process with any tool that reads Parquet.
+We believe this is the most complete and regularly updated structured mirror of public GitHub activity available on Hugging Face. The original 51.4 GB of raw GH Archive NDJSON has been parsed, flattened, and compressed into 16.6 GB of Zstd-compressed Parquet. Every nested JSON field is expanded into typed columns — no JSON parsing needed downstream. The data is partitioned as `data/TABLE/YYYY/MM/DD.parquet`, making it straightforward to query with DuckDB, load with the `datasets` library, or process with any tool that reads Parquet.
 
 The underlying data comes from [GH Archive](https://www.gharchive.org/), created by [Ilya Grigorik](https://www.igvita.com/), which has been recording every public GitHub event via the [Events API](https://docs.github.com/en/rest/activity/events) since 2011. Released under the [Open Data Commons Attribution License (ODC-By) v1.0](https://opendatacommons.org/licenses/by/1-0/).
 
@@ -119,10 +119,8 @@ Events from today are captured in near-real-time from the GitHub Events API and
 | `payload_json` | string | Full event payload as JSON |
 
 ```python
-# Query today's live events with DuckDB.
-# Run: uv run live_events.py
+# Query today's live events with DuckDB
 import duckdb
-
 duckdb.sql("""
   SELECT event_type, COUNT(*) as n
   FROM read_parquet('hf://datasets/open-index/open-github/today/raw/**/*.parquet')
@@ -136,7 +134,7 @@ duckdb.sql("""
   2011  █████░░░░░░░░░░░░░░░░░░░░░░░░░  14.1M
   2012  █████████████░░░░░░░░░░░░░░░░░  34.3M
   2013  ██████████████████████████████  74.5M
-  2014  █████████████████████░░░░░░░░░  54.2M
+  2014  █████████████████████░░░░░░░░░  54.4M
   2015  █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  511.7K
 ```
 
@@ -145,7 +143,7 @@ duckdb.sql("""
 | 2011 | 243 | 14,096,144 | 58,008 | 2.7 GB | 1.4 GB | 1h06m | 50m30s | 1h55m |
 | 2012 | 291 | 34,256,841 | 117,721 | 9.2 GB | 3.2 GB | 2h14m | 3h16m | 2h50m |
 | 2013 | 344 | 74,483,412 | 216,521 | 22.7 GB | 7.0 GB | 3h27m | 10h53m | 4h29m |
-| 2014 | 167 | 54,211,265 | 324,618 | 16.5 GB | 5.0 GB | 1h48m | 9h26m | 2h32m |
+| 2014 | 168 | 54,413,584 | 323,890 | 16.6 GB | 5.0 GB | 1h49m | 9h28m | 2h32m |
 | 2015 | 2 | 511,749 | 255,874 | 166.6 MB | 85.1 MB | 20s | 2m59s | 48s |
 
 
@@ -157,16 +155,15 @@ Pushes are the most common event type, representing roughly half of all GitHub a
   2011  █████░░░░░░░░░░░░░░░░░░░░░░░░░  6.7M
   2012  ████████████░░░░░░░░░░░░░░░░░░  16.5M
   2013  ██████████████████████████████  38.1M
-  2014  █████████████████████░░░░░░░░░  27.6M
+  2014  █████████████████████░░░░░░░░░  27.7M
   2015  █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  274.6K
 ```
 
 
 ```sql
--- Top 20 repos by push volume this year.
--- Run: duckdb -c ".read pushes_top_repos.sql"
-SELECT repo_name, COUNT(*) as pushes, SUM(size) as commits
-FROM read_parquet('hf://datasets/open-index/open-github/data/pushes/2026/**/*.parquet')
+-- Top 20 repos by push volume this year
+SELECT repo_name, COUNT(*) as pushes, SUM(push_size) as commits
+FROM read_parquet('hf://datasets/open-index/open-github/data/pushes/2025/**/*.parquet')
 GROUP BY repo_name ORDER BY pushes DESC LIMIT 20;
 ```
 
@@ -184,12 +181,11 @@ Issue events track the full lifecycle: opened, closed, reopened, labeled, assign
 
 
 ```sql
--- Repos with the most issues opened vs closed this year.
--- Run: duckdb -c ".read issues_top_repos.sql"
+-- Repos with the most issues opened this year
 SELECT repo_name,
   COUNT(*) FILTER (WHERE action = 'opened') as opened,
   COUNT(*) FILTER (WHERE action = 'closed') as closed
-FROM read_parquet('hf://datasets/open-index/open-github/data/issues/2026/**/*.parquet')
+FROM read_parquet('hf://datasets/open-index/open-github/data/issues/2025/**/*.parquet')
 GROUP BY repo_name ORDER BY opened DESC LIMIT 20;
 ```
 
@@ -207,32 +203,30 @@ Pull request events cover the full review cycle: opened, merged, closed, review
 
 
 ```sql
--- Top repos by merged PRs this year.
--- Run: duckdb -c ".read prs_top_merged.sql"
+-- Top repos by merged PRs this year
 SELECT repo_name, COUNT(*) as merged_prs
-FROM read_parquet('hf://datasets/open-index/open-github/data/pull_requests/2026/**/*.parquet')
-WHERE action = 'merged'
+FROM read_parquet('hf://datasets/open-index/open-github/data/pull_requests/2025/**/*.parquet')
+WHERE action = 'closed' AND merged = true
 GROUP BY repo_name ORDER BY merged_prs DESC LIMIT 20;
 ```
 
 ### Stars per year
 
-Stars (WatchEvent in the GitHub API) reflect community interest and discovery. Starring patterns often correlate with Hacker News, Reddit, or Twitter posts. For 2012–2014 events, `repo_language`, `repo_stars_count`, and `repo_forks_count` are populated from the legacy Timeline API repository snapshot.
+Stars (WatchEvent in the GitHub API) reflect community interest and discovery. Starring patterns often correlate with Hacker News, Reddit, or Twitter posts.
 
 ```
   2011  ██████░░░░░░░░░░░░░░░░░░░░░░░░  1.4M
   2012  ██████████████░░░░░░░░░░░░░░░░  3.3M
   2013  ██████████████████████████████  7.0M
-  2014  █████████████████████░░░░░░░░░  4.9M
+  2014  █████████████████████░░░░░░░░░  5.0M
   2015  █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  50.3K
 ```
 
 
 ```sql
--- Most starred repos this year.
--- Run: duckdb -c ".read stars_top_repos.sql"
+-- Most starred repos this year
 SELECT repo_name, COUNT(*) as stars
-FROM read_parquet('hf://datasets/open-index/open-github/data/stars/2026/**/*.parquet')
+FROM read_parquet('hf://datasets/open-index/open-github/data/stars/2025/**/*.parquet')
 GROUP BY repo_name ORDER BY stars DESC LIMIT 20;
 ```
 
@@ -241,48 +235,39 @@ GROUP BY repo_name ORDER BY stars DESC LIMIT 20;
 ### Python (`datasets`)
 
 ```python
-# Quick-start: load OpenGitHub data with the Hugging Face datasets library.
-# Run: uv run quickstart_datasets.py
 from datasets import load_dataset
 
-# Stream all stars without downloading everything
+# Stream all stars
 ds = load_dataset("open-index/open-github", "stars", streaming=True)
 for row in ds["train"]:
     print(row["repo_name"], row["actor_login"], row["created_at"])
-    break  # remove to stream all
 
 # Load a specific month of issues
 ds = load_dataset("open-index/open-github", "issues",
-                   data_files="data/issues/2026/03/*.parquet")
-print(f"March 2026 issues: {len(ds['train'])}")
+                   data_files="data/issues/2024/06/*.parquet")
 
 # Load all pull requests into memory
 ds = load_dataset("open-index/open-github", "pull_requests")
-print(f"Total PRs: {len(ds['train'])}")
 
 # Query today's live events
 ds = load_dataset("open-index/open-github", "live", streaming=True)
 for row in ds["train"]:
     print(row["event_type"], row["repo_name"], row["created_at"])
-    break  # remove to stream all
 ```
 
 ### DuckDB
 
 ```sql
--- Quick-start DuckDB queries for the OpenGitHub dataset.
--- Run: duckdb -c ".read quickstart.sql"
-
 -- Top 20 most-starred repos this year
 SELECT repo_name, COUNT(*) as stars
-FROM read_parquet('hf://datasets/open-index/open-github/data/stars/2026/**/*.parquet')
+FROM read_parquet('hf://datasets/open-index/open-github/data/stars/2025/**/*.parquet')
 GROUP BY repo_name ORDER BY stars DESC LIMIT 20;
 
--- Most active PR reviewers (approvals only)
-SELECT actor_login, COUNT(*) as approvals
-FROM read_parquet('hf://datasets/open-index/open-github/data/pr_reviews/2026/**/*.parquet')
+-- Most active PR reviewers (approved only)
+SELECT actor_login, COUNT(*) as reviews
+FROM read_parquet('hf://datasets/open-index/open-github/data/pr_reviews/2025/**/*.parquet')
 WHERE review_state = 'approved'
-GROUP BY actor_login ORDER BY approvals DESC LIMIT 20;
+GROUP BY actor_login ORDER BY reviews DESC LIMIT 20;
 
 -- Issue open/close rates by repo
 SELECT repo_name,
@@ -290,14 +275,13 @@ SELECT repo_name,
   COUNT(*) FILTER (WHERE action = 'closed') as closed,
   ROUND(COUNT(*) FILTER (WHERE action = 'closed') * 100.0 /
     NULLIF(COUNT(*) FILTER (WHERE action = 'opened'), 0), 1) as close_pct
-FROM read_parquet('hf://datasets/open-index/open-github/data/issues/2026/**/*.parquet')
-WHERE is_pull_request = false
+FROM read_parquet('hf://datasets/open-index/open-github/data/issues/2025/**/*.parquet')
 GROUP BY repo_name HAVING opened >= 10
 ORDER BY opened DESC LIMIT 20;
 
--- Full activity timeline for a repo (one month)
+-- Full activity timeline for a repo
 SELECT event_type, created_at, actor_login
-FROM read_parquet('hf://datasets/open-index/open-github/data/*/2026/03/*.parquet')
+FROM read_parquet('hf://datasets/open-index/open-github/data/*/2025/03/*.parquet')
 WHERE repo_name = 'golang/go'
 ORDER BY created_at DESC LIMIT 100;
 ```
@@ -305,20 +289,15 @@ ORDER BY created_at DESC LIMIT 100;
 ### Bulk download (`huggingface_hub`)
 
 ```python
-# Download OpenGitHub data locally with huggingface_hub.
-# Run: uv run quickstart_download.py
-# For faster downloads: HF_HUB_ENABLE_HF_TRANSFER=1 uv run quickstart_download.py
 from huggingface_hub import snapshot_download
 
 # Download only stars data
-snapshot_download("open-index/open-github", repo_type="dataset",
-                  local_dir="./open-github/",
-                  allow_patterns="data/stars/**/*.parquet")
-
-# Download a specific repo's data across all tables
-# snapshot_download("open-index/open-github", repo_type="dataset",
-#                   local_dir="./open-github/",
-#                   allow_patterns="data/*/2026/03/*.parquet")
+folder = snapshot_download(
+    "open-index/open-github",
+    repo_type="dataset",
+    local_dir="./open-github/",
+    allow_patterns="data/stars/**/*.parquet",
+)
 ```
 
 For faster downloads, install `pip install huggingface_hub[hf_transfer]` and set `HF_HUB_ENABLE_HF_TRANSFER=1`.
@@ -478,19 +457,13 @@ Line-level comments on pull request diffs. Includes the diff hunk for context an
 
 #### `stars`.WatchEvent
 
-Repository star events. Who starred which repo, and when. GitHub API quirk: the event is called `WatchEvent` but means starring. Action is always `"started"` so it is not stored.
+Repository star events. Simple, high-signal data: who starred which repo, and when. The `action` field is always `"started"` (GitHub API naming quirk: `WatchEvent` means starring, not watching).
 
-**Processing:** The WatchEvent payload carries no useful fields — all signal is in the event envelope (actor, repo, timestamp). For 2012–2014 events the legacy Timeline API included a full repository snapshot, so `repo_language`, `repo_stars_count`, `repo_forks_count`, `repo_description`, and `repo_is_fork` are populated for that era. `actor_type` is also populated from the legacy `actor_attributes` object. For 2015+ events those fields are empty; `actor_avatar_url` is populated instead.
+**Processing:** Minimal flattening: only the `action` field from payload. The event envelope (actor, repo, timestamp) carries all the useful information.
 
 | Column | Type | Description |
 |---|---|---|
-| `actor_avatar_url` | string | Actor avatar URL (2015+) |
-| `actor_type` | string | `User` or `Organization` (2012–2014 only) |
-| `repo_description` | string | Repo description at star time (2012–2014 only) |
-| `repo_language` | string | Primary language (2012–2014 only) |
-| `repo_stars_count` | int32 | Star count at star time (2012–2014 only) |
-| `repo_forks_count` | int32 | Fork count at star time (2012–2014 only) |
-| `repo_is_fork` | bool | Whether the starred repo is a fork (2012–2014 only) |
+| `action` | string | Always `started` |
 
 #### `forks`.ForkEvent
 
@@ -637,20 +610,20 @@ GitHub Discussions lifecycle: created, answered, category_changed, labeled, and
 
 | Table | GitHub Event | Events | % | Description |
 |-------|-------------|-------:|---:|-------------|
-| `pushes` | PushEvent | 89,160,701 | 50.2% | Git pushes with commits |
-| `issues` | IssuesEvent | 9,872,468 | 5.6% | Issue lifecycle events |
-| `issue_comments` | IssueCommentEvent | 15,502,011 | 8.7% | Comments on issues/PRs |
-| `pull_requests` | PullRequestEvent | 7,207,866 | 4.1% | PR lifecycle events |
-| `pr_review_comments` | PullRequestReviewCommentEvent | 1,638,718 | 0.9% | Line-level PR comments |
-| `stars` | WatchEvent | 16,624,800 | 9.4% | Repository stars |
-| `forks` | ForkEvent | 6,388,259 | 3.6% | Repository forks |
-| `creates` | CreateEvent | 22,328,666 | 12.6% | Branch/tag/repo creation |
-| `deletes` | DeleteEvent | 2,250,455 | 1.3% | Branch/tag deletion |
-| `releases` | ReleaseEvent | 204,965 | 0.1% | Release publications |
-| `commit_comments` | CommitCommentEvent | 1,659,638 | 0.9% | Comments on commits |
-| `wiki_pages` | GollumEvent | 2,952,983 | 1.7% | Wiki page edits |
+| `pushes` | PushEvent | 89,270,793 | 50.2% | Git pushes with commits |
+| `issues` | IssuesEvent | 9,880,790 | 5.6% | Issue lifecycle events |
+| `issue_comments` | IssueCommentEvent | 15,516,274 | 8.7% | Comments on issues/PRs |
+| `pull_requests` | PullRequestEvent | 7,215,059 | 4.1% | PR lifecycle events |
+| `pr_review_comments` | PullRequestReviewCommentEvent | 1,640,130 | 0.9% | Line-level PR comments |
+| `stars` | WatchEvent | 16,643,401 | 9.4% | Repository stars |
+| `forks` | ForkEvent | 6,396,762 | 3.6% | Repository forks |
+| `creates` | CreateEvent | 22,354,491 | 12.6% | Branch/tag/repo creation |
+| `deletes` | DeleteEvent | 2,253,387 | 1.3% | Branch/tag deletion |
+| `releases` | ReleaseEvent | 205,515 | 0.1% | Release publications |
+| `commit_comments` | CommitCommentEvent | 1,661,008 | 0.9% | Comments on commits |
+| `wiki_pages` | GollumEvent | 2,955,155 | 1.7% | Wiki page edits |
 | `members` | MemberEvent | 104,094 | 0.1% | Collaborator additions |
-| `public_events` | PublicEvent | 164,411 | 0.1% | Repo made public |
+| `public_events` | PublicEvent | 164,575 | 0.1% | Repo made public |
 
 ## How it's built
 

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stats.csv

@@ -1043,6 +1043,7 @@ date,total_events,parse_errors,pushes,issues,issue_comments,pull_requests,pr_rev
 2014-06-17,397284,1549,197943,20078,36869,19164,0,6149,36105,14948,47083,8280,989,3492,4249,0,386,0,141915613,278.6,40854501,45.0,278.6,105.1
 2014-06-18,395304,1511,198042,21382,36868,18956,0,6619,34722,14658,44196,6699,947,6265,4098,0,341,0,140973432,268.3,39112409,33.3,268.3,48.9
 2014-06-19,381455,1435,192403,19393,35171,18377,0,5650,35034,14278,44940,6740,1034,2929,3746,0,325,0,134349068,257.4,38286658,34.7,257.4,47.8
-2014-06-20,298206,1179,151406,14256,26384,14434,0,4241,27174,11752,34570,6042,812,2566,3126,0,264,0,105692313,195.4,30715112,39.2,195.4,0.0
+2014-06-20,298206,1179,151406,14256,26384,14434,0,4241,27174,11752,34570,6042,812,2566,3126,0,264,0,105692313,195.4,30715112,39.2,195.4,45.6
+2014-06-21,202319,920,110092,8322,14263,7193,0,1412,18601,8503,25825,2932,550,1370,2172,0,164,0,63875580,129.4,19903230,32.2,129.4,0.0
 2015-01-01,218939,0,119242,9843,17045,8735,0,2173,21939,7144,23913,3843,816,1399,2196,474,177,0,73764980,79.7,37810232,15.9,79.7,0.0
 2015-01-03,292810,0,155315,15037,26081,11958,0,2946,28410,9430,31862,4560,963,1829,3178,983,258,0,100890756,100.1,51394128,4.6,100.1,48.0