ActivePython 2.7.18 Documentation

18.7. Summary

This chapter has illustrated several important aspects of performance tuning in Python, and performance tuning in general.

If you need to choose between regular expressions and writing a loop, choose regular expressions. The regular expression engine is compiled in C and runs natively on your computer; your loop is written in Python and runs through the Python interpreter.
If you need to choose between regular expressions and string methods, choose string methods. Both are compiled in C, so choose the simpler one.
General-purpose dictionary lookups are fast, but specialtiy functions such as string.maketrans and string methods such as isalpha() are faster. If Python has a custom-tailored function for you, use it.
Don't be too clever. Sometimes the most obvious algorithm is also the fastest.
Don't sweat it too much. Performance isn't everything.

I can't emphasize that last point strongly enough. Over the course of this chapter, you made this function three times faster and saved 20 seconds over 1 million function calls. Great. Now think: over the course of those million function calls, how many seconds will your surrounding application wait for a database connection? Or wait for disk I/O? Or wait for user input? Don't spend too much time over-optimizing one algorithm, or you'll ignore obvious improvements somewhere else. Develop an instinct for the sort of code that Python runs well, correct obvious blunders if you find them, and leave the rest alone.

Dive Into Python

18.7. Summary