What Is a "Method" in Python

What is a method in Python?

It's a function which is a member of a class:

class C:
    def my_method(self):
        print("I am a C")

c = C()
c.my_method()  # Prints("I am a C")

Simple as that!

(There are also some alternative kinds of method, allowing you to control the relationship between the class and the function. But I'm guessing from your question that you're not asking about that, but rather just the basics.)

Python method vs function

Yes. To be clear, methods are functions, they are simply attached to the class, and when that function is called from an instance it gets that instance passed implicitly as the first argument automagically*. It doesn't actually matter where that function is defined. Consider:

class FooBar:
    def __init__(self, n):
        self.n = n
    def foo(self):
        return '|'.join(self.n*['foo'])

fb = FooBar(2)

print(fb.foo())

def bar(self):
    return '*'.join(self.n*['bar'])

print(bar(fb))

FooBar.bar = bar

print(fb.bar())

*I highly recommend reading the descriptor HOWTO. Spoiler alert, Functions are descriptors. This is how Python magically passes instances to methods (that is, all function objects are descriptors who's __get__ method passes the instance as the first argument to the function itself when accessed by an instance on a class!. The HOWTO shows Python implementations of all of these things, including how you could implement property in pure Python!

Difference between methods and functions, in Python compared to C++

Needs Attention: This answer seems to be outdated. Check this

A function is a callable object in Python, i.e. can be called using the call operator (though other objects can emulate a function by implementing __call__). For example:

>>> def a(): pass
>>> a
<function a at 0x107063aa0>
>>> type(a)
<type 'function'>

A method is a special class of function, one that can be bound or unbound.

>>> class A:
...   def a(self): pass
>>> A.a
<unbound method A.a>
>>> type(A.a)
<type 'instancemethod'>

>>> A().a
<bound method A.a of <__main__.A instance at 0x107070d88>>
>>> type(A().a)
<type 'instancemethod'>

Of course, an unbound method cannot be called (at least not directly without passing an instance as an argument):

>>> A.a()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unbound method a() must be called with A instance as first argument (got nothing instead)

In Python, in most cases, you won't notice the difference between a bound method, a function, or a callable object (i.e. an object that implements __call__), or a class constructor. They all look the same, they just have different naming conventions. Under the hood, the objects may look vastly different though.

This means that a bound method can be used as a function, this is one of the many small things that makes Python so powerful

>>> b = A().a
>>> b()

It also means that even though there is a fundamental difference between len(...) and str(...) (the latter is a type constructor), you won't notice the difference until you dig a little deeper:

>>> len
<built-in function len>
>>> str
<type 'str'>

Difference between methods and attributes in python

Terminology

Mental model:

A variable stored in an instance or class is called an attribute.
A function stored in an instance or class is called a method.

According to Python's glossary:

attribute: A value associated with an object which is referenced by
name using dotted expressions. For example, if an object o has an
attribute a it would be referenced as o.a
method: A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self). See function and nested scope.

Examples

Terminology applied to actual code:

a = 10                          # variable

def f(b):                       # function  
    return b ** 2

class C:

    c = 20                      # class attribute

    def __init__(self, d):      # "dunder" method
        self.d = d              # instance attribute

    def show(self):             # method
        print(self.c, self.d) 

e = C(30)
e.g = 40                        # another instance attribute

What is static method in python

Have you already read this?

https://en.wikipedia.org/wiki/Method_(computer_programming)

Especially this?

https://en.wikipedia.org/wiki/Method_(computer_programming)#Static_methods

Explanation

In OOP you define classes that you later on instantiate. A class is nothing more than a blueprint: Once you instantiate objects from a class your object will follow exactly the blueprint of your class. That means: If you define a field named "abc" in your class you will later on have a field "abc" in your object. If you define a method "foo()" in your class, you will later on have a method "foo()" to be invoked on your object.

Please note that this "on your object" is essential: You always instantiate a class and then you can invoke the method. This is the "normal" way.

A static method is different. While a normal method always requires to have an instance (where you then can invoke this method at) a static method does not. A static method exists independently from your instances (that's why it is named "static"). So a static method is associated with your class definition itself and therefore is always there and therefore can be invoked only at your class itself. It is completely independent from all instances.

That's a static method.

Python's implementation is a bit ... well ... simple. In details there are deviations from this description above. But that does not make any difference: To be in line with OOP concepts you always should use methods exactly as described above.

Example

Let's give you an example:

class FooBar:

  def someMethod(self):
    print("abc")

This is a regular (instance) method. You use it like this:

myObj = FooBar()
myObj.someMethod()

If you have ...

myObjB = FooBar()
myObjB.someMethod()

... you have an additional instance and therefore invoking someMethod() on this second instance will be the invocation of a second someMethod() method - defined at the second object. This is because you instantiate objects before use so all instances follow the blueprint FooBar defined. All instances therefore receive some kind of copy of someMethod().

(In practice Python will use optimizations internally, so there actually is only one piece of code that implements your someMethod() in memory, but forget about this for now. To a programmer it appears as that every instance of a class will have a copy of the method someMethod(). And that's the level of abstraction that is relevant to us as this is the "surface" we work on. Deep within the implementation of a programming or script language things might be a bit different but this is not very relevant.)

Let's have a look at a static method:

class FooBar:

  @staticmethod
  def someStaticMethod():
    print("abc")

Such static methods can be invoked like this:

FooBar.someStaticMethod()

As you can see: No instance. You directly invoke this method in the context of the class itself. While regular methods work on the particular instance itself - they typically modify data within this instance itself - a class method does not. It could modify static (!) data, but typically it does not anyway.

Consider a static method a special case. It is rarely needed. What you typically want if you write code is not to implement a static method. Only in very specific situations it makes sense to implement a static method.

The `self` parameter

Please note that a standard "instance" method always must have self as a first argument. This is a python specific. In the real world Python will (of course!) store your method only once in memory, even if you instantiate thousands of objects of your class. Consider this an optimization. If you then invoke your method on one of your thousands of instances, always the same single piece of code is called. But for it to distinguish on which particular object the code of the method should work on your instance is passed to this internally stored piece of code as the very first argument. This is the self argument. It is some kind of implicit argument and always needed for regular (instance) methods. (Not: static methods - there you don't need an instance to invoke them).

As this argument is implicit and always needed most programming languages hide it to the programmer (and handle this internally - under the hood - in the correct way). It does not really make much sense to expose this special argument anyway.

Unfortunately Python does not follow this principle. Python does not hide this argument which is implicitly required. (Python's incorporation of OOP concepts is a bit ... simple.) Therefore you see self almost everywhere in methods. In your mind you can ignore it, but you need to write it explicitly if you define your own classes. (Which is something you should do in order to structure your programs in a good way.)

The static method `new()`

Python is quite special. While regular programming languages follow a strict and immutable concept of how to create instances of particular classes, Python is a bit different here. This behavior can be changed. This behavior is implemented in __new__(). So if you do this ...

myObj = FooBar()

... Python implicitly invokes FooBar.__new__() which in turn invokes a constructor-like (instance) method named __init__() that you could (!) define in your class (as an instance method) and then returns the fully initialized instance. This instance is then what is stored in myObj in this example her.

You could modify this behavior if you want. But this would requires a very very very particularly unusual use case. You will likely never have anything to do with __new__() itself in your entire work with Python. My advice: If you're somehow new to Python just ignore it.

Difference between method and method

__method: private method.
__method__: special Python method. They are named like this to prevent name collisions. Check this page for a list of these special methods.
_method: This is the recommended naming convention for protected methods in the Python style guide.

From the style guide:

_single_leading_underscore: weak "internal use" indicator. E.g. from M import * does not import objects whose name starts with an underscore.
single_trailing_underscore_: used by convention to avoid conflicts with
Python keyword, e.g.
Tkinter.Toplevel(master, class_='ClassName')
__double_leading_underscore: when naming a class attribute, invokes name
mangling (inside class FooBar, __boo becomes _FooBar__boo; see below).

__double_leading_and_trailing_underscore__: "magic" objects or
attributes that live in user-controlled namespaces. E.g. __init__,
__import__ or __file__. Never invent such names; only use them
as documented.

What does - mean in Python function definitions?

It's a function annotation.

In more detail, Python 2.x has docstrings, which allow you to attach a metadata string to various types of object. This is amazingly handy, so Python 3 extends the feature by allowing you to attach metadata to functions describing their parameters and return values.

There's no preconceived use case, but the PEP suggests several. One very handy one is to allow you to annotate parameters with their expected types; it would then be easy to write a decorator that verifies the annotations or coerces the arguments to the right type. Another is to allow parameter-specific documentation instead of encoding it into the docstring.

Why we need corresponding class function with each method in python?

The key is

python internally converts it for you

From your standpoint:

meth(self, args) is the syntax you use to define member functions; and
obj.meth(args) is the syntax you use to call member functions.

The meth(obj,args) option is the way procedural languages work. That is often how the implementation works, but expressing the call as obj.meth(args) keeps focus on the object and makes it easier to read which data values (object instances) are being used.

Edit 1 If I understand your question correctly, you are asking why Python needs to know the class when it already has the instance available, and instances know their own types. In fact, Python fetches methods based on the instance all the time. I think the point the tutorial is making is that in Python, the class is the primary place the functions are defined. This is different from some object-oriented languages, in which each instance has its own methods, and they may be completely different from each other. So the tutorial is contrasting the usual approach in Python:

class Foo:
    def bar(self):
        pass

with an alternative (possible in Python, but not typical):

foo = object()   # an empty instance
foo.bar = lambda self: pass

Edit 2 Python methods normally live in the classes, not in the instances. Even if you create 1000 Point objects, there is only one copy of the actual instruction bytes for Point.distance. Those instruction bytes are executed anytime <some point variable>.distance() is called. You are correct that the self parameter is how those instruction bytes know what instance to work on, and how the method can access other data in the passed instance.

Edit 3 self isn't exactly a namespace in the way that local vs. global is. However, it is fair to say that self.foo refers to a foo that is indeed accessible to all the methods of this instance of the current class. Given

a = Point(1,2)
b = Point(3,4)

inside a Point.distance call, self refers to a or b, but not both. So when you call a.distance(), the self.x will be a.x, not b.x. But all methods of Point can access self.x to get whatever the current point's x is.

Edit 4 Suppose you weren't using objects, but instead dictionaries:

a = {'x':1, 'y':2}  # make a "point"
b = {'x':3, 'y':4}  # make another

def point_distance(point):
    print (point['x'])

then you could say:

point_distance(a)

to get the effect of

print (a['x'])

Classes do basically that, with cleaner syntax and some nice benefits. But just as the point parameter to point_distance() refers to one and only one point-like dictionary each time you call point_distance(), the self parameter to Point.distance() refers to one and only one Point instance each time you call <whatever point>.distance().

Why do some functions have underscores __ before and after the function name?

From the Python PEP 8 -- Style Guide for Python Code:

Descriptive: Naming Styles

The following special forms using leading or trailing underscores are
recognized (these can generally be combined with any case convention):

_single_leading_underscore: weak "internal use" indicator. E.g. from M import * does not import objects whose name starts with an underscore.

single_trailing_underscore_: used by convention to avoid conflicts with Python keyword, e.g.

Tkinter.Toplevel(master, class_='ClassName')

__double_leading_underscore: when naming a class attribute, invokes name mangling (inside class FooBar, __boo becomes _FooBar__boo; see below).

__double_leading_and_trailing_underscore__: "magic" objects or attributes that live in user-controlled namespaces. E.g. __init__,
__import__ or __file__. Never invent such names; only use them as documented.

Note that names with double leading and trailing underscores are essentially reserved for Python itself: "Never invent such names; only use them as documented".

What Is a "Method" in Python