Python列表理解昂贵

Question

我试图找到列表理解的效率,但它看起来比正常的功能操作更昂贵.谁能解释一下？

def squares(values):
    lst = []
    for x in range(values):
        lst.append(x*x)
    return lst

def main():
    t = timeit.Timer(stmt="lst = [x*x for x in range(10)]")
    print t.timeit()
    t = timeit.Timer(stmt="squares",setup="from __main__ import squares")
    print t.timeit()

    lst = [x*x for x in range(10)]
    print lst
    print squares(10)



----Output:---
2.4147507644
0.0284455255965
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

对于相同的输出,与列表理解相比,正常函数在非常短的时间内计算.

我认为列表理解更有效.

Answer 1

你永远不会调用你的squares函数,因此它没有做任何事情.

List内涵是实际上更快:

>>> import timeit
>>> def squares(values):
...     lst = []
...     for x in range(values):
...         lst.append(x*x)
...     return lst
... 
>>> def squares_comp(values):
...     return [x*x for x in range(values)]
... 
>>> timeit.timeit('f(10)', 'from __main__ import squares as f')
3.9415171146392822
>>> timeit.timeit('f(10)', 'from __main__ import squares_comp as f')
2.3243820667266846

如果您使用该dis模块查看每个函数的字节码,您可以看到原因:

>>> import dis
>>> dis.dis(squares)
  2           0 BUILD_LIST               0
              3 STORE_FAST               1 (lst)

  3           6 SETUP_LOOP              37 (to 46)
              9 LOAD_GLOBAL              0 (range)
             12 LOAD_FAST                0 (values)
             15 CALL_FUNCTION            1
             18 GET_ITER            
        >>   19 FOR_ITER                23 (to 45)
             22 STORE_FAST               2 (x)

  4          25 LOAD_FAST                1 (lst)
             28 LOAD_ATTR                1 (append)
             31 LOAD_FAST                2 (x)
             34 LOAD_FAST                2 (x)
             37 BINARY_MULTIPLY     
             38 CALL_FUNCTION            1
             41 POP_TOP             
             42 JUMP_ABSOLUTE           19
        >>   45 POP_BLOCK           

  5     >>   46 LOAD_FAST                1 (lst)
             49 RETURN_VALUE        
>>> dis.dis(squares_comp)
  2           0 BUILD_LIST               0
              3 LOAD_GLOBAL              0 (range)
              6 LOAD_FAST                0 (values)
              9 CALL_FUNCTION            1
             12 GET_ITER            
        >>   13 FOR_ITER                16 (to 32)
             16 STORE_FAST               1 (x)
             19 LOAD_FAST                1 (x)
             22 LOAD_FAST                1 (x)
             25 BINARY_MULTIPLY     
             26 LIST_APPEND              2
             29 JUMP_ABSOLUTE           13
        >>   32 RETURN_VALUE        

该squares函数.append()在每次迭代中查找列表的方法,并调用它.该.append()函数每次调用时都必须将列表增加一个元素.

另一方面,列表理解不一定要做那项工作.相反,python使用LIST_APPEND字节码,它使用C API将新元素附加到列表中,而不必执行查找和对函数的python调用.