You can access the Youtube Comments Scraper programmatically from your own 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.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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": ["https://www.youtube.com/watch?v=KrLj6nc516A"],
10    "proxyConfiguration": { "useApifyProxy": False },
11}
12
13# Run the Actor and wait for it to finish
14run = client.actor("scraply/youtube-comments-scraper").call(run_input=run_input)
15
16# Fetch and print Actor results from the run's dataset (if there are any)
17print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
18for item in client.dataset(run["defaultDatasetId"]).iterate_items():
19    print(item)
20
21# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Youtube Comments Scraper API in Python

The Apify API client for Python is the official library that allows you to use Youtube 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:

Youtube Comments Scraper API in JavaScript

Youtube Comments Scraper API through CLI

Youtube Comments Scraper OpenAPI definition

Youtube Comments Scraper API

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Effortlessly scrape YouTube video comments (and their replies, if you need them). Directly target one or more YouTube videos or specify a YouTube channel and let the scraper discover the videos for you. Easy to use and economical to run.

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Scrape YouTube comments fast and at scale. Extract comment text, likes, author info, timestamps, and replies from any video. Export to JSON, CSV. Perfect for sentiment analysis, research, or content strategy. Just $1 per 1,000 comments.