An open-source Python library for web scraping tasks. Includes support for both text and image scraping.
- Added new params to both
scrape_images
andscrape_text
to allow for following child links, and setting a maximum allowed followed child links. - Added a
json
export format for text scraping, with improvements to exporting.
Tip
We recommend disabling remove_duplicates
on large sites, to allow for faster text scraping (this can improve speed by 4x). It also may not work well with follow_child_links
enabled, as it may remove similar content from scraped child links.
- Added new parameters to
scrape_text
to allow automatic removal of duplicates or similar text, and another to specify the type of textual content to scrape (text
,content
,unseen
,links
).
- Added support for handling of different types of images on websites. Also now checks for invalid images, with added error handling.
Changes in version 0.1.2:
min
andmax
width and height parameters can now be specified when working with image scraping, allowing you to quickly exclude smaller resolution images, or images that are extremely large and take up too much space.- PyWebScrapr now uses BeautifulSoup4's
SoupStrainer
, making extracting content from webpages much faster.
You can install PyWebScrapr using pip:
pip install pywebscrapr
PyWebScrapr supports the following Python versions:
- Python 3.6
- Python 3.7
- Python 3.8
- Python 3.9
- Python 3.10
- Python 3.11
- Python 3.12/Later (Preferred)
Please ensure that you have one of these Python versions installed before using PyWebScrapr. PyWebScrapr may not work as expected on lower versions of Python than the supported.
- Text Scraping: Extract textual content from specified URLs.
- Image Scraping: Download images from specified URLs.
*for a full list check out the PyWebScrapr official documentation.
from pywebscrapr import scrape_text
# Specify links in a file or list
links_file = 'links.txt'
links_array = ['https://example.com/page1', 'https://example.com/page2']
# Scrape text and save to the 'output.txt' file
scrape_text(links_file=links_file, links_array=links_array, output_file='output.txt')
from pywebscrapr import scrape_images
# Specify links in a file or list
links_file = 'image_links.txt'
links_array = ['https://example.com/image1.jpg', 'https://example.com/image2.png']
# Scrape images and save to the 'images' folder
scrape_images(links_file=links_file, links_array=links_array, save_folder='images')
Contributions are welcome! If you encounter any issues, have suggestions, or want to contribute to PyWebScrapr, please open an issue or submit a pull request on GitHub.
PyWebScrapr is released under the terms of the MIT License (Modified). Please see the LICENSE file for the full text.
Modified License Clause
The modified license clause grants users the permission to make derivative works based on the PyWebScrapr software. However, it requires any substantial changes to the software to be clearly distinguished from the original work and distributed under a different name.