Why Everyone Says Python is Slow (and Why They Are Wrong) The Performance Comes from Smart Profiling. Code structure is the reason for slow execution and profiling reveals the bottleneck. Stop guessing which function slows the program. Do these 5 things to speed up your code: 1) Run cProfile to find functions with high cumulative time. 2) Replace append loops with list comprehensions to move work to the C level. 3) Use generators for large datasets to keep memory usage constant. 4) Move global variables into local scope inside loops to avoid dictionary lookups. 5) Add slots to your classes to reduce memory usage by 80%. Built-in functions like sum() or map() run in C. Converting their results back to lists adds computation time. 📌Here is the detailed article: https://lnkd.in/d4QpkT9E P.S. I share data analytics tips and my experience in a free newsletter. Join here: https://lnkd.in/d79Zv532
Python isn’t slow by default, unoptimized Python is, and most of the time the bottleneck is easier to fix than people think Mikhail Mikushin
Python isn’t slow, poor code patterns are, profiling shows you where to fix it ⚡ Mikhail Mikushin
Python is not slow, unoptimized thinking is. Most performance issues disappear once you actually measure instead of guessing.
Totally agreed! Mikhail Mikushin Most “Python is slow” conversations skip the profiling step. Once you actually see where time is spent, the fixes become pretty obvious.
This is great Mikhail Mikushin ! Python reminds me of my VB6 Days Object Oriented is Old Skool
The language gets blamed for what is usually a structural decision made before the code was written the wrong data structure, the wrong algorithm, the wrong layer to put the logic at. Python's overhead is real but rarely the primary constraint on performance in real analytical workloads. The constraint is almost always in how the code is structured, not in the language executing it. The list comprehension versus append loop point illustrates this exactly. The difference isn't Python versus something faster. It's Python code that pushes work to C versus Python code that stays in the interpreter for every iteration. Same language. Completely different performance profile. Profile before you optimise. Optimise before you blame the language.