# Stack Overflow Scraper - Questions & Tags (`benthepythondev/stackoverflow-scraper`) Actor Search Stack Overflow (or any Stack Exchange site) by keyword: question title, link, tags, score, views, answer count, accepted flag, asker and dates. Filter by tag, sort by relevance/votes/activity. Reliable via the public Stack Exchange API, no key. - **URL**: https://apify.com/benthepythondev/stackoverflow-scraper.md - **Developed by:** [ben](https://apify.com/benthepythondev) (community) - **Categories:** Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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 ## 💬 Stack Overflow Scraper — Questions, Tags & Votes Search **Stack Overflow** — or any Stack Exchange site — by keyword and get clean, structured question data for every result: title, direct link, tags, score, view count, answer count, answered and accepted-answer flags, the asker's name and reputation, and the creation and last-activity dates. Filter to a specific tag and sort by relevance, votes, activity or creation date to surface exactly the questions you need. The actor is powered by the public **Stack Exchange API**, so it is fast and reliable with no browser, no login and no API key. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n. ### 🔎 What is the Stack Overflow Scraper? Stack Overflow is the world's largest developer Q&A community, and the wider Stack Exchange network covers everything from server administration to data science, math and security. This actor turns a keyword search into a structured dataset: give it terms like `asyncio` or `pandas merge`, optionally restrict to a tag such as `python`, choose a sort order, and it returns the top matching questions as tidy rows. Because it queries the official Stack Exchange API instead of scraping HTML, results are consistent and well-typed, and every row carries the engagement signals that matter — score, views, answers and whether an accepted answer exists — so you can instantly rank questions by popularity or spot unanswered gaps worth writing about. #### What data does it extract? - **Question ID** and **title** - **Link** — the direct URL to the question - **Site** — the Stack Exchange site the question is from - **Tags** — the full list of tags on the question - **Score** — net upvotes - **View count** — total views - **Answer count** — number of answers - **Is answered** — whether the question has any answers - **Has accepted answer** — whether an answer has been accepted - **Created date** and **last-activity date** - **Asker** — the display name of the author - **Asker reputation** — the author's Stack Exchange reputation - **Query** — the search term that surfaced the row ### ⬇️ Input | Field | Type | Description | |-------|------|-------------| | `searchTerms` | array | Keywords to search, e.g. `asyncio`, `pandas merge`. One or many. | | `site` | string | Stack Exchange site to search. Default `stackoverflow` (e.g. `serverfault`, `superuser`, `datascience`). | | `tagged` | string | Optional: restrict results to a tag, e.g. `python`. | | `sort` | string | Result ordering: `relevance`, `votes`, `activity` or `creation`. Default `relevance`. | | `maxPerTerm` | integer | Max questions to return per search term. Default `20`, up to `100`. | #### Example input ```json { "searchTerms": ["asyncio", "pandas merge"], "site": "stackoverflow", "tagged": "python", "sort": "votes", "maxPerTerm": 50 } ```` ### ⬆️ Output Each question is one clean row (view as a **table**, or export **JSON / CSV / Excel**): ```json { "question_id": 123456, "title": "What is the difference between asyncio and threading?", "link": "https://stackoverflow.com/questions/123456/what-is-the-difference-between-asyncio-and-threading", "site": "stackoverflow", "tags": ["python", "asyncio", "multithreading", "concurrency"], "score": 412, "view_count": 285000, "answer_count": 7, "is_answered": true, "has_accepted_answer": true, "created_date": "2016-03-12", "last_activity_date": "2025-11-02", "asker": "jdoe", "asker_reputation": 18452, "query": "asyncio" } ``` ### 💡 Use cases - 👩‍💻 **Developer & product research** — find the most-viewed, highest-voted questions about a library, framework or error to understand what users struggle with. - 📈 **Tag & topic monitoring** — track activity around the tags that matter to your project, tool or open-source library over time. - ✍️ **Content & SEO** — discover high-traffic, poorly-answered questions to target with blog posts, docs and tutorials. - 📊 **Q\&A datasets & NLP** — build structured corpora of developer questions for analysis, benchmarking or LLM training. ### ❓ FAQ **How do I scrape Stack Overflow questions?** Enter one or more `searchTerms`, optionally set `tagged` and `sort`, and Run. You get structured rows with title, link, tags, score, views, answers and asker. **Do I need an API key or login?** No. It uses the public Stack Exchange API — just provide keywords. **Can I search other Stack Exchange sites?** Yes — set `site` to any site slug, e.g. `serverfault`, `superuser`, `datascience`, `askubuntu` or `math`. **Can I filter by tag?** Yes — set `tagged` (e.g. `python`) to restrict results to questions carrying that tag. **How can I sort the results?** By `relevance`, `votes`, `activity` or `creation` date, so you can rank by popularity or find the newest questions. **Does it return answer bodies?** No — it returns question metadata and engagement signals. Full answer text can bloat results, so it is omitted by design; the `link` takes you to the full thread. **How many questions can it return?** Up to your `maxPerTerm` cap (max 100) for each search term. **Can I run it on a schedule or via API?** Yes — schedule recurring runs on Apify, call it via the API/SDK, or connect it to Make, Zapier or n8n. **How does pricing work?** Pay per question returned — no subscription, no fixed monthly fee. **Is it legal?** It uses the public Stack Exchange API. User-contributed content on the network is licensed under Creative Commons (CC BY-SA) — attribute it accordingly and follow Stack Exchange's terms. ### 🔗 You might also like - **[GitHub Repository Scraper](https://apify.com/benthepythondev/github-repository-scraper)** — repos, stars, topics & metadata. - **[PyPI Scraper](https://apify.com/benthepythondev/pypi-scraper)** — Python package metadata & versions. - **[Dev.to Articles Scraper](https://apify.com/benthepythondev/devto-articles-scraper)** — developer articles by tag. - **[Hacker News Scraper](https://apify.com/benthepythondev/hacker-news-scraper)** — tech & startup discussions. *** **Keywords:** stack overflow scraper, stack exchange api, developer questions, q\&a data, programming questions, tag monitoring, stackoverflow data, dev research, coding questions, question scraper, technical q\&a, stackexchange scraper, developer dataset, stackoverflow api, serverfault scraper, superuser scraper, q\&a dataset, stack overflow questions, developer content research, so scraper # Actor input Schema ## `searchTerms` (type: `array`): Keywords to search for, e.g. 'asyncio', 'pandas merge'. ## `site` (type: `string`): Site to search, e.g. 'stackoverflow', 'serverfault', 'superuser'. ## `tagged` (type: `string`): Optional: restrict to a tag, e.g. 'python'. ## `sort` (type: `string`): Result ordering. ## `maxPerTerm` (type: `integer`): Max questions to return per search term. ## Actor input object example ```json { "searchTerms": [ "asyncio" ], "site": "stackoverflow", "sort": "relevance", "maxPerTerm": 20 } ``` # 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 = { "searchTerms": [ "asyncio" ], "site": "stackoverflow", "sort": "relevance" }; // Run the Actor and wait for it to finish const run = await client.actor("benthepythondev/stackoverflow-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 = { "searchTerms": ["asyncio"], "site": "stackoverflow", "sort": "relevance", } # Run the Actor and wait for it to finish run = client.actor("benthepythondev/stackoverflow-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 '{ "searchTerms": [ "asyncio" ], "site": "stackoverflow", "sort": "relevance" }' | apify call benthepythondev/stackoverflow-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=benthepythondev/stackoverflow-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stack Overflow Scraper - Questions & Tags", "description": "Search Stack Overflow (or any Stack Exchange site) by keyword: question title, link, tags, score, views, answer count, accepted flag, asker and dates. Filter by tag, sort by relevance/votes/activity. Reliable via the public Stack Exchange API, no key.", "version": "1.0", "x-build-id": "8lEmOPA0PkpRIDfOI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/benthepythondev~stackoverflow-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-benthepythondev-stackoverflow-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/benthepythondev~stackoverflow-scraper/runs": { "post": { "operationId": "runs-sync-benthepythondev-stackoverflow-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/benthepythondev~stackoverflow-scraper/run-sync": { "post": { "operationId": "run-sync-benthepythondev-stackoverflow-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "Search terms", "type": "array", "description": "Keywords to search for, e.g. 'asyncio', 'pandas merge'.", "items": { "type": "string" } }, "site": { "title": "Stack Exchange site", "type": "string", "description": "Site to search, e.g. 'stackoverflow', 'serverfault', 'superuser'.", "default": "stackoverflow" }, "tagged": { "title": "Tagged (filter)", "type": "string", "description": "Optional: restrict to a tag, e.g. 'python'." }, "sort": { "title": "Sort by", "enum": [ "relevance", "votes", "activity", "creation" ], "type": "string", "description": "Result ordering.", "default": "relevance" }, "maxPerTerm": { "title": "Max questions per term", "minimum": 1, "maximum": 100, "type": "integer", "description": "Max questions to return per search term.", "default": 20 } } }, "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 } } } } } } } } } } ```