Skip to content

Latest commit

 

History

History
79 lines (46 loc) · 2.5 KB

README.md

File metadata and controls

79 lines (46 loc) · 2.5 KB
Raw

Web Scraping Case Study

A Python program for web scraping, MongoDB interaction, data analysis, and statistics collection.

Overview

This Python script performs various operations such as scraping news articles from a website, storing data in MongoDB, analyzing word frequency, and collecting statistics.

Functionality Summary

Data Scraping

  • The scrape_data function extracts news articles from a specified website.
  • The scrape_and_store_data_worker function retrieves data from a specific page and stores it in MongoDB.
  • The scrape_and_store_data function retrieves and processes data from a range of pages in parallel.

MongoDB Interaction

  • The connect_to_mongodb function establishes a connection to a MongoDB database.
  • The scrape_and_store_data_worker function adds the scraped data to MongoDB.
  • The group_and_display_by_update_date function groups data in MongoDB based on update dates.

Data Analysis

  • The analyze_and_store_word_frequency function analyzes word frequency in the text content of scraped articles.
  • It generates bar charts for the top 10 most used words and stores the results in MongoDB.

Statistics Collection

  • The update_stats_collection function collects statistics such as elapsed time, success and failure counts, and stores them in MongoDB.

Main Program

  • The main function orchestrates the above functionalities in sequence.

Error Handling and Logging

  • try-except blocks handle potential errors during execution, and errors are logged in the logs.log file.

Installation Instructions

  1. Clone the repository to your local machine.
  2. Install the required dependencies using pip install -r requirements.txt.
  3. Make sure you have MongoDB installed and running on your local machine.

Usage

  1. Run the main function to execute the entire data processing workflow.

Dependencies

  • BeautifulSoup
  • requests
  • pymongo
  • matplotlib
  • datetime
  • concurrent.futures
  • logging

Analysis Results

  • The word frequency analysis results are stored in MongoDB.
  • Bar charts for the top 10 most used words can be found in the project directory (barchart.png).
    Bar Chart
  • Log information is available in the logs.log file.

Important Notes

  • Ensure compliance with the terms of use of the website being scraped.
  • Be aware of legal regulations related to web scraping.

License

This project is licensed under the MIT License.