为什么删除 else 会减慢我的代码? [英] Why does removing the else slow down my code?

问题描述

考虑以下功能:

def fact1(n):如果 n <2:返回 1别的:返回 n * 事实 1(n-1)事实上2(n):如果 n <2:返回 1返回 n * 事实 2(n-1)

它们应该是等价的.但存在性能差异:

<预><代码>>>>T(lambda : fact1(1)).repeat(number=10000000)[2.5754408836364746, 2.5710129737854004, 2.5678811073303223]>>>T(lambda : fact2(1)).repeat(number=10000000)[2.8432059288024902, 2.834425926208496, 2.8364310264587402]

没有 else 的版本慢 10%.这是相当重要的.为什么?

解决方案

对我来说，它们的速度几乎相同:(Debian 上的 Python 2.6.6)

在 [4]: %timeit fact1(1)10000000 个循环，最好的 3 个:每个循环 151 ns在 [5] 中:%timeit fact2(1)10000000 个循环，最好的 3 个:每个循环 154 ns

字节码也很相似:

在[6]中:dis.dis(fact1)2 0 LOAD_FAST 0 (n)3 LOAD_CONST 1 (2)6 COMPARE_OP 0 (<)9 JUMP_IF_FALSE 5(到 17)12 POP_TOP3 13 LOAD_CONST 2 (1)16 RETURN_VALUE>>17 POP_TOP5 18 LOAD_FAST 0 (n)21 LOAD_GLOBAL 0(事实)24 LOAD_FAST 0 (n)27 LOAD_CONST 2 (1)30 BINARY_SUBTRACT31 CALL_FUNCTION 134 BINARY_MULTIPLY35 RETURN_VALUE36 LOAD_CONST 0 (无)39 RETURN_VALUE在 [7] 中:dis.dis(fact2)2 0 LOAD_FAST 0 (n)3 LOAD_CONST 1 (2)6 COMPARE_OP 0 (<)9 JUMP_IF_FALSE 5(到 17)12 POP_TOP3 13 LOAD_CONST 2 (1)16 RETURN_VALUE>>17 POP_TOP4 18 LOAD_FAST 0 (n)21 LOAD_GLOBAL 0(事实)24 LOAD_FAST 0 (n)27 LOAD_CONST 2 (1)30 BINARY_SUBTRACT31 CALL_FUNCTION 134 BINARY_MULTIPLY35 RETURN_VALUE

唯一的区别是带有 else 的版本包括返回 None 的代码，以防控制到达函数体的末尾.

Consider the following functions:

def fact1(n):
    if n < 2:
        return 1
    else:
        return n * fact1(n-1)

def fact2(n):
    if n < 2:
        return 1
    return n * fact2(n-1)

They should be equivalent. But there's a performance difference:

>>> T(lambda : fact1(1)).repeat(number=10000000)
[2.5754408836364746, 2.5710129737854004, 2.5678811073303223]
>>> T(lambda : fact2(1)).repeat(number=10000000)
[2.8432059288024902, 2.834425926208496, 2.8364310264587402]

The version without the else is 10% slower. This is pretty significant. Why?

解决方案

For me, they are virtually the same speed: (Python 2.6.6 on Debian)

In [4]: %timeit fact1(1)
10000000 loops, best of 3: 151 ns per loop

In [5]: %timeit fact2(1)
10000000 loops, best of 3: 154 ns per loop

The byte code is also very similar:

In [6]: dis.dis(fact1)
  2           0 LOAD_FAST                0 (n)
              3 LOAD_CONST               1 (2)
              6 COMPARE_OP               0 (<)
              9 JUMP_IF_FALSE            5 (to 17)
             12 POP_TOP             

  3          13 LOAD_CONST               2 (1)
             16 RETURN_VALUE        
        >>   17 POP_TOP             

  5          18 LOAD_FAST                0 (n)
             21 LOAD_GLOBAL              0 (fact)
             24 LOAD_FAST                0 (n)
             27 LOAD_CONST               2 (1)
             30 BINARY_SUBTRACT     
             31 CALL_FUNCTION            1
             34 BINARY_MULTIPLY     
             35 RETURN_VALUE        
             36 LOAD_CONST               0 (None)
             39 RETURN_VALUE        

In [7]: dis.dis(fact2)
  2           0 LOAD_FAST                0 (n)
              3 LOAD_CONST               1 (2)
              6 COMPARE_OP               0 (<)
              9 JUMP_IF_FALSE            5 (to 17)
             12 POP_TOP             

  3          13 LOAD_CONST               2 (1)
             16 RETURN_VALUE        
        >>   17 POP_TOP             

  4          18 LOAD_FAST                0 (n)
             21 LOAD_GLOBAL              0 (fact)
             24 LOAD_FAST                0 (n)
             27 LOAD_CONST               2 (1)
             30 BINARY_SUBTRACT     
             31 CALL_FUNCTION            1
             34 BINARY_MULTIPLY     
             35 RETURN_VALUE        

The only difference is that the version with the else includes code to return None in case control reaches the end of the function body.

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