如果你导入foo(在bar.py内部)和导入bar(在foo.py内部)，它会工作得很好。在实际运行任何东西时，两个模块都将完全加载，并将相互引用。

问题是当你做from foo import abc(在bar.py内)和from bar import xyz(在foo.py内)时。因为现在每个模块都需要另一个模块已经被导入(以便导入的名称存在)，然后才能导入它。

我完全同意pythoneer的回答。但是我偶然发现了一些代码，它们在循环导入时存在缺陷，并在尝试添加单元测试时引起了问题。因此，为了快速修补它而不改变一切，你可以通过动态导入来解决这个问题。

# Hack to import something without circular import issue
def load_module(name):
    """Load module using imp.find_module"""
    names = name.split(".")
    path = None
    for name in names:
        f, path, info = imp.find_module(name, path)
        path = [path]
    return imp.load_module(name, f, path[0], info)
constants = load_module("app.constants")

同样，这不是一个永久性的修复，但可以帮助那些希望在不修改太多代码的情况下修复导入错误的人。

干杯!

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。

Ok, I think I have a pretty cool solution. Let's say you have file a and file b. You have a def or a class in file b that you want to use in module a, but you have something else, either a def, class, or variable from file a that you need in your definition or class in file b. What you can do is, at the bottom of file a, after calling the function or class in file a that is needed in file b, but before calling the function or class from file b that you need for file a, say import b Then, and here is the key part, in all of the definitions or classes in file b that need the def or class from file a (let's call it CLASS), you say from a import CLASS

这是可行的，因为您可以导入文件b，而无需Python执行文件b中的任何导入语句，因此您可以避免任何循环导入。

例如:

文件:

class A(object):

     def __init__(self, name):

         self.name = name

CLASS = A("me")

import b

go = B(6)

go.dostuff

文件b:

class B(object):

     def __init__(self, number):

         self.number = number

     def dostuff(self):

         from a import CLASS

         print "Hello " + CLASS.name + ", " + str(number) + " is an interesting number."

喉咙痛。

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

去年在comp.lang.python上对此进行了很好的讨论。它很彻底地回答了你的问题。

Imports are pretty straightforward really. Just remember the following: 'import' and 'from xxx import yyy' are executable statements. They execute when the running program reaches that line. If a module is not in sys.modules, then an import creates the new module entry in sys.modules and then executes the code in the module. It does not return control to the calling module until the execution has completed. If a module does exist in sys.modules then an import simply returns that module whether or not it has completed executing. That is the reason why cyclic imports may return modules which appear to be partly empty. Finally, the executing script runs in a module named __main__, importing the script under its own name will create a new module unrelated to __main__. Take that lot together and you shouldn't get any surprises when importing modules.