KyaNewsScraper 1.0.5

A Python-based tool for scraping news articles from various sources, using different techniques.

# NewsCrawler



NewsCrawler is a Python-based web scraping tool designed to extract news articles from various sources using multiple techniques. It navigates through paywalls and anti-bot measures to retrieve content, leveraging the Google Cache, Selenium with Stealth Mode, and Archive.is for comprehensive coverage.



## Features



- **Multiple Parsing Methods:** Includes Google Cache, Selenium Stealthed, Archive.is, and direct requests to fetch articles.

- **HTML Validation:** Ensures the integrity of the downloaded content, filtering out insufficient or irrelevant data.

- **Dynamic News Source Handling:** Utilizes a custom `NewsUrlGetter` to dynamically fetch news URLs based on specified topics.

- **Robust Error Handling:** Implements custom exceptions for HTML validation and download errors, ensuring reliability.

- **Extensible Design:** Easily adaptable to include more news sources or parsing methods.



## Dependencies



- Python 3.x

- `requests`

- `selenium`

- `newspaper3k`

- `selenium-stealth`

- `beautifulsoup4`



Ensure you have Chrome WebDriver installed and accessible in your system's PATH for Selenium to function properly.



## Installation



1. Clone the repository:

```sh

git clone https://github.com/yourgithubusername/newscrawler.git

```



2. Install the required Python packages:

```sh

pip install -r requirements.txt

```



## Usage



To use NewsCrawler, instantiate the `NewsParser` class with optional parameters for headless browsing and URL filtering. Then, call the `get_news` method with your topic of interest:



```python

from newscrawler import NewsParser, NewsUrlGetter



# Initialize the NewsParser with custom settings

news_parser = NewsParser(NewsUrlGetter(max_results=20, start_date=(2023, 1, 20), end_date=(2023, 12, 25)), headless=True)



# Fetch news articles about "Interest rates"

articles = news_parser.get_news("Interest rates")

```



## Contributing



Contributions are welcome! Please feel free to submit pull requests or create issues for bugs and feature requests.



## License



This project is licensed under the MIT License - see the LICENSE file for details.