PyPI Scraper

Extract Python package metadata from PyPI — the Python Package Index. Get versions, dependencies, download stats, descriptions, classifiers, and project URLs for any package.

What does PyPI Scraper do?

PyPI Scraper looks up packages on PyPI by name and extracts comprehensive metadata for each one. It fetches data directly from the PyPI JSON API and pypistats.org for download statistics. No browser needed — the actor uses fast HTTP requests for reliable, efficient extraction.

For each package you get: current version, summary, author info, license, Python version requirements, all dependencies, classifiers, keywords, release count, monthly download numbers, and direct URLs.

Why use PyPI Scraper?

• Fast and reliable — uses official PyPI JSON API, no HTML scraping or browser rendering
• Download statistics — includes monthly download counts from pypistats.org
• Complete metadata — versions, dependencies, classifiers, license, Python requirements
• Bulk lookup — process hundreds of packages in a single run
• Structured output — clean JSON ready for analysis, dashboards, or integration

Use cases

• Dependency auditing — check versions, licenses, and Python compatibility across your stack
• Package popularity tracking — monitor download trends for competing libraries
• Supply chain analysis — map dependency trees and identify widely-used packages
• Market research — analyze the Python ecosystem for trends and opportunities
• License compliance — verify licenses across all packages in your organization
• Developer tooling — feed package metadata into internal tools, dashboards, or reports

How to use PyPI Scraper

1. Go to the PyPI Scraper input page.
2. Add package names to the Package names list.
3. Click Start and wait for the run to finish.
4. Download your data in JSON, CSV, or Excel format.

Input parameters

Parameter	Type	Required	Description
packageNames	array	Yes	List of PyPI package names to look up (e.g., requests, flask, django)

Example input

{
    "packageNames": ["requests", "flask", "django", "numpy", "pandas"]
}

Output example

Each package returns a structured object with full metadata:

{
    "name": "requests",
    "version": "2.32.5",
    "summary": "Python HTTP for Humans.",
    "author": "Kenneth Reitz",
    "authorEmail": "me@kennethreitz.org",
    "license": "Apache-2.0",
    "homePage": "https://requests.readthedocs.io",
    "projectUrl": "https://pypi.org/project/requests/",
    "requiresPython": ">=3.9",
    "dependencies": [
        "charset_normalizer<4,>=2",
        "idna<4,>=2.5",
        "urllib3<3,>=1.21.1",
        "certifi>=2017.4.17"
    ],
    "classifiers": [
        "Development Status :: 5 - Production/Stable",
        "Programming Language :: Python :: 3"
    ],
    "keywords": [],
    "releaseCount": 157,
    "downloadsLastMonth": 1141725900,
    "packageUrl": "https://pypi.org/project/requests/",
    "scrapedAt": "2026-03-03T05:21:06.098Z"
}

Output fields

Field	Type	Description
name	string	Official package name on PyPI
version	string	Latest release version
summary	string	Short package description
author	string	Package author name
authorEmail	string	Author contact email
license	string	License identifier
homePage	string	Project home page URL
projectUrl	string	PyPI project page URL
requiresPython	string	Minimum Python version required
dependencies	array	List of package dependencies (requires_dist)
classifiers	array	PyPI trove classifiers
keywords	array	Package keywords
releaseCount	number	Total number of releases on PyPI
downloadsLastMonth	number	Download count in the last 30 days
packageUrl	string	Direct link to the PyPI project page
scrapedAt	string	ISO 8601 timestamp of extraction

Pricing

PyPI Scraper uses pay-per-event pricing:

Event	Price
Run started	$0.001
Package extracted	$0.001 per package

Cost examples

Packages	Cost
10 packages	$0.011
100 packages	$0.101
1,000 packages	$1.001

API usage

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("YOUR_USERNAME/pypi-scraper").call(
    run_input={"packageNames": ["requests", "flask", "django"]}
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} v{item['version']} — {item['downloadsLastMonth']:,} downloads/month")

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('YOUR_USERNAME/pypi-scraper').call({
    packageNames: ['requests', 'flask', 'django'],
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => {
    console.log(`${item.name} v${item.version} — ${item.downloadsLastMonth.toLocaleString()} downloads/month`);
});

Integrations

Connect PyPI Scraper to your workflow with Apify integrations:

• Webhooks — trigger actions when a run finishes
• Google Sheets — export package data to spreadsheets automatically
• Slack — get notifications about new package versions
• Zapier / Make — connect to 5,000+ apps and services
• REST API — call the actor programmatically from any language

Tips and best practices

• Use exact package names as they appear on PyPI (e.g., scikit-learn, not sklearn)
• Download statistics come from pypistats.org and may be slightly delayed
• The actor handles packages that don't exist gracefully — they're skipped with a warning
• For very large batches (1,000+ packages), consider splitting into multiple runs
• Keywords may be empty for many packages — check classifiers for categorization instead

Changelog

• v0.1 — Initial release with package metadata and download stats extraction