Some say the price of holding heat is often too high
You either be in a coffin or you be the new guy
The one that’s too fly to eat shoe pie


Suppose I am looping over a range of numbers to see if any of them matches some magic number:

for i in range(1_000_000_000):
    if i == -1:

On my modest desktop, this takes 60 seconds to execute.

But as everyone knows, using magic numbers in code is bad. It would be clearer and more maintainable to express the value as a variable:


for i in range(1_000_000_000):
    if i == MAGIC_NUMBER:

On my modest desktop, this takes 70 seconds to execute. Ten seconds longer – that’s not great!

Okay, so forget about variables. A better form of abstraction would be to get the comparison logic out of the loop and centralize it in a function:

def number_matches(num: int) -> bool:
    return num == -1

for i in range(1_000_000_000):
    if number_matches(i):

On my modest desktop, this one takes 110 seconds to execute. The price to be paid for this minor organizational improverment is a catastrophic degradation of performance.

The situation is grim if you have some Python hot spot code that needs to be cleaned up. Because it’s a hot spot, any abstraction could have dire consequences, and so the range of acceptable changes is constrained.

On the other hand, this is great news if you have a hot spot that uses abstractions. It may be possible to trade a little maintainability for a lot of speedup. Inline some constants, inline some function calls, that kind of thing. It doesn’t look nice, but hey, it’s Python.