Youtube Video Details Scraper

Youtube Video Details Scraper

The Youtube Video Details Scraper is a fast, reliable YouTube video metadata extractor that scrapes structured video details at scale — titles, descriptions, tags, views, likes, comment counts, publish dates, channel info, transcripts, thumbnails, and more. It helps marketers, developers, data analysts, and researchers automate YouTube video info collection for SEO research, competitor analysis, trend tracking, and content planning. Built for repeatable workflows, this YouTube video details scraper tool enables bulk YouTube video data collection with proxy fallback and engagement metrics computed automatically.

What data / output can you get?

Below are the exact fields this YouTube video info scraper pushes to the Apify dataset. You can export results to JSON, CSV, or Excel directly from the dataset.

Data type	Description	Example value
type	Record type identifier	"video"
video_id	Unique YouTube video ID	"dQw4w9WgXcQ"
title	Video title	"Rick Astley - Never Gonna Give You Up"
description	Full video description text	"The official video for "Never Gonna Give You Up" by Rick Astley..."
channel_id	Uploader/channel ID	"UCuAXFkgsw1L7xaCfnd5JJOw"
channel_name	Uploader/channel display name	"Rick Astley"
published_date	ISO date string (YYYY-MM-DD) parsed from upload_date	"2009-10-25"
duration_seconds	Video length in seconds	212
views	Total view count	1234567890
likes	Total like count	15000000
comment_count	Total public comment count	500000
tags	Video tags array	["rick astley","never gonna give you up","music video"]
thumbnails	Map of thumbnail sizes to URLs	{"default":".../default.jpg","medium":".../mqdefault.jpg","high":".../hqdefault.jpg"}
channel.id	Channel ID in nested object	"UCuAXFkgsw1L7xaCfnd5JJOw"
channel.name	Channel name in nested object	"Rick Astley"
channel.handle	Channel handle (if available)	"rickastley"
channel.url	Channel URL	"https://www.youtube.com/@rickastley"
channel.subscriberCount	Subscriber count string if available	"2.5M subscribers"
channel.logo	Channel avatar URL (best available)	"https://yt3.ggpht.com/..."
channel.badges	Channel badges array	["Verified"]
transcript	Array of caption segments with timing	[{"start":"0.000","dur":"3.500","text":"We're no strangers to love"}]
category	First category if available	"Music"
language	Detected language code	"en"
live_status	Live status flag	"none"
engagement_rate	(likes + comments) / views, rounded to 4 decimals	0.0162
hashtags	Hashtags parsed from description (without #)	["rickastley","nevergonnagiveyouup"]
upload_type	Upload type flag	"normal"
resolution	Reported video resolution if available	"1080p"
success	Boolean success flag	true
inputUrl	The input video URL that was processed	"https://www.youtube.com/watch?v=dQw4w9WgXcQ"

Notes:

• On failures, the scraper still outputs a structured record with success set to false and includes an error field describing the issue.
• Bonus metadata includes channel badges, channel logo, transcript segments, and computed engagement rate for richer analysis and SEO workflows.

Key features

• 🚀 Robust metadata coverage — Extracts titles, descriptions, tags, views, likes, comment_count, published_date, duration_seconds, thumbnails, category, language, live_status, and more in one pass. Ideal for YouTube video statistics scraper use cases.
• 🏷️ Tags & hashtags extraction — Acts as a YouTube video tags extractor by collecting tags and parsing hashtags from the description for SEO and keyword analysis.
• 📝 Transcript capture — Retrieves transcript segments when available and structures them as start/dur/text entries, enabling downstream NLP and content analysis.
• 📈 Computed engagement rate — Automatically calculates engagement_rate = (likes + comments) / views to benchmark performance across videos and channels.
• 🧠 Channel context — Enriches each record with channel.id, channel.name, channel.handle, channel.url, subscriberCount (if available), badges, and channel logo for a full channel video data picture.
• 📦 Bulk-ready & resilient — Process multiple startUrls in a single run with human-like delays and a smart proxy fallback flow (direct ➜ datacenter ➜ residential) to reduce blocks. Perfect for a bulk YouTube video data scraper workflow.
• 🔒 Proxy configuration — Optional Apify Proxy with automatic residential fallback for reliable large-scale scraping.
• 🔄 Easy export & integration — Download results from the Apify dataset or export YouTube video details to CSV, JSON, or Excel for BI tools, CRMs, and dashboards. Great for marketers and researchers who need a YouTube metadata scraper that plugs into existing pipelines.
• 💻 Developer-friendly — Apify SDK-based actor with structured JSON output suitable for API pipelines, Python workflows, and automation in tools like Zapier/Make/n8n.

How to use Youtube Video Details Scraper - step by step

1. Create or log in to your Apify account

   • Access the actor from your Apify dashboard to start scraping YouTube video details.

2. Open the actor and locate the input form

   • You’ll see fields for startUrls and an optional proxyConfiguration.

3. Add YouTube video URLs

   • Paste one or more full video URLs into startUrls (string list). Supported formats:
     • https://www.youtube.com/watch?v=VIDEO_ID
     • https://youtu.be/VIDEO_ID

4. (Optional) Configure proxy settings

   • Use proxyConfiguration to enable Apify Proxy for reliability. If YouTube rejects the connection, the actor automatically attempts residential fallback to maintain continuity.

5. Start the run

   • Click Start. The run log will show progress as each URL is processed, including proxy status and retry behavior for resilience.

6. Monitor progress

   • The actor processes each video with brief, random delays and logs success or failure. Engagement rate and transcript (when available) are included automatically.

7. Download your data

   • Go to the Dataset tab to view and export your results. Export formats include JSON, CSV, and Excel for analytics, SEO, and research workflows.

Pro Tip: Chain this YouTube video metadata extractor with automation (e.g., via the Apify API) to keep a rolling dataset of channel videos, or connect to your data warehouse for ongoing competitor tracking.

Use cases

Use case name	Description
SEO teams – keyword & tag mining	Extract tags, hashtags, and descriptions at scale to inform on-page SEO and content strategy with a reliable YouTube metadata scraper.
Content strategy – trend tracking	Track views, likes, comments, and engagement_rate over time to identify high-performing topics and formats.
Competitor analysis – channel benchmarking	Build comparable datasets of competitor videos to evaluate publishing cadence, categories, and performance.
Research & academia – transcript analysis	Collect transcript segments for NLP, topic modeling, and language research using a repeatable YouTube transcript scraper workflow.
Marketing analytics – campaign reporting	Export structured metrics to CSV/JSON and pipe into BI tools to measure campaign lift on video performance.
Developer pipelines – API ingestion	Use the structured JSON output in ETL/ELT jobs to enrich databases or power dashboards as part of an automated YouTube channel video data scraper pipeline.
Playlist or batch audits – bulk QA	Run multiple startUrls to audit playlists or back catalogs with a bulk YouTube video data scraper for catalog hygiene.

Why choose Youtube Video Details Scraper?

This YouTube video info scraper emphasizes precision, automation, and reliability for production workflows.

• ✅ Accurate, structured output: Consistently maps fields like video_id, duration_seconds, views, likes, comment_count, category, language, and more for downstream analysis.
• 📝 Transcript + hashtags support: Goes beyond basic metadata to include transcript segments and hashtags parsed from descriptions.
• 📈 Engagement metrics built-in: Computes engagement_rate automatically for quick benchmarking without extra processing.
• 📦 Built for scale: Handles multiple URLs with smart delays and robust proxy fallback for stable, automated runs.
• 💻 Developer-ready: Clean JSON output works seamlessly in Python/SDK pipelines and data engineering workflows.
• 🔒 Ethical by design: Targets public video metadata only; no login or cookies required.
• 💰 Cost-effective operations: Avoid brittle browser extensions and unstable tools; use a production-grade, Apify-powered YouTube video details scraper tool.

In short, this YouTube video metadata extractor offers the reliability and structure you need to move beyond the limitations of manual copy/paste and fragile scraping approaches.

Is it legal / ethical to use Youtube Video Details Scraper?

Yes — when used responsibly. This actor collects publicly available video information such as titles, descriptions, view counts, likes, upload dates, tags, and transcripts/captions when provided publicly.

Guidelines for compliant use:

• Scrape only public video and channel metadata.
• Do not attempt to access private or restricted data.
• Follow YouTube’s Terms of Service and applicable data protection laws (e.g., GDPR, CCPA).
• Use the data for legitimate analytics, reporting, research, and SEO purposes.
• Consult your legal team for edge cases or jurisdiction-specific considerations.

This tool does not access private profiles or authenticated data and is designed for ethical, public web data collection.

Input parameters & output format

Example JSON input

{
  "startUrls": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    "https://youtu.be/VIDEO_ID_2"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Parameters

• startUrls (array of strings) — Enter one or more YouTube video URLs to scrape. Each URL is processed to extract video details (title, description, views, likes, comments, channel info, transcript, tags, thumbnails, etc.). Required: Yes. Default: none (stringList editor with a prefill example).
• proxyConfiguration (object) — Optional proxy settings. Enable Apify Proxy for reliability. If YouTube rejects the proxy, a residential proxy is used automatically as fallback. Required: No. Default: {"useApifyProxy": false}.

Example JSON output

{
  "type": "video",
  "video_id": "dQw4w9WgXcQ",
  "title": "Rick Astley - Never Gonna Give You Up",
  "description": "The official video for \"Never Gonna Give You Up\" by Rick Astley...",
  "channel_id": "UCuAXFkgsw1L7xaCfnd5JJOw",
  "channel_name": "Rick Astley",
  "published_date": "2009-10-25",
  "duration_seconds": 212,
  "views": 1234567890,
  "likes": 15000000,
  "comment_count": 500000,
  "tags": ["rick astley", "never gonna give you up", "music video"],
  "thumbnails": {
    "default": "https://i.ytimg.com/vi/dQw4w9WgXcQ/default.jpg",
    "medium": "https://i.ytimg.com/vi/dQw4w9WgXcQ/mqdefault.jpg",
    "high": "https://i.ytimg.com/vi/dQw4w9WgXcQ/hqdefault.jpg"
  },
  "channel": {
    "id": "UCuAXFkgsw1L7xaCfnd5JJOw",
    "name": "Rick Astley",
    "handle": "rickastley",
    "url": "https://www.youtube.com/@rickastley",
    "subscriberCount": "2.5M subscribers",
    "logo": "https://yt3.ggpht.com/...",
    "badges": ["Verified"]
  },
  "transcript": [
    {
      "start": "0.000",
      "dur": "3.500",
      "text": "We're no strangers to love"
    }
  ],
  "category": "Music",
  "language": "en",
  "live_status": "none",
  "engagement_rate": 0.0162,
  "hashtags": ["rickastley", "nevergonnagiveyouup"],
  "upload_type": "normal",
  "resolution": "1080p",
  "success": true,
  "inputUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
}

Notes:

• On failure, the same schema is returned with success: false and an additional error field explaining what happened.
• Some fields may be empty when not available on the source page (e.g., subscriberCount, resolution, transcript).

Related tools

Tool	Tool
☎️ YouTube Channel Phone Number Scraper	💬 YouTube Comments Scraper
📝 YouTube Transcript Scraper	🔎 YouTube Search Scraper
📺 YouTube Channel Finder	🧠 YouTube Video Summarizer
👥 YouTube Community Posts Scraper	⏱️ YouTube Most Replayed Scraper
📊 YouTube Metadata Scraper	🌐 YouTube Video Subtitles Scraper
🔥 YouTube Trending Scraper	🏷️ YouTube Video Scraper by Hashtag
🎬 YouTube Shorts Scraper	🗂️ YouTube Playlist Scraper
📡 YouTube Channel Scraper	📞 YouTube Phone Number Scraper
📧 YouTube Email Scraper	📨 YouTube Channel Email Scraper

FAQ

Can I scrape dislikes?

No. Public dislike counts were removed in 2021, so they are not available. You can still collect views, likes, comment_count, tags, hashtags, and other public metadata.

How do I scrape YouTube videos at scale?

Use multiple startUrls and enable proxyConfiguration for reliability. The actor includes a fallback flow that tries datacenter and then residential proxies when needed, making it suitable as a bulk YouTube video data scraper.

Does this extract transcripts?

Yes, when available. The actor fetches transcript segments and outputs them as an array with start, dur, and text fields, making it a practical YouTube transcript scraper for analysis.

Can I export YouTube video details to CSV?

Yes. After the run, open the Dataset and export your structured records to CSV, JSON, or Excel for analysis, reporting, or integration.

Is there an API or Python integration?

Yes. This Apify actor produces clean JSON designed for API pipelines and Python/SDK workflows. It’s a developer-friendly YouTube video info scraper for automation.

Is it a YouTube Data API video details tool?

This scraper collects public metadata without relying on the official API and is useful when you need a YouTube metadata scraper beyond YouTube Data API limits.

Is it legal to scrape public YouTube data?

Yes, when done responsibly. The actor targets publicly available metadata and captions. Avoid private/restricted content and ensure compliance with YouTube’s Terms and applicable laws.

Can it handle playlists or channel batches?

Provide the individual video URLs from playlists or channels as startUrls to scrape YouTube video details in bulk. For discovery workflows, pair it with a YouTube search results scraper or playlist metadata scraper.

Final thoughts

The Youtube Video Details Scraper is built for accurate, scalable extraction of structured YouTube video data. With transcripts, hashtags, channel context, and engagement_rate included, it’s ideal for marketers, developers, analysts, and researchers who need dependable YouTube video details at scale. Export to CSV/JSON/Excel, plug into your API or Python pipeline, and automate reporting and insight generation. Start extracting smarter video insights today with a production-ready YouTube video metadata extractor.