How to Scrape TikTok Profiles and Posts: 5 Proven Methods for 2026

How to scrape TikTok profiles and posts with 5 tools: 1. BrowserAct 2. TikTok Research API 3. TikTokApi (Python) 4. BeautifulSoup + requests 5. Selenium --- Ever wondered how marketing agencies build databases of thousands of TikTok creators overnight? Or how competitor analysis tools track viral trends before they hit the mainstream? TikTok has become the world's most downloaded app, with over 1.5 billion monthly active users. For marketers, researchers, and brands, the platform is a goldmine o

Method 1: BrowserAct — The No-Code TikTok Scraper (Best for Beginners)

BrowserAct is a no-code browser automation platform that lets you scrape TikTok profiles, posts, and engagement data without writing a single line of code. Its pre-built TikTok Influencer Scraper template extracts comprehensive creator and video data using AI-powered extraction—just describe what you need in plain English.

What makes BrowserAct different from traditional scrapers is its real-browser infrastructure. Instead of sending HTTP requests that TikTok's anti-bot systems easily detect, BrowserAct runs actual browser sessions with stealth browsing, built-in residential proxies, and CAPTCHA handling. This means you can access TikTok pages that block conventional scrapers, and the AI automatically adapts when page structures change—no selector maintenance required.

Steps to Scrape TikTok with BrowserAct

Follow this quick start guide to scrape TikTok profiles and posts:

1. Sign up and access the template: Create a free account at BrowserAct, then navigate to the TikTok Influencer Scraper template in the template library. Click "Use this template" to load it into your workspace.

1. Configure input parameters: Set tiktok_link to a TikTok search results URL (e.g., https://www.tiktok.com/search/user?q=fitness) or a direct profile URL (e.g., https://www.tiktok.com/@username). Set max_results to the number of profiles or videos you want to extract (e.g., 20, 50, or 100).

1. Run the workflow: Click "Start" to execute. BrowserAct initializes a real browser session, navigates to your target page, and begins extracting data. The AI-powered extraction engine identifies creator profiles and video cards automatically—you don't need to specify CSS selectors or XPath.

1. Review and export data: Once the run completes, review the extracted data in the results panel. Export in your preferred format: CSV for Excel analysis, JSON for API integration, Google Sheets for team collaboration, or via Webhook for real-time processing.

1. Automate and integrate (optional): Schedule recurring runs (daily, weekly, monthly) for continuous monitoring. Connect BrowserAct to Make, n8n, or Zapier to automatically push TikTok data into your CRM, Slack, or data warehouse.

For advanced builds, you can customize the workflow by adding Loop nodes for infinite scrolling, Extract Data nodes with custom field prompts, or login-aware nodes that handle TikTok's age-gate and CAPTCHA challenges. The platform's visual workflow builder makes it easy to adapt the template to your specific needs.

What Data Can You Extract?

The TikTok Influencer Scraper template extracts both creator profile data and video analytics in a single run:

• Creator Profiles: Username, handle, profile URL, real-time follower count, following count, total likes, bio description, verification status (✓), account type (Personal/Business/Creator), external links (Instagram, YouTube, website), and privacy status (Public/Private).
• Video Analytics: View count, likes, comments, shares, video title, description, hashtags, posted date, video duration, sound/music information, user mentions, engagement rate, and Duet/Stitch availability.

Outputs are available in formats like JSON, CSV, XML, or Markdown, making it easy to integrate scraped data into existing analytics pipelines, CRM systems, or AI model training workflows.

Pros

• No coding required—describe what you need in plain English
• Real browser sessions with stealth browsing and residential proxies
• AI-powered extraction that adapts to page changes automatically
• Pre-built template ready in minutes (30-60 credits per run)
• Flexible export formats: CSV, JSON, Google Sheets, Webhook
• Built-in scheduling and integration with Make, n8n, Zapier

Cons

• Credit-based pricing may add up for very large-scale extraction (10,000+ profiles)
• Cloud-based—no offline execution

Ready to try it? Sign up for BrowserAct's free trial and start scraping TikTok profiles today!

Method 2: TikTok Research API (Official and Compliant)

TikTok offers a Research API for academic researchers who need structured access to public TikTok data. This is the most compliant method available, but it comes with strict eligibility requirements and rate limits.

Steps to Scrape TikTok with the Research API

1. Check eligibility: The Research API is currently limited to academic researchers affiliated with accredited universities. You'll need to submit an application describing your research objectives, institutional affiliation, and data handling practices.

1. Apply for access: Visit the TikTok Research API portal and submit your application. Approval typically takes 1-2 weeks, and not all applications are accepted.

1. Set up authentication: Once approved, register your application to receive client credentials. Implement OAuth 2.0 authentication to obtain access tokens for API calls.

1. Query the API: Use the API endpoints to search for videos by hashtag, username, or keyword. Each endpoint returns structured JSON with fields like video ID, view count, like count, comment count, share count, and creator username.

1. Handle rate limits and pagination: The Research API enforces strict rate limits (typically 1,000 requests per day for most endpoints). Implement proper pagination using cursors and respect the daily quota to avoid being throttled.

import requests
 
# Authenticate
auth_response = requests.post(
    "https://open.tiktokapis.com/v2/oauth/token/",
    data={
        "client_key": "YOUR_CLIENT_KEY",
        "client_secret": "YOUR_CLIENT_SECRET",
        "grant_type": "client_credentials",
    }
)
access_token = auth_response.json()["access_token"]
 
# Search for videos by hashtag
headers = {"Authorization": f"Bearer {access_token}"}
response = requests.post(
    "https://open.tiktokapis.com/v2/research/video/query/",
    headers=headers,
    json={
        "query": {
            "and": [
                {"operation": "IN", "field_name": "hashtag_name", "field_values": ["ai"]}
            ]
        },
        "max_count": 20,
        "fields": ["id", "view_count", "like_count", "comment_count", "share_count", "username"]
    }
)
 
videos = response.json()["data"]["videos"]
for video in videos:
    print(f"@{video['username']}: {video['view_count']} views, {video['like_count']} likes")

Pros

• Fully compliant with TikTok's terms of service
• Structured, reliable JSON responses
• No risk of IP bans or CAPTCHAs
• Official documentation and support
• Access to engagement metrics not available via web scraping

Cons

• Restricted to academic researchers—commercial use not permitted
• Strict daily rate limits (1,000 requests/day)
• Limited to video data; no creator profile fields (follower count, bio, etc.)
• Application approval process takes 1-2 weeks

Method 3: TikTokApi Python Library (Open-Source)

TikTokApi is an unofficial Python library that reverse-engineers TikTok's internal API endpoints to extract data. It's popular among developers who need more flexibility than the official API offers but don't want to build a scraper from scratch.

Steps to Scrape TikTok with TikTokApi

1. Install the library: Run pip install TikTokApi to install the package. You'll also need a Playwright browser installation: python -m playwright install chromium.

1. Configure browser context: TikTokApi uses Playwright to generate the necessary headers and tokens for API requests. Initialize a browser context with appropriate user-agent and proxy settings.

1. Scrape user profiles: Use the user module to extract profile data including follower count, following count, total likes, bio, and verification status.

1. Scrape user videos: Use the user.videos() method to paginate through a creator's video posts, extracting view counts, likes, comments, and shares for each video.

1. Handle anti-bot detection: Rotate proxies, add random delays between requests, and use the library's built-in verification token generation to avoid being blocked.

from TikTokApi import TikTokApi
import asyncio
import json
 
async def scrape_tiktok_profiles():
    async with TikTokApi() as api:
        await api.create_sessions(
            num_sessions=1,
            sleep_after=3,
            headless=True,
            browser="chromium",
            proxy="http://user:pass@proxy:8080"
        )
 
        # Scrape a user profile
        user = api.user("chefboyrc")
        user_info = await user.info()
        print(f"Username: @{user_info['userInfo']['user']['uniqueId']}")
        print(f"Followers: {user_info['userInfo']['stats']['followerCount']}")
        print(f"Total Likes: {user_info['userInfo']['stats']['heartCount']}")
        print(f"Bio: {user_info['userInfo']['user']['signature']}")
 
        # Scrape their videos
        async for video in user.videos(count=10):
            print(f"Video: {video.as_dict['desc']}")
            print(f"  Views: {video.as_dict['stats']['playCount']}")
            print(f"  Likes: {video.as_dict['stats']['diggCount']}")
            print(f"  Comments: {video.as_dict['stats']['commentCount']}")
 
asyncio.run(scrape_tiktok_profiles())

Pros

• Free and open-source (MIT license)
• Access to both profile data and video metrics
• Active community and regular updates
• Supports hashtag search, sound search, and trend discovery
• Built-in proxy and session management

Cons

• Breaks frequently when TikTok updates its internal API
• Requires proxy rotation to avoid IP bans
• Playwright dependency adds complexity to deployment
• No guarantee of data completeness or accuracy

Method 4: BeautifulSoup + Requests (Lightweight and Customizable)

For developers who want maximum control over what data to extract, using Python's requests and BeautifulSoup libraries to parse TikTok's HTML is a lightweight approach. However, TikTok's heavy reliance on JavaScript rendering means this method has significant limitations.

Steps to Scrape TikTok with BeautifulSoup

1. Install dependencies: Run pip install requests beautifulsoup4 lxml to install the required packages.

1. Inspect TikTok's page structure: Open a TikTok profile page in your browser's developer tools. You'll notice that most data is loaded dynamically via JavaScript—initial HTML contains minimal structured data.

1. Extract embedded JSON data: TikTok embeds some initial data in a