Ebay Kleinanzeigen API

Ebay Kleinanzeigen API

A powerful API interface for Ebay-Kleinanzeigen.de that enables you to fetch listings and specific data.

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✓ Automated Search Agents
✓ Search & Detail API
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Getting Started

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Visit kleinanzeigen-agent.de for our hosted solution with additional features and zero configuration required.

Prerequisites

• Python 3.12 or higher
• pip (Python package manager)
• Playwright

Installation

1. Clone the repository

git clone https://github.com/DanielWTE/ebay-kleinanzeigen-api.git
cd ebay-kleinanzeigen-api

2. Install dependencies

pip install -r requirements.txt
playwright install chromium

3. Start the API

uvicorn main:app --reload

The API will be available at http://localhost:8000

Installation using UV

Prerequisites

• uv package manager

Installation of dependencies

uv sync

Start the API

uv run uvicorn main:app --reload

Installation using Docker

1. Build the Docker image

docker build -t ebay-kleinanzeigen-api .

2. Run the Docker container

docker run -p 8000:8000 ebay-kleinanzeigen-api

The API will be available at http://localhost:8000

API Endpoints

1. Fetch Listings (Standard)

Endpoint: GET /inserate

Description: Retrieves a list of listings based on search criteria.

Query Parameters

• query (string, optional): The search term (e.g., "fahrrad" to search for bicycles).
• location (string, optional): The location or postal code to narrow the search (e.g., 10178 for Berlin).
• radius (integer, optional): The search radius in kilometers from the specified location (e.g., 5 for a 5 km radius).
• min_price (integer, optional): The minimum price in Euros for the listings (e.g., 200 for at least 200 Euros).
• max_price (integer, optional): The maximum price in Euros for the listings (e.g., 500 for at most 500 Euros).
• page_count (integer, optional): The number of pages to search or return (e.g., 5 for the first 5 pages, default is 1, max: 20 pages).

Example Request

GET /inserate?query=fahrrad&location=10178&radius=5&min_price=200&page_count=5

2. Fetch Listing Details

Endpoint: GET /inserat/{id}

Description: Retrieves detailed information about a specific listing.

Path Parameters

• id (string): The unique identifier of the listing to fetch details for.

Example Request

GET /inserat/12345

3. Fetch Listings with Details (Combined)

Endpoint: GET /inserate-detailed

Description: Retrieves listings and their detailed information in a single request.

Query Parameters

Same as /inserate endpoint, plus:

• max_concurrent_details (integer, optional): Maximum concurrent detail fetches (default: 5, max: 10).

Example Request

GET /inserate-detailed?query=laptop&page_count=2&max_concurrent_details=5

Documentation

API Response Format

All API endpoints return responses in the following JSON format:

API Response Format

{
  "success": true,
  "time_taken": 1.23,
  "unique_results": 100,
  "data": [...],
  "performance_metrics": {
    "pages_requested": 5,
    "pages_successful": 5,
    "success_rate": 100.0,
    "average_page_time": 2.45
  }
}

Combined Endpoint Response Format

{
  "success": true,
  "time_taken": 3.45,
  "unique_results": 25,
  "data": [
    {
      "adid": "123456",
      "title": "Example Item",
      "price": "100",
      "details": {
        "id": "123456",
        "description": "Full description...",
        "seller": {...},
        "location": {...}
      }
    }
  ],
  "performance_metrics": {
    "listings_found": 25,
    "details_fetched": 25,
    "success_rate": 100.0
  }
}

Performance Features

📊 Performance Benchmarks

Performance tests conducted on Arch Linux with Intel i7-1260P processor:

Endpoint	Operation	Avg Time	Min Time	Max Time	Success Rate	Results
Root	API status check	0.004s	0.001s	0.009s	100%	-
Listings	1 page search	1.209s	1.081s	1.596s	100%	25
Listings	5 pages search	2.436s	2.328s	2.532s	100%	125
Listings	10 pages search	4.989s	4.790s	5.229s	100%	250
Details	Single listing details	1.072s	0.928s	1.276s	100%	1
Combined	1 page + details	9.058s	8.804s	9.319s	100%	25
Combined	2 pages + details	17.512s	17.063s	18.038s	100%	50

Performance Highlights

• Single page search: ~1.2s average response time
• 10-page search: ~5.0s average response time
• Individual listing details: ~1.1s average response time
• Combined search + details: ~9.1s average for 1 page with full details

All tests performed with uvloop optimization and browser context pooling enabled.

🚀 Technical Features

• uvloop Integration: High-performance asyncio event loop
• Context Pooling: Efficient browser resource reuse
• Memory Optimization: Automatic garbage collection and efficient processing
• Intelligent Concurrency: Optimal concurrent processing with resource control

🔧 Production Ready

• Clean API Responses: Minimal overhead with essential data only
• Resource Management: Automatic cleanup and efficient resource usage
• Scalable Architecture: Handles concurrent requests efficiently
• Docker Optimized: Fast container builds with uv package manager

API documentation is available at http://localhost:8000/docs when running locally.

License

Distributed under the MIT License. See LICENSE for more information.

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