To export the results of a Python cProfile run to a file, you can use the cProfile
module in combination with Python’s pstats
module. Here are the steps to profile your code and export the results:
- Import the necessary modules:
import cProfile
import pstats
Code language: Python (python)
- Create a function or block of code that you want to profile. For example:
def my_function():
# Your code to profile here
for _ in range(1000000):
pass
if __name__ == "__main__":
cProfile.run("my_function()", filename="profile_results.prof")
Code language: Python (python)
In this example, we’re profiling the my_function
and saving the results to a file called “profile_results.prof”.
- Run your Python script. The profiling data will be written to the specified file.
- To view and analyze the profiling data, you can use the
pstats
module. Here’s an example of how to load and print the profiling results:
import pstats
profile_data = pstats.Stats("profile_results.prof")
profile_data.strip_dirs() # Optional: Remove extraneous path information
profile_data.sort_stats("cumulative") # Sort the data by cumulative time
profile_data.print_stats() # Print the profiling results
Code language: Python (python)
Make sure to replace "profile_results.prof"
with the actual filename you used when running the cProfile
.
This will display a report showing the functions that consume the most time, helping you identify performance bottlenecks in your code.
You can also export the profiling data to other formats like text or JSON for further analysis if needed.
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