https://github.com/shadowfaxx1/improved-dollop
web-scraper using beautiful Soup that uses Rotational IP's
https://github.com/shadowfaxx1/improved-dollop
Last synced: 2 months ago
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web-scraper using beautiful Soup that uses Rotational IP's
- Host: GitHub
- URL: https://github.com/shadowfaxx1/improved-dollop
- Owner: shadowfaxx1
- License: mit
- Created: 2023-06-15T07:38:48.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-15T07:43:33.000Z (almost 2 years ago)
- Last Synced: 2025-01-26T08:41:41.621Z (4 months ago)
- Language: Python
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Rotational IP Web Scraper with Beautiful Soup
[](LICENSE)
This repository contains a web scraper built using Beautiful Soup in Python. The scraper is designed to extract data from web pages and incorporates rotational IP functionality to enhance scraping efficiency and bypass IP blocking or rate limiting.
## Features
- **Data Extraction**: The web scraper utilizes Beautiful Soup's powerful parsing capabilities to extract data from HTML or XML web pages. It can handle complex HTML structures and extract specific elements based on CSS selectors or other filtering criteria.
- **Rotational IP**: The scraper incorporates a rotational IP mechanism that allows it to switch between a pool of IP addresses during the scraping process. This helps to overcome IP blocking or rate limiting by distributing requests across different IPs.
- **Proxy Integration**: The scraper seamlessly integrates with proxy services to acquire a pool of rotating IP addresses. It supports popular proxy providers and allows you to configure and manage the proxy settings easily.
- **Concurrency**: The scraper employs concurrent processing techniques to enhance performance. It can make multiple concurrent requests and process the retrieved data efficiently.
- **Data Transformation**: The extracted data can be transformed and processed using Python's data manipulation libraries such as Pandas or NumPy. This allows for further analysis, filtering, or transformation of the scraped data.
## Installation
1. Clone this repository to your local machine.
2. Install the required dependencies by running `pip install -r requirements.txt`.
## Usage
1. Set up your proxy service and obtain the necessary credentials or API keys.
2. Configure the proxy settings in the scraper code, specifying the proxy provider, credentials, and other relevant details.
3. Customize the scraping behavior by modifying the target URLs, data extraction rules, and output formats in the scraper code.
4. Run the scraper script, and it will initiate the rotational IP scraping process, extracting data from the specified web pages.
5. Process or analyze the extracted data as needed, using Python libraries or tools of your choice.
## License
This project is licensed under the [MIT License](LICENSE).