# Medium Scraper (`automation-lab/medium-scraper`) Actor Extract Medium articles by tag, author, or publication. Get title, author, date, tags, excerpt, thumbnail, and article content. No login required. JSON/CSV/Excel export. - **URL**: https://apify.com/automation-lab/medium-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** News - **Stats:** 3 total users, 2 monthly users, 33.3% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Medium Scraper **Medium Scraper** extracts articles, metadata, and content from [Medium.com](https://medium.com) — the world's largest publishing platform with 170M+ monthly readers. Scrape by tag/topic, author profile, or publication without any API key or login. Use it to monitor trending content, research thought leaders, analyze publishing patterns, or build content datasets — all from a single, no-code tool. ### What does Medium Scraper do? Medium Scraper reads Medium's public RSS feeds to collect article data in bulk. Point it at any Medium tag page (e.g., `medium.com/tag/artificial-intelligence`), author profile (e.g., `medium.com/@username`), or publication (e.g., `medium.com/towards-data-science`) and it returns structured JSON records for every article — title, author, publication date, tags, excerpt, thumbnail, and article content (for author/publication feeds). No browser automation, no API keys, no rate-limit headaches. The actor uses **pure HTTP** requests, making it extremely fast and cheap — 100 articles in under 5 seconds. ### Who is Medium Scraper for? **Content researchers & analysts** - Track what topics are trending in your industry week over week - Build content datasets for NLP models or sentiment analysis - Find the most-published authors in a niche for outreach **SEO & content marketing teams** - Monitor competitor publications and author output - Analyze which tags and topics drive the most engagement - Track new article publication frequency by author or tag **Investors & market researchers** - Follow thought leaders on specific investment themes (AI, biotech, fintech) - Monitor startup founders' public writing for product/strategy signals - Aggregate newsletter-style content from multiple sources automatically **Developers & data engineers** - Build content aggregation pipelines without scraping browser pages - Feed article data into vector databases for RAG (retrieval-augmented generation) - Power internal knowledge bases with curated Medium content ### Why use Medium Scraper? - 🚀 **Blazing fast** — pure RSS parsing, no browser overhead. 100 articles in ~1 second - 💰 **Extremely cheap** — HTTP-only, no proxy needed. The cheapest way to get Medium data - 🔑 **No API key required** — Medium's RSS feeds are fully public - 📦 **Ready-to-use data** — structured JSON/CSV/Excel export, no cleaning needed - 🏷️ **Full tag metadata** — every article's topic tags included - 📝 **Article content included** — full article text available for author/publication feeds - 🔄 **Scheduled runs** — monitor tags or authors on a cron schedule via Apify platform - 🔌 **5,000+ integrations** — connect to Google Sheets, Slack, Make, Zapier, Airtable and more ### What data can you extract? | Field | Description | Available | |-------|-------------|-----------| | `title` | Article headline | ✅ Always | | `url` | Full article URL (cleaned, no tracking params) | ✅ Always | | `author` | Author display name | ✅ Always | | `publicationDate` | ISO 8601 date (YYYY-MM-DD) | ✅ Always | | `tags` | Topic tags (e.g., `["python", "machine-learning"]`) | ✅ Always | | `excerpt` | Article preview snippet | ✅ Always | | `thumbnail` | Cover image URL | ✅ Always | | `id` | Unique Medium article ID | ✅ Always | | `content` | Full article text | ✅ Author/publication feeds | | `publicationName` | Publication name (if in a publication) | ✅ Always | | `isLocked` | Whether article is member-only | ✅ Always | | `clapCount` | Number of claps | ❌ Not in public feeds | | `readingTimeMinutes` | Estimated reading time | ❌ Not in public feeds | > **Note:** Clap counts and reading times are not exposed in Medium's public RSS feeds. This is a platform limitation, not a scraper limitation. ### How much does it cost to scrape Medium? This actor uses **pay-per-event** pricing — you only pay for articles you actually scrape. No monthly subscription. All platform costs are included. | | Free | Starter ($29/mo) | Scale ($199/mo) | Business ($999/mo) | |---|---|---|---|---| | **Per article** | $0.0023 | $0.002 | $0.00156 | $0.0012 | | **100 articles** | $0.23 | $0.20 | $0.156 | $0.12 | | **1,000 articles** | $2.30 | $2.00 | $1.56 | $1.20 | A run fee of $0.005 is charged once per run (covers initialization overhead). **Real-world cost examples:** | Input | Articles | Duration | Cost (Free tier) | |-------|----------|----------|-----------------| | 1 tag page | ~10 | ~1s | ~$0.03 | | 1 author profile | ~10 | ~1s | ~$0.03 | | 10 tag pages | ~100 | ~3s | ~$0.23 | **Free plan:** Apify gives you $5 in free credits. At $0.0023/article, that's **~2,100 articles free** to start. ### How to scrape Medium articles 1. Go to [Medium Scraper on Apify Store](https://apify.com/automation-lab/medium-scraper) 2. Click **Try for free** 3. In the **Start URLs** field, enter Medium URLs you want to scrape: - Tag page: `https://medium.com/tag/technology` - Author profile: `https://medium.com/@username` - Publication: `https://medium.com/towards-data-science` 4. Set **Max articles** (default: 50) 5. Click **Start** and wait for results (usually under 10 seconds) 6. Download results as JSON, CSV, or Excel from the **Dataset** tab **Example input for scraping a tag:** ```json { "startUrls": [ { "url": "https://medium.com/tag/artificial-intelligence" } ], "maxArticles": 100 } ```` **Example input for scraping an author profile:** ```json { "startUrls": [ { "url": "https://medium.com/@ev" } ], "maxArticles": 50 } ``` **Example input for multiple sources:** ```json { "startUrls": [ { "url": "https://medium.com/tag/python" }, { "url": "https://medium.com/tag/javascript" }, { "url": "https://medium.com/@towardsdatascience" } ], "maxArticles": 200 } ``` ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `startUrls` | Array | Required | Medium tag pages, author profiles, or publications to scrape | | `maxArticles` | Integer | 50 | Maximum number of articles to extract across all URLs | | `includeLockedArticles` | Boolean | true | Whether to include member-only (paywalled) articles | | `maxConcurrency` | Integer | 5 | Number of parallel feed requests | | `requestTimeoutSecs` | Integer | 30 | HTTP request timeout in seconds | | `proxy` | Object | None | Optional proxy configuration | **Supported URL formats:** | URL format | Example | |-----------|---------| | Tag page | `https://medium.com/tag/technology` | | Author profile | `https://medium.com/@username` | | Custom domain author | `https://username.medium.com` | | Publication | `https://medium.com/towards-data-science` | > **Direct article URLs** (e.g., `https://medium.com/p/abc123`) are not supported because Medium's Cloudflare protection blocks individual article pages without a real browser. Use tag/author/publication feeds to discover articles instead. ### Output examples **Article from tag feed:** ```json { "id": "ea82231fdcdc", "title": "18 Years on a MacBook: 3 Principles I Use Every Single Day", "url": "https://medium.com/macoclock/18-years-on-a-macbook-3-principles-i-use-every-single-day-ea82231fdcdc", "author": "Georg Plankl", "authorUrl": "", "publicationDate": "2026-04-04", "publicationName": null, "excerpt": "After 30,000 hours, three habits survived everything else — and they'll change how you work.", "thumbnail": "https://cdn-images-1.medium.com/max/600/1*8wF4i2sk4g8ypZ-uzyvhkA.jpeg", "clapCount": null, "responseCount": null, "readingTimeMinutes": null, "isLocked": false, "tags": ["mac", "productivity", "technology", "advice", "apple"], "content": null } ``` **Article from author feed (content included):** ```json { "id": "0126fa5c6ce8", "title": "Making \"Social\" Social Again", "url": "https://ev.medium.com/making-social-social-again-0126fa5c6ce8", "author": "Ev Williams", "authorUrl": "", "publicationDate": "2024-12-12", "publicationName": null, "excerpt": null, "thumbnail": "https://cdn-images-1.medium.com/max/1024/1*NMXyOoeQu3L1ZAXqf8QIYw.jpeg", "clapCount": null, "responseCount": null, "readingTimeMinutes": null, "isLocked": false, "tags": ["social", "relationships"], "content": "Announcing MoziEv Williams, Twitter and Medium Founder, Unveils New Social App I think it's tough to appreciate how much relationships determine the course of our lives..." } ``` ### Tips for best results - 🏷️ **Tag pages return the 10 most recent articles** — for a specific author's full history, use their profile URL - 📚 **Author profiles include full content** — Medium's author RSS feeds include `content:encoded` with the full article HTML converted to text - 🔄 **Schedule runs for monitoring** — use Apify's scheduler to run every hour/day and track new publications - 🧩 **Combine multiple tags** — add several tag URLs to capture articles across related topics in one run - 📊 **Filter by date in post-processing** — use `publicationDate` to filter to articles published in the last N days - 💡 **Use the `maxArticles` limit** — start with 10-20 to verify your URLs work before running large batches ### Integrations **Medium Scraper → Google Sheets** Use the [Google Sheets integration](https://apify.com/integrations) to automatically append new articles to a spreadsheet. Great for content calendars or competitive tracking dashboards. **Medium Scraper → Slack alerts** Connect via Make or Zapier to post new articles matching a tag to a Slack channel. Monitor when key authors or topics publish new content. **Medium Scraper → Vector database (RAG)** Export article content to Pinecone, Weaviate, or Chroma for semantic search. Power internal knowledge bases or AI assistants grounded in curated Medium content. **Scheduled monitoring** Set up a daily Apify schedule to scrape `medium.com/tag/your-industry` and detect new articles automatically. Combine with webhooks to trigger downstream workflows. **Medium Scraper → Airtable content database** Build a content research database — pipe article data into Airtable to track publications by tag, author, and date with built-in filtering and views. ### Using the Apify API #### Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('automation-lab/medium-scraper').call({ startUrls: [{ url: 'https://medium.com/tag/technology' }], maxArticles: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient(token="YOUR_APIFY_TOKEN") run = client.actor("automation-lab/medium-scraper").call( run_input={ "startUrls": [{"url": "https://medium.com/tag/technology"}], "maxArticles": 100, } ) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], item["author"], item["publicationDate"]) ``` #### cURL ```bash ## Start the actor run curl -X POST \ "https://api.apify.com/v2/acts/automation-lab~medium-scraper/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "startUrls": [{"url": "https://medium.com/tag/technology"}], "maxArticles": 100 }' ## Get results (replace DATASET_ID from the run response) curl "https://api.apify.com/v2/datasets/DATASET_ID/items?token=YOUR_APIFY_TOKEN" ``` ### Use with AI agents via MCP Medium Scraper is available as a tool for AI assistants that support the [Model Context Protocol (MCP)](https://docs.apify.com/platform/integrations/mcp). Add the Apify MCP server to your AI client — this gives you access to all Apify actors, including this one: #### Setup for Claude Code ```bash claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/medium-scraper" ``` #### Setup for Claude Desktop, Cursor, or VS Code Add this to your MCP config file: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=automation-lab/medium-scraper" } } } ``` Your AI assistant will use OAuth to authenticate with your Apify account on first use. #### Example prompts Once connected, try asking your AI assistant: - "Use automation-lab/medium-scraper to scrape the 50 most recent articles from medium.com/tag/artificial-intelligence and summarize the top themes" - "Scrape all articles by @ev on Medium and tell me what topics he writes about most" - "Get the latest 20 articles from the Towards Data Science publication and create a reading list with titles, authors, and links" Learn more in the [Apify MCP documentation](https://docs.apify.com/platform/integrations/mcp). ### Is it legal to scrape Medium? Medium's public RSS feeds (`medium.com/feed/...`) are designed for automated consumption — they're how RSS readers, aggregators, and tools like this one work. The data returned is the same data displayed on publicly accessible pages. **Best practices for responsible use:** - Only scrape publicly available content (this actor does not access member-only content) - Respect Medium's robots.txt and rate limits (this actor is rate-limited by default) - Do not use scraped content for spam or deceptive purposes - Attribution: always credit Medium and the original authors when republishing - Review [Medium's Terms of Service](https://policy.medium.com/medium-terms-of-service-9db0094a1e0f) for your specific use case This actor does not log in, does not bypass paywalls, and does not access private or member-only content. ### FAQ **How many articles can I scrape from one tag page?** Medium's tag RSS feeds return the 10 most recent articles per request. To get more articles from a topic, combine multiple tag URLs (e.g., `technology`, `software-engineering`, `programming`) or monitor the same tag over time with scheduled runs. **Why does some article content show as `null`?** Article content (`content` field) is only included in author profile and publication feeds — not in tag/topic feeds. Tag feeds only include a short snippet. Use an author profile URL (e.g., `medium.com/@username`) or publication URL (e.g., `medium.com/towards-data-science`) if you need full article text. **Why are clap counts not available?** Clap counts and reading times are not exposed in Medium's public RSS feeds — they're only available on individual article pages, which require JavaScript execution (Cloudflare protection). The actor uses RSS for reliability and speed. If you need clap counts, note that they change frequently anyway, making historical comparisons unreliable. **How fast does this scraper run?** Very fast. A single tag page (10 articles) takes about 1 second. Multiple sources run in parallel — 10 feeds with 10 articles each finishes in 2-3 seconds. This actor uses pure HTTP (no browser), making it among the fastest scrapers on Apify Store. **Why can't I scrape direct article URLs?** Individual article pages on `medium.com` are protected by Cloudflare's bot management, which requires JavaScript execution to pass. This actor uses HTTP-only requests (no browser), so article pages return a Cloudflare challenge instead of content. Workaround: scrape the author's profile feed to get all their articles, or use a tag feed to discover articles by topic. **Does it work with custom Medium domains?** Yes! If an author has a custom domain like `username.medium.com`, use that URL directly — the actor automatically converts it to the correct RSS feed URL. **Can I scrape member-only (paywalled) articles?** This actor collects metadata (title, author, date, tags, excerpt) for member-only articles from the feed. Full content of paywalled articles is not available without a Medium membership, so the `content` field will be `null` for locked articles. ### Other scrapers you might find useful - [Reddit Scraper](https://apify.com/automation-lab/reddit-scraper) — Collect posts and comments from subreddits - [Substack Scraper](https://apify.com/automation-lab/substack-scraper) — Extract newsletters and posts from Substack - [RSS Feed Reader](https://apify.com/automation-lab/rss-feed-reader) — Aggregate content from any RSS/Atom feed - [YouTube Transcript](https://apify.com/automation-lab/youtube-transcript) — Extract transcripts and metadata from YouTube videos - [Trustpilot Scraper](https://apify.com/automation-lab/trustpilot) — Scrape reviews and ratings from Trustpilot # Actor input Schema ## `startUrls` (type: `array`): Enter Medium URLs to scrape. Supported formats:
• Tag/topic pages: https://medium.com/tag/technology
• Author profiles: https://medium.com/@username or https://username.medium.com
• Publication pages: https://medium.com/towards-data-science
• Direct article URLs: https://medium.com/p/article-id ## `maxArticles` (type: `integer`): Maximum number of articles to scrape. Set to 0 for no limit. ## `includeLockedArticles` (type: `boolean`): Include articles that are behind the Medium paywall (member-only). Metadata (title, author, date, claps) is always available, but full content cannot be extracted for locked articles. ## `proxy` (type: `object`): Proxy settings. Datacenter proxies are recommended — Medium does not require residential proxies. ## `maxConcurrency` (type: `integer`): Maximum number of parallel requests. Higher values speed up scraping but may trigger rate limits. ## `requestTimeoutSecs` (type: `integer`): Timeout for each HTTP request in seconds. ## Actor input object example ```json { "startUrls": [ { "url": "https://medium.com/tag/technology" } ], "maxArticles": 10, "includeLockedArticles": true, "proxy": { "useApifyProxy": false }, "maxConcurrency": 3, "requestTimeoutSecs": 30 } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "startUrls": [ { "url": "https://medium.com/tag/technology" } ], "maxArticles": 10, "proxy": { "useApifyProxy": false }, "maxConcurrency": 3 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/medium-scraper").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 = { "startUrls": [{ "url": "https://medium.com/tag/technology" }], "maxArticles": 10, "proxy": { "useApifyProxy": False }, "maxConcurrency": 3, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/medium-scraper").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 '{ "startUrls": [ { "url": "https://medium.com/tag/technology" } ], "maxArticles": 10, "proxy": { "useApifyProxy": false }, "maxConcurrency": 3 }' | apify call automation-lab/medium-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/medium-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Medium Scraper", "description": "Extract Medium articles by tag, author, or publication. Get title, author, date, tags, excerpt, thumbnail, and article content. No login required. JSON/CSV/Excel export.", "version": "0.1", "x-build-id": "d5sbhawH1FAgdizbr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~medium-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-medium-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~medium-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-medium-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~medium-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-medium-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "🔗 Start URLs", "type": "array", "description": "Enter Medium URLs to scrape. Supported formats:
• Tag/topic pages: https://medium.com/tag/technology
• Author profiles: https://medium.com/@username or https://username.medium.com
• Publication pages: https://medium.com/towards-data-science
• Direct article URLs: https://medium.com/p/article-id", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxArticles": { "title": "Max articles", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of articles to scrape. Set to 0 for no limit.", "default": 50 }, "includeLockedArticles": { "title": "Include member-only articles", "type": "boolean", "description": "Include articles that are behind the Medium paywall (member-only). Metadata (title, author, date, claps) is always available, but full content cannot be extracted for locked articles.", "default": true }, "proxy": { "title": "⚙️ Proxy configuration", "type": "object", "description": "Proxy settings. Datacenter proxies are recommended — Medium does not require residential proxies." }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of parallel requests. Higher values speed up scraping but may trigger rate limits.", "default": 5 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Timeout for each HTTP request in seconds.", "default": 30 } } }, "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 } } } } } } } } } } ```