How to Scrape TikTok Using Python Playwright

TikTok has emerged as a vast repository of entertaining content in the realm of social media, with millions of users worldwide. The data obtained after web scraping TikTok can be invaluable for researchers, marketers, and data enthusiasts.

In this article, let’s learn how to scrape TikTok’s ‘For You’ page using Playwright browser automation and extract data points such as likes, shares, comments, usernames, and descriptions.

Prerequisites

You need to set up an environment and gather the necessary tools before web scraping TikTok.

1. Python Installation

Install Python on your system. Here Python version 3.10 is used.

2. Install Third Party Libraries

You’ll need the Python library:

Playwright – Playwright is used for browser-based automation. It is used for web scraping as well as interacting with web APIs.

Installation:

Copypip install playwright

Install the required browsers:

Copyplaywright install

Understanding TikTok

Before learning how to scrape data from TikTok, you should first understand TikTok’s ‘For You’ page. This page showcases trending and personalized content that is tailored to each user’s preferences. Once you scrape data from TikTok, it can be used for analysis, ranging from user engagement metrics to content trends.

1. Importing Libraries

For web scraping TikTok using Python you need to import necessary libraries.

Copyimport asyncio
import csv
from playwright.async_api import Playwright, async_playwright

Note that ‘asyncio’ is for asynchronous execution, ‘csv’ for handling CSV files, and ‘Playwright’ for browser automation.

2. Browser Launch and Page Creation

The code lines mentioned can launch a Chromium browser, create a new browser context, and open a new page within that context.

Copybrowser = await playwright.chromium.launch(headless=False)
context = await browser.new_context()
page = await context.new_page()

3. Navigation and Element Interaction

Homepage

Copyawait page.goto("https://www.TikTok.com/foryou", timeout=120000)

Pop-up to be Handled

Copyawait page.locator('//div[@id="loginContainer"]').wait_for()
await page.get_by_role("link", name="Continue as guest").click()
await page.wait_for_timeout(2000)

Here, you navigate to the TikTok “For You” page, wait for the login container to appear, click on the “Continue as guest” link, and wait for 2 seconds.

4. Data Extraction

You can extract usernames, descriptions, likes, comments, shares, and other data from the TikTok page using specific CSS selectors.

Copyusernames = await extract_text(page, 'h3[data-e2e="video-author-uniqueid"]')
descriptions = await extract_text(page, 'div[data-e2e="video-desc"]')
likes = await extract_text(page, 'strong[data-e2e="like-count"]')
comments = await extract_text(page, 'strong[data-e2e="comment-count"]')
shares = await extract_text(page, 'strong[data-e2e="share-count"]')
others = await extract_text(page, 'strong[data-e2e="undefined-count"]')

4.1 extract_text(page, selector)

Based on a provided CSS selector, this function extracts text content from elements on a web page. It also accepts the input parameters page and selector.

Note that Page is a playwright page object on which the extraction is performed, and selector is an XPath or CSS selector used to identify the elements containing the required data.

Copyasync def extract_text(page, selector):
    elements = await page.query_selector_all(selector)
    texts = []
    for element in elements:
        texts.append(await element.inner_text() if element else "")
    return texts

5. CSV Writing

Write the extracted data into a CSV file.

Copywrite_to_csv([usernames, descriptions, likes, comments, shares, others])

5.1 write_to_csv(data_lists)

This function is used to write data to a CSV file. Here data_lists are lists of data to be written to the CSV file, each list corresponding to a column.

Copydef write_to_csv(data_lists):
    headers = ["Username", "Description", "Likes", "Comments", "Shares", "Others"]
    filename = "instagram_extracted_data.csv"
    with open(filename, "w", newline="") as csvfile:
        writer = csv.writer(csvfile)
        writer.writerow(headers)
        for row in zip(*data_lists):
            writer.writerow(row)

6. Browser Closure

As a final step, close both the browser context and the browser itself.

Copyawait context.close()
await browser.close()

Access the complete code for the TikTok scraper on GitHub.

Wrapping Up

Web scraping TikTok using Python Playwright offers numerous opportunities for data analysis, content monitoring, and trend tracking. But TikTok web scraping is challenging due to its anti-scraping measures like rate limits and IP blocking.

Moreover, the video content and login requirements of TikTok make it even more difficult, especially for large-scale web scraping. In such situations, you need an enterprise-grade web scraping service provider like ScrapeHero.

The pre-built crawlers and APIs of ScrapeHero Cloud can provide you with hassle-free, affordable, fast, and reliable solutions for your scraping needs. ScrapeHero web scraping services can develop custom solutions for your businesses, providing unmatched data quality and consistency.

Frequently Asked Questions