# X Twitter (`canadesk/x-twitter`) Actor Collect Tweets and Usernames from X.com (Twitter). It's fast and costs little! - **URL**: https://apify.com/canadesk/x-twitter.md - **Developed by:** [Canadesk Support](https://apify.com/canadesk) (community) - **Categories:** Lead generation, SEO tools, News - **Stats:** 1,181 total users, 3 monthly users, 100.0% runs succeeded, 12 bookmarks - **User rating**: 1.00 out of 5 stars ## Pricing $10.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 #### Features - **Get Tweets by Username** [Input] ``` { "keyword": string, // Must be a username (e.g., elonmusk) "sincedate": string, // Optional "untildate": string, // Optional "maximum": integer // Optional } ``` [Output] ``` { "author": string, // Full name "verified": boolean, // Blue or Business badge "avatar": string, // Username profile picture "content": string, // Tweet description "time": string, // Date (MM-DD) "media": string, // Media attached "quote": string, // Quote attached "comments": integer || null, // Number of comments "reposts": integer || null, // Number of reposts "mentions": integer || null, // Number of quotes "likes": integer || null, // Number of likes "link": string, // Tweet URL "type": string // "tweet" or "retweet" or "tweet_w_media" or "tweet_w_quote" } ``` - **Search for Usernames** [Input] ``` { "keyword": string, // Must be a username (e.g., elonmusk) "maximum": integer // Optional } ``` [Output] ``` { "username": string, // X Twitter Username "fullname": string, // Full name "verified": boolean, // Blue or Business badge "avatar": string, // Username profile picture "content": string, // Tweet description "url": string, // Username URL "type": string // "username" } ``` - **Search for Tweets** [Input] ``` { "keyword": string, "sincedate": string, // Optional "untildate": string, // Optional "maximum": integer // Optional } ``` [Output] ``` { "author": string, // Full name "verified": boolean, // Blue or Business badge "avatar": string, // Username profile picture "content": string, // Tweet description "time": string, // Date (MM-DD) "media": string, // Media attached "quote": string, // Quote attached "comments": integer || null, // Number of comments "reposts": integer || null, // Number of reposts "mentions": integer || null, // Number of quotes "likes": integer || null, // Number of likes "link": string, // Tweet URL "type": string // "tweet" or "retweet" or "tweet_w_media" or "tweet_w_quote" } ``` ### Support Always use a high-quality or custom proxy, and make sure to wait between requests! Open a new issue or contact support. Please provide us with your run URL, and a screenshot of the original website output. Cheers! # Actor input Schema ## `process` (type: `string`): No description ## `keyword` (type: `string`): Username or Keyword to search for. ## `fromdate` (type: `string`): Only works in combination with Until date. Format: 2024-01-01 ## `untildate` (type: `string`): Also works on its own. Format: 2024-01-01 ## `maximum` (type: `integer`): No description ## `retry` (type: `integer`): No description ## `proxy` (type: `object`): Select proxies to be used by your crawler. ## Actor input object example ```json { "process": "gt", "keyword": "elonmusk", "maximum": 2, "retry": 2, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # 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 = { "keyword": "elonmusk", "fromdate": "", "untildate": "", "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("canadesk/x-twitter").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 = { "keyword": "elonmusk", "fromdate": "", "untildate": "", "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("canadesk/x-twitter").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 '{ "keyword": "elonmusk", "fromdate": "", "untildate": "", "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call canadesk/x-twitter --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=canadesk/x-twitter", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X Twitter", "description": "Collect Tweets and Usernames from X.com (Twitter). It's fast and costs little!", "version": "2.0", "x-build-id": "UIWxrXADxw71Bi4oF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/canadesk~x-twitter/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-canadesk-x-twitter", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/canadesk~x-twitter/runs": { "post": { "operationId": "runs-sync-canadesk-x-twitter", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/canadesk~x-twitter/run-sync": { "post": { "operationId": "run-sync-canadesk-x-twitter", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword" ], "properties": { "process": { "title": "Process", "enum": [ "gt", "su", "st" ], "type": "string", "description": "", "default": "gt" }, "keyword": { "title": "Keyword", "type": "string", "description": "Username or Keyword to search for." }, "fromdate": { "title": "Filter - Since date", "type": "string", "description": "Only works in combination with Until date. Format: 2024-01-01" }, "untildate": { "title": "Filter - Until date", "type": "string", "description": "Also works on its own. Format: 2024-01-01" }, "maximum": { "title": "Maximum pages", "minimum": 1, "maximum": 20, "type": "integer", "description": "", "default": 2 }, "retry": { "title": "Maximum retries", "minimum": 1, "maximum": 5, "type": "integer", "description": "", "default": 2 }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used by your crawler." } } }, "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 } } } } } } } } } } ```