🎬 YouTube Video Details Scraper — Extract Metadata

🎬 YouTube Video Details Scraper — Extract Metadata

The 🎬 YouTube Video Details Scraper — Extract Metadata is a focused YouTube metadata extractor that collects rich, structured video information at scale. It solves the pain of manual copy-paste by automatically capturing titles, descriptions, tags, engagement metrics, channel details, thumbnails, transcripts, and more — making it a reliable YouTube video metadata scraper for marketers, developers, data analysts, and researchers. Use it to scrape YouTube video details in clean JSON for analysis, dashboards, and reporting — all in a single automated run.

What data / output can you get?

Below are real output fields produced by the scraper, with examples to illustrate the structure. You can export results from the Apify dataset in JSON, CSV, or Excel.

Data type	Description	Example value
type	Record type indicator	"video"
video_id	Unique YouTube video ID	"dQw4w9WgXcQ"
title	Video title	"Rick Astley - Never Gonna Give You Up"
description	Full description text	"The official video for "Never Gonna Give You Up" by Rick Astley..."
channel_id	Uploader/channel ID	"UCuAXFkgsw1L7xaCfnd5JJOw"
channel_name	Uploader/channel name	"Rick Astley"
published_date	ISO-like date derived from upload_date	"2009-10-25"
duration_seconds	Video length in seconds	212
views	View count	1234567890
likes	Like count	15000000
comment_count	Comment count	500000
tags	Video tags array	["rick astley","never gonna give you up","music video"]
thumbnails	Thumbnail URLs keyed by quality	{"default":".../default.jpg","medium":".../mqdefault.jpg","high":".../hqdefault.jpg"}
channel	Nested channel metadata	{"id":"...","name":"...","handle":"rickastley","url":"https://www.youtube.com/@rickastley","subscriberCount":"2.5M subscribers","logo":"https://yt3.ggpht.com/...","badges":["Verified"]}
transcript	Timed transcript/captions array	[{"start":"0.000","dur":"3.500","text":"We're no strangers to love"}]
category	Video category if available	"Music"
language	Detected language code if available	"en"
live_status	Live status	"none"
engagement_rate	Computed (likes + comments) / views	0.0162
hashtags	Hashtags parsed from description (without #)	["rickastley","nevergonnagiveyouup"]
upload_type	Static label for upload type	"normal"
resolution	Reported resolution if available	"1080p"
success	Boolean flag for per-item success	true
inputUrl	Input video URL	"https://www.youtube.com/watch?v=dQw4w9WgXcQ"

Bonus: The tool also enriches channel context (handle, logo, badges) and provides a structured transcript when available, making it a strong YouTube tags extractor, YouTube title and description scraper, and YouTube video transcript extractor in one.

Key features

• 🎯 Accurate metadata capture
  Extracts comprehensive fields (title, description, tags, views, likes, comments, category, language, resolution) for reliable analysis with a developer-friendly YouTube video info JSON extractor.

• 🧠 Transcript extraction with smart fallback
  Attempts human subtitles first, then falls back to automatic captions — returning a clean, time-coded transcript array when available.

• 🧩 Channel metadata enrichment
  Adds nested channel details including id, name, handle, URL, subscriberCount (when available), logo, and badges — effectively acting as a YouTube channel metadata scraper alongside video details.

• 🔎 Hashtags + engagement rate
  Parses hashtags directly from the description and computes engagement_rate as (like_count + comment_count) / views for instant performance insights.

• 🔁 Resilient proxy & retry logic
  Optional Apify proxy with fallback flow and retry policy, plus human-like random delays, to stabilize high-volume scraping jobs.

• 📦 Batch processing from multiple URLs
  Provide a list of video URLs and process them in one run — a practical way to scrape YouTube video details at scale.

• 💾 Easy exports
  Download results from the Apify dataset as JSON, CSV, or Excel for use in BI tools, dashboards, or SEO reports.

• 👨‍💻 Built on Apify Actors (Python)
  Production-ready automation with Apify’s Python stack and dataset API access — ideal for developers integrating a YouTube video metadata scraper into pipelines.

How to use 🎬 YouTube Video Details Scraper — Extract Metadata - step by step

1. Log in to Apify
   Sign in to your Apify account and open the “youtube-video-details-scraper” actor.

2. Prepare your input
   Add one or more YouTube video URLs under startUrls. The tool accepts full URLs like:

• https://www.youtube.com/watch?v=VIDEO_ID
• https://youtu.be/VIDEO_ID

3. Configure proxy (optional)
   Use proxyConfiguration to enable Apify proxy for reliability at scale. By default (prefill), useApifyProxy is false, which is fine for quick tests.

4. Start the run
   Click Start. The actor will fetch each video’s metadata, compute engagement_rate, parse hashtags, enrich channel info, and attempt transcript extraction.

5. Monitor progress
   Follow live logs for progress, retries, and proxy status. The actor reports per-video success/failure and overall summary at the end.

6. Review dataset items
   Open the run’s Dataset to preview structured records including type, video_id, title, tags, channel, transcript, and more.

7. Export your data
   Download the dataset as JSON, CSV, or Excel for analysis and reporting.

Pro tip: For larger batches, enable Apify proxy and supply more URLs in startUrls to run a robust YouTube video metadata scraper job with stable throughput.

Use cases

Use case	Description
SEO audits + keyword analysis	Extract titles, descriptions, and tags to benchmark optimization and identify content gaps across competitor videos.
Content research & trend tracking	Compile views, likes, comments, and category to evaluate performance patterns over time.
Competitor analysis	Compare channel-level badges, branding (logo), and engagement_rate across competing uploads.
Reporting & dashboards	Export structured fields (CSV/JSON/Excel) for BI dashboards and weekly/monthly performance reports.
Academic/media research	Gather public metadata and transcripts to study narratives, language usage, and audience engagement at scale.
Data pipeline ingestion (API)	Use the Apify dataset API to feed clean JSON into analytics pipelines and enrichment workflows.

Why choose 🎬 YouTube Video Details Scraper — Extract Metadata?

A precise, automation-ready YouTube video details parser built for reliability and structured outputs.

• ✅ Comprehensive fields in one pass: video details, channel metadata, thumbnails, hashtags, transcripts.
• 🧮 Built-in metrics: engagement_rate and parsed hashtags for faster analysis.
• 🔁 Robustness at scale: optional proxy with fallback and retry logic for resilient scraping.
• 📊 Clean exports: ready-to-use JSON/CSV/Excel via the Apify dataset.
• 👨‍💻 Developer-ready: Python-based Actor with straightforward dataset access for integrations.
• 🛡️ Public data focus: designed for extracting publicly available metadata and captions.
• 💸 Cost-efficient operations: run targeted batches from URL lists to control scope and spend.

Unlike unstable browser extensions or manual workflows, this YouTube video metadata scraper provides consistent, structured results with production-grade reliability.

Is it legal / ethical to use this scraper?

Yes — when done responsibly. This tool is designed to extract publicly available YouTube video metadata and captions. Avoid private or restricted data and ensure your use complies with YouTube’s Terms of Service and applicable laws.

Guidelines for compliant use:

• Collect only publicly visible information.
• Do not attempt to access private videos or authenticated resources.
• Respect platform terms and applicable data protection regulations.
• Consult your legal team if you’re unsure about your specific use case.

Input parameters & output format

Example input

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

Parameters

Field	Type	Description	Default	Required
startUrls	array	Enter one or more YouTube video URLs to scrape. Accepts full URLs like watch and youtu.be links. Each URL is processed to extract video details (title, description, views, likes, comments, channel info, transcript, tags, thumbnails, and more).	None	Yes
proxyConfiguration	object	Optional proxy settings. Enable Apify proxy for better reliability; if YouTube rejects the proxy, a residential proxy is used automatically as fallback. Leave default (no proxy) for quick testing with a few videos.	{"useApifyProxy": false} (prefill)	No

Example 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 failures, success is false and an error message is included (error). Some fields may be empty if not present on the source page.

FAQ

What URLs are supported as input?

Provide full video URLs. The actor supports standard watch links (https://www.youtube.com/watch?v=VIDEO_ID) and short links (https://youtu.be/VIDEO_ID). Add multiple URLs to process them in one batch.

Does it extract transcripts or captions?

Yes. It attempts to load human subtitles first and falls back to automatic captions. When available, it returns a time-coded transcript array with start, dur, and text items.

What channel data does it return?

For each video, it includes a nested channel object with id, name, handle, url, subscriberCount (if available), logo, and badges (e.g., Verified). This makes it a practical YouTube channel metadata scraper within a video-focused workflow.

How are hashtags and engagement rate calculated?

Hashtags are parsed from the description by collecting words that start with # and returning them without the symbol. The engagement_rate is computed as (likes + comment_count) divided by views.

Can I run it without a proxy?

Yes. By default (prefill), useApifyProxy is false and the actor uses a direct connection. For larger or sustained runs, enable Apify proxy for better reliability. The actor includes proxy fallback logic and retries.

What export formats are available?

Results are stored in the Apify dataset. You can export data as JSON, CSV, or Excel directly from the run’s dataset view.

Does it handle multiple videos in one run?

Yes. Add multiple items to startUrls to scrape YouTube video details in batches. The actor logs per-item progress, applies human-like delays, and summarizes results at the end.

What happens if a video fails to scrape?

The actor will retry with proxy fallback. If all retries fail, it pushes a structured item with success set to false, inputUrl populated, and an error message to help you diagnose the issue.

Closing CTA / Final thoughts

This YouTube video metadata scraper is built for structured, reliable extraction of video and channel details — at scale. Get titles, descriptions, tags, thumbnails, transcripts, engagement metrics, and channel context in clean JSON for SEO audits, content research, competitor tracking, and analytics. Marketers, developers, analysts, and researchers can run batches from URL lists, export CSV/JSON/Excel, or pull data via the Apify dataset API. Start extracting smarter with a resilient, production-ready YouTube video details parser that fits straight into your workflows.