How to Profile Python Code With cProfile

How to Profile Python Code with cProfile


  • How to Profile Python Code With cProfile

    Sadra Yahyapour

    Sadra is a Python back-end developer who loves the architectural design behind the software. A GitHub Campus Expert and open-source contributor. He spends his free time writing high-quality technical articles.

Frequently Asked Questions

When time complexity and execution time become a concern for the service your team is providing.

The main cProfile use-case shines when dealing with complexity and time analysis of code. Profile, on the other hand, allows you to more easily extend your profiling system with its available base classes.

cProfile works in an underlayer that can easily keep track of all operations and functionalities happening through the codebase.

Since cProfile provides the raw statistics, making use of third-party libraries and modules like pstat and io will help you deal with importing and exporting the reports and manipulating the statistics.

cProfile is faster and more efficient than profile. It’s also available as a C extension that is suitable for determining long-running programs.

With the help of cProfile.Profile and pstats.Stats classes and decorators in Python, you can design your own profiling system.

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