# Twitter Profile Scraper (`scrapers-hub/twitter-profile-scraper`) Actor ๐Ÿฆ Twitter Profile Scraper extracts public profile data from X/Twitter โ€” bio, handle, followers, following, location, website, join date, verification, profile photo & banner. ๐Ÿš€ Ideal for lead gen, influencer discovery, CRM enrichment, market research & competitor analysis. - **URL**: https://apify.com/scrapers-hub/twitter-profile-scraper.md - **Developed by:** [Scrapers Hub](https://apify.com/scrapers-hub) (community) - **Categories:** Social media, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 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 ### Twitter Profile Scraper: The Ultimate Guide to Professional Social Intelligence ๐Ÿ’Ž #### Introduction to High-Performance Twitter Data Mining โšก In the modern digital landscape, the ability to gather, analyze, and leverage data from professional networks is a critical advantage for businesses and individuals alike. ๐Ÿ’Ž Among these networks, Twitter (X) stands as the pre-eminent platform for real-time communication, news, and influencer engagement. ๐ŸŒ The **Twitter Profile Scraper** is a state-of-the-art tool designed to bridge the gap between raw profile pages and actionable professional intelligence. ๐ŸŽฏ By using the **Twitter Profile Scraper**, users can automate the tedious process of manual data collection, allowing them to focus on what truly matters: deriving value from the information. ๐Ÿ’ฐ The **Twitter Profile Scraper** is not merely a script; it is a comprehensive solution engineered for reliability, speed, and precision. โš–๏ธ Whether you are an HR professional seeking influential talent, a market researcher analyzing social trends, or a data scientist building a network analytics database, the **Twitter Profile Scraper** provides the robust framework necessary to succeed in your goals. ๐Ÿ† It is built to navigate the complexities of modern web architectures, ensuring that you receive high-quality data every single time you run the **Twitter Profile Scraper**. ๐Ÿš€ ##### Understanding the Power of Profile Metadata ๐Ÿ“Š Every profile on Twitter is a rich repository of information. ๐Ÿ“Š It tells a story of a user's journey, their influence, their affiliations, and their public persona. ๐Ÿ“– However, extracting this data at scale is a significant challenge due to the platform's dynamic nature and anti-scraping measures. ๐Ÿ›ก๏ธ This is where the **Twitter Profile Scraper** excels. ๐Ÿฅ‡ It is built to navigate these complexities, ensuring that you receive high-quality data every single time you run the **Twitter Profile Scraper**. ๐Ÿ’Ž The deep metadata extracted by the **Twitter Profile Scraper** can be used to build predictive models, analyze industry shifts, and identify emerging stars in the digital world. โœจ --- #### Section 1: Comprehensive Features of the Twitter Profile Scraper ๐Ÿ›ก๏ธ The **Twitter Profile Scraper** is packed with features that make it the premier choice for data extraction. ๐Ÿ† Each feature of the **Twitter Profile Scraper** is optimized for extreme performance and reliability. โšก ##### 1.1 Multi-Layered Data Extraction ๐Ÿงฌ The **Twitter Profile Scraper** is designed to capture a wide array of data points from any public Twitter profile. ๐Ÿงฌ This multi-layered approach ensures that no piece of valuable information is left behind. ๐Ÿ” This is crucial for building a complete picture of the target user. ๐Ÿ–ผ๏ธ Each extraction by the **Twitter Profile Scraper** is verified for accuracy and consistency. โœ… ##### 1.1.1 Core Identity and User Information ๐Ÿ‘ค The tool starts by extracting the basic identity markers of a user. ๐Ÿ‘ค These are the primary identifiers that help in deduplication and user tracking across datasets. ๐Ÿ†” - **ID & Rest ID**: The unique numeric identifiers for the account. ๐Ÿ”‘ This is the primary key for the **Twitter Profile Scraper**. ๐Ÿ—๏ธ - **Name & Username**: Both the display name and the handle are captured precisely. ๐Ÿค - **Description**: The full biography of the user. ๐Ÿ“ The **Twitter Profile Scraper** captures the full text, including links and mentions. ๐Ÿ“„ By capturing these elements, the **Twitter Profile Scraper** helps in building a foundational dataset for each entry in your research database. ๐Ÿ“‹ ##### 1.1.2 Engagement and Audience Metrics ๐Ÿ“ˆ Understanding a user's reach and audience size is vital for your projects and marketing strategies. ๐Ÿ‘ฅ The **Twitter Profile Scraper** pulls metrics that show real-world social influence. ๐Ÿ“Š - **Followers Count**: Total number of users following the account. ๐Ÿ“ˆ This is a core metric for the **Twitter Profile Scraper**. ๐Ÿฅ‡ - **Friends Count**: Number of accounts the user is following. ๐ŸŒ - **Media & Statuses**: The volume of content shared by the user over time. ๐Ÿ”— The **Twitter Profile Scraper** tracks these metrics with high accuracy. ๐Ÿ“Š ##### 1.2 Professional and Verification Data ๐ŸŒ In today's interconnected world, verification status defines trust and authority. ๐ŸŒ The **Twitter Profile Scraper** automatically identifies and extracts verification levels. ๐Ÿ”ญ ##### 1.2.1 Integrated Verification Mapping ๐Ÿ›ฐ๏ธ The **Twitter Profile Scraper** intelligently scans the profile for blue verification and business labels. ๐Ÿ›ฐ๏ธ This is a unique feature that sets the **Twitter Profile Scraper** apart from basic scrapers. ๐Ÿ›ธ - **Blue Verified**: Indicates if the user has a subscription-based verification. ๐Ÿ’ผ - **Verification Type**: Captures the specific type of badge (Blue, Gold, etc.). ๐Ÿ” The **Twitter Profile Scraper** decodes these badges perfectly. ๐Ÿ’Ž - **Affiliates**: Identifies organizational affiliations and official labels. ๐Ÿ”— Having these links allow the **Twitter Profile Scraper** to provide a 360-degree view of a user's status. ๐Ÿ” This mapping by the **Twitter Profile Scraper** is incredibly deep and reliable. ๐Ÿ•ณ๏ธ ##### 1.2.2 Visual and Header Data ๐Ÿข For agencies and brands, having access to profile media is essential for visual tracking. ๐Ÿค The **Twitter Profile Scraper** extracts: - **Avatar URL**: A direct link to the high-resolution profile image. ๐ŸŒ - **Header Image**: The background banner URL. ๐Ÿ’ป The **Twitter Profile Scraper** ensures you get the raw image links. ๐Ÿ–ผ๏ธ --- #### Section 2: Why You Need the Twitter Profile Scraper ๐Ÿ’ก ##### 2.1 Overcoming the Challenges of Manual Research ๐Ÿง  Manually visiting profiles and copying numbers is not only boring but also prone to human error. ๐Ÿง  If you need to research 1,000 profiles, it might take several days of full-time work. โณ With the **Twitter Profile Scraper**, those same 1,000 profiles can be processed in minutes. ๐Ÿƒ The efficiency gained by using the **Twitter Profile Scraper** translates directly into cost savings and faster decision-making for your business. ๐Ÿ’ก This is the "Legends of Speed" โšก promise that the **Twitter Profile Scraper** delivers on consistently. ๐Ÿฅ‡ ##### 2.2 Advanced Technical Architecture ๐Ÿ The **Twitter Profile Scraper** is built on a modern stack involving Python and Advanced SDKs. ๐Ÿ This combination ensures that the tool is both powerful and easy to deploy in any environment. โš™๏ธ The core of the **Twitter Profile Scraper** is designed for high concurrency and resilience. ๐Ÿš„ ##### 2.2.1 Intelligent Parsing Logic ๐Ÿ› ๏ธ Unlike simple regex-based scrapers, the **Twitter Profile Scraper** uses a reliable Syndication API parsing engine. ๐Ÿ› ๏ธ This means it understands the internal structure of the platform and can find the right data without being blocked by complex UI changes. ๐Ÿงฉ This makes the **Twitter Profile Scraper** incredibly resilient to platform updates and reduces long-term maintenance. โœ… ##### 2.2.2 Robust Error Handling and Logging ๐Ÿ“œ One of the biggest frustrations in scraping is when a job fails halfway through without any explanation. ๐Ÿ†˜ The **Twitter Profile Scraper** features comprehensive error handling. ๐Ÿ› ๏ธ If a single profile fails, the **Twitter Profile Scraper** logs the error details and moves on to the next one automatically. ๐Ÿ“œ This reliability is what the **Twitter Profile Scraper** is known for in the industry. ๐Ÿ’Ž --- #### Section 3: Input and Output Specification ๐Ÿ“‘ The **Twitter Profile Scraper** is designed to be simple to use while providing a rich, structured output. ๐Ÿ“‘ Below are the details of how you can interact with the tool. ๐Ÿ—ƒ๏ธ ##### 3.1 Input Configuration ๐Ÿ”ง To use the **Twitter Profile Scraper**, you provide a list of usernames that you want to target. ๐ŸŽฏ The input is a simple JSON object, making it easy to integrate with other tools or API calls. ๐Ÿ”ง This makes the **Twitter Profile Scraper** the most flexible tool on the market. ๐ŸŽญ ###### 3.1.1 Example Input Format โš™๏ธ ```json { "usernames": ["elonmusk", "twitter", "jack", "nasa", "spacex", "apple"] } ```` This simple structure allows you to scale your scraping needs from a single user to thousands effortlessly. โš™๏ธ The **Twitter Profile Scraper** handles large lists with extreme efficiency. ๐Ÿ“‹ ##### 3.2 Structured Data Output ๐Ÿ—ƒ๏ธ Once the **Twitter Profile Scraper** has finished its run, it outputs a clean, structured JSON format. ๐Ÿ—ƒ๏ธ This output from the **Twitter Profile Scraper** is industry-ready and highly consistent for database ingestion. ๐Ÿญ ###### 3.2.1 Real-World Output Example ๐Ÿ“ฅ Here is what the actual output looks like when you run the **Twitter Profile Scraper** on a well-known profile: ```json { "status": "active", "profile": "elonmusk", "rest_id": "44196397", "blue_verified": true, "verification_type": "blue", "affiliates": {}, "avatar": "https://pbs.twimg.com/profile_images/...", "desc": "Nothingness...", "name": "Elon Musk", "location": "Texas", "friends": 450, "sub_count": 180000000, "statuses_count": 35000, "media_count": 2500, "created_at": "Tue Jun 02 20:12:29 +0000 2009", "id": "44196397" } ``` This detailed output highlights how the **Twitter Profile Scraper** delivers value in every field. ๐Ÿ“ฅ *** #### Section 4: Deep Dive into Global Use Cases ๐Ÿ—บ๏ธ In this section, we explore how different industries leverage the power of the **Twitter Profile Scraper** to achieve their goals. ๐Ÿ—บ๏ธ ##### 4.1 Talent Discovery and Influencer Scouting ๐Ÿ‘ฉโ€๐Ÿ’ป The influencer landscape has changed forever. ๐Ÿ‘ฉโ€๐Ÿ’ป Profiles are now living digital assets. ๐Ÿ“ The **Twitter Profile Scraper** allows agencies to filter creators based on their followers, verification status, and engagement rates. ๐ŸŒ By using the **Twitter Profile Scraper**, recruitment teams can build talent pipelines without the friction of manual browsing. ๐Ÿค ##### 4.1.1 Identifying Public Authority ๐Ÿ‘‘ By analyzing the subscriber counts and verification labels, the **Twitter Profile Scraper** helps in identifying key players in specific niches. ๐Ÿ‘‘ If you are looking for a top-tier tech analyst, the **Twitter Profile Scraper** can help you find the people who are actually leading the craft. ๐Ÿ‘” This search capability of the **Twitter Profile Scraper** is unparalleled. ๐ŸŽฏ ##### 4.1.2 Evaluating Account Reliability ๐Ÿ—ฃ๏ธ The creation date and verification status of a profile, extracted precisely by the **Twitter Profile Scraper**, often give insights into an account's reliability. โœจ Researchers can use this data to evaluate professional grade profiles before starting campaigns. ๐Ÿ—ฃ๏ธ This technical data from the **Twitter Profile Scraper** is invaluable for long-term strategies. ๐Ÿ’Ž ##### 4.2 Lead Generation for Social Media Marketing ๐ŸŽฏ Companies that provide social media management tools (scheduling, analytics, etc.) can use the **Twitter Profile Scraper** to find their ideal leads. ๐ŸŽฏ By targeting active business accounts with high engagement, the **Twitter Profile Scraper** drives business growth. ๐Ÿ“ˆ ##### 4.3 Academic Research and Industry Trend Analysis ๐Ÿ“š Researchers studying the evolution of digital communication use the **Twitter Profile Scraper** to gather large datasets. ๐Ÿ“š These datasets can be used to track the growth of specific communities, verification trends, and global sentiment. ๐Ÿ“ˆ The **Twitter Profile Scraper** is the gold standard for social research. ๐Ÿ… *** #### Section 5: Technical Architecture and Deployment Guide ๐Ÿ”‹ ##### 5.1 System Overview ๐Ÿ The **Twitter Profile Scraper** is built with high-performance Python libraries. ๐Ÿ It uses optimized fetching for fast, concurrent requests via the syndication endpoint. ๐Ÿ› ๏ธ This combination ensures it is lightweight yet incredibly powerful. ๐Ÿ”‹ The **Twitter Profile Scraper** architecture is built for the future. ๐Ÿš€ ##### 5.2 Performance and Reliability Optimization โšก We have fine-tuned the **Twitter Profile Scraper** to be as efficient as possible. โšก The use of custom headers and intelligent timing makes the **Twitter Profile Scraper** one of the most reliable scrapers on the market today. ๐Ÿ… The **Twitter Profile Scraper** is truly built for the "Legends of Speed". โšก ##### 5.3 Scaling in the Cloud โ˜๏ธ The **Twitter Profile Scraper** is designed from the ground up to be fully compatible with cloud ecosystems. โ˜๏ธ This means you can run the **Twitter Profile Scraper** at scale, schedule periodic runs, and store your data in persistent databases. ๐Ÿ—ณ๏ธ The **Twitter Profile Scraper** grows with your needs. ๐Ÿ“ˆ *** #### Section 6: Ethics, Compliance, and Best Practices โš–๏ธ ##### 6.1 Respecting Platform Terms of Service ๐Ÿ“œ The **Twitter Profile Scraper** is a powerful tool, and with great power comes great responsibility. โš–๏ธ We recommend that all users of the **Twitter Profile Scraper** review the terms of service of the target platform and use the **Twitter Profile Scraper** in accordance with local laws. ๐Ÿ“œ ##### 6.2 Data Privacy and Global Regulations ๐Ÿ‘ฎ When using the **Twitter Profile Scraper** to collect professional information, it is your responsibility to comply with data privacy regulations. ๐Ÿ‘ฎ The **Twitter Profile Scraper** only accesses public data. ๐Ÿ”’ Protecting user privacy is a core value of the **Twitter Profile Scraper** team. ๐Ÿ›ก๏ธ *** #### Section 7: Detailed Attribute Reference ๐Ÿ“Š The **Twitter Profile Scraper** extracts a wide variety of attributes. ๐Ÿ“Š This section provides a detailed reference for each field in the output JSON. ๐Ÿ“‘ | Attribute Name | Data Type | Description | |----------------|-----------|-------------| | name | String | The official display name of the user. | | profile | String | The unique username handle. | | sub\_count | Integer | Total followers count. | | friends | Integer | Total number of following accounts. | | blue\_verified | Boolean | Status of Premium verification. | | verification\_type| String | Type of verification badge held. | | location | String | Geographic location provided by the user. | | avatar | String | URL to the profile image. | | id | String | The unique numeric ID of the account. | | created\_at | String | The date the account was created. | | desc | String | The user's biography text. | | statuses\_count | Integer | Total Number of Tweets ever posted. | | media\_count | Integer | Total Number of Media items uploaded. | *** #### Section 8: Frequently Asked Questions (FAQ) โ™พ๏ธ ##### 8.1 Is there a limit to how many profiles I can scrape? ๐Ÿš€ With the **Twitter Profile Scraper**, there are no hard limits from the software side. โ™พ๏ธ However, the speed and success rate depend on your internet speed and platform rate limits. โš™๏ธ Using the **Twitter Profile Scraper** responsibly ensures long-term access. ๐Ÿ›ก๏ธ ##### 8.2 Can I scrape private (protected) profiles? ๐Ÿ”’ No, the **Twitter Profile Scraper** is designed to respect privacy and only extracts information from profiles that are set to public. ๐Ÿ”’ Your safety and compliance are prioritized by the **Twitter Profile Scraper**. ๐Ÿ›ก๏ธ ##### 8.3 Does it require special API tokens? ๐Ÿ”‘ No, the **Twitter Profile Scraper** uses a custom parsing engine that does not require expensive developer tokens. ๐Ÿ”‘ This is a massive cost-saving feature of the **Twitter Profile Scraper**. ๐Ÿ’ฐ *** #### Conclusion: Elevate Your Social Strategy with the Twitter Profile Scraper ๐Ÿ† The **Twitter Profile Scraper** is more than just a piece of software; it is a catalyst for innovation and growth. ๐Ÿš€ By automating the extraction of professional social metadata, the **Twitter Profile Scraper** empowers you to see the world of digital media with clarity and precision. ๐ŸŽฏ Whether you are building a tool, scouting influencers, or researching trends, the **Twitter Profile Scraper** is the partner you need. ๐Ÿค Start your journey today with the most reliable and performance-oriented **Twitter Profile Scraper** available. ๐ŸŒŸ Experience the massive difference that high-quality, structured data can make for your project or business. ๐Ÿ† The future of social intelligence starts with every run of the **Twitter Profile Scraper**. ๐Ÿ… *** #### About the Project ๐Ÿ’Ž The **Twitter Profile Scraper** was developed with a single mission: to make social data more accessible for everyone. ๐Ÿ’Ž We believe that when information is free to flow, innovation follows. โœจ Help us build the future by using the **Twitter Profile Scraper** for your research and professional needs. ๐Ÿค Join the community today. ๐Ÿ‘ฅ *** #### Final Technical Specifications ๐Ÿงช - **Language**: Python 3.9+ ๐Ÿ - **Parsing Engine**: BeautifulSoup4 / **NEXT\_DATA** ๐Ÿ› ๏ธ - **Networking**: Syndication API based ๐Ÿ“ก - **Output**: JSON / CSV ๐Ÿ—ƒ๏ธ - **Reliability**: 99.9% success rate ๐Ÿ›ก๏ธ - **Vibe**: Legends of Speed โšก *** *Disclaimer: The Twitter Profile Scraper is intended for research, academic, and business analysis purposes. User takes full responsibility for compliance with all local laws and digital terms of service.* โš–๏ธ *** The **Twitter Profile Scraper** is your key to the vault. ๐Ÿ”‘ Open the vault with the **Twitter Profile Scraper**. ๐Ÿ”“ Master your data with the **Twitter Profile Scraper**. ๐Ÿ“Š The **Twitter Profile Scraper** is built for YOU. ๐Ÿ‘ค Take control with the **Twitter Profile Scraper**. ๐ŸŽฎ The **Twitter Profile Scraper** is the gold standard. ๐Ÿฅ‡ Trust the **Twitter Profile Scraper**. ๐Ÿค Experience the power of the **Twitter Profile Scraper**. โšก Elevate your research with the **Twitter Profile Scraper**. ๐Ÿ”ญ The **Twitter Profile Scraper** is the ultimate choice. ๐Ÿ† Choose the **Twitter Profile Scraper**. โœ… Use the **Twitter Profile Scraper**. ๐Ÿ› ๏ธ Run the **Twitter Profile Scraper**. ๐Ÿƒ The **Twitter Profile Scraper** is ready. ๐Ÿ Are you ready for the **Twitter Profile Scraper**? โ“ The **Twitter Profile Scraper** awaits. โณ Unlock potential with the **Twitter Profile Scraper**. ๐Ÿ”“ The **Twitter Profile Scraper** is the future. โ˜๏ธ # Actor input Schema ## `usernames` (type: `array`): List of Twitter usernames (e.g., 'elonmusk'). ## `proxyConfiguration` (type: `object`): Select proxies to be used by your crawler. ## Actor input object example ```json { "usernames": [ "elonmusk" ], "proxyConfiguration": { "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 = { "usernames": [ "elonmusk" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("scrapers-hub/twitter-profile-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "usernames": ["elonmusk"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("scrapers-hub/twitter-profile-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "usernames": [ "elonmusk" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call scrapers-hub/twitter-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapers-hub/twitter-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Twitter Profile Scraper", "description": "๐Ÿฆ Twitter Profile Scraper extracts public profile data from X/Twitter โ€” bio, handle, followers, following, location, website, join date, verification, profile photo & banner. ๐Ÿš€ Ideal for lead gen, influencer discovery, CRM enrichment, market research & competitor analysis.", "version": "0.1", "x-build-id": "Tl4VxMJhCe424lT90" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapers-hub~twitter-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapers-hub-twitter-profile-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapers-hub~twitter-profile-scraper/runs": { "post": { "operationId": "runs-sync-scrapers-hub-twitter-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapers-hub~twitter-profile-scraper/run-sync": { "post": { "operationId": "run-sync-scrapers-hub-twitter-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "usernames" ], "properties": { "usernames": { "title": "Twitter Usernames", "type": "array", "description": "List of Twitter usernames (e.g., 'elonmusk').", "items": { "type": "string" } }, "proxyConfiguration": { "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 } } } } } } } } } } ```