The WildBerries Parser is a Python script that allows you to collect information on items from the Wildberries website and save it into an xlsx file. The parser provides two modes: scanning items in a specific directory of the marketplace or parsing all items in the search results based on a given keyword. It collects various data from each item, including the link, ID, name, brand name, regular price, discounted price, rating, number of reviews, and total sales.
- Retrieve item data from Wildberries based on categories or search keywords
- Extract information such as link, ID, name, brand, pricing, rating, reviews, and sales
- Save the collected data in xlsx format for further analysis
- Clone this repository to your local machine.
- Navigate to the project directory.
- Python 3.x
- Requests library (
pip install requests) - Pandas library (
pip install pandas)
- Open a terminal or command prompt.
- Navigate to the project directory.
- Run the script using the following command:
python wbparser.py - Follow the on-screen instructions to choose the desired parsing mode and provide the necessary input.
To parse a specific category:
- Choose the parsing mode for a category.
- Enter the category name or URL.
- The script will retrieve all products in the category, collect sales data, and save the parsed data to an xlsx file.
To parse by keywords:
- Choose the parsing mode for keywords.
- Enter the search query.
- The script will retrieve all products in the search results, collect sales data, and save the parsed data to an xlsx file.
Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
Special thanks to Timerlan Nalimov for inspiring this project with his initial parser. I appreciate his work and its contribution to the development of this parser.