PEP 8规定:

导入总是放在文件的顶部,就在任何模块注释和文档字符串之后,在模块全局变量和常量之前。

然而,如果我导入的类/方法/函数只在很少的情况下使用,那么在需要时进行导入肯定会更有效吗?

这不是:

class SomeClass(object):

    def not_often_called(self)
        from datetime import datetime
        self.datetime = datetime.now()

比这更有效率?

from datetime import datetime

class SomeClass(object):

    def not_often_called(self)
        self.datetime = datetime.now()

当前回答

在函数中导入变量/局部作用域可以提高性能。这取决于函数中导入对象的使用情况。如果你多次循环并访问一个模块全局对象,将它导入为本地会有帮助。

test.py

X=10
Y=11
Z=12
def add(i):
  i = i + 10

runlocal.py

from test import add, X, Y, Z

    def callme():
      x=X
      y=Y
      z=Z
      ladd=add 
      for i  in range(100000000):
        ladd(i)
        x+y+z

    callme()

run.py

from test import add, X, Y, Z

def callme():
  for i in range(100000000):
    add(i)
    X+Y+Z

callme()

在Linux上的时间显示了一个小的增益

/usr/bin/time -f "\t%E real,\t%U user,\t%S sys" python run.py 
    0:17.80 real,   17.77 user, 0.01 sys
/tmp/test$ /usr/bin/time -f "\t%E real,\t%U user,\t%S sys" python runlocal.py 
    0:14.23 real,   14.22 user, 0.01 sys

真实的是挂钟。用户是程序中的时间。Sys是系统调用的时间。

https://docs.python.org/3.5/reference/executionmodel.html#resolution-of-names

其他回答

以下是对这个问题的最新答案总结 而且 相关的 的问题。

PEP 8 recommends putting imports at the top. It's often more convenient to get ImportErrors when you first run your program rather than when your program first calls your function. Putting imports in the function scope can help avoid issues with circular imports. Putting imports in the function scope helps keep maintain a clean module namespace, so that it does not appear among tab-completion suggestions. Start-up time: imports in a function won't run until (if) that function is called. Might get significant with heavy-weight libraries. Even though import statements are super fast on subsequent runs, they still incur a speed penalty which can be significant if the function is trivial but frequently in use. Imports under the __name__ == "__main__" guard seem very reasonable. Refactoring might be easier if the imports are located in the function where they're used (facilitates moving it to another module). It can also be argued that this is good for readability. However, most would argue the contrary, i.e. Imports at the top enhance readability, since you can see all your dependencies at a glance. It seems unclear if dynamic or conditional imports favour one style over another.

Putting the import statement inside of a function can prevent circular dependencies. For example, if you have 2 modules, X.py and Y.py, and they both need to import each other, this will cause a circular dependency when you import one of the modules causing an infinite loop. If you move the import statement in one of the modules then it won't try to import the other module till the function is called, and that module will already be imported, so no infinite loop. Read here for more - effbot.org/zone/import-confusion.htm

下面是一个示例,其中所有导入都位于最顶部(这是我唯一一次需要这样做)。我希望能够在Un*x和Windows上终止子进程。

import os
# ...
try:
    kill = os.kill  # will raise AttributeError on Windows
    from signal import SIGTERM
    def terminate(process):
        kill(process.pid, SIGTERM)
except (AttributeError, ImportError):
    try:
        from win32api import TerminateProcess  # use win32api if available
        def terminate(process):
            TerminateProcess(int(process._handle), -1)
    except ImportError:
        def terminate(process):
            raise NotImplementedError  # define a dummy function

(回顾:约翰·米利金所说。)

Curt提出了一个很好的观点:第二个版本更清晰,并且会在加载时失败,而不是在加载后失败,而且出乎意料。

通常我不担心加载模块的效率,因为它(a)非常快,(b)大多数只发生在启动时。

如果你不得不在意想不到的时候加载重量级模块,使用__import__函数动态加载它们可能更有意义,并确保捕获ImportError异常,并以合理的方式处理它们。

这是一个引人入胜的讨论。和许多人一样,我从未考虑过这个话题。我不得不在函数中导入,因为我想在我的一个库中使用Django ORM。在导入我的模型类之前,我不得不调用django.setup(),因为这是在文件的顶部,它被拖到完全非django库代码中,因为IoC注入器结构。

我稍微改了一下,最后把django.setup()放在了单例构造函数中,并把相关的导入放在了每个类方法的顶部。现在这运行得很好,但让我感到不安,因为导入不在顶部,而且我开始担心导入的额外时间。然后我来到这里,怀着极大的兴趣阅读了大家对此的看法。

我有很长的c++背景,现在使用Python/Cython。我对此的看法是,为什么不把导入放在函数中,除非它会导致一个概要瓶颈。这就像在你需要变量之前为它们声明空间一样。问题是我有数千行代码,所有的导入都在顶部!所以我想从现在开始,当我有时间的时候,我会在这里和那里改变奇怪的文件。