Python cProfile Graphviz With Example

To create a visual representation of Python code profiling data using cProfile and Graphviz, you can follow these steps:

  1. First, make sure you have cProfile and Graphviz installed. You can install cProfile as it’s included in the Python standard library. To install Graphviz, you can use pip:
pip install graphvizCode language: Python (python)
  1. Create a Python script that uses cProfile to profile your code. For example, let’s assume you have a script named
import cProfile

def your_function_to_profile():
    # Your code to profile here

if __name__ == "__main__":
    profiler = cProfile.Profile()

    # Call the function you want to profile

    profiler.print_stats(sort="cumulative")Code language: Python (python)

Replace your_function_to_profile with the actual function or code you want to profile.

  1. Run your Python script to generate the profiling data. This will print the profiling data to the console.
python my_script.pyCode language: Python (python)
  1. Now, you can use gprof2dot to convert the profiling data to a format that can be visualized with Graphviz. If you don’t have gprof2dot installed, you can install it using pip:
pip install gprof2dotCode language: Python (python)
  1. Generate a dot file using gprof2dot. Redirect the output to a file like this:
python -m gprof2dot -f pstats > my_script.dotCode language: Python (python)

Replace with the actual name of the profiling data file generated by your script.

  1. Finally, use Graphviz to convert the dot file to an image format (e.g., PNG):
dot -Tpng -o my_script.png my_script.dotCode language: Python (python)

This command will create a PNG image (my_script.png) that represents the profiling data in a graphical form.

You can open the generated PNG file with an image viewer to visualize the profiling results. This graphical representation will help you identify bottlenecks and performance issues in your Python code.

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  • Abdullah Walied Allama

    Abdullah Walied Allama is a driven programmer who earned his Bachelor's degree in Computer Science from Alexandria University's Faculty of Computer and Data Science. He is passionate about constructing problem-solving models and excels in various technical skills, including Python, data science, data analysis, Java, SQL, HTML, CSS, and JavaScript.

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