Youtube Video Details Scraper

YouTube Video Details Scraper 🔍

YouTube Video Details Scraper automatically pulls YouTube video metadata (views, likes, comments, etc.) and full transcripts with timestamps. If you’re looking for a YouTube video details scraper or a YouTube metadata scraper to speed up research, it’s built for one job: turning video URLs into structured, export-ready data—without manual copy-pasting.

Whether you’re a marketer, data analyst, researcher, or YouTube-focused operator, this actor helps you extract consistent YouTube video info extraction tool outputs at scale—saving you hours of manual work.

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Why choose YouTube Video Details Scraper?

Feature	Benefit
✅ All-in-one video metadata + transcript	Extract YouTube video details scraper results including stats plus full transcript segments with timestamps
✅ Structured output for easy analysis	Produces a consistent dataset with fields like views, likes, comment_count, and engagement_rate
✅ Built-in reliability with fallbacks	Includes retries for metadata requests and multiple transcript language fallbacks
✅ Residential proxy support	Built to work reliably on larger batches with proxy support for more consistent scraping
✅ Real-time dataset writing	Saves each processed video immediately to reduce risk of losing progress
✅ Simple automation workflow	Feed a list of video URLs and get results without building custom scraping scripts

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Key features

• 📊 YouTube video statistics extraction: Captures views, likes, comment_count, and computes engagement_rate
• 📝 Full transcript with timestamps: Returns transcript segments with start, dur, and text
• 🔗 URL input for video pages: Accepts startUrls as a list of YouTube video URLs to process
• 🛡️ Resilience for real-world availability: Uses retries for metadata fetching to improve success rate during transient issues
• 🔄 Transcript language fallbacks: Tries your language preference, then falls back through common English options and generated transcripts
• 💾 Dataset-ready output: Writes results into the Apify dataset titled Video Results
• 🌐 Metadata completeness focus: Extracts key video fields such as title, channel_name, published_date, duration_seconds, category, language, and live_status
• ⚙️ Clear success signaling: Includes a boolean success so you can filter successful scrapes quickly

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Input

Provide input via an input.json file. Example structure:

{
  "startUrls": [
    {
      "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
    },
    {
      "url": "https://www.youtube.com/watch?v=VIDEO_ID_HERE"
    }
  ]
}

Input Fields

Field	Required	Description
startUrls	Yes	A list of YouTube video URLs to scrape. Each item can be either a plain string URL or an object with a url field.

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Output

The actor saves each processed video’s data as JSON records in the Video Results dataset.

Example output record:

{
  "type": "video",
  "video_id": "dQw4w9WgXcQ",
  "title": "Some video title",
  "description": "Some short description",
  "channel_id": "CHANNEL_ID",
  "channel_name": "Channel name",
  "published_date": "2009-10-01",
  "duration_seconds": 213,
  "views": 1000000,
  "likes": 50000,
  "comment_count": 12000,
  "tags": ["music", "example"],
  "thumbnails": { "default": "https://example.com/thumb.jpg" },
  "channel": {
    "id": "CHANNEL_ID",
    "name": "Channel name",
    "handle": null,
    "url": "https://www.youtube.com/channel/CHANNEL_ID",
    "subscriberCount": null,
    "logo": null,
    "badges": []
  },
  "transcript": [
    { "start": "0.000", "dur": "3.500", "text": "First transcript segment..." }
  ],
  "category": "Music",
  "language": "en",
  "live_status": "not_live",
  "engagement_rate": 0.0625,
  "hashtags": ["example", "music"],
  "upload_type": "normal",
  "resolution": "640x360",
  "success": true,
  "inputUrl": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
}

Output Fields

Field	Type	Description
video_id	string | null	The extracted YouTube video ID
title	string | null	The video title
channel_name	string | null	The channel name associated with the video
published_date	string | null	Publication date in YYYY-MM-DD format (when available)
views	number	View count (parsed into an integer value)
likes	number	Like count (parsed into an integer value)
comment_count	number	Comment count (parsed into an integer value)
duration_seconds	number	Video duration in seconds
category	string	Video category (defaults to "Music" when not found)
language	string	Language (defaults to "en" in this actor)
live_status	string	"live" or "not_live"
engagement_rate	number	Computed engagement rate: (likes + comment_count) / views rounded to 4 decimals
inputUrl	string	The input video URL you provided
success	boolean	true when the actor extracted a video_id, otherwise false

Note: The actor also populates additional fields such as transcript and hashtags on each record, and pushes the full video_metadata object to the dataset.

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How to use YouTube Video Details Scraper (via Apify Console)

1. Open Apify Console: Log in at console.apify.com and navigate to the Actors tab.
2. Find the actor: Search for YouTube Video Details Scraper (YouTube Video Details Scraper).
3. Go to the INPUT panel: Paste your input JSON into the input editor.
4. Add your video URLs: In startUrls, provide one or more YouTube video links (either as strings or as { "url": "..." } objects).
5. Choose proxy settings (optional): The actor attempts to create residential proxy support automatically; if proxy configuration cannot be created, it continues without a proxy.
6. Run the actor: Click Run. Watch logs to see which URLs are being processed and whether requests or transcripts fall back during failures.
7. Review the dataset output: After completion, open the Video Results dataset to view rows in the table format.
8. Export your data: Export the dataset to your preferred format (for example, JSON or CSV) for spreadsheets, CRM imports, or analytics workflows.

No coding required—get accurate results in minutes.

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Advanced features & SEO optimization

• 🔍 Engineered for YouTube metadata scraping: Optimized specifically for “YouTube video details scraper” workflows—video title, description, channel info, and engagement metrics in one pass.
• 📼 Transcript-first extraction: Designed to return transcript segments with timestamps, making it useful for “YouTube transcript scraper and details” use cases.
• 🛡️ Retry and fallback logic: Includes retries for metadata fetching and multiple transcript language fallbacks to improve resilience.
• 🌐 Residential proxy support: Uses residential proxy support for more reliable scraping at scale, especially when processing larger URL batches.
• 🧩 Keyword-ready extraction: Includes hashtags derived from the video description, which can help with topic tagging for “YouTube video metadata parser” pipelines.

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Best use cases

• 📈 Marketing teams building influencer insights: Turn YouTube video links into a dataset of views, likes, comments, and engagement rate for campaign benchmarking.
• 🎓 Researchers analyzing audience engagement: Compare video performance across channels using consistent YouTube metadata scraper outputs.
• 🧠 Content analysts researching themes: Use scraped titles/descriptions plus transcript timestamps for qualitative analysis and coding.
• 🛠️ Developers creating enrichment pipelines: Feed video URLs in startUrls and store structured YouTube video info extraction tool results for downstream processing.
• 💼 Agencies running competitive audits: Quickly compile “YouTube video statistics views likes comments” snapshots for content strategy and reporting.
• 📚 Dataset builders for machine learning: Combine video metadata and transcript segments to build training corpora and evaluation sets.
• 🔎 Playlist and channel research at scale: Use video URLs you already have (from other tools or workflows) to populate a “YouTube playlist video details scraper” dataset.

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Technical specifications

• Supported Input Formats

  • ✅ startUrls as an array of YouTube video URLs (strings or { "url": "..." } objects)

• Proxy Support

  • ✅ Residential proxy support (attempted automatically via actor proxy configuration)
  • ❌ No other proxy modes are defined by the actor input schema

• Retry Mechanism

  • ✅ Retries metadata requests up to 3 attempts with backoff behavior

• Dataset Structure

  • ✅ Dataset title: Video Results
  • ✅ Output uses the dataset transformation fields including video_id, title, views, likes, comment_count, duration_seconds, engagement_rate, inputUrl, success, and more

• Rate Limits & Performance

  • ✅ Designed for batch processing via async requests per run
  • ❗ Performance varies depending on availability and network conditions

• Limitations

  • ❌ If a video page cannot be fetched or parsed, you’ll see success: false
  • ❌ Transcript availability can vary; the actor returns an empty transcript list when it can’t retrieve transcripts

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FAQ

Do I need to log in to use YouTube Video Details Scraper?

❓ No. YouTube Video Details Scraper is designed to scrape video metadata and transcripts from publicly accessible sources without requiring authenticated access.

What does the actor extract from each YouTube video?

✅ It extracts YouTube video metadata including title, channel_name, published_date, views, likes, comment_count, duration_seconds, category, language, live_status, and computes engagement_rate. It also fetches a full transcript with timestamps and returns it in the record.

Where can I see the results after the run?

✅ The actor saves outputs to the Video Results dataset. You can view them in the dataset table and export the dataset for JSON/CSV use.

Can the actor handle large lists of YouTube URLs?

✅ Yes. YouTube Video Details Scraper is built to process multiple items from startUrls and includes residential proxy support plus retries to improve resilience during batch runs.

Does it always return a transcript?

❌ Not always. Transcript availability depends on what’s accessible for the video. If the transcript can’t be retrieved, the actor returns an empty transcript list.

How can I tell if a specific video was scraped successfully?

✅ Each record includes a boolean success. In this actor, success is true when a video_id is successfully extracted; otherwise it’s false.

Is this tool meant for YouTube metadata scraper workflows or contact enrichment?

✅ It’s meant for YouTube video metadata scraping and transcript extraction. (For example, it can support analytics and research pipelines that use YouTube metadata parser outputs.)

Can I use it from a code workflow or only via the UI?

✅ You can run it via Apify Console for quick runs, and it’s also compatible with standard Apify automation patterns where you provide input.json containing startUrls.

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Support & feature requests

Have questions or want improvements to YouTube Video Details Scraper (YouTube video details scraper and metadata scraping workflows)? We’d love to hear from you.

• 💡 Feature Requests: Want enhancements like additional transcript formatting, more export-friendly fields, or new output shapes for your YouTube metadata scraper pipeline? Share your ideas.
• 📧 Contact: Email us at dataforleads@gmail.com

Your feedback helps shape the roadmap for YouTube video metadata parser use cases.

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• YouTube Video Details Scraper is the most comprehensive, structured way to extract YouTube video metadata and transcript timestamps at scale.
• Get started now and turn video URLs into analysis-ready data with this SEO-optimized YouTube Video Details Scraper.

Disclaimer

This tool only accesses publicly accessible sources. It does not access private profiles, authenticated data, or password-protected pages. It is your responsibility to comply with applicable laws and regulations (including GDPR, CCPA where relevant), as well as platform terms of service and any anti-spam requirements.

For data removal requests, contact dataforleads@gmail.com. Please use this tool responsibly, ethically, and for legitimate purposes only.