red-crawler 0.1.1

Xiaohongshu contact lead crawler for fashion creators

red-crawler

CLI crawler for collecting Xiaohongshu beauty creator contact leads from profile bios and recommendation chains, with SQLite persistence and nightly automation.

Usage

Install the published CLI:

uv tool install red-crawler==0.1.1

Install the Playwright browser runtime:

red-crawler install-browsers

For local development from a checkout:

uv sync
uv run playwright install chromium

Save a reusable login session first:

red-crawler login --save-state "./state.json"

It will open a visible browser. Log in to Xiaohongshu there, then come back to the terminal and press Enter to save the session file.

Run a manual crawl with an existing Playwright storage state file:

red-crawler crawl-seed \
  --seed-url "https://www.xiaohongshu.com/user/profile/USER_ID" \
  --storage-state "./state.json" \
  --max-accounts 20 \
  --max-depth 2 \
  --db-path "./data/red_crawler.db" \
  --output-dir "./output"

crawl-seed defaults to safe mode, adding slower request pacing and dwell/scroll delays that look more like a normal browsing session. Use --no-safe-mode only if you explicitly want a faster run.

crawl-seed now does both:

• exports accounts.csv, contact_leads.csv, run_report.json
• upserts the same result into SQLite

Optional note-page expansion:

red-crawler crawl-seed \
  --seed-url "https://www.xiaohongshu.com/user/profile/USER_ID" \
  --storage-state "./state.json" \
  --include-note-recommendations

List high-quality contactable creators from the SQLite database:

red-crawler list-contactable \
  --db-path "./data/red_crawler.db" \
  --min-relevance-score 0.7 \
  --limit 20

Run nightly auto-collection with queue, search bootstrap, seed promotion, and daily report output:

red-crawler collect-nightly \
  --storage-state "./state.json" \
  --db-path "./data/red_crawler.db" \
  --report-dir "./reports" \
  --cache-dir "./.cache/red-crawler" \
  --crawl-budget 30

Export weekly growth report and a contactable creator CSV:

red-crawler report-weekly \
  --db-path "./data/red_crawler.db" \
  --report-dir "./reports" \
  --days 7

Key outputs:

• manual crawl:
  • accounts.csv
  • contact_leads.csv
  • run_report.json
• nightly automation:
  • reports/daily-run-report.json
  • reports/weekly-growth-report.json
  • reports/contactable_creators.csv
• SQLite database:
  • data/red_crawler.db

OpenClaw

The OpenClaw skill for this project lives at openclaw-skills/red-crawler-ops/.

To install it from a local path, point OpenClaw at that folder, or copy the skill directory into your OpenClaw skills location and register the same path.

Use the OpenClaw skill actions in this order:

• bootstrap validates a local working directory and can run Chromium installation when explicitly requested.
• login creates the Playwright storage state explicitly.
• crawl_seed and collect_nightly require an authenticated Playwright storage state file.
• report_weekly and list_contactable run from the SQLite database and do not require --storage-state.

The skill does not clone repositories or create login sessions implicitly. Install the red-crawler CLI package first, point workspace_path at a local working directory, run bootstrap only for reviewed local setup steps, then run login when you are ready to create state.json.

Publishing

The package builds as a standard Python wheel and source distribution:

uv build

See docs/publishing.md for the release checklist and PyPI/TestPyPI commands.

launchd

For macOS local scheduling, use the template at docs/launchd/red-crawler.collect-nightly.plist.

Replace the placeholder paths:

• __WORKDIR__
• __UV_BIN__
• __STORAGE_STATE__
• __DB_PATH__
• __REPORT_DIR__
• __CACHE_DIR__
• __LOG_DIR__

Then load it with:

launchctl unload ~/Library/LaunchAgents/com.red-crawler.collect-nightly.plist 2>/dev/null || true
cp docs/launchd/red-crawler.collect-nightly.plist ~/Library/LaunchAgents/com.red-crawler.collect-nightly.plist
launchctl load ~/Library/LaunchAgents/com.red-crawler.collect-nightly.plist