Youtube Comments Scraper (Pay Per Result)
Pay $0.50 for 1,000 comments
Youtube Comments Scraper (Pay Per Result)
Pay $0.50 for 1,000 comments
YouTube Comments Scraper, the ultimate solution for extensive YouTube comments data retrieval. With its high-speed scraping abilities, it provides unmatched effectiveness and thoroughness. Additionally, its cost-effectiveness is unmatched, priced at just $0.50 per 1000 comments!
You can access the Youtube Comments Scraper (Pay Per Result) 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, you’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 "startUrls": [
10 "https://www.youtube.com/watch?v=xuCn8ux2gbs",
11 "https://www.youtube.com/shorts/vVTa1_hm4n4",
12 ],
13 "sort": "top",
14 "maxItems": 1000,
15 "customMapFunction": "(object) => { return {...object} }",
16}
17
18# Run the Actor and wait for it to finish
19run = client.actor("apidojo/youtube-comments-scraper").call(run_input=run_input)
20
21# Fetch and print Actor results from the run's dataset (if there are any)
22print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
23for item in client.dataset(run["defaultDatasetId"]).iterate_items():
24 print(item)
25
26# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
Youtube Comments Scraper (Pay Per Result) API in Python
The Apify API client for Python is the official library that allows you to use Youtube Comments Scraper (Pay Per Result) API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
pip install apify-client
Other API clients include:
- 34 monthly users
- 4 stars
- 99.4% runs succeeded
- 1.1 days response time
- Created in Jan 2024
- Modified about 8 hours ago