Merge pull request #2972 from vinta/feature/fetch-stats-workflow

ci: consolidate star fetch into deploy workflow with Actions cache
This commit is contained in:
Vinta Chen
2026-03-18 22:57:43 +08:00
committed by GitHub
7 changed files with 296 additions and 3227 deletions

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@@ -4,6 +4,8 @@ on:
push:
branches:
- master
schedule:
- cron: "0 0 * * *"
permissions:
contents: read
@@ -26,10 +28,40 @@ jobs:
enable-cache: true
- name: Install dependencies
run: uv sync --no-dev
run: uv sync --group build
- name: Restore star data cache
id: cache-stars
uses: actions/cache/restore@v4
with:
path: website/data/github_stars.json
key: github-stars-${{ github.run_id }}
restore-keys: github-stars-
- name: Fetch GitHub stars
id: fetch-stars
continue-on-error: true
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: make fetch_github_stars
- name: Save star data cache
if: steps.fetch-stars.outcome == 'success'
uses: actions/cache/save@v4
with:
path: website/data/github_stars.json
key: github-stars-${{ github.run_id }}
- name: Verify star data exists
run: |
if [ ! -f website/data/github_stars.json ]; then
echo "::error::github_stars.json not found. No cache and fetch failed or was skipped."
exit 1
fi
echo "Star data found: $(wc -l < website/data/github_stars.json) lines"
- name: Build site
run: uv run python website/build.py
run: make build
- name: Upload artifact
uses: actions/upload-pages-artifact@v4

1
.gitignore vendored
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@@ -7,6 +7,7 @@
# website
website/output/
website/data/
# claude code
.claude/skills/

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@@ -4,7 +4,7 @@ export
install:
uv sync
fetch_stats:
fetch_github_stars:
uv run python website/fetch_github_stars.py
test:

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@@ -8,62 +8,144 @@ from pathlib import Path
from typing import TypedDict
from jinja2 import Environment, FileSystemLoader
from readme_parser import parse_readme, slugify
# Thematic grouping of categories. Each category name must match exactly
# as it appears in README.md (the ## heading text).
SECTION_GROUPS: list[tuple[str, list[str]]] = [
("Web & API", [
"Web Frameworks", "RESTful API", "GraphQL", "WebSocket",
"ASGI Servers", "WSGI Servers", "HTTP Clients", "Template Engine",
"Web Asset Management", "Web Content Extracting", "Web Crawling",
]),
("Data & ML", [
"Data Analysis", "Data Validation", "Data Visualization",
"Machine Learning", "Deep Learning", "Computer Vision",
"Natural Language Processing", "Recommender Systems", "Science",
"Quantum Computing",
]),
("DevOps & Infrastructure", [
"DevOps Tools", "Distributed Computing", "Task Queues",
"Job Scheduler", "Serverless Frameworks", "Logging", "Processes",
"Shell", "Network Virtualization", "RPC Servers",
]),
("Database & Storage", [
"Database", "Database Drivers", "ORM", "Caching", "Search",
"Serialization",
]),
("Development Tools", [
"Testing", "Debugging Tools", "Code Analysis", "Build Tools",
"Refactoring", "Documentation", "Editor Plugins and IDEs",
"Interactive Interpreter",
]),
("CLI & GUI", [
"Command-line Interface Development", "Command-line Tools",
"GUI Development",
]),
("Content & Media", [
"Audio", "Video", "Image Processing", "HTML Manipulation",
"Text Processing", "Specific Formats Processing",
"File Manipulation", "Downloader",
]),
("System & Runtime", [
"Asynchronous Programming", "Environment Management",
"Package Management", "Package Repositories", "Distribution",
"Implementations", "Built-in Classes Enhancement",
"Functional Programming", "Configuration Files",
]),
("Security & Auth", [
"Authentication", "Cryptography", "Penetration Testing",
"Permissions",
]),
("Specialized", [
"CMS", "Admin Panels", "Email", "Game Development", "Geolocation",
"Hardware", "Internationalization", "Date and Time",
"URL Manipulation", "Robotics", "Microsoft Windows", "Miscellaneous",
"Algorithms and Design Patterns", "Static Site Generator",
]),
(
"Web & API",
[
"Web Frameworks",
"RESTful API",
"GraphQL",
"WebSocket",
"ASGI Servers",
"WSGI Servers",
"HTTP Clients",
"Template Engine",
"Web Asset Management",
"Web Content Extracting",
"Web Crawling",
],
),
(
"Data & ML",
[
"Data Analysis",
"Data Validation",
"Data Visualization",
"Machine Learning",
"Deep Learning",
"Computer Vision",
"Natural Language Processing",
"Recommender Systems",
"Science",
"Quantum Computing",
],
),
(
"DevOps & Infrastructure",
[
"DevOps Tools",
"Distributed Computing",
"Task Queues",
"Job Scheduler",
"Serverless Frameworks",
"Logging",
"Processes",
"Shell",
"Network Virtualization",
"RPC Servers",
],
),
(
"Database & Storage",
[
"Database",
"Database Drivers",
"ORM",
"Caching",
"Search",
"Serialization",
],
),
(
"Development Tools",
[
"Testing",
"Debugging Tools",
"Code Analysis",
"Build Tools",
"Refactoring",
"Documentation",
"Editor Plugins and IDEs",
"Interactive Interpreter",
],
),
(
"CLI & GUI",
[
"Command-line Interface Development",
"Command-line Tools",
"GUI Development",
],
),
(
"Content & Media",
[
"Audio",
"Video",
"Image Processing",
"HTML Manipulation",
"Text Processing",
"Specific Formats Processing",
"File Manipulation",
"Downloader",
],
),
(
"System & Runtime",
[
"Asynchronous Programming",
"Environment Management",
"Package Management",
"Package Repositories",
"Distribution",
"Implementations",
"Built-in Classes Enhancement",
"Functional Programming",
"Configuration Files",
],
),
(
"Security & Auth",
[
"Authentication",
"Cryptography",
"Penetration Testing",
"Permissions",
],
),
(
"Specialized",
[
"CMS",
"Admin Panels",
"Email",
"Game Development",
"Geolocation",
"Hardware",
"Internationalization",
"Date and Time",
"URL Manipulation",
"Robotics",
"Microsoft Windows",
"Miscellaneous",
"Algorithms and Design Patterns",
"Static Site Generator",
],
),
("Resources", []), # Filled dynamically from parsed resources
]
@@ -85,20 +167,24 @@ def group_categories(
group_cats = [cat_by_name[n] for n in cat_names if n in cat_by_name]
if group_cats:
groups.append({
"name": group_name,
"slug": slugify(group_name),
"categories": group_cats,
})
groups.append(
{
"name": group_name,
"slug": slugify(group_name),
"categories": group_cats,
}
)
# Any categories not in a group go into "Other"
ungrouped = [c for c in categories if c["name"] not in grouped_names]
if ungrouped:
groups.append({
"name": "Other",
"slug": "other",
"categories": ungrouped,
})
groups.append(
{
"name": "Other",
"slug": "other",
"categories": ungrouped,
}
)
return groups
@@ -121,9 +207,7 @@ class StarData(TypedDict):
fetched_at: str
GITHUB_REPO_URL_RE = re.compile(
r"^https?://github\.com/([^/]+/[^/]+?)(?:\.git)?/?$"
)
GITHUB_REPO_URL_RE = re.compile(r"^https?://github\.com/([^/]+/[^/]+?)(?:\.git)?/?$")
def extract_github_repo(url: str) -> str | None:
@@ -144,12 +228,14 @@ def load_stars(path: Path) -> dict[str, StarData]:
def sort_entries(entries: list[dict]) -> list[dict]:
"""Sort entries by stars descending, then name ascending. No-star entries go last."""
def sort_key(entry: dict) -> tuple[int, int, str]:
stars = entry["stars"]
name = entry["name"].lower()
if stars is None:
return (1, 0, name)
return (0, -stars, name)
return sorted(entries, key=sort_key)
@@ -167,17 +253,19 @@ def extract_entries(
for cat in categories:
group_name = cat_to_group.get(cat["name"], "Other")
for entry in cat["entries"]:
entries.append({
"name": entry["name"],
"url": entry["url"],
"description": entry["description"],
"category": cat["name"],
"group": group_name,
"stars": None,
"owner": None,
"last_commit_at": None,
"also_see": entry["also_see"],
})
entries.append(
{
"name": entry["name"],
"url": entry["url"],
"description": entry["description"],
"category": cat["name"],
"group": group_name,
"stars": None,
"owner": None,
"last_commit_at": None,
"also_see": entry["also_see"],
}
)
return entries
@@ -241,6 +329,8 @@ def build(repo_root: str) -> None:
if static_src.exists():
shutil.copytree(static_src, static_dst, dirs_exist_ok=True)
shutil.copy(repo / "README.md", site_dir / "llms.txt")
print(f"Built single page with {len(categories)} categories + {len(resources)} resources")
print(f"Total entries: {total_entries}")
print(f"Output: {site_dir}")

File diff suppressed because it is too large Load Diff

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@@ -12,7 +12,7 @@ import httpx
from build import extract_github_repo, load_stars
CACHE_MAX_AGE_DAYS = 7
CACHE_MAX_AGE_HOURS = 12
DATA_DIR = Path(__file__).parent / "data"
CACHE_FILE = DATA_DIR / "github_stars.json"
README_PATH = Path(__file__).parent.parent / "README.md"
@@ -120,8 +120,8 @@ def main() -> None:
entry = cache.get(repo)
if entry and "fetched_at" in entry:
fetched = datetime.fromisoformat(entry["fetched_at"])
age_days = (now - fetched).days
if age_days < CACHE_MAX_AGE_DAYS:
age_hours = (now - fetched).total_seconds() / 3600
if age_hours < CACHE_MAX_AGE_HOURS:
continue
to_fetch.append(repo)

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@@ -137,3 +137,95 @@ class TestParseGraphqlResponse:
assert len(result) == 2
assert result["a/x"]["stars"] == 100
assert result["b/y"]["stars"] == 200
class TestMainSkipsFreshCache:
"""Verify that main() skips fetching when all cache entries are fresh."""
def test_skips_fetch_when_cache_is_fresh(self, tmp_path, monkeypatch, capsys):
from datetime import datetime, timedelta, timezone
from fetch_github_stars import main
# Set up a minimal README with one repo
readme = tmp_path / "README.md"
readme.write_text("* [req](https://github.com/psf/requests) - HTTP.\n")
monkeypatch.setattr("fetch_github_stars.README_PATH", readme)
# Pre-populate cache with a fresh entry (1 hour ago)
data_dir = tmp_path / "data"
data_dir.mkdir()
cache_file = data_dir / "github_stars.json"
now = datetime.now(timezone.utc)
fresh_cache = {
"psf/requests": {
"stars": 52000,
"owner": "psf",
"last_commit_at": "2025-01-01T00:00:00+00:00",
"fetched_at": (now - timedelta(hours=1)).isoformat(),
}
}
cache_file.write_text(json.dumps(fresh_cache), encoding="utf-8")
monkeypatch.setattr("fetch_github_stars.CACHE_FILE", cache_file)
monkeypatch.setattr("fetch_github_stars.DATA_DIR", data_dir)
monkeypatch.setenv("GITHUB_TOKEN", "fake-token")
main()
output = capsys.readouterr().out
assert "0 repos to fetch" in output
assert "Cache is up to date" in output
def test_fetches_when_cache_is_stale(self, tmp_path, monkeypatch, capsys):
from datetime import datetime, timedelta, timezone
from unittest.mock import MagicMock
from fetch_github_stars import main
# Set up a minimal README with one repo
readme = tmp_path / "README.md"
readme.write_text("* [req](https://github.com/psf/requests) - HTTP.\n")
monkeypatch.setattr("fetch_github_stars.README_PATH", readme)
# Pre-populate cache with a stale entry (24 hours ago)
data_dir = tmp_path / "data"
data_dir.mkdir()
cache_file = data_dir / "github_stars.json"
now = datetime.now(timezone.utc)
stale_cache = {
"psf/requests": {
"stars": 52000,
"owner": "psf",
"last_commit_at": "2025-01-01T00:00:00+00:00",
"fetched_at": (now - timedelta(hours=24)).isoformat(),
}
}
cache_file.write_text(json.dumps(stale_cache), encoding="utf-8")
monkeypatch.setattr("fetch_github_stars.CACHE_FILE", cache_file)
monkeypatch.setattr("fetch_github_stars.DATA_DIR", data_dir)
monkeypatch.setenv("GITHUB_TOKEN", "fake-token")
# Mock httpx.Client to avoid real API calls
mock_response = MagicMock()
mock_response.json.return_value = {
"data": {
"repo_0": {
"stargazerCount": 53000,
"owner": {"login": "psf"},
"defaultBranchRef": {"target": {"committedDate": "2025-06-01T00:00:00Z"}},
}
}
}
mock_response.raise_for_status = MagicMock()
mock_client = MagicMock()
mock_client.__enter__ = MagicMock(return_value=mock_client)
mock_client.__exit__ = MagicMock(return_value=False)
mock_client.post.return_value = mock_response
monkeypatch.setattr("fetch_github_stars.httpx.Client", lambda **kwargs: mock_client)
main()
output = capsys.readouterr().out
assert "1 repos to fetch" in output
assert "Done. Fetched 1 repos" in output
mock_client.post.assert_called_once()