Why do Python circular imports work higher up but raise ImportError deeper in the call stack?

General Discussions
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#1

Why do python circular import issues seem to work higher up in the call stack but raise an ImportError further down?

I’m encountering this error in my project:

Traceback (most recent call last):
  File "/Users/alex/dev/runswift/utils/sim2014/simulator.py", line 3, in <module>
    from world import World
  File "/Users/alex/dev/runswift/utils/sim2014/world.py", line 2, in <module>
    from entities.field import Field
  File "/Users/alex/dev/runswift/utils/sim2014/entities/field.py", line 2, in <module>
    from entities.goal import Goal
  File "/Users/alex/dev/runswift/utils/sim2014/entities/goal.py", line 2, in <module>
    from entities.post import Post
  File "/Users/alex/dev/runswift/utils/sim2014/entities/post.py", line 4, in <module>
    from physics import PostBody
  File "/Users/alex/dev/runswift/utils/sim2014/physics.py", line 21, in <module>
    from entities.post import Post
ImportError: cannot import name Post

I see that the same import statement works higher up in the stack but causes an issue when it gets deeper into the call stack. Is there an unwritten rule regarding python circular import? How can I use the same class further down the call stack without running into this error?

#2

Ah, Python circular import issues can be tricky! I’ve run into this a few times in my projects. From what I’ve seen, a quick solution is to reorganize your imports by making them local. Instead of importing at the module level, you can delay the import until it’s absolutely needed. This can prevent the circular dependency from breaking things down when Python first loads the module.

For example, in your case, you could move the import statement for PostBody inside a function, like this:

def some_function():
    from physics import PostBody  # Local import to avoid python circular import at the module level
    # Now, you can use PostBody class here

This keeps the import scoped to just the function, which is run only when needed, so it avoids causing that annoying circular import error during module initialization.

#3

Great point, Archana! That approach works, but I’ve also found that sometimes it’s better to completely refactor the design to avoid circular imports altogether. A major cause of circular imports is tightly coupled modules. If you have interdependent classes or functions that keep referencing each other, splitting them into smaller, more focused modules can really help."*

“For example, if both entities.post and physics need to import Post, consider moving the Post class to a separate module. Then, both entities.post and physics can import it from this new module, preventing the direct circular import between them.”

Another approach could be creating a shared module for common functionality that both modules need, which will break the cycle and give you more modular and maintainable code.

#4

Good suggestions, Priyada! If you want to take this one step further, I’ve had success using Python’s importlib module to avoid circular imports in some cases. It allows you to dynamically import modules during runtime, which can totally sidestep the issue by deferring the import until after the modules are loaded.

Instead of the standard import statement, you use importlib.import_module() to import the module only when you actually need it. This way, the circular import won’t hit you during the initial module loading phase. Here’s a quick example:

import importlib

def get_post_class():
    post = importlib.import_module('entities.post')  # Importing dynamically
    return post.Post

With this approach, you avoid the python circular import error that usually happens when the module is first being loaded.