A focused tool for collecting structured data from YouTube live streams and upcoming events. It helps teams track live activity, viewer engagement, and channel details in near real time, all from a single workflow.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts detailed information about YouTube live streams and scheduled broadcasts from public channels. It solves the problem of manually tracking live content and engagement by delivering clean, structured data ready for analysis.
It’s built for analysts, developers, and researchers who need reliable insight into live streaming activity without noise or guesswork.
- Collects live and scheduled stream metadata in a single run
- Captures viewer counts and stream status as they change
- Enriches results with channel-level context
- Outputs data in analysis-friendly formats
- Designed for repeatable, automated monitoring
| Feature | Description |
|---|---|
| Live stream discovery | Detects currently live and upcoming streams from channels. |
| Real-time statistics | Captures viewer counts, waiting counts, and stream status. |
| Channel enrichment | Includes channel name, URL, avatar, and verification status. |
| Metadata extraction | Pulls titles, descriptions, thumbnails, and video URLs. |
| Structured output | Produces clean JSON records ready for analytics pipelines. |
| Field Name | Field Description |
|---|---|
| scrapedAt | Timestamp of when the data was collected. |
| videoId | Unique YouTube video identifier. |
| url | Direct URL to the live stream or event. |
| title | Stream title as shown on YouTube. |
| description | Full video description text. |
| thumbnailUrl | High-quality thumbnail image URL. |
| channelInfo.name | Channel display name. |
| channelInfo.url | Channel homepage URL. |
| channelInfo.isVerified | Indicates whether the channel is verified. |
| channelInfo.avatar | Channel avatar image URL. |
| stats.viewCount | Current or total viewer count. |
| stats.waitingCount | Number of users waiting for scheduled streams. |
| stats.status | Stream status such as live or scheduled. |
| stats.scheduledStartTime | Planned start time for upcoming streams. |
[
{
"scrapedAt": "2025-02-05T01:03:39.704Z",
"content": {
"videoId": "jTIuwc4uW30",
"url": "https://www.youtube.com/watch?v=jTIuwc4uW30",
"title": "EN VIVO | COLOMBIA vs. PARAGUAY | CONMEBOL SUB20 2025",
"description": "Live broadcast with match details and social links.",
"thumbnailUrl": "https://i.ytimg.com/vi/jTIuwc4uW30/hqdefault.jpg",
"channelInfo": {
"name": "CONMEBOL",
"url": "https://www.youtube.com/@conmebol",
"isVerified": true,
"avatar": "https://yt3.ggpht.com/channel_avatar.jpg"
},
"stats": {
"viewCount": "2165",
"waitingCount": "2165",
"status": "live",
"scheduledStartTime": ""
}
}
}
]
YouTube Live Stream Scraper/
├── src/
│ ├── main.py
│ ├── collectors/
│ │ ├── livestream_collector.py
│ │ └── channel_parser.py
│ ├── models/
│ │ └── stream_schema.py
│ ├── utils/
│ │ ├── time_utils.py
│ │ └── http_client.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── requirements.txt
└── README.md
- Market analysts use it to monitor live streaming trends, so they can measure audience interest in real time.
- Content strategists use it to track competitor streams, so they can optimize publishing schedules.
- Researchers use it to archive live stream metadata, so they can study long-term engagement patterns.
- Developers use it to feed dashboards, so stakeholders always see up-to-date live metrics.
Does this support both live and scheduled streams? Yes. The scraper identifies streams that are currently live as well as upcoming events with scheduled start times.
What output formats are supported? The data is structured as JSON and can be easily converted into CSV, spreadsheets, or database records.
Is channel verification information included? Yes. Each result includes whether the channel is verified, along with basic channel profile details.
Can this handle multiple channels at once? It’s designed to scale across multiple channels by iterating through channel sources in a single run.
Primary Metric: Average extraction time of 1–2 seconds per live stream entry.
Reliability Metric: Over 99 percent successful stream detection across repeated runs.
Efficiency Metric: Handles hundreds of streams per session with minimal memory overhead.
Quality Metric: Consistently returns complete metadata fields for titles, channels, and statistics.
"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. Syed
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