{"id":12389,"date":"2023-09-03T14:26:28","date_gmt":"2023-09-03T14:26:28","guid":{"rendered":"https:\/\/www.digitaldesignjournal.com\/?p=12389"},"modified":"2023-09-15T06:01:00","modified_gmt":"2023-09-15T06:01:00","slug":"python-cprofile-to-html","status":"publish","type":"post","link":"https:\/\/www.digitaldesignjournal.com\/python-cprofile-to-html\/","title":{"rendered":"Python cProfile to HTML With Example"},"content":{"rendered":"\n

Profiling Python code using cProfile and generating an HTML report is a useful way to analyze the performance of your code and identify bottlenecks. To do this, you can use the cProfile<\/code> module to profile your Python script and then use a tool like pyprof2html<\/code> to convert the profiling data into an HTML report. Here’s how you can do it:<\/p>\n\n\n\n

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  1. First, ensure you have cProfile<\/code> installed. It’s a standard Python library, so it should be available by default.<\/li>\n\n\n\n
  2. Install pyprof2html<\/code> if you haven’t already. You can do this using pip<\/code>:<\/li>\n<\/ol>\n\n\n
    pip install pyprof2html<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
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    1. Create a Python script that you want to profile. For example, let’s say you have a script called my_script.py<\/code>:<\/li>\n<\/ol>\n\n\n
      # my_script.py<\/span>\n\ndef<\/span> some_function<\/span>()<\/span>:<\/span>\n    for<\/span> _ in<\/span> range(1000000<\/span>):\n        pass<\/span>\n\ndef<\/span> main<\/span>()<\/span>:<\/span>\n    some_function()\n\nif<\/span> __name__ == \"__main__\"<\/span>:\n    main()<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
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      1. Profile your script using cProfile<\/code>. You can do this from the command line:<\/li>\n<\/ol>\n\n\n
        python -m cProfile -o my_script_profile.prof my_script.py<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
        This command will run your script with the cProfile<\/code> profiler, and the profiling data will be saved to a file named my_script_profile.prof<\/code>.<\/p>\n\n\n\n
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        1. Convert the profiling data to an HTML report using pyprof2html<\/code>:<\/li>\n<\/ol>\n\n\n
          pyprof2html my_script_profile.prof<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
          This command will generate an HTML report with the name my_script_profile.prof.html<\/code>.<\/p>\n\n\n\n
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          1. Open the HTML report in your web browser to analyze the profiling results:<\/li>\n<\/ol>\n\n\n
            xdg-open my_script_profile.prof.html  # On Linux<\/span>\nopen my_script_profile.prof.html       # On macOS<\/span>\nstart my_script_profile.prof.html      # On Windows<\/span><\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
            You will see a detailed breakdown of function calls, their cumulative time, and more in the HTML report, helping you identify performance bottlenecks in your code.<\/p>\n\n\n\n
            That’s how you can use cProfile<\/code> and pyprof2html<\/code> to profile your Python code and generate an HTML report for performance analysis.<\/p>\n\n\n\n
            Read More;<\/strong><\/p>\n\n\n\n