public interface IInterface
{
void show();
}
public class MyClass : IInterface
{
#region IInterface Members
public void show()
{
Console.WriteLine("Hello World!");
}
#endregion
}
How do I implement Python equivalent of this C# code ?
class IInterface(object):
def __init__(self):
pass
def show(self):
raise Exception("NotImplementedException")
class MyClass(IInterface):
def __init__(self):
IInterface.__init__(self)
def show(self):
print 'Hello World!'
Is this a good idea?? Please give examples in your answers.
Using the abc module for abstract base classes seems to do the trick.
from abc import ABCMeta, abstractmethod
class IInterface:
__metaclass__ = ABCMeta
@classmethod
def version(self): return "1.0"
@abstractmethod
def show(self): raise NotImplementedError
class MyServer(IInterface):
def show(self):
print 'Hello, World 2!'
class MyBadServer(object):
def show(self):
print 'Damn you, world!'
class MyClient(object):
def __init__(self, server):
if not isinstance(server, IInterface): raise Exception('Bad interface')
if not IInterface.version() == '1.0': raise Exception('Bad revision')
self._server = server
def client_show(self):
self._server.show()
# This call will fail with an exception
try:
x = MyClient(MyBadServer)
except Exception as exc:
print 'Failed as it should!'
# This will pass with glory
MyClient(MyServer()).client_show()
There are third-party implementations of interfaces for Python (most popular is Zope's, also used in Twisted), but more commonly Python coders prefer to use the richer concept known as an "Abstract Base Class" (ABC), which combines an interface with the possibility of having some implementation aspects there too. ABCs are particularly well supported in Python 2.6 and later, see the PEP, but even in earlier versions of Python they're normally seen as "the way to go" -- just define a class some of whose methods raise NotImplementedError so that subclasses will be on notice that they'd better override those methods!-)
Something like this (might not work as I don't have Python around):
class IInterface:
def show(self): raise NotImplementedError
class MyClass(IInterface):
def show(self): print "Hello World!"
Implementing interfaces with abstract base classes is much simpler in modern Python 3 and they serve a purpose as an interface contract for plug-in extensions.
Create the interface/abstract base class:
from abc import ABC, abstractmethod
class AccountingSystem(ABC):
@abstractmethod
def create_purchase_invoice(self, purchase):
pass
@abstractmethod
def create_sale_invoice(self, sale):
log.debug('Creating sale invoice', sale)
Create a normal subclass and override all abstract methods:
class GizmoAccountingSystem(AccountingSystem):
def create_purchase_invoice(self, purchase):
submit_to_gizmo_purchase_service(purchase)
def create_sale_invoice(self, sale):
super().create_sale_invoice(sale)
submit_to_gizmo_sale_service(sale)
You can optionally have common implementation in the abstract methods as in create_sale_invoice(), calling it with super() explicitly in the subclass as above.
Instantiation of a subclass that does not implement all the abstract methods fails:
class IncompleteAccountingSystem(AccountingSystem):
pass
>>> accounting = IncompleteAccountingSystem()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Can't instantiate abstract class IncompleteAccountingSystem with abstract methods
create_purchase_invoice, create_sale_invoice
You can also have abstract properties, static and class methods by combining corresponding annotations with @abstractmethod.
Abstract base classes are great for implementing plugin-based systems. All imported subclasses of a class are accessible via __subclasses__(), so if you load all classes from a plugin directory with importlib.import_module() and if they subclass the base class, you have direct access to them via __subclasses__() and you can be sure that the interface contract is enforced for all of them during instantiation.
Here's the plugin loading implementation for the AccountingSystem example above:
...
from importlib import import_module
class AccountingSystem(ABC):
...
_instance = None
@classmethod
def instance(cls):
if not cls._instance:
module_name = settings.ACCOUNTING_SYSTEM_MODULE_NAME
import_module(module_name)
subclasses = cls.__subclasses__()
if len(subclasses) > 1:
raise InvalidAccountingSystemError('More than one '
f'accounting module: {subclasses}')
if not subclasses or module_name not in str(subclasses[0]):
raise InvalidAccountingSystemError('Accounting module '
f'{module_name} does not exist or does not '
'subclass AccountingSystem')
cls._instance = subclasses[0]()
return cls._instance
Then you can access the accounting system plugin object through the AccountingSystem class:
>>> accountingsystem = AccountingSystem.instance()
(Inspired by this PyMOTW-3 post.)
interface supports Python 2.7 and Python 3.4+.
To install interface you have to
pip install python-interface
Example Code:
from interface import implements, Interface
class MyInterface(Interface):
def method1(self, x):
pass
def method2(self, x, y):
pass
class MyClass(implements(MyInterface)):
def method1(self, x):
return x * 2
def method2(self, x, y):
return x + y
I invite you to explore what Python 3.8 has to offer for the subject matter in form of Structural subtyping (static duck typing) (PEP 544)
See the short description https://docs.python.org/3/library/typing.html#typing.Protocol
For the simple example here it goes like this:
from typing import Protocol
class MyShowProto(Protocol):
def show(self):
...
class MyClass:
def show(self):
print('Hello World!')
class MyOtherClass:
pass
def foo(o: MyShowProto):
return o.show()
foo(MyClass()) # ok
foo(MyOtherClass()) # fails
foo(MyOtherClass()) will fail static type checks:
$ mypy proto-experiment.py
proto-experiment.py:21: error: Argument 1 to "foo" has incompatible type "MyOtherClass"; expected "MyShowProto"
Found 1 error in 1 file (checked 1 source file)
In addition, you can specify the base class explicitly, for instance:
class MyOtherClass(MyShowProto):
but note that this makes methods of the base class actually available on the subclass, and thus the static checker will not report that a method definition is missing on the MyOtherClass.
So in this case, in order to get a useful type-checking, all the methods that we want to be explicitly implemented should be decorated with @abstractmethod:
from typing import Protocol
from abc import abstractmethod
class MyShowProto(Protocol):
@abstractmethod
def show(self): raise NotImplementedError
class MyOtherClass(MyShowProto):
pass
MyOtherClass() # error in type checker
My understanding is that interfaces are not that necessary in dynamic languages like Python. In Java (or C++ with its abstract base class) interfaces are means for ensuring that e.g. you're passing the right parameter, able to perform set of tasks.
E.g. if you have observer and observable, observable is interested in subscribing objects that supports IObserver interface, which in turn has notify action. This is checked at compile time.
In Python, there is no such thing as compile time and method lookups are performed at runtime. Moreover, one can override lookup with __getattr__() or __getattribute__() magic methods. In other words, you can pass, as observer, any object that can return callable on accessing notify attribute.
This leads me to the conclusion, that interfaces in Python do exist - it's just their enforcement is postponed to the moment in which they are actually used
Source: Stackoverflow.com