The best YouTube comment scraper depends on whether you need top-level comments only or full reply context. This comparison covers Octoparse, Apify, Bright Data, scraper APIs, scripts, the official YouTube Data API, and UScraper's YouTube Comments and Replies Scraper template.
Decision frame
What changes when replies matter
A basic YouTube comments scraper can stop at top-level rows. A YouTube replies scraper has to open reply drawers, expand read-more controls, pair each reply with its parent comment, and preserve the source video context.
Searches for how to scrape YouTube comments usually split into these lanes:
- Official API access through
commentThreads.listandcomments.list. - Cloud actors such as Apify YouTube comments actors.
- No-code SaaS templates such as Octoparse.
- Managed products such as Bright Data or Scrapingdog.
- Local desktop workflows such as UScraper templates.
- Custom scripts and open-source projects.
The practical question is not "can this collect comments?" It is "will the rows preserve parent comment, reply text, video URL, timing, and a maintenance path your team can own?"
Side-by-side
YouTube comments scraper alternatives compared
| Option | Best fit | Hosting | Code | Output | Price model | Main trade-off |
|---|---|---|---|---|---|---|
| UScraper YouTube Comments and Replies Scraper | Known watch URLs to local CSV | Local desktop app | No code | CSV | Free template; app licensing applies | Best for supervised local exports, not cloud crawling |
| Octoparse YouTube comments template | Hosted no-code tasks | Vendor cloud and app workflow | No code | Excel, CSV, JSON | SaaS plan and task limits | Convenient, with less local custody |
| Apify YouTube comments actors | Actors, datasets, APIs, schedules | Apify cloud | Low to medium | JSON, CSV, Excel, API | Platform usage plus actor pricing | Strong automation, variable cost |
| Bright Data YouTube comments scraper | Managed extraction at scale | Vendor infrastructure | Low to medium | API or dataset | Usage or dataset pricing | Powerful, often heavy for one CSV |
| Scrapingdog YouTube Comment API | Scraper API responses | API provider | Code | JSON | API usage plan | Good API path, not visual CSV |
| YouTube Data API | Sanctioned integrations | Google API | Code | JSON | Quota plus engineering time | Needs pagination and reply handling |
| Open-source scripts | Custom collection | Local or self-hosted | High | TXT, CSV, JSON | Engineering time | Full control and full maintenance |
UScraper wins in a narrower job: run a visible local workflow and save reply-aware CSV rows to a folder you choose.
Where UScraper wins
When UScraper is the better YouTube replies scraper
UScraper is strongest when the deliverable is a spreadsheet and the operator needs to see what happened. The YouTube Comments and Replies Scraper template opens each watch URL, scrolls to lazy-load comments, expands visible reply and read-more controls, creates normalized export rows, and appends them to youtube-comments-replies-scraper.csv.
The visual flow matters during QA. If the CSV is empty, you can inspect whether YouTube showed a sign-in gate, comments were disabled, replies stayed collapsed, or a selector stopped matching.
Source URLs, browser state, and CSV output remain in the desktop workflow unless you add a sync or upload step. The template JSON is free to import; UScraper itself is licensed.
Choose UScraper when reply rows need to repeat the parent comment fields so analysts can filter, code, deduplicate, or audit conversations in Excel or Sheets.
Choose Apify, Bright Data, Scrapingdog, or a custom service when the job needs cloud queues, API delivery, retries, proxy infrastructure, and monitoring.
Choose the YouTube Data API when policy, quota-backed endpoints, OAuth, documented responses, and developer contracts matter more than no-code CSV export.
API fit
When the YouTube Data API is the safer choice
The official API is not just another competitor. commentThreads.list returns comment threads for a video, while comments.list can retrieve replies by parent comment. Production code also has to handle page tokens, quotas, and errors.
Use the API for product features, customer dashboards, or repeatable integrations that need sanctioned access and predictable JSON. Use a scraper only when browser-visible collection fits your legal, privacy, and platform review.
Output
Export shape summary and JSON workflow sample
There is no bundled CSV sample for this workflow. The authoritative sample is the exported JSON definition: multi-URL Navigate, reply expansion script, synthetic row selector, and Structured Export columns.
| CSV column group | Columns | Why it matters |
|---|---|---|
| Source video | video_url, video_title | Ties rows to the watch URL. |
| Parent comment | comment_user, content, comment_time, like_count, dislike_count | Preserves thread context. |
| Reply fields | reply_user, reply_content, reply_comment_time, reply_like_count, reply_dislike_count, reply_count | Shows who replied and what loaded. |
| Audit fields | post_comment_count, CrawlTime, comment_url | Supports QA and reruns. |
{
"project": {
"name": "YouTube Comments Replies Scraper",
"description": "Best-effort scraper for public YouTube video comment threads."
},
"blocks": [
{
"title": "Navigate",
"config": {
"urls": [
"https://www.youtube.com/watch?v=xBBAD407zzU",
"https://www.youtube.com/watch?v=WOuzDxHdz6I"
]
}
},
{
"title": "Inject JavaScript",
"config": {
"waitForCompletion": true,
"timeout": 150
}
},
{
"title": "Structured Export",
"config": {
"rowSelector": "[data-uscraper-comment-row]",
"fileName": "youtube-comments-replies-scraper.csv",
"includeHeaders": true,
"fileMode": "append",
"columns": [
"video_url",
"video_title",
"comment_user",
"content",
"comment_time",
"like_count",
"reply_user",
"reply_content",
"reply_comment_time",
"reply_like_count",
"post_comment_count",
"CrawlTime",
"reply_count",
"comment_url"
]
}
}
]
}
Selection guide
Which YouTube comments scraper should you choose?
Choose UScraper for defined video lists, no-code local CSV, and reply text beside parent comment context. Choose Octoparse for hosted no-code tasks, Apify for actors and datasets, Bright Data or a scraper API for managed scale, and scripts for parser ownership.
For adjacent workflows, browse the template library, read the YouTube comments and replies tutorial, or compare options in the UScraper blog.
FAQ
Frequently asked questions
The best choice depends on the operating model. UScraper fits local CSV exports, Apify and Bright Data fit hosted scale, Octoparse fits hosted no-code tasks, and the YouTube Data API fits sanctioned integrations.

