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TikTok Comments Scraper

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Pay $1.00 for 1,000 comments

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TikTok Comments Scraper

TikTok Comments Scraper

clockworks/tiktok-comments-scraper
Try for free

Pay $1.00 for 1,000 comments

Extract TikTok comments. Just add a TikTok URL and get TikTok video and profile data: comments, URLs, numbers of shares, followers, hashtags, hearts, video, and music metadata. Export scraped data, run the scraper via API, schedule and monitor runs or integrate with other tools.

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You can access the TikTok Comments Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youā€™ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "postURLs": ["https://www.tiktok.com/@bellapoarch/video/6862153058223197445"],
10    "commentsPerPost": 100,
11    "maxRepliesPerComment": 0,
12}
13
14# Run the Actor and wait for it to finish
15run = client.actor("clockworks/tiktok-comments-scraper").call(run_input=run_input)
16
17# Fetch and print Actor results from the run's dataset (if there are any)
18print("šŸ’¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
19for item in client.dataset(run["defaultDatasetId"]).iterate_items():
20    print(item)
21
22# šŸ“š Want to learn more šŸ“–? Go to ā†’ https://docs.apify.com/api/client/python/docs/quick-start

šŸ’¬ TikTok Comments Scraper API in Python

The Apify API client for Python is the official library that allows you to use TikTok Comments Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Apify

Actor Metrics

  • 520 monthly users

  • 71 stars

  • >99% runs succeeded

  • 3.3 hours response time

  • Created in Feb 2023

  • Modified 5 days ago