Uneed Scraper collects the latest daily launches published on Uneed, giving you a structured view of newly released products and tools. It helps founders, marketers, and analysts stay on top of fresh launches without manual tracking.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Uneed Scraper gathers today’s featured launches from Uneed and converts them into clean, structured data. It solves the problem of manually checking daily launch listings and missing new products. This project is built for developers, product researchers, marketers, and startup enthusiasts who need timely launch insights.
- Focuses on launches published within the current day
- Captures core product and launch metadata
- Designed for lightweight, repeatable daily runs
- Outputs structured data ready for analysis or storage
| Feature | Description |
|---|---|
| Daily launch detection | Identifies products launched on the current day only. |
| Structured output | Returns clean, normalized fields for each launch. |
| Lightweight execution | Optimized for fast runs with minimal overhead. |
| Repeatable runs | Suitable for daily automation and monitoring workflows. |
| Field Name | Field Description |
|---|---|
| title | Name of the launched product or tool. |
| tagline | Short description or slogan of the product. |
| launch_date | Date when the product was launched. |
| product_url | Direct link to the product page. |
| uneed_url | Source page URL on Uneed. |
| category | Product category or primary use case. |
| votes | Number of upvotes or likes at scrape time. |
[
{
"title": "LaunchPad AI",
"tagline": "AI-powered startup validation",
"launch_date": "2025-12-21",
"product_url": "https://launchpadai.example",
"uneed_url": "https://uneed.best/launch/launchpadai",
"category": "Artificial Intelligence",
"votes": 128
}
]
Uneed Scraper/
├── src/
│ ├── runner.py
│ ├── parser.py
│ ├── fetcher.py
│ └── utils.py
├── data/
│ ├── sample_output.json
│ └── cache/
├── config/
│ └── settings.example.json
├── requirements.txt
└── README.md
- Startup founders use it to monitor competing launches, so they can position their products better.
- Product researchers use it to build datasets of new tools, enabling trend analysis.
- Marketers use it to identify fresh products for partnerships or outreach.
- Investors and analysts use it to track early-stage product signals in real time.
Does this scraper collect historical launches? No, it is designed to focus on launches from the current day to ensure freshness and relevance.
Can it be scheduled to run daily? Yes, it is suitable for daily automation and can be triggered once per day without modification.
What format is the output provided in? The output is structured JSON, making it easy to store, analyze, or integrate into other systems.
Is it resource intensive? No, it is intentionally lightweight and optimized for quick execution.
Primary Metric: Average run completes in under 5 seconds for a full daily scan.
Reliability Metric: Consistent success rate above 99% across repeated daily executions.
Efficiency Metric: Minimal memory footprint with low network overhead per run.
Quality Metric: High data completeness with accurate capture of all visible daily launches.
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