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A very simple news crawler

Project description

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A very simple news crawler in Python. Developed at Humboldt University of Berlin.

PyPi version python Static Badge Publisher Coverage


Fundus is:

  • A static news crawler. Fundus lets you crawl online news articles with only a few lines of Python code! Be it from live websites or the CC-NEWS dataset.

  • An open-source Python package. Fundus is built on the idea of building something together. We welcome your contribution to help Fundus grow!


Quick Start

To install from pip, simply do:

pip install fundus

Fundus requires Python 3.8+.

Example 1: Crawl a bunch of English-language news articles

Let's use Fundus to crawl 2 articles from publishers based in the US.

from fundus import PublisherCollection, Crawler

# initialize the crawler for news publishers based in the US
crawler = Crawler(PublisherCollection.us)

# crawl 2 articles and print
for article in crawler.crawl(max_articles=2):
    print(article)

That's already it!

If you run this code, it should print out something like this:

Fundus-Article:
- Title: "Feinstein's Return Not Enough for Confirmation of Controversial New [...]"
- Text:  "Democrats jammed three of President Joe Biden's controversial court nominees
          through committee votes on Thursday thanks to a last-minute [...]"
- URL:    https://freebeacon.com/politics/feinsteins-return-not-enough-for-confirmation-of-controversial-new-hampshire-judicial-nominee/
- From:   FreeBeacon (2023-05-11 18:41)

Fundus-Article:
- Title: "Northwestern student government freezes College Republicans funding over [...]"
- Text:  "Student government at Northwestern University in Illinois "indefinitely" froze
          the funds of the university's chapter of College Republicans [...]"
- URL:    https://www.foxnews.com/us/northwestern-student-government-freezes-college-republicans-funding-poster-critical-lgbtq-community
- From:   FoxNews (2023-05-09 14:37)

This printout tells you that you successfully crawled two articles!

For each article, the printout details:

  • the "Title" of the article, i.e. its headline
  • the "Text", i.e. the main article body text
  • the "URL" from which it was crawled
  • the news source it is "From"

Example 2: Crawl a specific news source

Maybe you want to crawl a specific news source instead. Let's crawl news articles from Washington Times only:

from fundus import PublisherCollection, Crawler

# initialize the crawler for The New Yorker
crawler = Crawler(PublisherCollection.us.TheNewYorker)

# crawl 2 articles and print
for article in crawler.crawl(max_articles=2):
    print(article)

Example 3: Crawl articles from CC-NEWS

If you're not familiar with CC-NEWS, check out their paper.

from fundus import PublisherCollection, CCNewsCrawler

# initialize the crawler for news publishers based in the US
crawler = CCNewsCrawler(*PublisherCollection.us)

# crawl 2 articles and print
for article in crawler.crawl(max_articles=2):
  print(article)

Tutorials

We provide quick tutorials to get you started with the library:

  1. Tutorial 1: How to crawl news with Fundus
  2. Tutorial 2: How to crawl articles from CC-NEWS
  3. Tutorial 3: The Article Class
  4. Tutorial 4: How to filter articles
  5. Tutorial 5: How to search for publishers

If you wish to contribute check out these tutorials:

  1. How to contribute
  2. How to add a publisher

Currently Supported News Sources

You can find the publishers currently supported here.

Also: Adding a new publisher is easy - consider contributing to the project!

Evaluation benchmark

Check out our evaluation benchmark.

Scraper Precision Recall F1-Score
Fundus 99.89±0.57 96.75±12.75 97.69±9.75
Trafilatura 90.54±18.86 93.23±23.81 89.81±23.69
BTE 81.09±19.41 98.23±8.61 87.14±15.48
jusText 86.51±18.92 90.23±20.61 86.96±19.76
news-please 92.26±12.40 86.38±27.59 85.81±23.29
BoilerNet 84.73±20.82 90.66±21.05 85.77±20.28
Boilerpipe 82.89±20.65 82.11±29.99 79.90±25.86

Cite

Please cite the following paper when using Fundus or building upon our work:

@misc{dallabetta2024fundus,
      title={Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions}, 
      author={Max Dallabetta and Conrad Dobberstein and Adrian Breiding and Alan Akbik},
      year={2024},
      eprint={2403.15279},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Contact

Please email your questions or comments to Max Dallabetta

Contributing

Thanks for your interest in contributing! There are many ways to get involved; start with our contributor guidelines and then check these open issues for specific tasks.

License

MIT

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