PyPI Intel: Packages, Releases, Dependencies & Maintainer Leads

Turn the Python Package Index (PyPI) into structured, B2B-ready data. This actor pulls package metadata, release history, dependency trees, and maintainer contacts straight from the official public PyPI API. No proxy, no auth, no API key.

Built for sales, dev-recruiting, competitive intelligence, VC sizing, and supply-chain / security teams who need clean Python ecosystem data they can act on.

Three modes

1. Package deep-dive / release monitor

Give it a list of package names and get a full structured record for each: latest version, summary, license, author and maintainer emails, repository, keywords, topics, dependency count, release history, and recent download counts (day / week / month).

Turn on Delta mode and it becomes a release monitor: it remembers each package's version and, on later runs, emits only the packages whose latest version changed. Pair it with a schedule and a webhook to get alerted the moment a dependency ships a new release.

2. Maintainer leads

Give it a PyPI username and get every package that user maintains, each enriched with contact email, repository, and download reach. A maintainer of widely-installed packages is a high-intent technical lead for recruiting, dev-tool sales, or partnership outreach.

3. Dependency graph (supply chain)

Give it one or more root packages and it walks the runtime dependency tree breadth-first (up to 3 levels deep), emitting every package in the chain. Each link carries its maintainer, license, and download weight. This is the SBOM / supply-chain / security angle: map exactly what a project pulls in and who is behind each piece.

Example input

Monitor releases of your stack:

{
  "mode": "package",
  "packages": ["requests", "flask", "numpy", "pydantic"],
  "deltaMode": true
}

Build a developer lead list:

{
  "mode": "maintainer",
  "maintainer": "kennethreitz",
  "minDownloads": 10000
}

Map a project's supply chain:

{
  "mode": "dependencies",
  "packages": ["flask"],
  "depth": 2
}

Output fields

name, version, summary, author, authorEmail, maintainer, maintainerEmail, license, keywords, topics, requiresPython, homepage, repository, dependencies, dependenciesCount, releasesCount, firstReleaseAt, lastReleaseAt, yanked, downloadsLastDay, downloadsLastWeek, downloadsLastMonth, pypiUrl. Dependency and release-monitor records add depth, dependencyOf, previousVersion, and versionChanged.

Pricing

Pay per result: you are billed per record saved to the dataset. No subscription, no minimum.

Data source and limits

All data comes from the official public PyPI endpoints (pypi.org/pypi/<package>/json), the pypistats download API, and the PyPI XML-RPC user_packages method. PyPI retired its keyword search API years ago, so discovery here is dependency-graph and maintainer driven rather than free-text search. Everything is public and anonymous.

Part of the B2B data suite

This actor pairs with the rest of the founder / VC / sales / dev-intel suite:

• npm Registry Intel for the JavaScript side of the same dependency and maintainer data
• GitHub Intel for repos, developer leads, and stargazers
• Hacker News Intel for hiring signals and launch tracking
• Y Combinator Companies Scraper and IndieHackers Product Scraper for startup data
• BetaList Startup Scraper for early launches
• SEC EDGAR Intel for filings and financials of public companies