Using ‘try’ vs. ‘if’ in Python

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You often hear that Python encourages EAFP style (“it’s easier to ask for forgiveness than permission”) over LBYL style (“look before you leap”). To me, it’s a matter of efficiency and readability.

In your example (say that instead of returning a list or an empty string, the function were to return a list or None), if you expect that 99 % of the time result will actually contain something iterable, I’d use the try/except approach. It will be faster if exceptions really are exceptional. If result is None more than 50 % of the time, then using if is probably better.

To support this with a few measurements:

>>> import timeit
>>> timeit.timeit(setup="a=1;b=1", stmt="a/b") # no error checking
0.06379691968322732
>>> timeit.timeit(setup="a=1;b=1", stmt="try:\n a/b\nexcept ZeroDivisionError:\n pass")
0.0829463709378615
>>> timeit.timeit(setup="a=1;b=0", stmt="try:\n a/b\nexcept ZeroDivisionError:\n pass")
0.5070195056614466
>>> timeit.timeit(setup="a=1;b=1", stmt="if b!=0:\n a/b")
0.11940114974277094
>>> timeit.timeit(setup="a=1;b=0", stmt="if b!=0:\n a/b")
0.051202772912802175

So, whereas an if statement always costs you, it’s nearly free to set up a try/except block. But when an Exception actually occurs, the cost is much higher.

Moral:

  • It’s perfectly OK (and “pythonic”) to use try/except for flow control,
  • but it makes sense most when Exceptions are actually exceptional.

From the Python docs:

EAFP

Easier to ask for forgiveness than
permission. This common Python coding
style assumes the existence of valid
keys or attributes and catches
exceptions if the assumption proves
false. This clean and fast style is
characterized by the presence of many
try and except statements. The
technique contrasts with the LBYL
style common to many other languages
such as C.

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