Factory & Composite Design Patterns combo in Python & circular imports - python

I've built a couple projects now using the composite pattern where the objects hierarchy is built from a configuration file. My problem is that I's like to save each subclass in a separate file, to allow extensions without changing the base classes' files or having huge files. Each object once instantiated is then going to instantiate a different subclass, based on a type listed in its configuration. To do this I thought of including a factory function which will live in its own file, import all accessible subclasses, and contain a single function that will just return the appropriate subclass based on the name passed to it. The problem with this, is that each of those subclass modules, in order to use this factory, must import it. This creates a circular import situation since the factory module imports all subclasses which all import it back. How can this be avoided or is there a cleaner way to instantiate a subclass dynamically within another ?
As an example - I wrote a "Pipeline" project, useful for automation of different procedures I often need to repeat. The basic parent class is called "Block", it is inherited from to create blocks that comply with a certain interface (i.e. other projects that perform actions) and from those I inherit to blocks that actually execute specific operations. A block only needs to see the its successor in the pipeline, and does not care weather this is a single block or an entire, separate pipeline. To implement this I want each block to instantiate its successor based on the order defined in the config file that is passed along the chain. If I were to write a file that imports all implemented concrete blocks and returns whichever one requested, then I wouldn't be able to import it for use in any of the concrete blocks' modules, since they are imported into the factory one in order to be available for instantiation themselves.

You know that if you write your import statement itself inside a method or function, it will only be executed after all module-level classes and functions have been defined, right? Your circular-dependency can be fixed as simply as writing a "factory" method in the base class that will contain a from factory import factory_function statement and call it.
# basemodel.py Base file
class Base:
def factory(self, *args, **kw):
from factory import factory_function
# baseblock.py Block class hierarchy base file
from basemodel import Base
class Block(Base):
...
# blockXX.py Other block classes files:
from baseblock import Block
class SpecializedBlock31(Block):
...
# factory.py:
from block import Block
...
from block31 import Block31
...
# (or some dynamic importing using __import__ and looking at the filesystem)
def factory_function(*args, **kw):
# logic to decide which class to use
...
instance = decided_class(...)
return instance

Related

What is the correct way to write a class that pulls in sub-classes (methods) from several files

I have written a class as a central data management engine for a register map. I have written sub-classes (well more like extensions) which provide various input parsers and output formatters. However they rely on being able to access the internal variables of the main class in order to operate. I would like to keep the extensions separate from the main class but be able to advertise all the methods to the instantiator of the main class.
It all works fine actually except that I get many errors from Pylint of the form:
E:275, 8: Instance of 'RegMapXLS' has no 'log' member (no-member)
where log is a shared function in the main class.
# typical "extension" class
class RegMapXLS():
''' The part of RegisterMap class which contains the xlsx source file
parsing functions
'''
def parse_config(self, configsheet):
# main class including all "extension class inherritance"
class RegisterMap(RegMapXLS, RegMapPy, RegMapDocx, RegMapVhdl):
'''Register map bundling settings as instances of the class Setting.
'''
# only this class has an __init__ call to instantiate it and its code
def __init__(self, name, output_path, report=None):
I could of course write the whole thing as one big class but for maintainability reasons I have split them up into several files. The other way would be to write a "base class" which all the "sister"-classes inherit and create an empty class which simply inherits all of the parts (though its not clear then how I call the init method 2 levels down). My question is what is the best/Pythonic way and for maintenance and readability.
What I want in the end is a simple UI where I can write:
with RegisterMap(udi, output_path=output_path) as regmap:
regmap.parse_source(regmap_source)
#these methods are pulled in from other source files/authors
regmap.export_HDF5(output_path)
regmap.to_vhdl(regmap_reg_pkg_template)
regmap.to_pin()
regmap.to_docx(doc_template=doc_template)

How to split python class into multiple files [duplicate]

Using "new" style classes (I'm in python 3.2) is there a way to split a class over multiple files? I've got a large class (which really should be a single class from an object-oriented design perspective, considering coupling, etc, but it'd be nice to split over a few files just for ease of editing the class.
If your problem really is just working with a large class in an editor, the first solution I'd actually look for is a better way to break down the problem. The second solution would be a better editor, preferably one with code folding.
That said, there are a couple of ways you might break up a class into multiple files. Python lets you use a folder as a module by putting an __init__.py in it, which can then import things from other files. We'll use this capability in each solution. Make a folder called, say, bigclass first.
In the folder put the various .py files that will eventually comprise your class. Each should contain functions and variable definitions for the eventual class, not classes. In __init__.py in the same folder write the following to join them all together.
class Bigclass(object):
from classdef1 import foo, bar, baz, quux
from classdef2 import thing1, thing2
from classdef3 import magic, moremagic
# unfortunately, "from classdefn import *" is an error or warning
num = 42 # add more members here if you like
This has the advantage that you end up with a single class derived directly from object, which will look nice in your inheritance graphs.
You could use multiple inheritance to combine the various parts of your class. In your individual modules you would write a class definition for Bigclass with parts of the class. Then in your __init__.py write:
import classdef1, classdef2, classdef3
class Bigclass(classdef1.Bigclass, classdef2.Bigclass, classdef3.Bigclass):
num = 42 # add more members if desired
If the multiple inheritance becomes an issue, you can use single inheritance: just have each class inherit from another one in chain fashion. Assuming you don't define anything in more than one class, the order doesn't matter. For example, classdef2.py would be like:
import classdef1
class Bigclass(classdef1.Bigclass):
# more member defs here
classdef3 would import Bigclass from classdef2 and add to it, and so on. Your __init__.py would just import the last one:
from classdef42 import Bigclass
I'd generally prefer #1 because it's more explicit about what members you're importing from which files but any of these solutions could work for you.
To use the class in any of these scenarios you can just import it, using the folder name as the module name: from bigclass import Bigclass
You can do this with decorators like so:
class Car(object):
def start(self):
print 'Car has started'
def extends(klass):
def decorator(func):
setattr(klass, func.__name__, func)
return func
return decorator
#this can go in a different module/file
#extends(Car)
def do_start(self):
self.start()
#so can this
car = Car()
car.do_start()
#=> Car has started
Class definitions containing hundreds of lines do occur "in the wild" (I have seen some in popular open-source Python-based frameworks), but I believe that if you ponder what the methods are doing, it will be possible to reduce the length of most classes to a manageable point. Some examples:
Look for places where mostly the same code occurs more than once. Break that code out into its own method and call it from each place with arguments.
"Private" methods that do not use any of the object state can be brought out of the class as stand-alone functions.
Methods that should be called only under certain conditions may indicate a need to place those methods in a subclass.
To directly address your question, it is possible to split up the definition of a class. One way is to "monkey-patch" the class by defining it and then adding outside functions to it as methods. Another is to use the built-in type function to create the class "by hand", supplying its name, any base classes, and its methods and attributes in a dictionary. But I do not recommend doing this just because the definition would be long otherwise. That sort of cure is worse than the disease in my opinion.
I've previously toyed around with something similar. My usecase was a class hierarchy of nodes in an abstract syntax tree, and then I wanted to put all e.g. prettyprinting functions in a separate prettyprint.py file but still have them as methods in the classes.
One thing I tried was to use a decorator that puts the decorated function as an attribute on a specified class. In my case this would mean that prettyprint.py contains lots of def prettyprint(self) all decorated with different #inclass(...)
A problem with this is that one must make sure that the sub files are always imported, and that they depend on the main class, which makes for a circular dependency, which may be messy.
def inclass(kls):
"""
Decorator that adds the decorated function
as a method in specified class
"""
def _(func):
setattr(kls,func.__name__, func)
return func
return _
## exampe usage
class C:
def __init__(self, d):
self.d = d
# this would be in a separate file.
#inclass(C)
def meth(self, a):
"""Some method"""
print "attribute: %s - argument: %s" % (self.d, a)
i = C(10)
print i.meth.__doc__
i.meth(20)
I've not used it, but this package called partial claims to add support for partial classes.
It seems like there's a few other ways you could implement this yourself as well.
You could implement separate parts of the class as mixins in seperate files, then import them all somewhere and subclass them.
Alternatively, you could implement each of the methods of your class somewhere then in a central file import them and assign them as attributes on a class, to create the whole object. Like so:
a.py:
def AFunc( self, something ):
# Do something
pass
b.py:
def BFunc( self, something ):
# Do something else
pass
c.py:
import a, b
class C:
AFunc = a.AFunc
BFunc = b.BFunc
You could even go so far as to automate this process if you really wanted - loop through all the functions provided by modules a and b and then add them as attributes on C. Though that might be total overkill.
There might be other (possibly better) ways to go about it, but those are the 2 that popped into mind.
I would like to add that the pythonic way of doing this is through multiple inheritance, not necessarily using mixins. Instance attributes can be added using super().__init__(*args, **kwargs) in __init__ calls to pass arguments to baseclasses (see ‘super considered super’ presentation by Raymond Hettinger 1). This also enables dependency injection and kind of forces you to think about organization of base classes (it works best if only one baseclass sets an attribute in __init__ and all classes using the attribute inherit from it).
This does usually require you having control over the base classes (or they being written for this pattern).
Another option is using descriptors returning functions through __get__ to add functionality to classes in a decoupled way.
You could also look at __init_subclass__ to add e.g. methods to classes during class generation (i think added in python 3.6, but check)
First I'd like to say that something this complicated it probably not a good idea just to make finding your place in the class easier - it would be best to add comments, highlight sections etc. However, I see two ways you could do this:
Write the class in several files, then read them in as text, concatenate them and exec the resulting string.
Create a separate class in each file, then inherit them all into a master class as mixins. However, if you're subclassing another class already this could lead to MRO problems. You could get around this by creating a metaclass for your master class which manually resolves the MRO, but this could get messy.
The easiest would be the first option.
First off, I don't see how splitting the class into multiple files makes editing any easier. A decent IDE should be able to find any method easily whether in one file or multiple; if you're not using a decent IDE, splitting the class means the maintainer has to guess which file a given method is in, which sounds harder rather than easier.
More fundamentally, this class - so large that you want a special language feature just to support its weight - sounds fundamentally broken. How many lines of code are we talking about? Almost certainly, it would be a better idea to do one of:
Refactor duplicated code into fewer, more general primitives
Define a base class and extend it with subclasses as Karoly Horvath suggests in comments (this is the closest thing to the 'partial classes' that you're asking for that I would endorse)
Define a few separate classes to encapsulate different parts of this
class's functionality, and compose this class of instances of those
smaller ones.
I met the same situation - I want to slipt my class to 2 files.
the reason is that - I want part 1 for GUI layout, only layout
and another file keeps all function.
like c#'s Partial class. one for XAML and another one for functions.

Python - What's the proper way to unittest methods in a different class?

I've written a module called Consumer.py, containing a class (Consumer). This class is initialized using a configuration file thay contains different parameters it uses for computation and the name of a loq que used for logging.
I want to write unit tests for this class so i've made a script called test_Consumer.py with a class called TestConsumerMethods(unittest.TestCase).
Now, what i've done is create a new object of the Consumer class called cons, and then i use that to call on the class methods for testing. For example, Consumer has a simple method that checks if a file exists in a given directory. The test i've made looks like this
import Consumer
from Consumer import Consumer
cons = Consumer('mockconfig.config', 'logque1')
class TestConsumerMethods(unittest.TestCase):
def test_fileExists(self):
self.assertEqual(cons.file_exists('./dir/', 'thisDoesntExist.config), False)
self. assertEqual(cons.file_exists('./dir/', thisDoesExist.config), True)
Is this the correct way to test my class? I mean, ideally i'd like to just use the class methods without having to instantiate the class because to "isolate" the code, right?
Don't make a global object to test against, as it opens up the possibility that some state will get set on it by one test, and affect another.
Each test should run in isolation and be completely independent from others.
Instead, either create the object in your test, or have it automatically created for each test by putting it in the setUp method:
import Consumer
from Consumer import Consumer
class TestConsumerMethods(unittest.TestCase):
def setUp(self):
self.cons = Consumer('mockconfig.config', 'logque1')
def test_fileExists(self):
self.assertEqual(self.cons.file_exists('./dir/', 'thisDoesntExist.config), False)
self. assertEqual(self.cons.file_exists('./dir/', thisDoesExist.config), True)
As far as whether you actually have to instantiate your class at all, that depends on the implementation of the class. I think generally you'd expect to instantiate a class to test its methods.
I'm not sure if that's what you're searching for, but you could add your tests at the end of your file like this :
#!/usr/bin/python
...
class TestConsumerMethods(...):
...
if __name__ == "__main__":
# add your tests here.
This way, by executing the file containing the class definition, you execute the tests you put in the if statement.
This way the tests will only be executed if you directly execute the file itself, but not if you import the class from it.

Can I use a python metaclass to keep track of subclasses in separate files?

I am new to the community. In my Django project, I have a module called "social" in which I have several files like facebook.py, and twitter.py, each with classes that are subclasses of "SocialProvider"
Example
class Facebook(SocialProvider):
Also in my social module is a file called "helper.py" which contains a SocialProviderHelper, which I would like to keep track of all SocialProvider subclasses, and generate different lists, and identifiers for them. For example.. the SocialProviderHelper could "find" Facebook and Twitter and add them to various lists like cool_providers = [] popular_providers = [] old_providers, etc, etc. The goal is to make a universal SocialProviderHelper that other areas of code can import and use... for example.. in a view I may want to get all the "popular_providers" names.. so I would import SocialProviderHelper.. and do something like
helper = SocialProviderHelper()
helper.getOldProviders()
In my SocialProviderHelper, I have:
class SocialProviderHelper(object):
_providers = SocialProvider.__subclasses__()
but
subclasses()
returns an empty list seemingly because the "providers" are defined in other files that haven't been imported, and subclasses() only maintains weak references to the class if they are "alive".
Is there any way around this ?
**The end goal is to be able to whip up another subclass of SocialProvider anywhere simply by doing..
import SocialProvider
class NewSocialNetwork(SocialProvider)
...and have the SocialProviderHelper know of its existence.**
I have tried to implement "subclasses() with a metaclass that keeps a registry of subclasses, but a similar problem persists.
This could be done with a decorator:
from SocialProvider import SocialProvider
#SocialProvider.Register
class NewSocialProvider( SocialProvider ):
pass
I've assumed SocialProvider is a superclass written by you. If so, in your superclass file, the Register helper could be defined as a class method:
class SocialProvider:
subclasses = []
#classmethod
def Register( cls, subcl ):
cls.subclasses.append( subcl )
return subcl
If not, then you could still define a function somewhere, to be used as a decorator, but it and the list it appends to would have to be defined somewhere else, separate from the SocialProvider class. You mention the problem of not-yet-imported files. There's nothing you can do to detect a class that hasn't been defined yet, so you'd have to make sure that the files with the subclass definitions are imported (e.g. via statements like import facebook etc in the ___init__.py file of your module).

Is it possible to divide functions of an python class into different files ? [duplicate]

Using "new" style classes (I'm in python 3.2) is there a way to split a class over multiple files? I've got a large class (which really should be a single class from an object-oriented design perspective, considering coupling, etc, but it'd be nice to split over a few files just for ease of editing the class.
If your problem really is just working with a large class in an editor, the first solution I'd actually look for is a better way to break down the problem. The second solution would be a better editor, preferably one with code folding.
That said, there are a couple of ways you might break up a class into multiple files. Python lets you use a folder as a module by putting an __init__.py in it, which can then import things from other files. We'll use this capability in each solution. Make a folder called, say, bigclass first.
In the folder put the various .py files that will eventually comprise your class. Each should contain functions and variable definitions for the eventual class, not classes. In __init__.py in the same folder write the following to join them all together.
class Bigclass(object):
from classdef1 import foo, bar, baz, quux
from classdef2 import thing1, thing2
from classdef3 import magic, moremagic
# unfortunately, "from classdefn import *" is an error or warning
num = 42 # add more members here if you like
This has the advantage that you end up with a single class derived directly from object, which will look nice in your inheritance graphs.
You could use multiple inheritance to combine the various parts of your class. In your individual modules you would write a class definition for Bigclass with parts of the class. Then in your __init__.py write:
import classdef1, classdef2, classdef3
class Bigclass(classdef1.Bigclass, classdef2.Bigclass, classdef3.Bigclass):
num = 42 # add more members if desired
If the multiple inheritance becomes an issue, you can use single inheritance: just have each class inherit from another one in chain fashion. Assuming you don't define anything in more than one class, the order doesn't matter. For example, classdef2.py would be like:
import classdef1
class Bigclass(classdef1.Bigclass):
# more member defs here
classdef3 would import Bigclass from classdef2 and add to it, and so on. Your __init__.py would just import the last one:
from classdef42 import Bigclass
I'd generally prefer #1 because it's more explicit about what members you're importing from which files but any of these solutions could work for you.
To use the class in any of these scenarios you can just import it, using the folder name as the module name: from bigclass import Bigclass
You can do this with decorators like so:
class Car(object):
def start(self):
print 'Car has started'
def extends(klass):
def decorator(func):
setattr(klass, func.__name__, func)
return func
return decorator
#this can go in a different module/file
#extends(Car)
def do_start(self):
self.start()
#so can this
car = Car()
car.do_start()
#=> Car has started
Class definitions containing hundreds of lines do occur "in the wild" (I have seen some in popular open-source Python-based frameworks), but I believe that if you ponder what the methods are doing, it will be possible to reduce the length of most classes to a manageable point. Some examples:
Look for places where mostly the same code occurs more than once. Break that code out into its own method and call it from each place with arguments.
"Private" methods that do not use any of the object state can be brought out of the class as stand-alone functions.
Methods that should be called only under certain conditions may indicate a need to place those methods in a subclass.
To directly address your question, it is possible to split up the definition of a class. One way is to "monkey-patch" the class by defining it and then adding outside functions to it as methods. Another is to use the built-in type function to create the class "by hand", supplying its name, any base classes, and its methods and attributes in a dictionary. But I do not recommend doing this just because the definition would be long otherwise. That sort of cure is worse than the disease in my opinion.
I've previously toyed around with something similar. My usecase was a class hierarchy of nodes in an abstract syntax tree, and then I wanted to put all e.g. prettyprinting functions in a separate prettyprint.py file but still have them as methods in the classes.
One thing I tried was to use a decorator that puts the decorated function as an attribute on a specified class. In my case this would mean that prettyprint.py contains lots of def prettyprint(self) all decorated with different #inclass(...)
A problem with this is that one must make sure that the sub files are always imported, and that they depend on the main class, which makes for a circular dependency, which may be messy.
def inclass(kls):
"""
Decorator that adds the decorated function
as a method in specified class
"""
def _(func):
setattr(kls,func.__name__, func)
return func
return _
## exampe usage
class C:
def __init__(self, d):
self.d = d
# this would be in a separate file.
#inclass(C)
def meth(self, a):
"""Some method"""
print "attribute: %s - argument: %s" % (self.d, a)
i = C(10)
print i.meth.__doc__
i.meth(20)
I've not used it, but this package called partial claims to add support for partial classes.
It seems like there's a few other ways you could implement this yourself as well.
You could implement separate parts of the class as mixins in seperate files, then import them all somewhere and subclass them.
Alternatively, you could implement each of the methods of your class somewhere then in a central file import them and assign them as attributes on a class, to create the whole object. Like so:
a.py:
def AFunc( self, something ):
# Do something
pass
b.py:
def BFunc( self, something ):
# Do something else
pass
c.py:
import a, b
class C:
AFunc = a.AFunc
BFunc = b.BFunc
You could even go so far as to automate this process if you really wanted - loop through all the functions provided by modules a and b and then add them as attributes on C. Though that might be total overkill.
There might be other (possibly better) ways to go about it, but those are the 2 that popped into mind.
I would like to add that the pythonic way of doing this is through multiple inheritance, not necessarily using mixins. Instance attributes can be added using super().__init__(*args, **kwargs) in __init__ calls to pass arguments to baseclasses (see ‘super considered super’ presentation by Raymond Hettinger 1). This also enables dependency injection and kind of forces you to think about organization of base classes (it works best if only one baseclass sets an attribute in __init__ and all classes using the attribute inherit from it).
This does usually require you having control over the base classes (or they being written for this pattern).
Another option is using descriptors returning functions through __get__ to add functionality to classes in a decoupled way.
You could also look at __init_subclass__ to add e.g. methods to classes during class generation (i think added in python 3.6, but check)
First I'd like to say that something this complicated it probably not a good idea just to make finding your place in the class easier - it would be best to add comments, highlight sections etc. However, I see two ways you could do this:
Write the class in several files, then read them in as text, concatenate them and exec the resulting string.
Create a separate class in each file, then inherit them all into a master class as mixins. However, if you're subclassing another class already this could lead to MRO problems. You could get around this by creating a metaclass for your master class which manually resolves the MRO, but this could get messy.
The easiest would be the first option.
First off, I don't see how splitting the class into multiple files makes editing any easier. A decent IDE should be able to find any method easily whether in one file or multiple; if you're not using a decent IDE, splitting the class means the maintainer has to guess which file a given method is in, which sounds harder rather than easier.
More fundamentally, this class - so large that you want a special language feature just to support its weight - sounds fundamentally broken. How many lines of code are we talking about? Almost certainly, it would be a better idea to do one of:
Refactor duplicated code into fewer, more general primitives
Define a base class and extend it with subclasses as Karoly Horvath suggests in comments (this is the closest thing to the 'partial classes' that you're asking for that I would endorse)
Define a few separate classes to encapsulate different parts of this
class's functionality, and compose this class of instances of those
smaller ones.
I met the same situation - I want to slipt my class to 2 files.
the reason is that - I want part 1 for GUI layout, only layout
and another file keeps all function.
like c#'s Partial class. one for XAML and another one for functions.

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