Python imports issue - python

I have a Utilities module which defines a few functions which are repeatedly used and am also adding in some constants. I'm running into trouble importing these constants though...
Let's say I'm working in class A, and I have a class in my constants also named A
from Utils.Constants import A as DistinctA
class A(object):
.... Implementation ....
some_var = DistinctA.SOME_CONSTANT
class Utils(object):
class Constants(object):
class A(object):
SOME_CONSTANT = "Constant"
I'm probably making this too much like Java, so if so just yell / smack my knuckles with a ruler.
When I attempt to import that class, I get an error that there is no module named Constants. What's this python newbie missing?

The identifier after 'from' must point to a module; you can't refer to a class. While I'm not qualified to say whether your nested classes are 'pythonic', I have never seen it done like that before. I'd be more inclined to create a constants.py module that contains the A class. Then you could do this:
from constants import A as DistinctA
If you really want those constants to live inside utils, you could make utils a package:
utils/
utils/__init__.py
utils/constants.py
Then you can do:
from utils.constants import A as DistinctA

Related

Why does using import on two files/modules at once giving me errors, but not when I only do it on one? [duplicate]

This question already has answers here:
What can I do about "ImportError: Cannot import name X" or "AttributeError: ... (most likely due to a circular import)"?
(17 answers)
Closed 6 months ago.
I know the issue of circular imports in python has come up many times before and I have read these discussions. The comment that is made repeatedly in these discussions is that a circular import is a sign of a bad design and the code should be reorganised to avoid the circular import.
Could someone tell me how to avoid a circular import in this situation?: I have two classes and I want each class to have a constructor (method) which takes an instance of the other class and returns an instance of the class.
More specifically, one class is mutable and one is immutable. The immutable class is needed
for hashing, comparing and so on. The mutable class is needed to do things too. This is similar to sets and frozensets or to lists and tuples.
I could put both class definitions in the same module. Are there any other suggestions?
A toy example would be class A which has an attribute which is a list and class B which has an attribute which is a tuple. Then class A has a method which takes an instance of class B and returns an instance of class A (by converting the tuple to a list) and similarly class B has a method which takes an instance of class A and returns an instance of class B (by converting the list to a tuple).
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.
Only import the module, don't import from the module:
Consider a.py:
import b
class A:
def bar(self):
return b.B()
and b.py:
import a
class B:
def bar(self):
return a.A()
This works perfectly fine.
We do a combination of absolute imports and functions for better reading and shorter access strings.
Advantage: Shorter access strings compared to pure absolute imports
Disadvantage: a bit more overhead due to extra function call
main/sub/a.py
import main.sub.b
b_mod = lambda: main.sub.b
class A():
def __init__(self):
print('in class "A":', b_mod().B.__name__)
main/sub/b.py
import main.sub.a
a_mod = lambda: main.sub.a
class B():
def __init__(self):
print('in class "B":', a_mod().A.__name__)

Unable to import class within package

i have following project structure: 1
and here is content of files:
# run.py
from module.submodule.base import DefaultObject
d = DefaultObject()
# module/sumbodule/base.py
from module.submodule.modulea import A
class BaseObject(object):
pass
class DefaultObject(BaseObject):
def return_something(self):
return A()
# module/submodule/modulea.py
from module.submodule.moduleb import B
class A(object):
def return_something(self):
return B()
# module/submodule/moduleb.py
from module.submodule.base import BaseObject
class B(BaseObject):
pass
and when I try to run python3 run.py I get ImportError: cannot import name 'BaseObject
I don't understand why I am able to import class B in modulea.py, but I am not able to class BaseObject in moduleb.py
What is correct way to make imports in such situation?
You have a circular import - base imports modulea which imports moduleb which imports base. Python doesn't support circular imports so it cannot technically work, and even for languages that technically supports them, circular dependencies are a very bad thing anyway.
Your solutions here are either to regroup interdependant objects (classes, functions etc) in a same module - note that Python is not Java and doesn't require "one module per class" (it's even actually an antipattern in Python) - or to move DefaultObject to it's own module.

python import nested class

I'm new to python. This is not my actual case, it's just my curiosity about importing nested class.
So I have a main.py and test.py.
test.py:
class one():
class two():
def twodef():
pass
so in my main.py, I can do 'import test' or 'from test import one'. But I got error when do: 'from test.one import two'.
error : ImportError: No module named one
Anyone can explain this?
You can only do from module import name for names that exist in the module's global scope - basically, names that are defined in top-level module code. Names that are defined in lower-level scopes - for example within classes as in your example - are not importable. You need to import the object that contains the name, and access it from there.
from test import one
my_two = one.two()
You could do the following:
from test import one
two_object = one.two()
two_object.twodef()
inside test.py
class One:
class Two:
#staticmethod
def twodef():
print("twodef")
My main logic:
from test import One
two_obj = One.Two
two_obj.twodef()
Remove the parenthesis at the end of class definition.
Coding standards:
Always declare your class names in upper camel case (class one => class One).
For more about scope
Preference:
And if you have a single class inside python file, always name that file in that class name but in lower camel case. (test.py => one.py). I have thought this as a standard earlier, but seems its practiced widely. I would use this because, if then project size grew and if you end up having a lot of classes and modules, it's logical and easy to access, rather than visiting the module to find the class name.
Ref1
Ref2

Inheriting from a class defined in an imported module in Python

I have two Python classes in two separate modules. The modules reference each other, so I must use the import XXX syntax rather than from XXX import YYY. I can't figure out how to access a class defiend in one module in the other, importing module though:
### testa.py
import testb
class TestA():
...
### testb.py
import testa
class TestB(testa.TestA): # doesn't work
...
How do I do this?
You can solve this by putting import testb after the definition of TestA. However, you might need to rethink your module structure since circular imports are difficult to deal with.

Modules with Classes and Imports

If I were to use a class in a module how would I make it "top level" in it's instance?
Structure:
/package
__init__.py
/subPackage
__init__.py
module.py
subModule.py
/theScript.py
python theScript.py
Source of theScript:
import package.subPackage.module
package.subPackage.module.method()
Source of /package/subPackage/module.py:
class module:
def method(self): pass
moduleInstance = module()
I guess what I am asking is how would I make it so that I don't have to do package.subPackage.module.moduleInstance.method() and could package.subPackage.module.method()
I know I can just remove the class and instance but I prefer the class because it makes it easier to subclass later if somebody wants to without needing to modify our source directly but if I ultimately have to I will just use methods instead of class/method in module.
Here is how the random module in the standard lib solved this problem:
_inst = Random()
seed = _inst.seed
random = _inst.random
uniform = _inst.uniform
triangular = _inst.triangular
...
Seems a reasonable solution to me. Of course there is the drawback that you have to manually keep the method lists in sync, but the worst thing that will happen if you forget to add a method name is an error message that tells you exactly what is missing.

Categories