Python 实用宝典

Question 1

In Java, for example, the @Override annotation not only provides compile-time checking of an override but makes for excellent self-documenting code.

I’m just looking for documentation (although if it’s an indicator to some checker like pylint, that’s a bonus). I can add a comment or docstring somewhere, but what is the idiomatic way to indicate an override in Python?

Question 2

Based on this and fwc:s answer I created a pip installable package https://github.com/mkorpela/overrides

From time to time I end up here looking at this question. Mainly this happens after (again) seeing the same bug in our code base: Someone has forgotten some “interface” implementing class while renaming a method in the “interface”..

Well Python ain’t Java but Python has power — and explicit is better than implicit — and there are real concrete cases in the real world where this thing would have helped me.

So here is a sketch of overrides decorator. This will check that the class given as a parameter has the same method (or something) name as the method being decorated.

If you can think of a better solution please post it here!

def overrides(interface_class):
    def overrider(method):
        assert(method.__name__ in dir(interface_class))
        return method
    return overrider

It works as follows:

class MySuperInterface(object):
    def my_method(self):
        print 'hello world!'


class ConcreteImplementer(MySuperInterface):
    @overrides(MySuperInterface)
    def my_method(self):
        print 'hello kitty!'

and if you do a faulty version it will raise an assertion error during class loading:

class ConcreteFaultyImplementer(MySuperInterface):
    @overrides(MySuperInterface)
    def your_method(self):
        print 'bye bye!'

>> AssertionError!!!!!!!

Question 3

Here’s an implementation that doesn’t require specification of the interface_class name.

import inspect
import re

def overrides(method):
    # actually can't do this because a method is really just a function while inside a class def'n  
    #assert(inspect.ismethod(method))

    stack = inspect.stack()
    base_classes = re.search(r'class.+\((.+)\)\s*\:', stack[2][4][0]).group(1)

    # handle multiple inheritance
    base_classes = [s.strip() for s in base_classes.split(',')]
    if not base_classes:
        raise ValueError('overrides decorator: unable to determine base class') 

    # stack[0]=overrides, stack[1]=inside class def'n, stack[2]=outside class def'n
    derived_class_locals = stack[2][0].f_locals

    # replace each class name in base_classes with the actual class type
    for i, base_class in enumerate(base_classes):

        if '.' not in base_class:
            base_classes[i] = derived_class_locals[base_class]

        else:
            components = base_class.split('.')

            # obj is either a module or a class
            obj = derived_class_locals[components[0]]

            for c in components[1:]:
                assert(inspect.ismodule(obj) or inspect.isclass(obj))
                obj = getattr(obj, c)

            base_classes[i] = obj


    assert( any( hasattr(cls, method.__name__) for cls in base_classes ) )
    return method

Question 4

If you want this for documentation purposes only, you can define your own override decorator:

def override(f):
    return f


class MyClass (BaseClass):

    @override
    def method(self):
        pass

This is really nothing but eye-candy, unless you create override(f) in such a way that is actually checks for an override.

But then, this is Python, why write it like it was Java?

Question 5

Python ain’t Java. There’s of course no such thing really as compile-time checking.

I think a comment in the docstring is plenty. This allows any user of your method to type help(obj.method) and see that the method is an override.

You can also explicitly extend an interface with class Foo(Interface), which will allow users to type help(Interface.method) to get an idea about the functionality your method is intended to provide.

Question 6

Improvising on @mkorpela great answer, here is a version with

more precise checks, naming, and raised Error objects

def overrides(interface_class):
    """
    Function override annotation.
    Corollary to @abc.abstractmethod where the override is not of an
    abstractmethod.
    Modified from answer https://stackoverflow.com/a/8313042/471376
    """
    def confirm_override(method):
        if method.__name__ not in dir(interface_class):
            raise NotImplementedError('function "%s" is an @override but that'
                                      ' function is not implemented in base'
                                      ' class %s'
                                      % (method.__name__,
                                         interface_class)
                                      )

        def func():
            pass

        attr = getattr(interface_class, method.__name__)
        if type(attr) is not type(func):
            raise NotImplementedError('function "%s" is an @override'
                                      ' but that is implemented as type %s'
                                      ' in base class %s, expected implemented'
                                      ' type %s'
                                      % (method.__name__,
                                         type(attr),
                                         interface_class,
                                         type(func))
                                      )
        return method
    return confirm_override

Here is what it looks like in practice:

`NotImplementedError` “not implemented in base class“

class A(object):
    # ERROR: `a` is not a implemented!
    pass

class B(A):
    @overrides(A)
    def a(self):
        pass

results in more descriptive NotImplementedError error

function "a" is an @override but that function is not implemented in base class <class '__main__.A'>

full stack

Traceback (most recent call last):
  …
  File "C:/Users/user1/project.py", line 135, in <module>
    class B(A):
  File "C:/Users/user1/project.py", line 136, in B
    @overrides(A)
  File "C:/Users/user1/project.py", line 110, in confirm_override
    interface_class)
NotImplementedError: function "a" is an @override but that function is not implemented in base class <class '__main__.A'>

`NotImplementedError` “expected implemented type“

class A(object):
    # ERROR: `a` is not a function!
    a = ''

class B(A):
    @overrides(A)
    def a(self):
        pass

results in more descriptive NotImplementedError error

function "a" is an @override but that is implemented as type <class 'str'> in base class <class '__main__.A'>, expected implemented type <class 'function'>

full stack

Traceback (most recent call last):
  …
  File "C:/Users/user1/project.py", line 135, in <module>
    class B(A):
  File "C:/Users/user1/project.py", line 136, in B
    @overrides(A)
  File "C:/Users/user1/project.py", line 125, in confirm_override
    type(func))
NotImplementedError: function "a" is an @override but that is implemented as type <class 'str'> in base class <class '__main__.A'>, expected implemented type <class 'function'>

The great thing about @mkorpela answer is the check happens during some initialization phase. The check does not need to be “run”. Referring to the prior examples, class B is never initialized (B()) yet the NotImplementedError will still raise. This means overrides errors are caught sooner.

Question 7

Like others have said unlike Java there is not @Overide tag however above you can create your own using decorators however I would suggest using the getattrib() global method instead of using the internal dict so you get something like the following:

def Override(superClass):
    def method(func)
        getattr(superClass,method.__name__)
    return method

If you wanted to you could catch getattr() in your own try catch raise your own error but I think getattr method is better in this case.

Also this catches all items bound to a class including class methods and vairables

Question 8

Based on @mkorpela’s great answer, I’ve written a similar package (ipromise pypi github) that does many more checks:

Suppose A inherits from B and C, B inherits from C.

Module ipromise checks that:

If A.f overrides B.f, B.f must exist, and A must inherit from B. (This is the check from the overrides package).
You don’t have the pattern A.f declares that it overrides B.f, which then declares that it overrides C.f. A should say that it overrides from C.f since B might decide to stop overriding this method, and that should not result in downstream updates.
You don’t have the pattern A.f declares that it overrides C.f, but B.f does not declare its override.
You don’t have the pattern A.f declares that it overrides C.f, but B.f declares that it overrides from some D.f.

It also has various features for marking and checking implementing an abstract method.

Question 9

Hear is simplest and working under Jython with Java classes:

class MyClass(SomeJavaClass):
     def __init__(self):
         setattr(self, "name_of_method_to_override", __method_override__)

     def __method_override__(self, some_args):
         some_thing_to_do()

Question 10

Not only did the decorator I made check if the name of the overriding attribute in is any superclass of the class the attribute is in without having to specify a superclass, this decorator also check to ensure the overriding attribute must be the same type as the overridden attribute. Class Methods are treated like methods and Static Methods are treated like functions. This decorator works for callables, class methods, static methods, and properties.

For source code see: https://github.com/fireuser909/override

This decorator only works for classes that are instances of override.OverridesMeta but if your class is an instance of a custom metaclass use the create_custom_overrides_meta function to create a metaclass that is compatible with the override decorator. For tests, run the override.__init__ module.

Question 11

In Python 2.6+ and Python 3.2+ you can do it (Actually simulate it, Python doesn’t support function overloading and child class automatically overrides parent’s method). We can use Decorators for this. But first, note that Python’s @decorators and Java’s @Annotations are totally different things. The prior one is a wrapper with concrete code while later one is a flag to compiler.

For this, first do pip install multipledispatch

from multipledispatch import dispatch as Override
# using alias 'Override' just to give you some feel :)

class A:
    def foo(self):
        print('foo in A')

    # More methods here


class B(A):
    @Override()
    def foo(self):
        print('foo in B')
    
    @Override(int)
    def foo(self,a):
        print('foo in B; arg =',a)
        
    @Override(str,float)
    def foo(self,a,b):
        print('foo in B; arg =',(a,b))
        
a=A()
b=B()
a.foo()
b.foo()
b.foo(4)
b.foo('Wheee',3.14)

output:

foo in A
foo in B
foo in B; arg = 4
foo in B; arg = ('Wheee', 3.14)

Note that you must have to use decorator here with parenthesis

One thing to remember is that since Python doesn’t have function overloading directly, so even if Class B don’t inherit from Class A but needs all those foos than also you need to use @Override (though using alias ‘Overload’ will look better in that case)

Question 12

I was reading ‘Dive Into Python’ and in the chapter on classes it gives this example:

class FileInfo(UserDict):
    "store file metadata"
    def __init__(self, filename=None):
        UserDict.__init__(self)
        self["name"] = filename

The author then says that if you want to override the __init__ method, you must explicitly call the parent __init__ with the correct parameters.

What if that FileInfo class had more than one ancestor class?
- Do I have to explicitly call all of the ancestor classes’ __init__ methods?
Also, do I have to do this to any other method I want to override?

Question 13

The book is a bit dated with respect to subclass-superclass calling. It’s also a little dated with respect to subclassing built-in classes.

It looks like this nowadays:

class FileInfo(dict):
    """store file metadata"""
    def __init__(self, filename=None):
        super(FileInfo, self).__init__()
        self["name"] = filename

Note the following:

We can directly subclass built-in classes, like dict, list, tuple, etc.
The super function handles tracking down this class’s superclasses and calling functions in them appropriately.

Question 14

In each class that you need to inherit from, you can run a loop of each class that needs init’d upon initiation of the child class…an example that can copied might be better understood…

class Female_Grandparent:
    def __init__(self):
        self.grandma_name = 'Grandma'

class Male_Grandparent:
    def __init__(self):
        self.grandpa_name = 'Grandpa'

class Parent(Female_Grandparent, Male_Grandparent):
    def __init__(self):
        Female_Grandparent.__init__(self)
        Male_Grandparent.__init__(self)

        self.parent_name = 'Parent Class'

class Child(Parent):
    def __init__(self):
        Parent.__init__(self)
#---------------------------------------------------------------------------------------#
        for cls in Parent.__bases__: # This block grabs the classes of the child
             cls.__init__(self)      # class (which is named 'Parent' in this case), 
                                     # and iterates through them, initiating each one.
                                     # The result is that each parent, of each child,
                                     # is automatically handled upon initiation of the 
                                     # dependent class. WOOT WOOT! :D
#---------------------------------------------------------------------------------------#



g = Female_Grandparent()
print g.grandma_name

p = Parent()
print p.grandma_name

child = Child()

print child.grandma_name

Question 15

You don’t really have to call the __init__ methods of the base class(es), but you usually want to do it because the base classes will do some important initializations there that are needed for rest of the classes methods to work.

For other methods it depends on your intentions. If you just want to add something to the base classes behavior you will want to call the base classes method additionally to your own code. If you want to fundamentally change the behavior, you might not call the base class’ method and implement all the functionality directly in the derived class.

Question 16

If the FileInfo class has more than one ancestor class then you should definitely call all of their __init__() functions. You should also do the same for the __del__() function, which is a destructor.

Question 17

Yes, you must call __init__ for each parent class. The same goes for functions, if you are overriding a function that exists in both parents.

Question 18

Consider the following code:

class Base(object):

    @classmethod
    def do(cls, a):
        print cls, a

class Derived(Base):

    @classmethod
    def do(cls, a):
        print 'In derived!'
        # Base.do(cls, a) -- can't pass `cls`
        Base.do(a)

if __name__ == '__main__':
    d = Derived()
    d.do('hello')

> $ python play.py  
> In derived! 
> <class '__main__.Base'> msg

From Derived.do, how do I call Base.do?

I would normally use super or even the base class name directly if this is a normal object method, but apparently I can’t find a way to call the classmethod in the base class.

In the above example, Base.do(a) prints Base class instead of Derived class.

Question 19

If you’re using a new-style class (i.e. derives from object in Python 2, or always in Python 3), you can do it with super() like this:

super(Derived, cls).do(a)

This is how you would invoke the code in the base class’s version of the method (i.e. print cls, a), from the derived class, with cls being set to the derived class.

Question 20

this has been a while, but I think I may have found an answer. When you decorate a method to become a classmethod the original unbound method is stored in a property named ‘im_func’:

class Base(object):
    @classmethod
    def do(cls, a):
        print cls, a

class Derived(Base):

    @classmethod
    def do(cls, a):
        print 'In derived!'
        # Base.do(cls, a) -- can't pass `cls`
        Base.do.im_func(cls, a)

if __name__ == '__main__':
    d = Derived()
    d.do('hello')

Question 21

This works for me:

Base.do('hi')

Python 实用宝典

标签归档：overriding

在Python中，如何指示我要覆盖方法？

问题：在Python中，如何指示我要覆盖方法？

回答 0

回答 1

回答 2

回答 3

回答 4

更精确的检查，命名和引发的Error对象

`NotImplementedError`“ 未在基类中实现 ”

`NotImplementedError`“ 预期的实现类型 ”

more precise checks, naming, and raised Error objects

`NotImplementedError` “not implemented in base class“

`NotImplementedError` “expected implemented type“

回答 5

回答 6

回答 7

回答 8

回答 9

在python中继承和覆盖init

问题：在python中继承和覆盖init

回答 0

回答 1

回答 2

回答 3

回答 4

在Python中调用基类的类方法

问题：在Python中调用基类的类方法

回答 0

回答 1

回答 2

有趣好用的Python教程

问题：在Python中，如何指示我要覆盖方法？

回答 0

回答 1

回答 2

回答 3

回答 4

更精确的检查，命名和引发的Error对象

NotImplementedError“ 未在基类中实现 ”

NotImplementedError“ 预期的实现类型 ”

more precise checks, naming, and raised Error objects

NotImplementedError “not implemented in base class“

NotImplementedError “expected implemented type“

回答 5

回答 6

回答 7

回答 8

回答 9

问题：在python中继承和覆盖__init__

回答 0

回答 1

回答 2

回答 3

回答 4

问题：在Python中调用基类的类方法

回答 0

回答 1

回答 2

有趣好用的Python教程

`NotImplementedError`“ 未在基类中实现 ”

`NotImplementedError`“ 预期的实现类型 ”

`NotImplementedError` “not implemented in base class“

`NotImplementedError` “expected implemented type“

问题：在python中继承和覆盖init