How to Scrape YouTube Comments from a Video to CSV

Before you scrape YouTube comments

You need UScraper as a local desktop app, one or more YouTube watch URLs, a folder where the CSV should be saved, and a short validation plan. Start with one video that has visible public comments. A small first run makes it easier to spot disabled comments, age checks, region gates, consent screens, or empty exports before you add a long list of URLs.

You also need a clear reason for collecting the data. YouTube comments are user-generated content. Public visibility does not automatically mean you can republish, sell, profile, or train models on the export. Keep the batch narrow, avoid private or restricted content, and get legal review for commercial, research, or model-training workflows.

Write down the source videos, purpose, fields needed, retention period, and who can access the CSV before you run the scraper. The best scraping workflow is the one you can explain later.

YouTube comments API vs scraper

There are three common ways to export YouTube comments to CSV: the official API, a Python script, or a no-code scraper. The right path depends on your team, the size of the job, and how much control you need over replies and pagination.

The official commentThreads.list endpoint is the primary API route for retrieving comment threads for a video. Google's comments implementation guide explains that commentThreads.list can request snippet for top-level comments or snippet,replies when you also want included replies. For full reply pagination, developers typically pair it with comments.list, which lists comments that match request parameters such as a parent comment ID.

How the YouTube comments scraper works

The template follows a readable browser workflow: Set Window Size -> Navigate -> Wait for Page Load -> handle consent -> scroll to comments -> wait for comment rows -> bounded scroll loop -> Structured Export -> Loop Continue. The Navigate block accepts multiple watch URLs. The Loop Continue block advances to the next URL after the current video's loaded comments are exported.

The important part is the bounded scroll loop. YouTube comments load dynamically, so the workflow scrolls until continuation rows stop appearing or the guard reaches 20 cycles. That prevents a single large video from running forever while still giving the page time to load a practical comment sample.

The JSON workflow definition is the authoritative source for the export shape. In the bundled template, the file name is youtube-video-comments-scraper.csv, the output mode is append, and the row selector is ytd-comment-thread-renderer.

{
  "project": {
    "name": "YouTube Video Comments Scraper"
  },
  "blocks": [
    { "title": "Navigate", "config": { "urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"] } },
    { "title": "Wait for Element", "config": { "selector": "ytd-comment-thread-renderer", "timeout": 90 } },
    {
      "title": "Structured Export",
      "config": {
        "rowSelector": "ytd-comment-thread-renderer",
        "fileName": "youtube-video-comments-scraper.csv",
        "includeHeaders": true,
        "fileMode": "append"
      }
    }
  ]
}

How to export YouTube comments to CSV

CSV fields from the YouTube comments scraper

The export is designed for analysis rather than archiving every possible YouTube object. Each row represents a loaded top-level comment thread with video context repeated beside the comment fields.

For adjacent workflows, browse the UScraper templates library, pair this with the YouTube Video List Scraper for video discovery, or read more no-code scraping tutorials in the UScraper blog.

Common issues when scraping YouTube comments

Frequently asked questions