Consider the following example python package where a.py and b.py depend on each other:

/package
    __init__.py
    a.py
    b.py

Types of circular import problems

Circular import dependencies typically fall into two categories depending
on what you’re trying to import and where you’re using it inside each
module. (And whether you’re using python 2 or 3).

1. Errors importing modules with circular imports

In some cases, just importing a module with a circular import dependency
can result in errors even if you’re not referencing anything from the
imported module.

There are several standard ways to import a module in python

import package.a           # (1) Absolute import
import package.a as a_mod  # (2) Absolute import bound to different name
from package import a      # (3) Alternate absolute import
import a                   # (4) Implicit relative import (deprecated, python 2 only)
from . import a            # (5) Explicit relative import

Unfortunately, only the 1st and 4th options actually work when you
have circular dependencies (the rest all raise ImportError
or AttributeError). In general, you shouldn’t be using the
4th syntax, since it only works in python2 and runs the risk of
clashing with other 3rd party modules. So really, only the first
syntax is guaranteed to work.

EDIT: The ImportError and AttributeError issues only occur in
python 2. In python 3 the import machinery has been rewritten and all
of these import statements (with the exception of 4) will work, even with
circular dependencies. While the solutions in this section may help refactoring python 3 code, they are mainly intended
for people using python 2.

Absolute Import

Just use the first import syntax above. The downside to this method is
that the import names can get super long for large packages.

In a.py

import package.b

In b.py

import package.a

Defer import until later

I’ve seen this method used in lots of packages, but it still feels
hacky to me, and I dislike that I can’t look at the top of a module
and see all its dependencies, I have to go searching through all the
functions as well.

In a.py

def func():
    from package import b

In b.py

def func():
    from package import a

Put all imports in a central module

This also works, but has the same problem as the first method, where
all the package and submodule calls get super long. It also has two
major flaws — it forces all the submodules to be imported, even if
you’re only using one or two, and you still can’t look at any of the
submodules and quickly see their dependencies at the top, you have to
go sifting through functions.

In __init__.py

from . import a
from . import b

In a.py

import package

def func():
    package.b.some_object()

In b.py

import package

def func():
    package.a.some_object()

2. Errors using imported objects with circular dependencies

Now, while you may be able to import a module with a circular import
dependency, you won’t be able to import any objects defined in the module
or actually be able to reference that imported module anywhere
in the top level of the module where you’re importing it. You can,
however, use the imported module inside functions and code blocks that don’t
get run on import.

For example, this will work:

package/a.py

import package.b

def func_a():
    return "a"

package/b.py

import package.a

def func_b():
    # Notice how package.a is only referenced *inside* a function
    # and not the top level of the module.
    return package.a.func_a() + "b"

But this won’t work

package/a.py

import package.b

class A(object):
    pass

package/b.py

import package.a

# package.a is referenced at the top level of the module
class B(package.a.A):
    pass

You’ll get an exception

AttributeError: module ‘package’ has no attribute ‘a’

Generally, in most valid cases of circular dependencies, it’s possible
to refactor or reorganize the code to prevent these errors and move
module references inside a code block.