There are many ways using which a user can optemize the Python code for faster performance,a few of them are:
Use built-in functions and libraries instead of writing custom code can lead to significant speed improvements.
Avoid using global variables as accessing global variables can be slower.Whenever possible, use local variables instead.
Use list comprehension instead of loops as it is faster.
Use generators instead of lists because they are more memory-efficient than lists.
Use the built-in functions map(), filter(), and reduce() function instead of writing your own.
Try to minimize function calls where possible as calling these functions can be expensive.
Use Cython or Numba for computationally intensive tasks because they can significantly speed up computationally intensive Python code
Thee Role of Python in natural language processing (NLP)