# npm & PyPI Package Scraper — Downloads, Health & Maintenance (`samwise.agency/package-intel`) Actor Package intelligence for npm and PyPI: download stats, publish recency, maintenance scores, license and repo metadata. Find abandoned dependencies, benchmark libraries, monitor your stack. Official APIs, keyless. - **URL**: https://apify.com/samwise.agency/package-intel.md - **Developed by:** [samwise.agency](https://apify.com/samwise.agency) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## npm & PyPI Package Scraper — Downloads, Health & Maintenance Dependency and market intelligence for the two biggest package ecosystems. Pulls **official registry data** (npm + PyPI) into one clean, unified schema: download trends, publish recency, maintenance signals, licenses, repos. **What you can extract:** - 📦 **Deep package lookups** — metadata + last-week/month/year downloads - 🔍 **npm keyword search** — with npm's own quality/popularity/maintenance scores - 🚨 **Maintenance signals** — `daysSinceLastPublish`, `deprecated`, version counts - ⚖️ **Compliance fields** — license, repository, homepage ### Quick start 1. Click **Run** — default input looks up `npm:express` and `pypi:requests` 2. Paste your own dependency list (one package per line) 3. Schedule monthly = automated dependency health audit ### Sample output ```json { "ecosystem": "npm", "name": "express", "url": "https://www.npmjs.com/package/express", "description": "Fast, unopinionated, minimalist web framework", "latestVersion": "5.1.0", "license": "MIT", "repository": "https://github.com/expressjs/express.git", "maintainersCount": 3, "versionsCount": 279, "createdAt": "2010-12-29T19:38:25.450Z", "lastPublishedAt": "2026-03-11T09:14:02.000Z", "daysSinceLastPublish": 131, "deprecated": false, "downloadsLastWeek": 32411890, "downloadsLastMonth": 138902114, "downloadsLastYear": 1620044120, "dependenciesCount": 27 } ```` ### Use cases - **Dependency audits** — flag abandoned packages (`daysSinceLastPublish` > 365) across your stack - **Dev-tool market research** — compare adoption of competing libraries over time - **Security/compliance** — license inventory for legal review - **Content & DevRel** — "state of X ecosystem" posts backed by real download data - **Investment research** — open-source traction signals for dev-tool startups ### Input reference | Field | Type | Notes | |---|---|---| | `packages` | array | `npm:name`, `pypi:name`, or bare name (tries both) | | `npmSearchQueries` | array | Keyword search with npm score fields | | `maxSearchResults` | integer | Cap per search | ### Pricing Pay per result row. Auditing a 100-dependency project costs well under a dollar. ### FAQ **Where does the data come from?** Official APIs only: registry.npmjs.org, api.npmjs.org (downloads), pypi.org JSON API, pypistats.org. **Scoped npm packages?** Supported — `npm:@scope/name` works. # Actor input Schema ## `packages` (type: `array`): Package names for full metadata + download stats. Prefix to target one ecosystem: 'npm:express', 'pypi:requests'. No prefix = try both. ## `npmSearchQueries` (type: `array`): Keyword searches on the npm registry (returns quality/popularity/maintenance scores per package). ## `maxSearchResults` (type: `integer`): Cap per npm search query. ## Actor input object example ```json { "packages": [ "npm:express", "pypi:requests" ], "npmSearchQueries": [], "maxSearchResults": 25 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "packages": [ "npm:express", "pypi:requests" ], "npmSearchQueries": [] }; // Run the Actor and wait for it to finish const run = await client.actor("samwise.agency/package-intel").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "packages": [ "npm:express", "pypi:requests", ], "npmSearchQueries": [], } # Run the Actor and wait for it to finish run = client.actor("samwise.agency/package-intel").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "packages": [ "npm:express", "pypi:requests" ], "npmSearchQueries": [] }' | apify call samwise.agency/package-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=samwise.agency/package-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "npm & PyPI Package Scraper — Downloads, Health & Maintenance", "description": "Package intelligence for npm and PyPI: download stats, publish recency, maintenance scores, license and repo metadata. Find abandoned dependencies, benchmark libraries, monitor your stack. Official APIs, keyless.", "version": "0.1", "x-build-id": "RLyTNo5Wj6hAehWn5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/samwise.agency~package-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-samwise.agency-package-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/samwise.agency~package-intel/runs": { "post": { "operationId": "runs-sync-samwise.agency-package-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/samwise.agency~package-intel/run-sync": { "post": { "operationId": "run-sync-samwise.agency-package-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "packages": { "title": "Packages (deep lookup)", "type": "array", "description": "Package names for full metadata + download stats. Prefix to target one ecosystem: 'npm:express', 'pypi:requests'. No prefix = try both.", "default": [ "npm:express", "pypi:requests" ], "items": { "type": "string" } }, "npmSearchQueries": { "title": "npm search queries", "type": "array", "description": "Keyword searches on the npm registry (returns quality/popularity/maintenance scores per package).", "default": [], "items": { "type": "string" } }, "maxSearchResults": { "title": "Max results per search", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Cap per npm search query.", "default": 25 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```