循环导入可能令人困惑，因为导入做了两件事:

它执行导入的模块代码 将导入的模块添加到导入模块全局符号表中

前者只执行一次，而后者则在每个import语句中执行。循环导入会在导入模块使用已导入的模块和部分执行的代码时产生这种情况。因此，它将看不到import语句后创建的对象。下面的代码示例演示了它。

循环进口并不是要不惜一切代价避免的终极祸害。在一些框架中，比如Flask，它们是很自然的，调整你的代码来消除它们并不会让代码变得更好。

main.py

print 'import b'
import b
print 'a in globals() {}'.format('a' in globals())
print 'import a'
import a
print 'a in globals() {}'.format('a' in globals())
if __name__ == '__main__':
    print 'imports done'
    print 'b has y {}, a is b.a {}'.format(hasattr(b, 'y'), a is b.a)

b.by

print "b in, __name__ = {}".format(__name__)
x = 3
print 'b imports a'
import a
y = 5
print "b out"

a.py

print 'a in, __name__ = {}'.format(__name__)
print 'a imports b'
import b
print 'b has x {}'.format(hasattr(b, 'x'))
print 'b has y {}'.format(hasattr(b, 'y'))
print "a out"

Python main.py输出带有注释

import b
b in, __name__ = b    # b code execution started
b imports a
a in, __name__ = a    # a code execution started
a imports b           # b code execution is already in progress
b has x True
b has y False         # b defines y after a import,
a out
b out
a in globals() False  # import only adds a to main global symbol table 
import a
a in globals() True
imports done
b has y True, a is b.a True # all b objects are available

这里有很多很棒的答案。虽然通常有快速解决问题的解决方案，其中一些比其他的更python化，但如果您有能力进行一些重构，另一种方法是分析代码的组织，并尝试删除循环依赖。例如，你可能会发现:

文件a.py

from b import B

class A:
    @staticmethod
    def save_result(result):
        print('save the result')

    @staticmethod
    def do_something_a_ish(param):
        A.save_result(A.use_param_like_a_would(param))
    
    @staticmethod
    def do_something_related_to_b(param):
        B.do_something_b_ish(param)

文件b.py

from a import A

class B:
    @staticmethod
    def do_something_b_ish(param):
        A.save_result(B.use_param_like_b_would(param))

在这种情况下，只需要将一个静态方法移动到一个单独的文件中，例如c.py:

文件c.py

def save_result(result):
    print('save the result')

将允许从A中删除save_result方法，从而允许从b中的A中删除A的导入:

重构文件a.py

from b import B
from c import save_result

class A:
    @staticmethod
    def do_something_a_ish(param):
        save_result(A.use_param_like_a_would(param))
    
    @staticmethod
    def do_something_related_to_b(param):
        B.do_something_b_ish(param)

重构文件b.py

from c import save_result

class B:
    @staticmethod
    def do_something_b_ish(param):
        save_result(B.use_param_like_b_would(param))

总之，如果你有一个工具(例如pylint或PyCharm)，它报告的方法可以是静态的，只是在它们上抛出一个staticmethod装饰器可能不是静音警告的最好方法。尽管方法看起来与类相关，但最好将其分离出来，特别是如果您有几个密切相关的模块，它们可能需要相同的功能，并且您打算实践DRY原则。

令我惊讶的是，还没有人提到由类型提示引起的循环导入。 如果只有由于类型提示才有循环导入，则可以以干净的方式避免它们。

考虑main.py，它使用了来自另一个文件的异常:

from src.exceptions import SpecificException

class Foo:
    def __init__(self, attrib: int):
        self.attrib = attrib

raise SpecificException(Foo(5))

专用异常类exceptions.py:

from src.main import Foo

class SpecificException(Exception):
    def __init__(self, cause: Foo):
        self.cause = cause

    def __str__(self):
        return f'Expected 3 but got {self.cause.attrib}.'

这将引发ImportError，因为main.py导入了exception.py，反之亦然，通过Foo和SpecificException。

Because Foo is only required in exceptions.py during type checking, we can safely make its import conditional using the TYPE_CHECKING constant from the typing module. The constant is only True during type checking, which allows us to conditionally import Foo and thereby avoid the circular import error. Something to note is that by doing so, Foo is not declared in exceptions.py at runtime, which leads to a NameError. To avoid that, we add from __future__ import annotations which transforms all type annotations in the module to strings.

因此，我们得到以下Python 3.7+的代码:

from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:  # Only imports the below statements during type checking
   ​from src.main import Foo

class SpecificException(Exception):
   def __init__(self, cause: Foo):  # Foo becomes 'Foo' because of the future import
       ​self.cause = cause

   ​def __str__(self):
       ​return f'Expected 3 but got {self.cause.attrib}.'

在Python 3.6中，future import不存在，所以Foo必须是一个字符串:

from typing import TYPE_CHECKING
if TYPE_CHECKING:  # Only imports the below statements during type checking
   ​from src.main import Foo

class SpecificException(Exception):
   ​def __init__(self, cause: 'Foo'):  # Foo has to be a string
       ​self.cause = cause

   ​def __str__(self):
       ​return f'Expected 3 but got {self.cause.attrib}.'

在Python 3.5及以下版本中，类型提示功能还不存在。 在Python的未来版本中，注解特性可能会成为强制性的，之后就不再需要导入了。这将发生在哪个版本尚未确定。

这个答案是基于Stefaan Lippens的另一个解决方案，它将你从Python的循环导入洞中挖出来。

模块a.py:

import b
print("This is from module a")

模块b.py

import a
print("This is from module b")

运行“Module a”将输出:

>>> 
'This is from module a'
'This is from module b'
'This is from module a'
>>> 

它输出了这3行，而由于循环导入，它应该输出不定式。 这里列出了运行“模块a”时逐行发生的事情:

The first line is import b. so it will visit module b The first line at module b is import a. so it will visit module a The first line at module a is import b but note that this line won't be executed again anymore, because every file in python execute an import line just for once, it does not matter where or when it is executed. so it will pass to the next line and print "This is from module a". After finish visiting whole module a from module b, we are still at module b. so the next line will print "This is from module b" Module b lines are executed completely. so we will go back to module a where we started module b. import b line have been executed already and won't be executed again. the next line will print "This is from module a" and program will be finished.

这里有个例子让我震惊!

foo.py

import bar

class gX(object):
    g = 10

bar.py

from foo import gX

o = gX()

main.py

import foo
import bar

print "all done"

在命令行:$ python main.py

Traceback (most recent call last):
  File "m.py", line 1, in <module>
    import foo
  File "/home/xolve/foo.py", line 1, in <module>
    import bar
  File "/home/xolve/bar.py", line 1, in <module>
    from foo import gX
ImportError: cannot import name gX

bar.py

print('going to import foo')
from foo import printx

foo.py

print('trying to import bar')
import bar

def printx():
    print('x')

$ python bar.py

going to import foo
trying to import bar
going to import foo
Traceback (most recent call last):
  File "bar.py", line 2, in <module>
    from foo import printx
  File "/home/suhail/Desktop/temp/circularimport/foo.py", line 2, in <module>
    import bar
  File "/home/suhail/Desktop/temp/circularimport/bar.py", line 2, in <module>
    from foo import printx
ImportError: cannot import name 'printx' from partially initialized module 'foo' (most likely due to a circular import) (/home/suhail/Desktop/temp/circularimport/foo.py)