In Python web scraping, how do I profile bottlenecks?

Profiling bottlenecks in Python web scraping involves identifying and optimizing slow parts of your code to improve performance. By using profiling tools, you can pinpoint areas that take longer to execute, allowing you to make necessary adjustments for efficiency.
web scraping, Python, performance optimization, profiling, code bottlenecks
import cProfile import pstats import io def scrape_data(): # Your scraping logic here pass def main(): scrape_data() # Profiling the main function pr = cProfile.Profile() pr.enable() main() pr.disable() s = io.StringIO() sortby = pstats.SortKey.CUMULATIVE ps = pstats.Stats(pr, stream=s).sort_stats(sortby) ps.print_stats() print(s.getvalue())

web scraping Python performance optimization profiling code bottlenecks

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