Add 2014-07-05 — 214.8K events, 11 files

README.md

@@ -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')
@@ -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 | 182 | 59,126,968 | 324,873 | 18.1 GB | 5.4 GB | 1h59m | 10h22m | 2h43m |
+| 2014 | 182 | 59,126,968 | 324,873 | 18.1 GB | 5.4 GB | 1h59m | 10h22m | 2h44m |
 | 2015 | 2 | 511,749 | 255,874 | 166.6 MB | 85.1 MB | 20s | 2m59s | 48s |
 
 
@@ -163,10 +161,9 @@ Pushes are the most common event type, representing roughly half of all GitHub a
 
 
 ```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;
 ```
 
@@ -207,17 +203,16 @@ 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
@@ -229,10 +224,9 @@ Stars (WatchEvent in the GitHub API) reflect community interest and discovery. S
 
 
 ```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
 

data/commit_comments/2014/07/05.parquet

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+size 1408090

data/pushes/2014/07/05.parquet

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data/wiki_pages/2014/07/05.parquet

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stats.csv

@@ -1057,7 +1057,7 @@ date,total_events,parse_errors,pushes,issues,issue_comments,pull_requests,pr_rev
 2014-07-01,379868,1648,189541,19063,36490,18467,0,5505,35248,13747,44462,7005,1198,3031,4116,0,347,0,136549099,289.6,38646203,39.2,289.6,47.1
 2014-07-02,396669,1612,194481,21293,39623,19122,0,5656,38848,14545,45075,6766,1123,3802,4378,0,345,0,139724749,290.0,38909083,57.6,290.1,42.8
 2014-07-03,384108,1529,187822,22003,37389,18211,0,6606,39055,13800,42373,6737,1019,3033,4195,0,336,0,136822670,285.6,37599674,54.1,285.7,69.2
-2014-07-04,286151,1003,140538,15260,29960,12270,0,3507,29226,10278,33245,4818,737,2238,2845,0,226,0,94705025,199.9,27186254,41.3,199.9,30.9
+2014-07-04,286151,1003,140538,15260,29960,12270,0,3507,29226,10278,33245,4818,737,2238,2845,0,226,0,94705025,199.9,27186254,41.3,199.9,117.1
 2014-07-05,214785,789,112381,10450,15696,8119,0,1619,24312,7807,26049,3383,552,1326,2131,0,171,0,67845437,146.4,20385555,27.2,146.4,0.0
 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