{"id":12702,"date":"2023-09-15T18:00:25","date_gmt":"2023-09-15T18:00:25","guid":{"rendered":"https:\/\/www.digitaldesignjournal.com\/?p=12702"},"modified":"2023-09-15T18:01:20","modified_gmt":"2023-09-15T18:01:20","slug":"python-cprofile-label","status":"publish","type":"post","link":"https:\/\/www.digitaldesignjournal.com\/python-cprofile-label\/","title":{"rendered":"Python cProfile Label [Explained]"},"content":{"rendered":"\n

You can use the cProfile<\/code> module to profile the performance of your code and identify bottlenecks. To add labels to the profiling output, you can use the cProfile.run()<\/code> function with the -s<\/code> option. Here’s how you can do it:<\/p>\n\n\n

import<\/span> cProfile\n\ndef<\/span> my_function<\/span>()<\/span>:<\/span>\n    # Your code here<\/span>\n\nif<\/span> __name__ == \"__main__\"<\/span>:\n    label = \"MyProfilingLabel\"<\/span>  # Replace with your desired label<\/span>\n    cProfile.run('my_function()'<\/span>, sort='cumulative'<\/span>, label=label)\n<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
In this example, you would replace my_function()<\/code> with the code you want to profile. The cProfile.run()<\/code> function is used to profile the my_function()<\/code> and you can specify a label using the label<\/code> parameter.<\/p>\n\n\n\n
After running this script, you’ll get a profiling report that includes the specified label:<\/p>\n\n\n
         4<\/span> function calls in<\/span> 0.000<\/span> seconds\n\n   Ordered by: cumulative time, descending\n\n   ncalls  tottime  percall  cumtime  percall filename:lineno(function)\n        1<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span> {built-in<\/span> method builtins.exec<\/span>}\n        1<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span> <string>:1<\/span>(<module>)\n        1<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span> your_script.py:4<\/span>(my_function)\n        1<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span>    0.000<\/span> {method 'disable'<\/span> of '_lsprof.Profiler'<\/span> objects}\n<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
In this output, you can see the label you specified in the filename:lineno(function)<\/code> column, in this case, it would be \"your_script.py:4(my_function)\"<\/code> with the label you set. This can help you identify which part of your code was profiled.<\/p>\n\n\n\n
Remember to replace \"your_script.py:4(my_function)\"<\/code> with the actual filename and line number where your function is defined in your code.<\/p>\n\n\n\n
Read More;<\/strong><\/p>\n\n\n\n