Logging is essential in Python web scraping to track the progress of your scraping script, handle exceptions, and maintain an overview of the data being extracted. A good logging setup helps in debugging and understanding the behavior of your application.
python web scraping, logging, effective logging, exception handling, debug, data extraction
import logging
import requests
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
try:
response = requests.get('http://example.com')
response.raise_for_status() # Raise an error for bad responses
logging.info('Successfully retrieved the page.')
except requests.exceptions.RequestException as e:
logging.error('Failed to retrieve the page: %s', e)
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?