# Dev.to Articles & Developer Leads Scraper (`mangudai/devto-articles-developer-leads-scraper`) Actor Scrape Dev.to articles by tag, author, top, or latest and extract developer leads: author name, GitHub, X/Twitter, website, and location. No login or API key. Export to JSON, CSV, or Excel. - **URL**: https://apify.com/mangudai/devto-articles-developer-leads-scraper.md - **Developed by:** [MangudΓ€i](https://apify.com/mangudai) (community) - **Categories:** Developer tools, Lead generation, Open source - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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.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 ## Dev.to Articles & Developer Leads Scraper Pull articles from [Dev.to](https://dev.to) (the Forem developer community) and turn them into structured data and developer leads. No login, no cookies, no API key. The scraper reads the public Dev.to API and respects its robots rules and rate limits. ### What it does Give it a tag, an author, a "top" period, or the latest feed. For every article you get the post details plus the author's public profile: name, GitHub, X/Twitter, personal website, and location. That mix works for developer marketing, DevRel research, content analysis, and building lists of developers who write about a topic. ### Search modes - By tag: every article under a tag, for example `python`, `webdev`, `rust`. - By author: everything published by one username. - Top: highest-ranked articles over the last day, week, month, or year. - Latest: the freshest posts across Dev.to. ### Input | Field | Description | | --- | --- | | mode | tag, author, top, or latest | | tag | Tag to scrape in tag mode | | username | Author username in author mode | | topDays | Ranking window in top mode (1, 7, 30, 365) | | maxItems | Cap on articles returned | | enrichAuthors | Fetch each author's profile for lead fields | ### Output One row per article: - Article: `title`, `url`, `slug`, `description`, `publishedAt`, `tags`, `positiveReactions`, `comments`, `readingTimeMinutes`, `coverImage`, `canonicalUrl`, `organization` - Author lead: `authorName`, `authorUsername`, `authorProfileUrl`, `authorGithub`, `authorTwitter`, `authorWebsite`, `authorLocation`, `authorSummary`, `authorJoinedAt` Export to JSON, CSV, or Excel, run on a schedule, or call it from the API. ### Notes Author profiles are cached during a run, so scraping many posts from the same person costs one profile lookup. Only public data is collected. # Actor input Schema ## `mode` (type: `string`): How to select articles: by tag, by author username, by top-ranked over a period, or the latest feed. ## `tag` (type: `string`): Tag to scrape when mode is 'By tag' (for example python, javascript, webdev). ## `username` (type: `string`): Dev.to username to scrape when mode is 'By author' (for example ben). ## `topDays` (type: `string`): Ranking window when mode is 'Top'. ## `maxItems` (type: `integer`): Maximum number of articles to return. ## `enrichAuthors` (type: `boolean`): Fetch each unique author's public profile to add name, GitHub, X/Twitter, website, and location. ## Actor input object example ```json { "mode": "tag", "tag": "javascript", "topDays": "7", "maxItems": 100, "enrichAuthors": true } ```` # Actor output Schema ## `results` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("mangudai/devto-articles-developer-leads-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("mangudai/devto-articles-developer-leads-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call mangudai/devto-articles-developer-leads-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mangudai/devto-articles-developer-leads-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Dev.to Articles & Developer Leads Scraper", "description": "Scrape Dev.to articles by tag, author, top, or latest and extract developer leads: author name, GitHub, X/Twitter, website, and location. No login or API key. Export to JSON, CSV, or Excel.", "version": "0.0", "x-build-id": "zOwGFOSIy76LcGSeM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mangudai~devto-articles-developer-leads-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mangudai-devto-articles-developer-leads-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mangudai~devto-articles-developer-leads-scraper/runs": { "post": { "operationId": "runs-sync-mangudai-devto-articles-developer-leads-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mangudai~devto-articles-developer-leads-scraper/run-sync": { "post": { "operationId": "run-sync-mangudai-devto-articles-developer-leads-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "mode": { "title": "Search mode", "enum": [ "tag", "author", "top", "latest" ], "type": "string", "description": "How to select articles: by tag, by author username, by top-ranked over a period, or the latest feed.", "default": "tag" }, "tag": { "title": "Tag", "type": "string", "description": "Tag to scrape when mode is 'By tag' (for example python, javascript, webdev).", "default": "javascript" }, "username": { "title": "Author username", "type": "string", "description": "Dev.to username to scrape when mode is 'By author' (for example ben)." }, "topDays": { "title": "Top period", "enum": [ "1", "7", "30", "365" ], "type": "string", "description": "Ranking window when mode is 'Top'.", "default": "7" }, "maxItems": { "title": "Max articles", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of articles to return.", "default": 100 }, "enrichAuthors": { "title": "Enrich author leads", "type": "boolean", "description": "Fetch each unique author's public profile to add name, GitHub, X/Twitter, website, and location.", "default": true } } }, "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 } } } } } } } } } } ```