The Youtube Channel Scraper helps you collect structured video data quickly and reliably. It extracts rich metadata such as titles, descriptions, transcripts, and engagement metrics, giving analysts, developers, and researchers a powerful way to analyze YouTube content at scale. Designed for accuracy and efficiency, this scraper simplifies the process of gathering actionable insights from YouTube channels or keyword-based searches.
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This project automates the extraction of detailed information from YouTube videos. It solves the challenge of manually gathering video metadata, channel info, and transcripts — tasks that are otherwise time-consuming and error-prone. It is ideal for marketers, analysts, data scientists, content researchers, and anyone who needs structured YouTube data.
- Scrapes videos from a given YouTube channel or keyword search.
- Retrieves extensive metadata including views, likes, comments, and transcription.
- Supports toggles for keyword-based search or detailed video information.
- Designed for scalable and repeatable data extraction workflows.
- Delivers clean JSON output suitable for analysis or downstream automation.
| Feature | Description |
|---|---|
| Channel or Keyword Scraping | Extract videos either from specific channels or via keyword queries. |
| Detailed Metadata Collection | Captures titles, descriptions, engagement stats, and thumbnails. |
| Transcript Extraction | Retrieves full transcriptions when available. |
| Channel-Level Insights | Gets subscriber counts, descriptions, country, and social links. |
| Adjustable Result Count | Control how many videos to collect per run. |
| High-Quality JSON Output | Clean structured format ready for storage, analysis, or dashboards. |
| Field Name | Field Description |
|---|---|
| title | The title of the video. |
| description | The full description text of the video. |
| coverImage | URL of the video’s thumbnail image. |
| videoUrl | Direct link to the video. |
| author | Name of the video’s creator. |
| viewCount | Total number of views. |
| likeCount | Number of likes. |
| commentCount | Number of comments. |
| subscriberCount | Total channel subscribers. |
| transcript | Extracted transcription of the video. |
| publishedAt | Timestamp of publication. |
| amountOfVideos | Total number of videos on the channel, including live and shorts. |
| channelInfo | Object containing global channel details like description, social links, and country. |
[
{
"title": "PAIN HUSTLERS | Emily Blunt & Catherine O'Hara Clip | Netflix",
"author": "@netflix",
"videoUrl": "https://www.youtube.com/watch?v=mEbVjufYiFE",
"coverImage": "https://i.ytimg.com/vi/mEbVjufYiFE/hqdefault.jpg",
"subscriberCount": "27,2 M d’abonnés",
"likeCount": 424,
"description": "Emily Blunt, Chris Evans, Catherine O’Hara...",
"viewCount": 29280,
"commentCount": 0,
"publishedAt": "2023-10-25T14:00:00-07:00",
"id": "mEbVjufYiFE",
"amountOfVideos": null,
"profilePicture": null,
"channelInfo": {
"actifFrom": "Actif depuis le 17 juil. 2012",
"viewCounter": "7 569 331 655 vues",
"channelDescription": "Description GEEKED WEEK is BACK...",
"country": "États-Unis",
"link": {
"Netflix": "signup.netflix.com",
"Facebook": "facebook.com/netflixus",
"Twitter": "twitter.com/netflix",
"Instagram": "instagram.com/netflix",
"Tumblr": "netflix.tumblr.com"
}
}
}
]
Youtube Channel Scraper/
├── src/
│ ├── index.js
│ ├── browser/
│ │ └── puppeteerLauncher.js
│ ├── extractors/
│ │ ├── videoParser.js
│ │ └── transcriptFetcher.js
│ ├── helpers/
│ │ └── utils.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.json
│ └── sampleOutput.json
├── package.json
└── README.md
- Marketing teams use it to analyze competitor channels, so they can identify trending topics and content opportunities.
- Data scientists use it to collect large datasets of video metadata, enabling machine-learning research or sentiment analysis.
- Journalists and media analysts use it to track creator activity, helping them spot emerging narratives or misinformation trends.
- Brands use it to monitor influencer performance, so they can optimize sponsorship decisions.
- Researchers use it to study online engagement, allowing them to measure audience behavior and communication patterns.
Q: Can I scrape videos by keyword instead of channel? Yes. Enable the keyword toggle to collect videos based on search terms rather than a specific channel.
Q: Does it pull transcripts for every video? Transcripts are extracted when available. Some videos may not provide automated captions, which limits transcript availability.
Q: How many videos can I scrape at once?
You can specify any number through the numberOfResults parameter. Performance depends on your system limits and network conditions.
Q: Does it include channel-level metadata? Yes. Subscriber count, country, description, social links, and more are included.
Primary Metric: Average scrape speed is optimized to process 3–5 videos per minute depending on transcript availability. Reliability Metric: Maintains a 95%+ success rate across varied channel structures and video formats. Efficiency Metric: Lightweight browser automation ensures minimal resource consumption during long scraping sessions. Quality Metric: Outputs over 98% complete metadata fields across large datasets, including consistent engagement metrics and channel details.
“Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time.” Nathan Pennington
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“Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on.” Eliza
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“Exceptional results, clear communication, and flawless delivery. Bitbash nailed it.” Syed
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