What happens when using mutual or circular (cyclic) imports?

If you do import foo (inside bar.py) and import bar (inside foo.py), it will work fine. By the time anything actually runs, both modules will be fully loaded and will have references to each other.

The problem is when instead you do from foo import abc (inside bar.py) and from bar import xyz (inside foo.py). Because now each module requires the other module to already be imported (so that the name we are importing exists) before it can be imported.

Examples of working circular imports in Python 2 and Python 3

The article When are Python circular imports fatal? gives four examples when circular imports are, for the reason explained above, nonfatal.

Top of module; no from; Python 2 only

# lib/foo.py # lib/bar.py import bar import foo def abc(): def xyz(): print(bar.xyz.__name__) print(foo.abc.__name__) 

Top of module; from ok; relative ok; Python 3 only

# lib/foo.py # lib/bar.py from . import bar from . import foo def abc(): def xyz(): print(bar.xyz.__name__) print(abc.__name__) 

Top of module; no from; no relative

# lib/foo.py # lib/bar.py import lib.bar import lib.foo def abc(): def xyz(): print(lib.bar.xyz.__name__) print(lib.foo.abc.__name__) 

Bottom of module; import attribute, not module; from okay

# lib/foo.py # lib/bar.py def abc(): def xyz(): print(xyz.__name__) print(abc.__name__) from .bar import xyz from .foo import abc 

Top of function; from okay

# lib/foo.py # lib/bar.py def abc(): def xyz(): from . import bar from . import foo print(bar.xyz.__name__) print(foo.abc.__name__) 

Additional examples

The article cited above does not discuss star imports.

Cyclic imports terminate, but you need to be careful not to use the cyclically-imported modules during module initialization.

Consider the following files:

a.py:

print "a in" import sys print "b imported: %s" % ("b" in sys.modules, ) import b print "a out" 

b.py:

print "b in" import a print "b out" x = 3 

If you execute a.py, you'll get the following:

$ python a.py a in b imported: False b in a in b imported: True a out b out a out 

On the second import of b.py (in the second a in), the Python interpreter does not import b again, because it already exists in the module dict.

If you try to access b.x from a during module initialization, you will get an AttributeError.

Append the following line to a.py:

print b.x 

Then, the output is:

$ python a.py a in b imported: False b in a in b imported: True a out Traceback (most recent call last): File "a.py", line 4, in <module> import b File "/home/shlomme/tmp/x/b.py", line 2, in <module> import a File "/home/shlomme/tmp/x/a.py", line 7, in <module> print b.x AttributeError: 'module' object has no attribute 'x' 

This is because modules are executed on import and at the time b.x is accessed, the line x = 3 has not be executed yet, which will only happen after b out.

To my surprise, no one has mentioned cyclic imports caused by type hints yet.
If you have cyclic imports only as a result of type hinting, they can be avoided in a clean manner.

Consider main.py which makes use of exceptions from another file:

from src.exceptions import SpecificException class Foo: def __init__(self, attrib: int): self.attrib = attrib raise SpecificException(Foo(5)) 

And the dedicated exception class 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}.' 

This will raise an ImportError since main.py imports exception.py and vice versa through Foo and 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.

Hence, we get the following code for Python 3.7+:

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}.' 

In Python 3.6, the future import does not exist, so Foo has to be a string:

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}.' 

In Python 3.5 and below, the type hinting functionality did not exist yet.
In future versions of Python, the annotations feature may become mandatory, after which the future import will no longer be necessary. Which version this will occur in is yet to be determined.

This answer is based on Yet another solution to dig you out of a circular import hole in Python by Stefaan Lippens.

As other answers describe this pattern is acceptable in python:

def dostuff(self): from foo import bar ... 

Which will avoid the execution of the import statement when the file is imported by other modules. Only if there is a logical circular dependency, this will fail.

Most Circular Imports are not actually logical circular imports but rather raise ImportError errors, because of the way import() evaluates top level statements of the entire file when called.

These ImportErrors can almost always be avoided if you positively want your imports on top:

Consider this circular import:

App A

# profiles/serializers.py from images.serializers import SimplifiedImageSerializer class SimplifiedProfileSerializer(serializers.Serializer): name = serializers.CharField() class ProfileSerializer(SimplifiedProfileSerializer): recent_images = SimplifiedImageSerializer(many=True) 

App B

# images/serializers.py from profiles.serializers import SimplifiedProfileSerializer class SimplifiedImageSerializer(serializers.Serializer): title = serializers.CharField() class ImageSerializer(SimplifiedImageSerializer): profile = SimplifiedProfileSerializer() 

From David Beazleys excellent talk Modules and Packages: Live and Let Die! - PyCon 2015, 1:54:00, here is a way to deal with circular imports in python:

try: from images.serializers import SimplifiedImageSerializer except ImportError: import sys SimplifiedImageSerializer = sys.modules[__package__ + '.SimplifiedImageSerializer'] 

This tries to import SimplifiedImageSerializer and if ImportError is raised, because it already is imported, it will pull it from the importcache.

PS: You have to read this entire post in David Beazley's voice.

Module a.py :

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

Module b.py

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

Running "Module a" will output:

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

It output this 3 lines while it was supposed to output infinitival because of circular importing. What happens line by line while running"Module a" is listed here:

1. The first line is import b. so it will visit module b
2. The first line at module b is import a. so it will visit module a
3. 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".
4. 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"
5. Module b lines are executed completely. so we will go back to module a where we started module b.
6. 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.

I got an example here that struck me!

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" 

At the command line: $ 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 

There are a lot of great answers here. While there are usually quick solutions to the problem, some of which feel more pythonic than others, if you have the luxury of doing some refactoring, another approach is to analyze the organization of your code, and try to remove the circular dependency. You may find, for example, that you have:

File 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) 

File 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)) 

In this case, just moving one static method to a separate file, say c.py:

File c.py

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

will allow removing the save_result method from A, and thus allow removing the import of A from a in b:

Refactored File 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) 

Refactored File 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)) 

In summary, if you have a tool (e.g. pylint or PyCharm) that reports on methods that can be static, just throwing a staticmethod decorator on them might not be the best way to silence the warning. Even though the method seems related to the class, it might be better to separate it out, especially if you have several closely related modules that might need the same functionality and you intend to practice DRY principles.

I completely agree with pythoneer's answer here. But I have stumbled on some code that was flawed with circular imports and caused issues when trying to add unit tests. So to quickly patch it without changing everything you can resolve the issue by doing a dynamic import.

# 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") 

Again, this isn't a permanent fix but may help someone that wants to fix an import error without changing too much of the code.

Cheers!

Circular imports can be confusing because import does two things:

1. it executes imported module code
2. adds imported module to importing module global symbol table

The former is done only once, while the latter at each import statement. Circular import creates situation when importing module uses imported one with partially executed code. In consequence it will not see objects created after import statement. Below code sample demonstrates it.

Circular imports are not the ultimate evil to be avoided at all cost. In some frameworks like Flask they are quite natural and tweaking your code to eliminate them does not make the code better.

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 output with comments

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 

Suppose you are running a test python file named request.py In request.py, you write

import request 

so this also most likely a circular import.

Solution:

Just change your test file to another name such as aaa.py, other than request.py.

Do not use names that are already used by other libs.

I solved the problem the following way, and it works well without any error. Consider two files a.py and b.py.

I added this to a.py and it worked.

if __name__ == "__main__": main () 

a.py:

import b y = 2 def main(): print ("a out") print (b.x) if __name__ == "__main__": main () 

b.py:

import a print ("b out") x = 3 + a.y 

The output I get is

>>> b out >>> a out >>> 5 

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

This works because you can import file b without Python executing any of the import statements in file b, and thus you elude any circular imports.

For example:

File a:

class A(object): def __init__(self, name): self.name = name CLASS = A("me") import b go = B(6) go.dostuff 

File 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." 

Voila.

This issue arose in my case when one of my python file was the same name as a library. Example you have a package 'abc' and file 'abc.py'. import abc will throw a cyclic error.

I encounter this error too. In my case, I fixed it by swapping import-statements in the __init__.py

My situiation

init.py

from .b import B, C form .a import A 

b.py

from <module name of __init__.py> import A 

a.py

class A(): a = 42 

My solution

init.py

form .a import A from .b import B, C