Web Scraping for AI Signal Digest

Name: web-scraping
Rating: 76
Author: piconnnie

Core Libraries

•Requests: For HTTP requests.
•BeautifulSoup4: For parsing HTML.
•Arxiv: Official Python library for arXiv API.

Content Acquisition Patterns

1. arXiv Fetching

Use the arxiv library to fetch papers by category.

python

import arxiv

client = arxiv.Client()
search = arxiv.Search(
    query = "cat:cs.AI OR cat:cs.CL",
    max_results = 100,
    sort_by = arxiv.SortCriterion.SubmittedDate
)

for result in client.results(search):
    print(result.title, result.published, result.pdf_url)

2. News Scraping

For news sites, use requests with a proper User-Agent header.

python

import requests
from bs4 import BeautifulSoup

headers = {'User-Agent': 'Mozilla/5.0 (compatible; AI_Signal_Digest/1.0)'}
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.content, 'html.parser')

# Extract title
title = soup.find('h1').text.strip()
# Extract text (simplified)
text = '\n'.join([p.text for p in soup.find_all('p')])

Anti-Blocking

•Respect robots.txt.
•Add delays between requests (time.sleep(1)).
•Use fake-useragent if needed, but prefer identifying your bot.

Error Handling

•Wrap requests in try-except blocks.
•Handle timeouts (requests.get(..., timeout=10)).
•Check response.status_code before parsing.