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

当函数被调用0次或1次时,第一种变体确实比第二种更有效。然而,对于第二次和后续调用,“导入每个调用”方法实际上效率较低。请参阅此链接,了解一种通过“惰性导入”将两种方法的优点结合起来的惰性加载技术。

但除了效率之外,还有其他原因可以解释为什么你会更喜欢其中一种。一种方法是让阅读代码的人更清楚地了解这个模块所具有的依赖关系。它们也有非常不同的失败特征——如果没有“datetime”模块,第一个将在加载时失败,而第二个直到方法被调用才会失败。

补充说明:在IronPython中,导入可能比在CPython中要昂贵一些,因为代码基本上是在导入时被编译的。

其他回答

I do not aspire to provide complete answer, because others have already done this very well. I just want to mention one use case when I find especially useful to import modules inside functions. My application uses python packages and modules stored in certain location as plugins. During application startup, the application walks through all the modules in the location and imports them, then it looks inside the modules and if it finds some mounting points for the plugins (in my case it is a subclass of a certain base class having a unique ID) it registers them. The number of plugins is large (now dozens, but maybe hundreds in the future) and each of them is used quite rarely. Having imports of third party libraries at the top of my plugin modules was a bit penalty during application startup. Especially some thirdparty libraries are heavy to import (e.g. import of plotly even tries to connect to internet and download something which was adding about one second to startup). By optimizing imports (calling them only in the functions where they are used) in the plugins I managed to shrink the startup from 10 seconds to some 2 seconds. That is a big difference for my users.

所以我的答案是否定的,不要总是把导入放在模块的顶部。

大多数情况下,这对于清晰和明智的做法是有用的,但并不总是如此。下面是模块导入可能存在于其他地方的两个例子。

首先,你可以有一个这样的单元测试模块:

if __name__ == '__main__':
    import foo
    aa = foo.xyz()         # initiate something for the test

其次,您可能需要在运行时有条件地导入一些不同的模块。

if [condition]:
    import foo as plugin_api
else:
    import bar as plugin_api
xx = plugin_api.Plugin()
[...]

在其他情况下,您可能会在代码的其他部分导入。

为了完成老谋子的回答和最初的问题:

当我们不得不处理循环依赖关系时,我们可以做一些“技巧”。假设我们正在处理模块a.py和b.py,它们分别包含x()和b.y()。然后:

我们可以移动模块底部的from导入之一。 我们可以将其中一个from导入移动到实际需要导入的函数或方法中(这并不总是可行的,因为您可能从多个地方使用它)。 我们可以把其中一个import改成import,就像import a

总结一下。如果您没有处理循环依赖关系,也没有使用某种技巧来避免它们,那么最好将所有导入放在顶部,因为原因已经在这个问题的其他答案中解释过了。请在做这些“技巧”时附上评论,这总是受欢迎的!:)

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。)

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