This repository contains Python scripts designed to extract data from wildberries.ru via its API. You can collect information about specific goods (products) and save it in .xlsx files.

This is a minimal example for my freelance portfolio. The real parsers/scrapers I build for clients are much more complex modular software. Often scraping is just the first part of a large-scale pipeline.

Description

The main script collects the following data fields (it's easily expandable though):

• Link
• ID
• Name
• Brand name
• Brand ID
• Price
• Discounted price
• Rating
• Number of reviews
• Number of sales

The script can scan items for the entire category of goods, or using search keywords.

For development purposes, see the docstrings inside the Parser class.

Installation

1. Clone and navigate to the repository:

   git clone git@github.com:avrtt/wildberries-parsers.git
   cd wildberries-parsers
   

2. For stable version, navigate to the folder:

   cd stable-version
   

   There is also a legacy version that is still work, but less optimized. If you need, navigate to another folder instead:

   cd legacy-version
   

3. Since using virtual environments is a good practice, I highly recommend you to create one:

   python3 -m venv venv
   

   Then activate the virtual environment:

   • On Linux/macOS:

     source venv/bin/activate
     

   • On Windows:

     venv\Scripts\activate
     

4. Install the required dependencies:

   pip install -r requirements.txt
   

5. Run:

   python start.py
   

Usage

After running the script, follow the instructions: select parsing method and input your data. You will get an .xlsx file with the parsed content once the program is finished.

Make sure you have a stable connection while parsing items since the script utilizes the requests library.

Contribution

Feel free to open PRs and issues.

License

These scripts are licensed under the MIT License. See the LICENSE file for details.