# Twitter (X.com) Scraper Unlimited: No Limits (`emt_getdataforu/twitter-scraper-lite`) Actor Introducing Twitter Scraper Unlimited, the most comprehensive Twitter data extraction solution available. Our enterprise-grade scraper offers unmatched capabilities with a transparent event-based pricing model, making it perfect for both small-scale and large-scale data extraction needs. - **URL**: https://apify.com/emt\_getdataforu/twitter-scraper-lite.md - **Developed by:** [EMT Crawler](https://apify.com/emt_getdataforu) (community) - **Categories:** Social media, Other, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.00001 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Actor mẫu — Free token pool + actor Store Gọi **bất kỳ actor free** trên Apify Store; **token** lấy từ Google Doc (xoay khi hết quota). Form **Input** clone từ actor gốc — **không sửa code** khi đổi actor. Chi tiết nhân bản: **[CLONE.md](./CLONE.md)** ### Nhân bản nhanh ```bash ## 1 lần apify secrets add GOOGLE_SERVICE_ACCOUNT '{"type":"service_account",...}' apify login ## Mỗi actor Store mới — chỉ 1 lệnh (+ apify push) npm run setup -- clockworks~tiktok-comments-scraper apify push ```` Sửa tay tối thiểu: `template.config.json` → `targetActorId`. ### Cách hoạt động ``` Input (form clone từ Store) → Actor proxy → API + token từ Google Doc → Actor Store → Dataset ``` - Token: Google Doc `KEY`, mỗi dòng `apify_api_...` - Hết free: thử dòng tiếp theo - Config: `template.config.json` + secret `GOOGLE_SERVICE_ACCOUNT` ### File quan trọng | File | Khi clone | |------|-----------| | `template.config.json` | Đổi `targetActorId` | | `npm run setup -- user~actor` | Tự cập nhật input schema + actor.json | | `src/*` | **Không sửa** | | Google Doc | Thêm/bớt token (không push) | ### Test local `input.json` — field theo actor vừa `setup` (xem `.actor/input_schema.json`). ```bash set GOOGLE_SERVICE_ACCOUNT={"type":"service_account",...} npm start ``` # Actor input Schema ## `searchTerms` (type: `array`): If you add search terms, the scraper will find and extract tweets that mention those terms. Alternatively, see further down to scrape by Twitter URL. ## `sort` (type: `string`): Sorts search results. If you are getting low results, try Top instead of Latest. Latest + Top runs both simultaneously to maximize results but may return some duplicate tweets. ## `maxItems` (type: `integer`): This value lets you set the maximum number of tweets to retrieve. Twitter has a default limit of around 800 tweets per query. Check the README for workarounds. ## `start` (type: `string`): Scrape tweets starting from this date ## `end` (type: `string`): Scrape tweets until this date ## `twitterHandles` (type: `array`): You can add the twitter handles of specific profiles you want to scrape. This is a shortcut so that you don't have to add full username URLs like https://twitter.com/apify ## `startUrls` (type: `array`): This lets you tell the scraper where to start. You can enter Twitter URLs one by one. You can also link to or upload a text file with a list of URLs ## `includeSearchTerms` (type: `boolean`): If selected, a field will be added to each tweets about the search term that was used to find it. ## Actor input object example ```json {} ``` # 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("emt_getdataforu/twitter-scraper-lite").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 = {} # Run the Actor and wait for it to finish run = client.actor("emt_getdataforu/twitter-scraper-lite").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 '{}' | apify call emt_getdataforu/twitter-scraper-lite --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=emt_getdataforu/twitter-scraper-lite", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter (X.com) Scraper Unlimited: No Limits", "description": "Introducing Twitter Scraper Unlimited, the most comprehensive Twitter data extraction solution available. Our enterprise-grade scraper offers unmatched capabilities with a transparent event-based pricing model, making it perfect for both small-scale and large-scale data extraction needs.", "version": "0.3", "x-build-id": "uifkwC5iNKT1WyY6r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/emt_getdataforu~twitter-scraper-lite/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-emt_getdataforu-twitter-scraper-lite", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/emt_getdataforu~twitter-scraper-lite/runs": { "post": { "operationId": "runs-sync-emt_getdataforu-twitter-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/emt_getdataforu~twitter-scraper-lite/run-sync": { "post": { "operationId": "run-sync-emt_getdataforu-twitter-scraper-lite", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "What search terms do you want to scrape?", "type": "array", "description": "If you add search terms, the scraper will find and extract tweets that mention those terms. Alternatively, see further down to scrape by Twitter URL.", "items": { "type": "string" } }, "sort": { "title": "Do you want to filter by content?", "enum": [ "Top", "Latest", "Latest + Top" ], "type": "string", "description": "Sorts search results. If you are getting low results, try Top instead of Latest. Latest + Top runs both simultaneously to maximize results but may return some duplicate tweets." }, "maxItems": { "title": "Maximum number of tweets", "type": "integer", "description": "This value lets you set the maximum number of tweets to retrieve. Twitter has a default limit of around 800 tweets per query. Check the README for workarounds." }, "start": { "title": "Tweets from this date", "type": "string", "description": "Scrape tweets starting from this date" }, "end": { "title": "Tweets until this date", "type": "string", "description": "Scrape tweets until this date" }, "twitterHandles": { "title": "Do you want to scrape by Twitter handle?", "type": "array", "description": "You can add the twitter handles of specific profiles you want to scrape. This is a shortcut so that you don't have to add full username URLs like https://twitter.com/apify", "items": { "type": "string" } }, "startUrls": { "title": "Do you want to scrape by Twitter URL?", "type": "array", "description": "This lets you tell the scraper where to start. You can enter Twitter URLs one by one. You can also link to or upload a text file with a list of URLs", "items": { "type": "string" } }, "includeSearchTerms": { "title": "Include Search Terms", "type": "boolean", "description": "If selected, a field will be added to each tweets about the search term that was used to find it." } } }, "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 } } } } } } } } } } ```