Share your experience in improving performance and reducing code execution time

To improve performance and reduce execution time of Python code, I usually apply the following approaches:

• Profiling code using modules like cProfile or timeit to identify bottlenecks.
• Using built-in functions and libraries — they are usually optimized in C and run faster than custom code.
• Algorithm optimization — replacing high-complexity algorithms with more efficient ones.
• Avoiding redundant operations — for example, minimizing the number of loops, using generators instead of lists when a full list is not needed.
• Using data structures with appropriate complexity — for example, set for fast lookup instead of a list.
• Memoization and caching of function results if they are called repeatedly with the same parameters.

Example of string concatenation optimization:

# Slow method
result = ""
for s in list_of_strings:
    result += s  # creates a new string each time

# Fast method
result = ''.join(list_of_strings)

This approach significantly reduces execution time when working with large data volumes.