A great example illustrating LSP (given by Uncle Bob in a podcast I heard recently) was how sometimes something that sounds right in natural language doesn't quite work in code.
In mathematics, a Square
is a Rectangle
. Indeed it is a specialization of a rectangle. The "is a" makes you want to model this with inheritance. However if in code you made Square
derive from Rectangle
, then a Square
should be usable anywhere you expect a Rectangle
. This makes for some strange behavior.
Imagine you had SetWidth
and SetHeight
methods on your Rectangle
base class; this seems perfectly logical. However if your Rectangle
reference pointed to a Square
, then SetWidth
and SetHeight
doesn't make sense because setting one would change the other to match it. In this case Square
fails the Liskov Substitution Test with Rectangle
and the abstraction of having Square
inherit from Rectangle
is a bad one.
Y'all should check out the other priceless SOLID Principles Motivational Posters.
Maybe a bit of example code will help: Notice the difference in the call signatures of foo
, class_foo
and static_foo
:
class A(object):
def foo(self, x):
print(f"executing foo({self}, {x})")
@classmethod
def class_foo(cls, x):
print(f"executing class_foo({cls}, {x})")
@staticmethod
def static_foo(x):
print(f"executing static_foo({x})")
a = A()
Below is the usual way an object instance calls a method. The object instance, a
, is implicitly passed as the first argument.
a.foo(1)
# executing foo(<__main__.A object at 0xb7dbef0c>, 1)
With classmethods, the class of the object instance is implicitly passed as the first argument instead of self
.
a.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
You can also call class_foo
using the class. In fact, if you define something to be
a classmethod, it is probably because you intend to call it from the class rather than from a class instance. A.foo(1)
would have raised a TypeError, but A.class_foo(1)
works just fine:
A.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)
One use people have found for class methods is to create inheritable alternative constructors.
With staticmethods, neither self
(the object instance) nor cls
(the class) is implicitly passed as the first argument. They behave like plain functions except that you can call them from an instance or the class:
a.static_foo(1)
# executing static_foo(1)
A.static_foo('hi')
# executing static_foo(hi)
Staticmethods are used to group functions which have some logical connection with a class to the class.
foo
is just a function, but when you call a.foo
you don't just get the function,
you get a "partially applied" version of the function with the object instance a
bound as the first argument to the function. foo
expects 2 arguments, while a.foo
only expects 1 argument.
a
is bound to foo
. That is what is meant by the term "bound" below:
print(a.foo)
# <bound method A.foo of <__main__.A object at 0xb7d52f0c>>
With a.class_foo
, a
is not bound to class_foo
, rather the class A
is bound to class_foo
.
print(a.class_foo)
# <bound method type.class_foo of <class '__main__.A'>>
Here, with a staticmethod, even though it is a method, a.static_foo
just returns
a good 'ole function with no arguments bound. static_foo
expects 1 argument, and
a.static_foo
expects 1 argument too.
print(a.static_foo)
# <function static_foo at 0xb7d479cc>
And of course the same thing happens when you call static_foo
with the class A
instead.
print(A.static_foo)
# <function static_foo at 0xb7d479cc>
Best Answer
Cohesion refers to what the class (or module) can do. Low cohesion would mean that the class does a great variety of actions - it is broad, unfocused on what it should do. High cohesion means that the class is focused on what it should be doing, i.e. only methods relating to the intention of the class.
Example of Low Cohesion:
Example of High Cohesion:
As for coupling, it refers to how related or dependent two classes/modules are toward each other. For low coupled classes, changing something major in one class should not affect the other. High coupling would make it difficult to change and maintain your code; since classes are closely knit together, making a change could require an entire system revamp.
Good software design has high cohesion and low coupling.