I am doing a refactor of our code base and was suggested we create a python module that will store functions that are used across different modules in Odoo 14 (sale, project for example), this is in a different file in the structure. My question is, Odoo will allow importing the new relative module and that way call the function I need?
Trying to import the module gives me ModulenotFoundError: no module named ...
from rw_utilities import working_hours_calculation
With the research that I've done, this should be possible with a simple python app but inside Odoo for the moment I'm not too clear. We run the application in the Odoo.sh cloud Not local.
File structure the goal is modules like sales and project can use the same function.
If you log something like that.
import logging
_logger = logging.getLogger(__name__)
_logger.info("Test")
Then you should get a log line like that, and it contains the right path to the module:
2022-01-01 00:01:01,111 1 INFO hostname odoo.addons.your_module.models.your_file: Test
And it should be usable like that
from odoo.addons.your_module.models.your_file import your_item
Another way would be:
class MyTools(models.Model):
_inherit = 'my.tools'
#api.model
def _my_function(self):
pass
# to call
self.env['my.tools']._my_function()
# or even
my_function = self.env['my.tools']._my_function
my_function()
I use Python 2.7. I'm trying to run my UI-automation script, but I got ImportError.
I have at least 30 Classes with methods. I want to have these methods in each and any class that's why I created BaseClass(MainClass) and created objects of all my classes. Please advise what should I do in this case or how I can solve this problem.
Here the example what similar to my code.
test_class/baseclass.py
from test_class.first_class import FirstClass
from test_class.second_class import SecondClass
class MainClass:
def __init__(self):
self.firstclass = FirstClass()
self.secondclass = SecondClass()
test_class/first_class.py
from test_class.baseclass import MainClass
class FirstClass(MainClass):
def __init__(self):
MainClass.__init__(self)
def add_two_number(self):
return 2 + 2
test_class/second_class.py
from test_class.baseclass import MainClass
class SecondClass(MainClass):
def __init__(self):
MainClass.__init__(self)
def minus_number(self):
return self.firstclass.add_two_number() - 10
if __name__ == '__main__':
print(SecondClass().minus_number())
When I run the last file I get this error
Traceback (most recent call last):
File "/Users/nik-edcast/git/ui-automation/test_class/second_class.py", line 1, in <module>
from test_class.baseclass import MainClass
File "/Users/nik-edcast/git/ui-automation/test_class/baseclass.py", line 1, in <module>
from test_class.first_class import FirstClass
File "/Users/nik-edcast/git/ui-automation/test_class/first_class.py", line 1, in <module>
from test_class.baseclass import MainClass
ImportError: cannot import name MainClass
check this line: from test_class.baseclass import MainClass -> it seems like all other imports had a '_' between the names like second_class. So try maybe to write base_class. who knows might work
Are you proabably running your code like python test_class/second_class.py. If you just do this then python will think the base directory to find modules is ./test_class. So when you import the test_class package python will start looking for a folder called ./test_class/test_class to find the sub-modules. This directory doesn't exist and so the import fails. There are several ways that you can tell python how to correctly find your modules.
Using PYTHONPATH
One way to get around this is to set PYTHONPATH before starting python. This is just an environment variable with which you can tell python where to look for your modules.
eg.
export PYTHONPATH=/path/to/your/root/folder
python test_class/second_class.py
Using the -m switch for python
Be default python treats the directory of the main module as the place to look for other modules. However, if you use -m python will fall back to looking in the current directory. But you also need to specify the full name of the module you want to run (rather than as a file). eg.
python -m test_class.second_class
Writing a root entry point
In this we just define your main module at the base level (the directory that contains test_class. Python will treat this folder as the place to look for user modules and will find everything appropriately. eg.
main.py (in /path/to/your/root/folder)
from test_class.second_class import SecondClass
if __name__ == '__main__':
print(SecondClass().minus_number())
at the command line
python main.py
You could try importing the full files instead of using from file import class. Then you would only need to add the file name before referencing something from another file.
I've read through about ten posts on how to import local modules, and I'm still stumped on why this isn't working. I have an extremely simple module, actor.py, with a single class inside it:
class Actor(object):
def __init__(self, name, age):
self.name = name
self.age = age
I'm trying to import it into another module, scraper.py, within the same directory:
Some fixes have listed not having init.py as being a problem with local imports, so I know that's not my problem.
Initially I tried these:
import actor
and
from actor import Actor
but it tells me that actor and Actor are unresolved references. here tells me that's Python 2 syntax, and I'm using Python 3. That answer instead recommends that I do:
from .actor import Actor
When I run my program with that syntax, I get this error:
ModuleNotFoundError: No module named '__main__.actor'; '__main__' is not a package
So I go searching again, and this post tells me to remove the dot from 'actor,' but as stated before, I've tried that as well. My final guess was
from . import actor
but that yields
ImportError: cannot import name 'actor'
which I follow to here, but the answers there mention circular dependencies, and I'm certain actor and scraper have none. Am I perhaps not writing my module correctly? I can't think of any other ways to write an import statement.
edit: if it helps at all, I'm using Intellij
Try from WebScraper.actor import Actor. If this doesn't work its because your package directory is not in the PYTHONPATH. You can set that in the IntelliJ Python run configuration.
The relative import is not working for you because you are trying to run a module as a script. You can see an explanation of what is happening at https://stackoverflow.com/a/8300343/7088038. If you want relative imports to work you will have to add a __main__.py file to your module to allow it to be runnable, or execute from an external script where you use an absolute import so you don't clobber the package namespace.
One other stylistic note- usually (but not always) package names in python use all lowercase names. CamelCase is reserved for class names. So if you wanted to follow convention you would call your package webscraper and use from webscraper.actor import Actor
To import a class into your script use:
from actor import Actor
Or to import the .py entirely (including whatever imports included in it) into the namespace use:
from actor import *
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
To illustrate what I am trying to do, let's say I have a module testmod that lives in ./testmod.py. The entire contents of this module is
x = test
I would like to be able to successfully import this module into Python, using any of the tools available in importlib or any other built in library.
Obviously doing a simple import testmod statement from the current directory results in an error: NameError: name 'test' is not defined.
I thought that maybe passing either globals or locals to __import__ correctly would modify the environment inside the script being run, but it does not:
>>> testmod = __import__('testmod', globals={'test': 'globals'}, locals={'test': 'locals'})
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jfoxrabi/testmod.py", line 1, in <module>
x = test
NameError: name 'test' is not defined
I was setting the value of test differently so I could see which dict testmod.x came from if this worked.
Since neither of these seems to work, I am stuck. Is it even possible to accomplish what I am trying to do? I would guess that yes, since this is Python, not Sparta.
I am using Python 3.5 on Anaconda. I would very much prefer not to use external libraries.
Update: The Why
I am importing a module into my program as a configuration file. The reason that I am not using JSON or INI is that I would like to have the full scope of Python's interpreter available to compute the values in the config from expressions. I would like to have certain values that I compute before-hand in the program available to do those calculations.
While I am aware of the fact that this is about as bad as calling eval (I do that too in my program), I am not concerned with the security aspect for the time being. I am, however, quite willing to entertain better solutions should this indeed turn out to be a case of XY.
I came up with a solution based on this answer and the importlib docs. Basically, I have access to the module object before it is loaded by using the correct sequence of calls to importlib:
from importlib.util import spec_from_file_location, module_from_spec
from os.path import splitext, basename
def loadConfig(fileName):
test = 'This is a test'
name = splitext(basename(fileName))[0]
spec = spec_from_file_location(name, fileName)
config = module_from_spec(spec)
config.test = test
spec.loader.exec_module(config)
return config
testmod = loadConfig('./testmod.py')
This is a bit better than modifying builtins, which may have unintended consequences in other parts of the program, and may also restrict the names I can pass in to the module.
I decided to put all the configuration items into a single field accessible at load time, which I named config. This allows me to do the following in testmod:
if 'test' in config:
x = config['test']
The loader now looks like this:
from importlib.util import spec_from_file_location, module_from_spec
from os.path import splitext, basename
def loadConfig(fileName, **kwargs):
name = splitext(basename(fileName))[0]
spec = spec_from_file_location(name, fileName)
config = module_from_spec(spec)
config.config = kwargs
spec.loader.exec_module(config)
return config
testmod = loadConfig('./testmod.py', test='This is a test')
After finding myself using this a bunch of times, I finally ended up adding this functionality to the utility library I maintain, haggis. haggis.load.load_module loads a text file as a module with injection, while haggis.load.module_as_dict does a more advanced version of the same that loads it as a potentially nested configuration file into a dict.
You could screw with Python's builtins to inject your own fake built-in test variable:
import builtins # __builtin__, no s, in Python 2
builtins.test = 5 # or whatever other placeholder value
import testmod
del builtins.test # clean up after ourselves