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This project is a web scraper designed to extract football match details from the Yallakora website based on a user-defined date. The extracted data is then stored in a CSV file for easy access and analysis. This tool is particularly useful for football enthusiasts, analysts, and developers who need to gather match information efficiently.

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AbdelrahmanElalfee/Yallakora-Match-Scraper

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Yallakora Matches Scraper

This project is a web scraper designed to extract football match details from the Yallakora website based on a user-defined date. The extracted data is then stored in a CSV file for easy access and analysis. This tool is particularly useful for football enthusiasts, analysts, and developers who need to gather match information efficiently.

Features

  • Date-based Scraping: Users can specify a date to fetch the football match details.
  • Comprehensive Data Extraction: Extracts various details such as match date, time, teams, and scores.
  • CSV Storage: Saves the scraped data into a well-structured CSV file for further use.

Requirements

  • Python 3.x
  • Required Python libraries:
    • requests
    • beautifulsoup4
    • lxml

Installation

  1. Clone this repository:

    git clone https://github.com/AbdelrahmanElalfee/Yallakora-Match-Scraper.git
    cd Yallakora-Match-Scraper
  2. Install the required Python libraries:

    pip install requests beautifulsoup4 pandas

Usage

  1. Run the scraper script:

    python3 scrapper.py
  2. Write the desired date:

    Please enter the date in the format of (MM/DD/YYYY):
    7/7/2024
  3. Write the filename to save the data in:

    Please enter the name of the file you want to save the data in ['filename.csv']:
    yallakora.csv
  4. Look for the csv file in the directory.

Notes

  • Ensure that the Yallakora website's structure has not changed, as this may affect the scraper's ability to extract data.

About

This project is a web scraper designed to extract football match details from the Yallakora website based on a user-defined date. The extracted data is then stored in a CSV file for easy access and analysis. This tool is particularly useful for football enthusiasts, analysts, and developers who need to gather match information efficiently.

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