First of all, this is very likely not a path issue.
I have a pydev project in eclipse. Here is the directory structure:
Genetic-Framework
| Genetic-Framework
| Genetic
| __init__.py
| GA.py
| crossover.py
| fitness.py
| individual.py
| mutation.py
| population.py
| selection.py
| settings.py
| visualization.py
In GA.py, I have the following line:
from Genetic import settings, selection, visualization as vis
And yes, Genetic is in sys.path. However, I get the following error:
File "/.../Genetic-Framework/Genetic-Framework/Genetic/GA.py", line 17, in <module>
from Genetic import settings, selection, visualization as vis
ImportError: cannot import name settings
However, when I remove settings from that line, everything else imports just fine.
Interestingly, among the first lines of settings.py is this:
from Genetic import fitness, selection, mutation, crossover, population, GA
And when I remove GA from that line, everything seems to import just fine.
Why am I getting this error? Is this some issue with circular imports? How can I fix this?
Yes, that's an issue with circular imports.
The problem
The problem is that when your GA.py is run, it first tries to import settings. This means that settings.py starts getting run, and it immediately tries to import GA.
However, GA is already in the process of loading, so GA.py doesn't get run a second time - instead, settings just loads the GA that is already in memory (which is currently mostly empty, because it's still executing its imports).
Thus, things in settings that try to use things out of GA fail, because the things they're looking for in GA haven't been defined yet (because processing of GA.py hasn't gotten past the imports yet).
This makes the evaluation of settings.py raise an exception, which manifests as a failure to be imported (because an exception raised during import makes the import fail).
The solution
a) Avoid the situation in the first place.
In general, you should try to avoid circular imports in the first place. They often mean that you have really odd dependency structure that will be hard to debug later.
One way to do this is to try to find things that are needed in both modules and break them out into a separate third module that can be shared between the other two - so instead of using A.x in B, and B.y in A, you instead use C.x and C.y in both A and B.
b) Don't actually try to use things from circular imports until everything's loaded.
Another thing you can do is to defer usage of something from another module until after all of the imports have finished. In other words, don't try to reference an imported module's contents from top-level code, but instead place it in a class initializer or a function that you can call later on, once all of the imports have finished.
For example, instead of this...
import Foo
class Baz:
top_level_variable = Foo.bar
you can do this:
import Foo
class Baz:
def __init__(self):
self.instance_variable = Foo.bar
Obviously, instance properties are slightly different from class properties, but the idea is to defer actually having to look things up from other modules until after all of the modules finish executing and thus have their contents available. Also note that from Foo import bar would fail here because that tries to access the contents of Foo at the time of the import, which is what needs to be avoided.
Related
I'm getting this error
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
and you can see that I use the same import statement further up and it works. Is there some unwritten rule about circular importing? How do I use the same class further down the call stack?
See also What happens when using mutual or circular (cyclic) imports in Python? for a general overview of what is allowed and what causes a problem WRT circular imports. See What can I do about "ImportError: Cannot import name X" or "AttributeError: ... (most likely due to a circular import)"? for techniques for resolving and avoiding circular dependencies.
I think the answer by jpmc26, while by no means wrong, comes down too heavily on circular imports. They can work just fine, if you set them up correctly.
The easiest way to do so is to use import my_module syntax, rather than from my_module import some_object. The former will almost always work, even if my_module included imports us back. The latter only works if my_object is already defined in my_module, which in a circular import may not be the case.
To be specific to your case: Try changing entities/post.py to do import physics and then refer to physics.PostBody rather than just PostBody directly. Similarly, change physics.py to do import entities.post and then use entities.post.Post rather than just Post.
When you import a module (or a member of it) for the first time, the code inside the module is executed sequentially like any other code; e.g., it is not treated any differently that the body of a function. An import is just a command like any other (assignment, a function call, def, class). Assuming your imports occur at the top of the script, then here's what's happening:
When you try to import World from world, the world script gets executed.
The world script imports Field, which causes the entities.field script to get executed.
This process continues until you reach the entities.post script because you tried to import Post
The entities.post script causes physics module to be executed because it tries to import PostBody
Finally, physics tries to import Post from entities.post
I'm not sure whether the entities.post module exists in memory yet, but it really doesn't matter. Either the module is not in memory, or the module doesn't yet have a Post member because it hasn't finished executing to define Post
Either way, an error occurs because Post is not there to be imported
So no, it's not "working further up in the call stack". This is a stack trace of where the error occurred, which means it errored out trying to import Post in that class. You shouldn't use circular imports. At best, it has negligible benefit (typically, no benefit), and it causes problems like this. It burdens any developer maintaining it, forcing them to walk on egg shells to avoid breaking it. Refactor your module organization.
To understand circular dependencies, you need to remember that Python is essentially a scripting language. Execution of statements outside methods occurs at compile time. Import statements are executed just like method calls, and to understand them you should think about them like method calls.
When you do an import, what happens depends on whether the file you are importing already exists in the module table. If it does, Python uses whatever is currently in the symbol table. If not, Python begins reading the module file, compiling/executing/importing whatever it finds there. Symbols referenced at compile time are found or not, depending on whether they have been seen, or are yet to be seen by the compiler.
Imagine you have two source files:
File X.py
def X1:
return "x1"
from Y import Y2
def X2:
return "x2"
File Y.py
def Y1:
return "y1"
from X import X1
def Y2:
return "y2"
Now suppose you compile file X.py. The compiler begins by defining the method X1, and then hits the import statement in X.py. This causes the compiler to pause compilation of X.py and begin compiling Y.py. Shortly thereafter the compiler hits the import statement in Y.py. Since X.py is already in the module table, Python uses the existing incomplete X.py symbol table to satisfy any references requested. Any symbols appearing before the import statement in X.py are now in the symbol table, but any symbols after are not. Since X1 now appears before the import statement, it is successfully imported. Python then resumes compiling Y.py. In doing so it defines Y2 and finishes compiling Y.py. It then resumes compilation of X.py, and finds Y2 in the Y.py symbol table. Compilation eventually completes w/o error.
Something very different happens if you attempt to compile Y.py from the command line. While compiling Y.py, the compiler hits the import statement before it defines Y2. Then it starts compiling X.py. Soon it hits the import statement in X.py that requires Y2. But Y2 is undefined, so the compile fails.
Please note that if you modify X.py to import Y1, the compile will always succeed, no matter which file you compile. However if you modify file Y.py to import symbol X2, neither file will compile.
Any time when module X, or any module imported by X might import the current module, do NOT use:
from X import Y
Any time you think there may be a circular import you should also avoid compile time references to variables in other modules. Consider the innocent looking code:
import X
z = X.Y
Suppose module X imports this module before this module imports X. Further suppose Y is defined in X after the import statement. Then Y will not be defined when this module is imported, and you will get a compile error. If this module imports Y first, you can get away with it. But when one of your co-workers innocently changes the order of definitions in a third module, the code will break.
In some cases you can resolve circular dependencies by moving an import statement down below symbol definitions needed by other modules. In the examples above, definitions before the import statement never fail. Definitions after the import statement sometimes fail, depending on the order of compilation. You can even put import statements at the end of a file, so long as none of the imported symbols are needed at compile time.
Note that moving import statements down in a module obscures what you are doing. Compensate for this with a comment at the top of your module something like the following:
#import X (actual import moved down to avoid circular dependency)
In general this is a bad practice, but sometimes it is difficult to avoid.
For those of you who, like me, come to this issue from Django, you should know that the docs provide a solution:
https://docs.djangoproject.com/en/1.10/ref/models/fields/#foreignkey
"...To refer to models defined in another application, you can explicitly specify a model with the full application label. For example, if the Manufacturer model above is defined in another application called production, you’d need to use:
class Car(models.Model):
manufacturer = models.ForeignKey(
'production.Manufacturer',
on_delete=models.CASCADE,
)
This sort of reference can be useful when resolving circular import dependencies between two applications...."
I was able to import the module within the function (only) that would require the objects from this module:
def my_func():
import Foo
foo_instance = Foo()
If you run into this issue in a fairly complex app it can be cumbersome to refactor all your imports. PyCharm offers a quickfix for this that will automatically change all usage of the imported symbols as well.
I was using the following:
from module import Foo
foo_instance = Foo()
but to get rid of circular reference I did the following and it worked:
import module.foo
foo_instance = foo.Foo()
According to this answer we can import another module's object in the block( like function/ method and etc), without circular import error occurring, for example for import Simple object of another.py module, you can use this:
def get_simple_obj():
from another import Simple
return Simple
class Example(get_simple_obj()):
pass
class NotCircularImportError:
pass
In this situation, another.py module can easily import NotCircularImportError, without any problem.
just check your file name see if it is not the same as library you are importing.
Eg - sympy.py
import sympy as sym
I have been tasked with researching improvements to a Python tool. However, the current tool is a mess. Just a collection of several hundred functions and imports spread across 10 files all in the same level of directory, all cross referencing each other, with each file importing some subset of the others, sometimes recursively.
There is an underlying hierarchy there, and so I intend to convert it all into a module, with sub-modules, and then to further refactor it into a class rather than a set of nested functions.
I am having some issue with imports though. I am self taught with python, and I am trying to remain PEP8 compliant, with little knowledge of how to. An additional complication is the system I am using is secure, and is unable to have an IDE installed on it, so I am battling with a glorified text editor with a terminal built in.
I thought I could import the sub-modules together in the highest level of the module, and they would then be available to all sub-modules, but this seems to produce name errors. My file structure and code is as follows:
Directory
dir
|
+-- run_module.py
|
+--top_module
|
+--__init__.py
|
+--module.py
|
+--sub_module
|
+--__init__.py
|
+--sub_module_one.py
|
+--sub_module_two.py
Content of run_module.py
from top_module import module
module.run_the_thing()
Content of init.py
Currently, both __init__ files are empty, though this issue persists if top_mod.__init__ has the imports instead of module, as well as importing module and being imported by run_module
Content of module.py
from .sub_module import sub_module_one, sub_module_two
def run_the_thing():
sub_module_one.hello()
sub_module_two.greeting()
Content of sub_module_one.py
def hello():
print('I am sub-module 1.')
Content of sub_module_two.py
def hello():
print('I am sub-module 2.')
def callout():
print('And this is my friend:')
sub_module_one.hello()
def greeting():
hello()
callout()
When run, it prints the output from sub_module_one as expected, and prints everything in sub_module_two up until the call to sub_module_one.
I cant say I am surprised by this behaviour, but is there a solution that will allow me to import all the sub-modules in the top level script, leaving them available for all the others, or will I have to have imports in each and every sub-module?
Clearly this isnt too messy for my MWE, but the real code will be horrible spaghetti.
I'm getting this error
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
and you can see that I use the same import statement further up and it works. Is there some unwritten rule about circular importing? How do I use the same class further down the call stack?
See also What happens when using mutual or circular (cyclic) imports in Python? for a general overview of what is allowed and what causes a problem WRT circular imports. See What can I do about "ImportError: Cannot import name X" or "AttributeError: ... (most likely due to a circular import)"? for techniques for resolving and avoiding circular dependencies.
I think the answer by jpmc26, while by no means wrong, comes down too heavily on circular imports. They can work just fine, if you set them up correctly.
The easiest way to do so is to use import my_module syntax, rather than from my_module import some_object. The former will almost always work, even if my_module included imports us back. The latter only works if my_object is already defined in my_module, which in a circular import may not be the case.
To be specific to your case: Try changing entities/post.py to do import physics and then refer to physics.PostBody rather than just PostBody directly. Similarly, change physics.py to do import entities.post and then use entities.post.Post rather than just Post.
When you import a module (or a member of it) for the first time, the code inside the module is executed sequentially like any other code; e.g., it is not treated any differently that the body of a function. An import is just a command like any other (assignment, a function call, def, class). Assuming your imports occur at the top of the script, then here's what's happening:
When you try to import World from world, the world script gets executed.
The world script imports Field, which causes the entities.field script to get executed.
This process continues until you reach the entities.post script because you tried to import Post
The entities.post script causes physics module to be executed because it tries to import PostBody
Finally, physics tries to import Post from entities.post
I'm not sure whether the entities.post module exists in memory yet, but it really doesn't matter. Either the module is not in memory, or the module doesn't yet have a Post member because it hasn't finished executing to define Post
Either way, an error occurs because Post is not there to be imported
So no, it's not "working further up in the call stack". This is a stack trace of where the error occurred, which means it errored out trying to import Post in that class. You shouldn't use circular imports. At best, it has negligible benefit (typically, no benefit), and it causes problems like this. It burdens any developer maintaining it, forcing them to walk on egg shells to avoid breaking it. Refactor your module organization.
To understand circular dependencies, you need to remember that Python is essentially a scripting language. Execution of statements outside methods occurs at compile time. Import statements are executed just like method calls, and to understand them you should think about them like method calls.
When you do an import, what happens depends on whether the file you are importing already exists in the module table. If it does, Python uses whatever is currently in the symbol table. If not, Python begins reading the module file, compiling/executing/importing whatever it finds there. Symbols referenced at compile time are found or not, depending on whether they have been seen, or are yet to be seen by the compiler.
Imagine you have two source files:
File X.py
def X1:
return "x1"
from Y import Y2
def X2:
return "x2"
File Y.py
def Y1:
return "y1"
from X import X1
def Y2:
return "y2"
Now suppose you compile file X.py. The compiler begins by defining the method X1, and then hits the import statement in X.py. This causes the compiler to pause compilation of X.py and begin compiling Y.py. Shortly thereafter the compiler hits the import statement in Y.py. Since X.py is already in the module table, Python uses the existing incomplete X.py symbol table to satisfy any references requested. Any symbols appearing before the import statement in X.py are now in the symbol table, but any symbols after are not. Since X1 now appears before the import statement, it is successfully imported. Python then resumes compiling Y.py. In doing so it defines Y2 and finishes compiling Y.py. It then resumes compilation of X.py, and finds Y2 in the Y.py symbol table. Compilation eventually completes w/o error.
Something very different happens if you attempt to compile Y.py from the command line. While compiling Y.py, the compiler hits the import statement before it defines Y2. Then it starts compiling X.py. Soon it hits the import statement in X.py that requires Y2. But Y2 is undefined, so the compile fails.
Please note that if you modify X.py to import Y1, the compile will always succeed, no matter which file you compile. However if you modify file Y.py to import symbol X2, neither file will compile.
Any time when module X, or any module imported by X might import the current module, do NOT use:
from X import Y
Any time you think there may be a circular import you should also avoid compile time references to variables in other modules. Consider the innocent looking code:
import X
z = X.Y
Suppose module X imports this module before this module imports X. Further suppose Y is defined in X after the import statement. Then Y will not be defined when this module is imported, and you will get a compile error. If this module imports Y first, you can get away with it. But when one of your co-workers innocently changes the order of definitions in a third module, the code will break.
In some cases you can resolve circular dependencies by moving an import statement down below symbol definitions needed by other modules. In the examples above, definitions before the import statement never fail. Definitions after the import statement sometimes fail, depending on the order of compilation. You can even put import statements at the end of a file, so long as none of the imported symbols are needed at compile time.
Note that moving import statements down in a module obscures what you are doing. Compensate for this with a comment at the top of your module something like the following:
#import X (actual import moved down to avoid circular dependency)
In general this is a bad practice, but sometimes it is difficult to avoid.
For those of you who, like me, come to this issue from Django, you should know that the docs provide a solution:
https://docs.djangoproject.com/en/1.10/ref/models/fields/#foreignkey
"...To refer to models defined in another application, you can explicitly specify a model with the full application label. For example, if the Manufacturer model above is defined in another application called production, you’d need to use:
class Car(models.Model):
manufacturer = models.ForeignKey(
'production.Manufacturer',
on_delete=models.CASCADE,
)
This sort of reference can be useful when resolving circular import dependencies between two applications...."
I was able to import the module within the function (only) that would require the objects from this module:
def my_func():
import Foo
foo_instance = Foo()
If you run into this issue in a fairly complex app it can be cumbersome to refactor all your imports. PyCharm offers a quickfix for this that will automatically change all usage of the imported symbols as well.
I was using the following:
from module import Foo
foo_instance = Foo()
but to get rid of circular reference I did the following and it worked:
import module.foo
foo_instance = foo.Foo()
According to this answer we can import another module's object in the block( like function/ method and etc), without circular import error occurring, for example for import Simple object of another.py module, you can use this:
def get_simple_obj():
from another import Simple
return Simple
class Example(get_simple_obj()):
pass
class NotCircularImportError:
pass
In this situation, another.py module can easily import NotCircularImportError, without any problem.
just check your file name see if it is not the same as library you are importing.
Eg - sympy.py
import sympy as sym
I am writing a python module and I am using many imports of other different modules.
I am bit confused that whether I should import all the necessary dependent modules in the opening of the file or shall I do it when necessary.
I also wanted to know the implications of both.
I come from C++ back ground so I am really thrilled with this feature and does not see any reason of not using __import__(), importing the modules only when needed inside my function.
Kindly throw some light on this.
To write less code, import a module at the first lines of the script, e.g.:
#File1.py
import os
#use os somewhere:
os.path.chdir(some_dir)
...
...
#use os somewhere else, you don't need to "import os" everywhere
os.environ.update(some_dict)
While sometimes you may need to import a module locally (e.g., in a function):
abc=3
def foo():
from some_module import abc #import inside foo avoids you from naming conflicts
abc(...) #call the function, nothing to do with the variable "abc" outside "foo"
Don't worry about the time consumption when calling foo() multiple times, since import statements loads modules/functions only one time. Once a module/function is imported, the object is stored in dictionary sys.modules, which is a lookup table for speedup when running the same import statement.
As #bruno desthuilliers mentioned, importing insede functions may not be that pythonic, it violates PEP8, here's a discussion I found, you should stick to importing at the top of the file most of the time.
First, __import__ isn't usually needed anywhere. It's main purpose is to support dynamic importing of things that you don't know ahead of time (think plug-ins). You can easily use the import statement inside your function:
import sys
def foo():
import this
if __name__ == "__main__":
print sys.version_info
foo()
The main advantage to importing everything up-front is that it is most customary. That's where people reading your code will go to see if something is imported or not. Also, you don't need to write import os in every function that uses os. The main downsides of this approach are that:
you can get yourself into unresolvable import loops (A imports B which imports A)
that you pull everything into memory even if you aren't going to use it.
The second problem isn't typically an issue -- very rarely do you notice the performance or memory impact of an import.
If you run into the first problem, it's likely a symptom of poorly grouped code and the common stuff should be factored into a new module C which both A and B can use.
Firstly, it's a violation of PEP8 using imports inside functions.
Calling import it's an expensive call EVEN if the module is already loaded, so if your function is gonna being called many times this will not compensate the performance gain.
Also when you call "import test" python do this:
dataFile = __ import__('test')
The only downside of imports at the top of file it's the namespace that get polluted very fast depending on complexity of the file, but if your file it's too complex it's a signal of bad design.
Python won't allow me to import classes into eachother. I know there is no "package" solution in Python, so I'm not sure how this could be done. Take a look at my files' codes:
file Main.py:
from Tile import tile
tile.assign()
class main:
x = 0
#staticmethod
def assign():
tile.x = 20
file Tile.py:
from Main import main
main.assign()
class tile:
x = 0
#staticmethod
def assign():
main.x = 20
I get the error "class tile can not be imported".
If file A imports file B, and file B imports file A, they would keep importing each other indefinitely until the program crashed.
You need to rethink your logic in a way that doesn't require this circular dependency. For example, a 3rd file could import both files and perform both assignments.
You have your import backwards and the from needs to have the name of the module
from Tile import tile
Python begins executing Main.py. It sees the import, and so goes to execute Tile.py. Note that it has not yet executed the class statement!
So Python begins executing Tile.py. It sees an import from Main, and it already has that module in memory, so it doesn't re-execute the code in Main.py (even worse things would go wrong if it did). It tries to pull out a variable main from the Main module, but the class statement binding main hasn't executed yet (we're still in the process of executing the import statement, advice that line). So you get the error about there not being a clsss main in module Main (or Tile, if you started from there).
You could avoid that by importing the modules rather than importing classes out of the modules, and using qualified names, but then you'd fall one line down when Main.main doesn't work. Your code makes no sense I'm a dynamic language; you can't have both the definition of class main wait until after tile.assign has been called and the definition of class tile wait until after main.assign has been called.
If you really need this circular dependency (it's often, but not always a sign that something has gone wrong at the design stage), then you need to separate out "scaffolding" like defining classes and functions and variables from "execution", where you actually call classes and functions or use variables. Then your circular imports of the "scaffolding" will work even though none of the modules will be properly initialized while the importing is going on, and by the time you get to starting the "execution" everything will work.