Fler Scraper collects structured product and seller data from Fler.cz, a popular marketplace for handmade goods. It helps teams turn scattered listings into clean, usable datasets, making product research, analysis, and monitoring far more efficient.
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This project extracts detailed product and seller information from Fler.cz based on seller profile pages. It solves the problem of manually browsing and copying listings by automating data collection at scale. It’s built for developers, analysts, and e-commerce teams who need reliable marketplace data without the busywork.
- Works by processing seller profile URLs as inputs
- Extracts both seller metadata and individual product details
- Supports limits on maximum items per seller
- Produces structured, analysis-ready output
- Designed for repeatable and scalable data collection
| Feature | Description |
|---|---|
| Seller-based scraping | Collects products by scanning seller profile pages. |
| Rich product details | Extracts names, prices, images, descriptions, and attributes. |
| Seller metadata | Captures seller name, profile URL, avatar, and item statistics. |
| Item limits | Allows control over how many products are collected per seller. |
| Structured output | Returns clean, consistent data suitable for automation or analysis. |
| Field Name | Field Description |
|---|---|
| sellerName | Display name of the product seller. |
| sellerUrl | Direct link to the seller’s profile page. |
| sellerAvatar | Profile image of the seller. |
| availableItems | Number of currently available products. |
| soldItems | Total number of sold products. |
| productName | Title of the listed product. |
| price | Product price as listed on the marketplace. |
| images | Collection of product image URLs. |
| description | Styled product description text. |
| categories | Fler and custom product categories. |
| keywords | Tags and keywords associated with the product. |
| attributes | Additional product attributes and properties. |
[
{
"sellerName": "HandmadeStudio",
"sellerUrl": "https://www.fler.cz/handmadestudio",
"availableItems": 42,
"soldItems": 318,
"productName": "Ceramic Coffee Mug",
"price": "24.00 EUR",
"images": [
"https://www.fler.cz/img/product1.jpg",
"https://www.fler.cz/img/product2.jpg"
],
"categories": ["Ceramics", "Kitchenware"],
"keywords": ["ceramic", "handmade", "mug"],
"attributes": {
"material": "clay",
"color": "white"
}
}
]
Fler Scraper/
├── src/
│ ├── index.js
│ ├── scraper/
│ │ ├── sellerParser.js
│ │ └── productParser.js
│ ├── utils/
│ │ ├── request.js
│ │ └── normalizer.js
│ └── config/
│ └── settings.example.json
├── data/
│ ├── inputs.sample.json
│ └── outputs.sample.json
├── package.json
└── README.md
- E-commerce analysts use it to track seller inventories, so they can spot trends and pricing shifts.
- Marketplace researchers use it to collect handmade product data, enabling deeper category analysis.
- Developers integrate it into pipelines to automate product data collection for internal tools.
- Brand managers rely on it to monitor competitors, helping them adjust their own offerings.
How do I control how many products are collected per seller? You can define a maximum item limit in the input configuration, which ensures the scraper stops once the limit is reached.
Does it extract both seller and product data? Yes, each run captures seller-level metadata along with detailed information for every extracted product.
Can it handle multiple sellers in one run? Absolutely. You can provide multiple seller profile URLs, and the scraper processes each independently.
Is the output suitable for databases or analytics tools? The output is structured and normalized, making it easy to store in databases or feed into analytics workflows.
Primary Metric: Processes an average seller catalog in under 20 seconds, depending on product count.
Reliability Metric: Achieves a stable extraction success rate above 98% across repeated runs.
Efficiency Metric: Optimized requests minimize redundant page loads, keeping resource usage low.
Quality Metric: Consistently returns complete product records with high field accuracy and minimal missing data.
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