Think Your Python Code Is Slow? Stop Guessing and Start Measuring

Performance issues in Python code can be diagnosed by profiling rather than guessing where optimizations are needed. The process uses `cProfile`, a built-in Python module, to collect detailed statistics on function calls and execution times. This raw data is then visualized using the `snakeviz` library, which generates an interactive icicle chart to clearly identify performance bottlenecks. Through a hands-on example, the article demonstrates how to pinpoint specific CPU-bound and iteration-heavy functions that are slowing down the program, enabling targeted fixes.