Related
Consider this example:
class MyClass:
def func(self, name):
self.name = name
I know that self refers to the specific instance of MyClass. But why must func explicitly include self as a parameter? Why do we need to use self in the method's code? Some other languages make this implicit, or use special syntax instead.
For a language-agnostic consideration of the design decision, see What is the advantage of having this/self pointer mandatory explicit?.
To close debugging questions where OP omitted a self parameter for a method and got a TypeError, use TypeError: method() takes 1 positional argument but 2 were given instead. If OP omitted self. in the body of the method and got a NameError, consider How can I call a function within a class?.
The reason you need to use self. is because Python does not use special syntax to refer to instance attributes. Python decided to do methods in a way that makes the instance to which the method belongs be passed automatically, but not received automatically: the first parameter of methods is the instance the method is called on. That makes methods entirely the same as functions, and leaves the actual name to use up to you (although self is the convention, and people will generally frown at you when you use something else.) self is not special to the code, it's just another object.
Python could have done something else to distinguish normal names from attributes -- special syntax like Ruby has, or requiring declarations like C++ and Java do, or perhaps something yet more different -- but it didn't. Python's all for making things explicit, making it obvious what's what, and although it doesn't do it entirely everywhere, it does do it for instance attributes. That's why assigning to an instance attribute needs to know what instance to assign to, and that's why it needs self..
Let's say you have a class ClassA which contains a method methodA defined as:
def methodA(self, arg1, arg2):
# do something
and objectA is an instance of this class.
Now when objectA.methodA(arg1, arg2) is called, python internally converts it for you as:
ClassA.methodA(objectA, arg1, arg2)
The self variable refers to the object itself.
Let’s take a simple vector class:
class Vector:
def __init__(self, x, y):
self.x = x
self.y = y
We want to have a method which calculates the length. What would it look like if we wanted to define it inside the class?
def length(self):
return math.sqrt(self.x ** 2 + self.y ** 2)
What should it look like when we were to define it as a global method/function?
def length_global(vector):
return math.sqrt(vector.x ** 2 + vector.y ** 2)
So the whole structure stays the same. How can me make use of this? If we assume for a moment that we hadn’t written a length method for our Vector class, we could do this:
Vector.length_new = length_global
v = Vector(3, 4)
print(v.length_new()) # 5.0
This works because the first parameter of length_global, can be re-used as the self parameter in length_new. This would not be possible without an explicit self.
Another way of understanding the need for the explicit self is to see where Python adds some syntactical sugar. When you keep in mind, that basically, a call like
v_instance.length()
is internally transformed to
Vector.length(v_instance)
it is easy to see where the self fits in. You don't actually write instance methods in Python; what you write is class methods which must take an instance as a first parameter. And therefore, you’ll have to place the instance parameter somewhere explicitly.
When objects are instantiated, the object itself is passed into the self parameter.
Because of this, the object’s data is bound to the object. Below is an example of how you might like to visualize what each object’s data might look. Notice how ‘self’ is replaced with the objects name. I'm not saying this example diagram below is wholly accurate but it hopefully with serve a purpose in visualizing the use of self.
The Object is passed into the self parameter so that the object can keep hold of its own data.
Although this may not be wholly accurate, think of the process of instantiating an object like this: When an object is made it uses the class as a template for its own data and methods. Without passing it's own name into the self parameter, the attributes and methods in the class would remain as a general template and would not be referenced to (belong to) the object. So by passing the object's name into the self parameter it means that if 100 objects are instantiated from the one class, they can all keep track of their own data and methods.
See the illustration below:
I like this example:
class A:
foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: [5]
class A:
def __init__(self):
self.foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: []
I will demonstrate with code that does not use classes:
def state_init(state):
state['field'] = 'init'
def state_add(state, x):
state['field'] += x
def state_mult(state, x):
state['field'] *= x
def state_getField(state):
return state['field']
myself = {}
state_init(myself)
state_add(myself, 'added')
state_mult(myself, 2)
print( state_getField(myself) )
#--> 'initaddedinitadded'
Classes are just a way to avoid passing in this "state" thing all the time (and other nice things like initializing, class composition, the rarely-needed metaclasses, and supporting custom methods to override operators).
Now let's demonstrate the above code using the built-in python class machinery, to show how it's basically the same thing.
class State(object):
def __init__(self):
self.field = 'init'
def add(self, x):
self.field += x
def mult(self, x):
self.field *= x
s = State()
s.add('added') # self is implicitly passed in
s.mult(2) # self is implicitly passed in
print( s.field )
[migrated my answer from duplicate closed question]
The following excerpts are from the Python documentation about self:
As in Modula-3, there are no shorthands [in Python] for referencing the object’s members from its methods: the method function is declared with an explicit first argument representing the object, which is provided implicitly by the call.
Often, the first argument of a method is called self. This is nothing more than a convention: the name self has absolutely no special meaning to Python. Note, however, that by not following the convention your code may be less readable to other Python programmers, and it is also conceivable that a class browser program might be written that relies upon such a convention.
For more information, see the Python documentation tutorial on classes.
As well as all the other reasons already stated, it allows for easier access to overridden methods; you can call Class.some_method(inst).
An example of where it’s useful:
class C1(object):
def __init__(self):
print "C1 init"
class C2(C1):
def __init__(self): #overrides C1.__init__
print "C2 init"
C1.__init__(self) #but we still want C1 to init the class too
>>> C2()
"C2 init"
"C1 init"
Its use is similar to the use of this keyword in Java, i.e. to give a reference to the current object.
Python is not a language built for Object Oriented Programming unlike Java or C++.
When calling a static method in Python, one simply writes a method with regular arguments inside it.
class Animal():
def staticMethod():
print "This is a static method"
However, an object method, which requires you to make a variable, which is an Animal, in this case, needs the self argument
class Animal():
def objectMethod(self):
print "This is an object method which needs an instance of a class"
The self method is also used to refer to a variable field within the class.
class Animal():
#animalName made in constructor
def Animal(self):
self.animalName = "";
def getAnimalName(self):
return self.animalName
In this case, self is referring to the animalName variable of the entire class. REMEMBER: If you have a variable within a method, self will not work. That variable is simply existent only while that method is running. For defining fields (the variables of the entire class), you have to define them OUTSIDE the class methods.
If you don't understand a single word of what I am saying, then Google "Object Oriented Programming." Once you understand this, you won't even need to ask that question :).
First of all, self is a conventional name, you could put anything else (being coherent) in its stead.
It refers to the object itself, so when you are using it, you are declaring that .name and .age are properties of the Student objects (note, not of the Student class) you are going to create.
class Student:
#called each time you create a new Student instance
def __init__(self,name,age): #special method to initialize
self.name=name
self.age=age
def __str__(self): #special method called for example when you use print
return "Student %s is %s years old" %(self.name,self.age)
def call(self, msg): #silly example for custom method
return ("Hey, %s! "+msg) %self.name
#initializing two instances of the student class
bob=Student("Bob",20)
alice=Student("Alice",19)
#using them
print bob.name
print bob.age
print alice #this one only works if you define the __str__ method
print alice.call("Come here!") #notice you don't put a value for self
#you can modify attributes, like when alice ages
alice.age=20
print alice
Code is here
self is an object reference to the object itself, therefore, they are same.
Python methods are not called in the context of the object itself.
self in Python may be used to deal with custom object models or something.
It’s there to follow the Python zen “explicit is better than implicit”. It’s indeed a reference to your class object. In Java and PHP, for example, it's called this.
If user_type_name is a field on your model you access it by self.user_type_name.
I'm surprised nobody has brought up Lua. Lua also uses the 'self' variable however it can be omitted but still used. C++ does the same with 'this'. I don't see any reason to have to declare 'self' in each function but you should still be able to use it just like you can with lua and C++. For a language that prides itself on being brief it's odd that it requires you to declare the self variable.
The use of the argument, conventionally called self isn't as hard to understand, as is why is it necessary? Or as to why explicitly mention it? That, I suppose, is a bigger question for most users who look up this question, or if it is not, they will certainly have the same question as they move forward learning python. I recommend them to read these couple of blogs:
1: Use of self explained
Note that it is not a keyword.
The first argument of every class method, including init, is always a reference to the current instance of the class. By convention, this argument is always named self. In the init method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called. For example the below code is the same as the above code.
2: Why do we have it this way and why can we not eliminate it as an argument, like Java, and have a keyword instead
Another thing I would like to add is, an optional self argument allows me to declare static methods inside a class, by not writing self.
Code examples:
class MyClass():
def staticMethod():
print "This is a static method"
def objectMethod(self):
print "This is an object method which needs an instance of a class, and that is what self refers to"
PS:This works only in Python 3.x.
In previous versions, you have to explicitly add #staticmethod decorator, otherwise self argument is obligatory.
Take a look at the following example, which clearly explains the purpose of self
class Restaurant(object):
bankrupt = False
def open_branch(self):
if not self.bankrupt:
print("branch opened")
#create instance1
>>> x = Restaurant()
>>> x.bankrupt
False
#create instance2
>>> y = Restaurant()
>>> y.bankrupt = True
>>> y.bankrupt
True
>>> x.bankrupt
False
self is used/needed to distinguish between instances.
Source: self variable in python explained - Pythontips
Is because by the way python is designed the alternatives would hardly work. Python is designed to allow methods or functions to be defined in a context where both implicit this (a-la Java/C++) or explicit # (a-la ruby) wouldn't work. Let's have an example with the explicit approach with python conventions:
def fubar(x):
self.x = x
class C:
frob = fubar
Now the fubar function wouldn't work since it would assume that self is a global variable (and in frob as well). The alternative would be to execute method's with a replaced global scope (where self is the object).
The implicit approach would be
def fubar(x)
myX = x
class C:
frob = fubar
This would mean that myX would be interpreted as a local variable in fubar (and in frob as well). The alternative here would be to execute methods with a replaced local scope which is retained between calls, but that would remove the posibility of method local variables.
However the current situation works out well:
def fubar(self, x)
self.x = x
class C:
frob = fubar
here when called as a method frob will receive the object on which it's called via the self parameter, and fubar can still be called with an object as parameter and work the same (it is the same as C.frob I think).
In the __init__ method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called.
self, as a name, is just a convention, call it as you want ! but when using it, for example to delete the object, you have to use the same name: __del__(var), where var was used in the __init__(var,[...])
You should take a look at cls too, to have the bigger picture. This post could be helpful.
self is acting as like current object name or instance of class .
# Self explanation.
class classname(object):
def __init__(self,name):
self.name=name
# Self is acting as a replacement of object name.
#self.name=object1.name
def display(self):
print("Name of the person is :",self.name)
print("object name:",object1.name)
object1=classname("Bucky")
object2=classname("ford")
object1.display()
object2.display()
###### Output
Name of the person is : Bucky
object name: Bucky
Name of the person is : ford
object name: Bucky
"self" keyword holds the reference of class and it is upto you if you want to use it or not but if you notice, whenever you create a new method in python, python automatically write self keyword for you. If you do some R&D, you will notice that if you create say two methods in a class and try to call one inside another, it does not recognize method unless you add self (reference of class).
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
self.m2()
def m2(self):
print('method 2')
Below code throws unresolvable reference error.
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
m2() #throws unresolvable reference error as class does not know if m2 exist in class scope
def m2(self):
print('method 2')
Now let see below example
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
def m2():
print('method 2')
Now when you create object of class testA, you can call method m1() using class object like this as method m1() has included self keyword
obj = testA()
obj.m1()
But if you want to call method m2(), because is has no self reference so you can call m2() directly using class name like below
testA.m2()
But keep in practice to live with self keyword as there are other benefits too of it like creating global variable inside and so on.
self is inevitable.
There was just a question should self be implicit or explicit.
Guido van Rossum resolved this question saying self has to stay.
So where the self live?
If we would just stick to functional programming we would not need self.
Once we enter the Python OOP we find self there.
Here is the typical use case class C with the method m1
class C:
def m1(self, arg):
print(self, ' inside')
pass
ci =C()
print(ci, ' outside')
ci.m1(None)
print(hex(id(ci))) # hex memory address
This program will output:
<__main__.C object at 0x000002B9D79C6CC0> outside
<__main__.C object at 0x000002B9D79C6CC0> inside
0x2b9d79c6cc0
So self holds the memory address of the class instance.
The purpose of self would be to hold the reference for instance methods and for us to have explicit access to that reference.
Note there are three different types of class methods:
static methods (read: functions),
class methods,
instance methods (mentioned).
The word 'self' refers to instance of a class
class foo:
def __init__(self, num1, num2):
self.n1 = num1 #now in this it will make the perimeter num1 and num2 access across the whole class
self.n2 = num2
def add(self):
return self.n1 + self.n2 # if we had not written self then if would throw an error that n1 and n2 is not defined and we have to include self in the function's perimeter to access it's variables
it's an explicit reference to the class instance object.
from the docs,
the special thing about methods is that the instance object is passed as the first argument of the function. In our example, the call x.f() is exactly equivalent to MyClass.f(x). In general, calling a method with a list of n arguments is equivalent to calling the corresponding function with an argument list that is created by inserting the method’s instance object before the first argument.
preceding this the related snippet,
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
x = MyClass()
I would say for Python at least, the self parameter can be thought of as a placeholder.
Take a look at this:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
p1 = Person("John", 36)
print(p1.name)
print(p1.age)
Self in this case and a lot of others was used as a method to say store the name value. However, after that, we use the p1 to assign it to the class we're using. Then when we print it we use the same p1 keyword.
Hope this helps for Python!
my little 2 cents
In this class Person, we defined out init method with the self and interesting thing to notice here is the memory location of both the self and instance variable p is same <__main__.Person object at 0x106a78fd0>
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def say_hi(self):
print("the self is at:", self)
print((f"hey there, my name is {self.name} and I am {self.age} years old"))
def say_bye(self):
print("the self is at:", self)
print(f"good to see you {self.name}")
p = Person("john", 78)
print("the p is at",p)
p.say_hi()
p.say_bye()
so as explained in above, both self and instance variable are same object.
Consider this example:
class MyClass:
def func(self, name):
self.name = name
I know that self refers to the specific instance of MyClass. But why must func explicitly include self as a parameter? Why do we need to use self in the method's code? Some other languages make this implicit, or use special syntax instead.
For a language-agnostic consideration of the design decision, see What is the advantage of having this/self pointer mandatory explicit?.
To close debugging questions where OP omitted a self parameter for a method and got a TypeError, use TypeError: method() takes 1 positional argument but 2 were given instead. If OP omitted self. in the body of the method and got a NameError, consider How can I call a function within a class?.
The reason you need to use self. is because Python does not use special syntax to refer to instance attributes. Python decided to do methods in a way that makes the instance to which the method belongs be passed automatically, but not received automatically: the first parameter of methods is the instance the method is called on. That makes methods entirely the same as functions, and leaves the actual name to use up to you (although self is the convention, and people will generally frown at you when you use something else.) self is not special to the code, it's just another object.
Python could have done something else to distinguish normal names from attributes -- special syntax like Ruby has, or requiring declarations like C++ and Java do, or perhaps something yet more different -- but it didn't. Python's all for making things explicit, making it obvious what's what, and although it doesn't do it entirely everywhere, it does do it for instance attributes. That's why assigning to an instance attribute needs to know what instance to assign to, and that's why it needs self..
Let's say you have a class ClassA which contains a method methodA defined as:
def methodA(self, arg1, arg2):
# do something
and objectA is an instance of this class.
Now when objectA.methodA(arg1, arg2) is called, python internally converts it for you as:
ClassA.methodA(objectA, arg1, arg2)
The self variable refers to the object itself.
Let’s take a simple vector class:
class Vector:
def __init__(self, x, y):
self.x = x
self.y = y
We want to have a method which calculates the length. What would it look like if we wanted to define it inside the class?
def length(self):
return math.sqrt(self.x ** 2 + self.y ** 2)
What should it look like when we were to define it as a global method/function?
def length_global(vector):
return math.sqrt(vector.x ** 2 + vector.y ** 2)
So the whole structure stays the same. How can me make use of this? If we assume for a moment that we hadn’t written a length method for our Vector class, we could do this:
Vector.length_new = length_global
v = Vector(3, 4)
print(v.length_new()) # 5.0
This works because the first parameter of length_global, can be re-used as the self parameter in length_new. This would not be possible without an explicit self.
Another way of understanding the need for the explicit self is to see where Python adds some syntactical sugar. When you keep in mind, that basically, a call like
v_instance.length()
is internally transformed to
Vector.length(v_instance)
it is easy to see where the self fits in. You don't actually write instance methods in Python; what you write is class methods which must take an instance as a first parameter. And therefore, you’ll have to place the instance parameter somewhere explicitly.
When objects are instantiated, the object itself is passed into the self parameter.
Because of this, the object’s data is bound to the object. Below is an example of how you might like to visualize what each object’s data might look. Notice how ‘self’ is replaced with the objects name. I'm not saying this example diagram below is wholly accurate but it hopefully with serve a purpose in visualizing the use of self.
The Object is passed into the self parameter so that the object can keep hold of its own data.
Although this may not be wholly accurate, think of the process of instantiating an object like this: When an object is made it uses the class as a template for its own data and methods. Without passing it's own name into the self parameter, the attributes and methods in the class would remain as a general template and would not be referenced to (belong to) the object. So by passing the object's name into the self parameter it means that if 100 objects are instantiated from the one class, they can all keep track of their own data and methods.
See the illustration below:
I like this example:
class A:
foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: [5]
class A:
def __init__(self):
self.foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: []
I will demonstrate with code that does not use classes:
def state_init(state):
state['field'] = 'init'
def state_add(state, x):
state['field'] += x
def state_mult(state, x):
state['field'] *= x
def state_getField(state):
return state['field']
myself = {}
state_init(myself)
state_add(myself, 'added')
state_mult(myself, 2)
print( state_getField(myself) )
#--> 'initaddedinitadded'
Classes are just a way to avoid passing in this "state" thing all the time (and other nice things like initializing, class composition, the rarely-needed metaclasses, and supporting custom methods to override operators).
Now let's demonstrate the above code using the built-in python class machinery, to show how it's basically the same thing.
class State(object):
def __init__(self):
self.field = 'init'
def add(self, x):
self.field += x
def mult(self, x):
self.field *= x
s = State()
s.add('added') # self is implicitly passed in
s.mult(2) # self is implicitly passed in
print( s.field )
[migrated my answer from duplicate closed question]
The following excerpts are from the Python documentation about self:
As in Modula-3, there are no shorthands [in Python] for referencing the object’s members from its methods: the method function is declared with an explicit first argument representing the object, which is provided implicitly by the call.
Often, the first argument of a method is called self. This is nothing more than a convention: the name self has absolutely no special meaning to Python. Note, however, that by not following the convention your code may be less readable to other Python programmers, and it is also conceivable that a class browser program might be written that relies upon such a convention.
For more information, see the Python documentation tutorial on classes.
As well as all the other reasons already stated, it allows for easier access to overridden methods; you can call Class.some_method(inst).
An example of where it’s useful:
class C1(object):
def __init__(self):
print "C1 init"
class C2(C1):
def __init__(self): #overrides C1.__init__
print "C2 init"
C1.__init__(self) #but we still want C1 to init the class too
>>> C2()
"C2 init"
"C1 init"
Its use is similar to the use of this keyword in Java, i.e. to give a reference to the current object.
Python is not a language built for Object Oriented Programming unlike Java or C++.
When calling a static method in Python, one simply writes a method with regular arguments inside it.
class Animal():
def staticMethod():
print "This is a static method"
However, an object method, which requires you to make a variable, which is an Animal, in this case, needs the self argument
class Animal():
def objectMethod(self):
print "This is an object method which needs an instance of a class"
The self method is also used to refer to a variable field within the class.
class Animal():
#animalName made in constructor
def Animal(self):
self.animalName = "";
def getAnimalName(self):
return self.animalName
In this case, self is referring to the animalName variable of the entire class. REMEMBER: If you have a variable within a method, self will not work. That variable is simply existent only while that method is running. For defining fields (the variables of the entire class), you have to define them OUTSIDE the class methods.
If you don't understand a single word of what I am saying, then Google "Object Oriented Programming." Once you understand this, you won't even need to ask that question :).
First of all, self is a conventional name, you could put anything else (being coherent) in its stead.
It refers to the object itself, so when you are using it, you are declaring that .name and .age are properties of the Student objects (note, not of the Student class) you are going to create.
class Student:
#called each time you create a new Student instance
def __init__(self,name,age): #special method to initialize
self.name=name
self.age=age
def __str__(self): #special method called for example when you use print
return "Student %s is %s years old" %(self.name,self.age)
def call(self, msg): #silly example for custom method
return ("Hey, %s! "+msg) %self.name
#initializing two instances of the student class
bob=Student("Bob",20)
alice=Student("Alice",19)
#using them
print bob.name
print bob.age
print alice #this one only works if you define the __str__ method
print alice.call("Come here!") #notice you don't put a value for self
#you can modify attributes, like when alice ages
alice.age=20
print alice
Code is here
self is an object reference to the object itself, therefore, they are same.
Python methods are not called in the context of the object itself.
self in Python may be used to deal with custom object models or something.
It’s there to follow the Python zen “explicit is better than implicit”. It’s indeed a reference to your class object. In Java and PHP, for example, it's called this.
If user_type_name is a field on your model you access it by self.user_type_name.
I'm surprised nobody has brought up Lua. Lua also uses the 'self' variable however it can be omitted but still used. C++ does the same with 'this'. I don't see any reason to have to declare 'self' in each function but you should still be able to use it just like you can with lua and C++. For a language that prides itself on being brief it's odd that it requires you to declare the self variable.
The use of the argument, conventionally called self isn't as hard to understand, as is why is it necessary? Or as to why explicitly mention it? That, I suppose, is a bigger question for most users who look up this question, or if it is not, they will certainly have the same question as they move forward learning python. I recommend them to read these couple of blogs:
1: Use of self explained
Note that it is not a keyword.
The first argument of every class method, including init, is always a reference to the current instance of the class. By convention, this argument is always named self. In the init method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called. For example the below code is the same as the above code.
2: Why do we have it this way and why can we not eliminate it as an argument, like Java, and have a keyword instead
Another thing I would like to add is, an optional self argument allows me to declare static methods inside a class, by not writing self.
Code examples:
class MyClass():
def staticMethod():
print "This is a static method"
def objectMethod(self):
print "This is an object method which needs an instance of a class, and that is what self refers to"
PS:This works only in Python 3.x.
In previous versions, you have to explicitly add #staticmethod decorator, otherwise self argument is obligatory.
Take a look at the following example, which clearly explains the purpose of self
class Restaurant(object):
bankrupt = False
def open_branch(self):
if not self.bankrupt:
print("branch opened")
#create instance1
>>> x = Restaurant()
>>> x.bankrupt
False
#create instance2
>>> y = Restaurant()
>>> y.bankrupt = True
>>> y.bankrupt
True
>>> x.bankrupt
False
self is used/needed to distinguish between instances.
Source: self variable in python explained - Pythontips
Is because by the way python is designed the alternatives would hardly work. Python is designed to allow methods or functions to be defined in a context where both implicit this (a-la Java/C++) or explicit # (a-la ruby) wouldn't work. Let's have an example with the explicit approach with python conventions:
def fubar(x):
self.x = x
class C:
frob = fubar
Now the fubar function wouldn't work since it would assume that self is a global variable (and in frob as well). The alternative would be to execute method's with a replaced global scope (where self is the object).
The implicit approach would be
def fubar(x)
myX = x
class C:
frob = fubar
This would mean that myX would be interpreted as a local variable in fubar (and in frob as well). The alternative here would be to execute methods with a replaced local scope which is retained between calls, but that would remove the posibility of method local variables.
However the current situation works out well:
def fubar(self, x)
self.x = x
class C:
frob = fubar
here when called as a method frob will receive the object on which it's called via the self parameter, and fubar can still be called with an object as parameter and work the same (it is the same as C.frob I think).
In the __init__ method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called.
self, as a name, is just a convention, call it as you want ! but when using it, for example to delete the object, you have to use the same name: __del__(var), where var was used in the __init__(var,[...])
You should take a look at cls too, to have the bigger picture. This post could be helpful.
self is acting as like current object name or instance of class .
# Self explanation.
class classname(object):
def __init__(self,name):
self.name=name
# Self is acting as a replacement of object name.
#self.name=object1.name
def display(self):
print("Name of the person is :",self.name)
print("object name:",object1.name)
object1=classname("Bucky")
object2=classname("ford")
object1.display()
object2.display()
###### Output
Name of the person is : Bucky
object name: Bucky
Name of the person is : ford
object name: Bucky
"self" keyword holds the reference of class and it is upto you if you want to use it or not but if you notice, whenever you create a new method in python, python automatically write self keyword for you. If you do some R&D, you will notice that if you create say two methods in a class and try to call one inside another, it does not recognize method unless you add self (reference of class).
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
self.m2()
def m2(self):
print('method 2')
Below code throws unresolvable reference error.
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
m2() #throws unresolvable reference error as class does not know if m2 exist in class scope
def m2(self):
print('method 2')
Now let see below example
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
def m2():
print('method 2')
Now when you create object of class testA, you can call method m1() using class object like this as method m1() has included self keyword
obj = testA()
obj.m1()
But if you want to call method m2(), because is has no self reference so you can call m2() directly using class name like below
testA.m2()
But keep in practice to live with self keyword as there are other benefits too of it like creating global variable inside and so on.
self is inevitable.
There was just a question should self be implicit or explicit.
Guido van Rossum resolved this question saying self has to stay.
So where the self live?
If we would just stick to functional programming we would not need self.
Once we enter the Python OOP we find self there.
Here is the typical use case class C with the method m1
class C:
def m1(self, arg):
print(self, ' inside')
pass
ci =C()
print(ci, ' outside')
ci.m1(None)
print(hex(id(ci))) # hex memory address
This program will output:
<__main__.C object at 0x000002B9D79C6CC0> outside
<__main__.C object at 0x000002B9D79C6CC0> inside
0x2b9d79c6cc0
So self holds the memory address of the class instance.
The purpose of self would be to hold the reference for instance methods and for us to have explicit access to that reference.
Note there are three different types of class methods:
static methods (read: functions),
class methods,
instance methods (mentioned).
The word 'self' refers to instance of a class
class foo:
def __init__(self, num1, num2):
self.n1 = num1 #now in this it will make the perimeter num1 and num2 access across the whole class
self.n2 = num2
def add(self):
return self.n1 + self.n2 # if we had not written self then if would throw an error that n1 and n2 is not defined and we have to include self in the function's perimeter to access it's variables
it's an explicit reference to the class instance object.
from the docs,
the special thing about methods is that the instance object is passed as the first argument of the function. In our example, the call x.f() is exactly equivalent to MyClass.f(x). In general, calling a method with a list of n arguments is equivalent to calling the corresponding function with an argument list that is created by inserting the method’s instance object before the first argument.
preceding this the related snippet,
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
x = MyClass()
I would say for Python at least, the self parameter can be thought of as a placeholder.
Take a look at this:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
p1 = Person("John", 36)
print(p1.name)
print(p1.age)
Self in this case and a lot of others was used as a method to say store the name value. However, after that, we use the p1 to assign it to the class we're using. Then when we print it we use the same p1 keyword.
Hope this helps for Python!
my little 2 cents
In this class Person, we defined out init method with the self and interesting thing to notice here is the memory location of both the self and instance variable p is same <__main__.Person object at 0x106a78fd0>
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def say_hi(self):
print("the self is at:", self)
print((f"hey there, my name is {self.name} and I am {self.age} years old"))
def say_bye(self):
print("the self is at:", self)
print(f"good to see you {self.name}")
p = Person("john", 78)
print("the p is at",p)
p.say_hi()
p.say_bye()
so as explained in above, both self and instance variable are same object.
Consider this example:
class MyClass:
def func(self, name):
self.name = name
I know that self refers to the specific instance of MyClass. But why must func explicitly include self as a parameter? Why do we need to use self in the method's code? Some other languages make this implicit, or use special syntax instead.
For a language-agnostic consideration of the design decision, see What is the advantage of having this/self pointer mandatory explicit?.
To close debugging questions where OP omitted a self parameter for a method and got a TypeError, use TypeError: method() takes 1 positional argument but 2 were given instead. If OP omitted self. in the body of the method and got a NameError, consider How can I call a function within a class?.
The reason you need to use self. is because Python does not use special syntax to refer to instance attributes. Python decided to do methods in a way that makes the instance to which the method belongs be passed automatically, but not received automatically: the first parameter of methods is the instance the method is called on. That makes methods entirely the same as functions, and leaves the actual name to use up to you (although self is the convention, and people will generally frown at you when you use something else.) self is not special to the code, it's just another object.
Python could have done something else to distinguish normal names from attributes -- special syntax like Ruby has, or requiring declarations like C++ and Java do, or perhaps something yet more different -- but it didn't. Python's all for making things explicit, making it obvious what's what, and although it doesn't do it entirely everywhere, it does do it for instance attributes. That's why assigning to an instance attribute needs to know what instance to assign to, and that's why it needs self..
Let's say you have a class ClassA which contains a method methodA defined as:
def methodA(self, arg1, arg2):
# do something
and objectA is an instance of this class.
Now when objectA.methodA(arg1, arg2) is called, python internally converts it for you as:
ClassA.methodA(objectA, arg1, arg2)
The self variable refers to the object itself.
Let’s take a simple vector class:
class Vector:
def __init__(self, x, y):
self.x = x
self.y = y
We want to have a method which calculates the length. What would it look like if we wanted to define it inside the class?
def length(self):
return math.sqrt(self.x ** 2 + self.y ** 2)
What should it look like when we were to define it as a global method/function?
def length_global(vector):
return math.sqrt(vector.x ** 2 + vector.y ** 2)
So the whole structure stays the same. How can me make use of this? If we assume for a moment that we hadn’t written a length method for our Vector class, we could do this:
Vector.length_new = length_global
v = Vector(3, 4)
print(v.length_new()) # 5.0
This works because the first parameter of length_global, can be re-used as the self parameter in length_new. This would not be possible without an explicit self.
Another way of understanding the need for the explicit self is to see where Python adds some syntactical sugar. When you keep in mind, that basically, a call like
v_instance.length()
is internally transformed to
Vector.length(v_instance)
it is easy to see where the self fits in. You don't actually write instance methods in Python; what you write is class methods which must take an instance as a first parameter. And therefore, you’ll have to place the instance parameter somewhere explicitly.
When objects are instantiated, the object itself is passed into the self parameter.
Because of this, the object’s data is bound to the object. Below is an example of how you might like to visualize what each object’s data might look. Notice how ‘self’ is replaced with the objects name. I'm not saying this example diagram below is wholly accurate but it hopefully with serve a purpose in visualizing the use of self.
The Object is passed into the self parameter so that the object can keep hold of its own data.
Although this may not be wholly accurate, think of the process of instantiating an object like this: When an object is made it uses the class as a template for its own data and methods. Without passing it's own name into the self parameter, the attributes and methods in the class would remain as a general template and would not be referenced to (belong to) the object. So by passing the object's name into the self parameter it means that if 100 objects are instantiated from the one class, they can all keep track of their own data and methods.
See the illustration below:
I like this example:
class A:
foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: [5]
class A:
def __init__(self):
self.foo = []
a, b = A(), A()
a.foo.append(5)
b.foo
ans: []
I will demonstrate with code that does not use classes:
def state_init(state):
state['field'] = 'init'
def state_add(state, x):
state['field'] += x
def state_mult(state, x):
state['field'] *= x
def state_getField(state):
return state['field']
myself = {}
state_init(myself)
state_add(myself, 'added')
state_mult(myself, 2)
print( state_getField(myself) )
#--> 'initaddedinitadded'
Classes are just a way to avoid passing in this "state" thing all the time (and other nice things like initializing, class composition, the rarely-needed metaclasses, and supporting custom methods to override operators).
Now let's demonstrate the above code using the built-in python class machinery, to show how it's basically the same thing.
class State(object):
def __init__(self):
self.field = 'init'
def add(self, x):
self.field += x
def mult(self, x):
self.field *= x
s = State()
s.add('added') # self is implicitly passed in
s.mult(2) # self is implicitly passed in
print( s.field )
[migrated my answer from duplicate closed question]
The following excerpts are from the Python documentation about self:
As in Modula-3, there are no shorthands [in Python] for referencing the object’s members from its methods: the method function is declared with an explicit first argument representing the object, which is provided implicitly by the call.
Often, the first argument of a method is called self. This is nothing more than a convention: the name self has absolutely no special meaning to Python. Note, however, that by not following the convention your code may be less readable to other Python programmers, and it is also conceivable that a class browser program might be written that relies upon such a convention.
For more information, see the Python documentation tutorial on classes.
As well as all the other reasons already stated, it allows for easier access to overridden methods; you can call Class.some_method(inst).
An example of where it’s useful:
class C1(object):
def __init__(self):
print "C1 init"
class C2(C1):
def __init__(self): #overrides C1.__init__
print "C2 init"
C1.__init__(self) #but we still want C1 to init the class too
>>> C2()
"C2 init"
"C1 init"
Its use is similar to the use of this keyword in Java, i.e. to give a reference to the current object.
Python is not a language built for Object Oriented Programming unlike Java or C++.
When calling a static method in Python, one simply writes a method with regular arguments inside it.
class Animal():
def staticMethod():
print "This is a static method"
However, an object method, which requires you to make a variable, which is an Animal, in this case, needs the self argument
class Animal():
def objectMethod(self):
print "This is an object method which needs an instance of a class"
The self method is also used to refer to a variable field within the class.
class Animal():
#animalName made in constructor
def Animal(self):
self.animalName = "";
def getAnimalName(self):
return self.animalName
In this case, self is referring to the animalName variable of the entire class. REMEMBER: If you have a variable within a method, self will not work. That variable is simply existent only while that method is running. For defining fields (the variables of the entire class), you have to define them OUTSIDE the class methods.
If you don't understand a single word of what I am saying, then Google "Object Oriented Programming." Once you understand this, you won't even need to ask that question :).
First of all, self is a conventional name, you could put anything else (being coherent) in its stead.
It refers to the object itself, so when you are using it, you are declaring that .name and .age are properties of the Student objects (note, not of the Student class) you are going to create.
class Student:
#called each time you create a new Student instance
def __init__(self,name,age): #special method to initialize
self.name=name
self.age=age
def __str__(self): #special method called for example when you use print
return "Student %s is %s years old" %(self.name,self.age)
def call(self, msg): #silly example for custom method
return ("Hey, %s! "+msg) %self.name
#initializing two instances of the student class
bob=Student("Bob",20)
alice=Student("Alice",19)
#using them
print bob.name
print bob.age
print alice #this one only works if you define the __str__ method
print alice.call("Come here!") #notice you don't put a value for self
#you can modify attributes, like when alice ages
alice.age=20
print alice
Code is here
self is an object reference to the object itself, therefore, they are same.
Python methods are not called in the context of the object itself.
self in Python may be used to deal with custom object models or something.
It’s there to follow the Python zen “explicit is better than implicit”. It’s indeed a reference to your class object. In Java and PHP, for example, it's called this.
If user_type_name is a field on your model you access it by self.user_type_name.
I'm surprised nobody has brought up Lua. Lua also uses the 'self' variable however it can be omitted but still used. C++ does the same with 'this'. I don't see any reason to have to declare 'self' in each function but you should still be able to use it just like you can with lua and C++. For a language that prides itself on being brief it's odd that it requires you to declare the self variable.
The use of the argument, conventionally called self isn't as hard to understand, as is why is it necessary? Or as to why explicitly mention it? That, I suppose, is a bigger question for most users who look up this question, or if it is not, they will certainly have the same question as they move forward learning python. I recommend them to read these couple of blogs:
1: Use of self explained
Note that it is not a keyword.
The first argument of every class method, including init, is always a reference to the current instance of the class. By convention, this argument is always named self. In the init method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called. For example the below code is the same as the above code.
2: Why do we have it this way and why can we not eliminate it as an argument, like Java, and have a keyword instead
Another thing I would like to add is, an optional self argument allows me to declare static methods inside a class, by not writing self.
Code examples:
class MyClass():
def staticMethod():
print "This is a static method"
def objectMethod(self):
print "This is an object method which needs an instance of a class, and that is what self refers to"
PS:This works only in Python 3.x.
In previous versions, you have to explicitly add #staticmethod decorator, otherwise self argument is obligatory.
Take a look at the following example, which clearly explains the purpose of self
class Restaurant(object):
bankrupt = False
def open_branch(self):
if not self.bankrupt:
print("branch opened")
#create instance1
>>> x = Restaurant()
>>> x.bankrupt
False
#create instance2
>>> y = Restaurant()
>>> y.bankrupt = True
>>> y.bankrupt
True
>>> x.bankrupt
False
self is used/needed to distinguish between instances.
Source: self variable in python explained - Pythontips
Is because by the way python is designed the alternatives would hardly work. Python is designed to allow methods or functions to be defined in a context where both implicit this (a-la Java/C++) or explicit # (a-la ruby) wouldn't work. Let's have an example with the explicit approach with python conventions:
def fubar(x):
self.x = x
class C:
frob = fubar
Now the fubar function wouldn't work since it would assume that self is a global variable (and in frob as well). The alternative would be to execute method's with a replaced global scope (where self is the object).
The implicit approach would be
def fubar(x)
myX = x
class C:
frob = fubar
This would mean that myX would be interpreted as a local variable in fubar (and in frob as well). The alternative here would be to execute methods with a replaced local scope which is retained between calls, but that would remove the posibility of method local variables.
However the current situation works out well:
def fubar(self, x)
self.x = x
class C:
frob = fubar
here when called as a method frob will receive the object on which it's called via the self parameter, and fubar can still be called with an object as parameter and work the same (it is the same as C.frob I think).
In the __init__ method, self refers to the newly created object; in other class methods, it refers to the instance whose method was called.
self, as a name, is just a convention, call it as you want ! but when using it, for example to delete the object, you have to use the same name: __del__(var), where var was used in the __init__(var,[...])
You should take a look at cls too, to have the bigger picture. This post could be helpful.
self is acting as like current object name or instance of class .
# Self explanation.
class classname(object):
def __init__(self,name):
self.name=name
# Self is acting as a replacement of object name.
#self.name=object1.name
def display(self):
print("Name of the person is :",self.name)
print("object name:",object1.name)
object1=classname("Bucky")
object2=classname("ford")
object1.display()
object2.display()
###### Output
Name of the person is : Bucky
object name: Bucky
Name of the person is : ford
object name: Bucky
"self" keyword holds the reference of class and it is upto you if you want to use it or not but if you notice, whenever you create a new method in python, python automatically write self keyword for you. If you do some R&D, you will notice that if you create say two methods in a class and try to call one inside another, it does not recognize method unless you add self (reference of class).
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
self.m2()
def m2(self):
print('method 2')
Below code throws unresolvable reference error.
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
m2() #throws unresolvable reference error as class does not know if m2 exist in class scope
def m2(self):
print('method 2')
Now let see below example
class testA:
def __init__(self):
print('ads')
def m1(self):
print('method 1')
def m2():
print('method 2')
Now when you create object of class testA, you can call method m1() using class object like this as method m1() has included self keyword
obj = testA()
obj.m1()
But if you want to call method m2(), because is has no self reference so you can call m2() directly using class name like below
testA.m2()
But keep in practice to live with self keyword as there are other benefits too of it like creating global variable inside and so on.
self is inevitable.
There was just a question should self be implicit or explicit.
Guido van Rossum resolved this question saying self has to stay.
So where the self live?
If we would just stick to functional programming we would not need self.
Once we enter the Python OOP we find self there.
Here is the typical use case class C with the method m1
class C:
def m1(self, arg):
print(self, ' inside')
pass
ci =C()
print(ci, ' outside')
ci.m1(None)
print(hex(id(ci))) # hex memory address
This program will output:
<__main__.C object at 0x000002B9D79C6CC0> outside
<__main__.C object at 0x000002B9D79C6CC0> inside
0x2b9d79c6cc0
So self holds the memory address of the class instance.
The purpose of self would be to hold the reference for instance methods and for us to have explicit access to that reference.
Note there are three different types of class methods:
static methods (read: functions),
class methods,
instance methods (mentioned).
The word 'self' refers to instance of a class
class foo:
def __init__(self, num1, num2):
self.n1 = num1 #now in this it will make the perimeter num1 and num2 access across the whole class
self.n2 = num2
def add(self):
return self.n1 + self.n2 # if we had not written self then if would throw an error that n1 and n2 is not defined and we have to include self in the function's perimeter to access it's variables
it's an explicit reference to the class instance object.
from the docs,
the special thing about methods is that the instance object is passed as the first argument of the function. In our example, the call x.f() is exactly equivalent to MyClass.f(x). In general, calling a method with a list of n arguments is equivalent to calling the corresponding function with an argument list that is created by inserting the method’s instance object before the first argument.
preceding this the related snippet,
class MyClass:
"""A simple example class"""
i = 12345
def f(self):
return 'hello world'
x = MyClass()
I would say for Python at least, the self parameter can be thought of as a placeholder.
Take a look at this:
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
p1 = Person("John", 36)
print(p1.name)
print(p1.age)
Self in this case and a lot of others was used as a method to say store the name value. However, after that, we use the p1 to assign it to the class we're using. Then when we print it we use the same p1 keyword.
Hope this helps for Python!
my little 2 cents
In this class Person, we defined out init method with the self and interesting thing to notice here is the memory location of both the self and instance variable p is same <__main__.Person object at 0x106a78fd0>
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def say_hi(self):
print("the self is at:", self)
print((f"hey there, my name is {self.name} and I am {self.age} years old"))
def say_bye(self):
print("the self is at:", self)
print(f"good to see you {self.name}")
p = Person("john", 78)
print("the p is at",p)
p.say_hi()
p.say_bye()
so as explained in above, both self and instance variable are same object.
Let me start off by saying that I understand how slots and metaclasses work in Python. Playing around with the two, I've run into an interesting problem. Here's a minimal example:
def decorator(cls):
dct = dict(cls.__dict__)
dct['__slots__'] = ('y',)
return type('NewClass', cls.__bases__, dct)
#decorator
class A(object):
__slots__= ('x',)
def __init__(self):
self.x = 'xx'
A()
This produces the following exception:
Traceback (most recent call last):
File "p.py", line 12, in <module>
A()
File "p.py", line 10, in __init__
self.x = 'xx'
TypeError: descriptor 'x' for 'A' objects doesn't apply to 'NewClass' object
Now, I know why this happens: the descriptor created for the slot x must be able to reference the reserved space for the slot. Only instances of class A, or instances of subclasses of A, have this reserved space, and therefore only those instances can use the descriptor x. In the above example, the metaclass creates a new type that is a sublcass of A's base classes, but not of A itself, so we get the exception. Simple enough.
Of course, in this simple example, either of the following two definitions of decorator will work around the problem:
def decorator(cls):
dct = dict(cls.__dict__)
dct['__slots__'] = ('y',)
return type('NewClass', (cls,) + cls.__bases__, dct)
def decorator(cls):
class NewClass(cls):
__slots__ = ('y',)
return NewClass
But these work-arounds aren't exactly he same as the original, as they both add A as a base class. They can fail in a more complicated set up. For example, if the inheritance tree is more complicated, you might run into the following exception: TypeError: multiple bases have instance lay-out conflict.
So my very specific question is:
Is there are way to create a new class, via a call to type, that modifies the __slots__ attribute of an existing class, but does not add the existing class as a base class of the new class?
Edit:
I know that strict metaclasses are another work around for my examples above. There are lots of ways to to make the minimal examples work, but my question is about creating a class via new that is based on an existing class, not about how to make the examples work. Sorry for the confusion.
Edit 2:
Discussion in the comments has led me a more precise question than what I originally asked:
Is it possible to create a class, via a call to type, that uses the slots and descriptors of an existing class without being a descendant of that class?
If the answer is "no", I'd appreciate a source as to why not.
No, unfortunately there is no way to do anything with the __slots__ after the class is created (and that's when the decorators on them are called). The only way is to use a metaclass, and modify/add __slots__ before calling the type.__new__.
An example of such a metaclass:
class MetaA(type):
def __new__(mcls, name, bases, dct):
slots = set(dct.get('__slots__', ()))
slots.add('y')
dct['__slots__'] = tuple(slots)
return super().__new__(mcls, name, bases, dct)
class BaseA(metaclass=MetaA):
pass
class A(BaseA):
__slots__ = ('x',)
def __init__(self):
self.x = 1
self.y = 2
print(A().x, A().y)
Without metaclasses, you can do some magic and copy everything from the defined class and create a new one on the fly, but that code smells ;)
def decorator(cls):
slots = set(cls.__slots__)
slots.add('y')
dct = cls.__dict__.copy()
for name in cls.__slots__:
dct.pop(name)
dct['__slots__'] = tuple(slots)
return type(cls)(cls.__name__, cls.__bases__, dct)
#decorator
class A:
__slots__ = ('x',)
def __init__(self):
self.x = self.y = 42
print(A().x, A().y)
The main disadvantage of such code, is that if someone applies another decorator, before yours one, and, let's say, creates a reference to the decorated class somewhere, then they will end up storing reference to a different class. Same for metaclasses - they will execute twice. So, the metaclass approach is better, since there are no side-effects.
The definitive answer of why you can't really change __slots__ after the class is created depends on implementation details of the python interpreter you're working with. For instance, in CPython, for each slot you defined, class has a descriptor (see PyMemberDescr_Type & PyMemberDef struct in CPython source code), that has an offset parameter of where the slot value is aligned in internal object storage. And you simply have no instruments of manipulating such things in public Python API. You trade flexibility for less memory usage (again, in CPython, as in PyPy you get the same memory effect automatically for all your classes).
If modification of __slots__ is absolutely required, you can, probably, write a C extension (or work with ctypes) and do it, but that's hardly a reliable solution.
You can do that with metaclasses:
class MetaSlot(type):
def __new__(mcs, name, bases, dic):
dic['__slots__'] += ('y',)
return type.__new__(mcs, name, bases, dic)
class C(metaclass=MetaSlot): # Python 3 syntax
__slots__ = ('x',)
Now both x and y can be used:
>>> c = C()
>>> c.y = 10
>>> c.x = 10
Is there a reasonable way in Python to implement mixin behavior similar to that found in Ruby -- that is, without using inheritance?
class Mixin(object):
def b(self): print "b()"
def c(self): print "c()"
class Foo(object):
# Somehow mix in the behavior of the Mixin class,
# so that all of the methods below will run and
# the issubclass() test will be False.
def a(self): print "a()"
f = Foo()
f.a()
f.b()
f.c()
print issubclass(Foo, Mixin)
I had a vague idea to do this with a class decorator, but my attempts led to confusion. Most of my searches on the topic have led in the direction of using inheritance (or in more complex scenarios, multiple inheritance) to achieve mixin behavior.
def mixer(*args):
"""Decorator for mixing mixins"""
def inner(cls):
for a,k in ((a,k) for a in args for k,v in vars(a).items() if callable(v)):
setattr(cls, k, getattr(a, k).im_func)
return cls
return inner
class Mixin(object):
def b(self): print "b()"
def c(self): print "c()"
class Mixin2(object):
def d(self): print "d()"
def e(self): print "e()"
#mixer(Mixin, Mixin2)
class Foo(object):
# Somehow mix in the behavior of the Mixin class,
# so that all of the methods below will run and
# the issubclass() test will be False.
def a(self): print "a()"
f = Foo()
f.a()
f.b()
f.c()
f.d()
f.e()
print issubclass(Foo, Mixin)
output:
a()
b()
c()
d()
e()
False
You can add the methods as functions:
Foo.b = Mixin.b.im_func
Foo.c = Mixin.c.im_func
I am not that familiar with Python, but from what I know about Python metaprogramming, you could actually do it pretty much the same way it is done in Ruby.
In Ruby, a module basically consists of two things: a pointer to a method dictionary and a pointer to a constant dictionary. A class consists of three things: a pointer to a method dictionary, a pointer to a constant dictionary and a pointer to the superclass.
When you mix in a module M into a class C, the following happens:
an anonymous class α is created (this is called an include class)
α's method dictionary and constant dictionary pointers are set equal to M's
α's superclass pointer is set equal to C's
C's superclass pointer is set to α
In other words: a fake class which shares its behavior with the mixin is injected into the inheritance hierarchy. So, Ruby actually does use inheritance for mixin composition.
I left out a couple of subleties above: first off, the module doesn't actually get inserted as C's superclass, it gets inserted as C's superclasses' (which is C's singleton class) superclass. And secondly, if the mixin itself has mixed in other mixins, then those also get wrapped into fake classes which get inserted directly above α, and this process is applied recursively, in case the mixed in mixins in turn have mixins.
Basically, the whole mixin hierarchy gets flattened into a straight line and spliced into the inheritance chain.
AFAIK, Python actually allows you to change a class's superclass(es) after the fact (something which Ruby does not allow you to do), and it also gives you access to a class's dict (again, something that is impossible in Ruby), so you should be able to implement this yourself.
EDIT: Fixed what could (and probably should) be construed as a bug. Now it builds a new dict and then updates that from the class's dict. This prevents mixins from overwriting methods that are defined directly on the class. The code is still untested but should work. I'm busy ATM so I'll test it later. It worked fine except for a syntax error. In retrospect, I decided that I don't like it (even after my further improvements) and much prefer my other solution even if it is more complicated. The test code for that one applies here as well but I wont duplicate it.
You could use a metaclass factory:
import inspect
def add_mixins(*mixins):
Dummy = type('Dummy', mixins, {})
d = {}
for mixin in reversed(inspect.getmro(Dummy)):
d.update(mixin.__dict__)
class WithMixins(type):
def __new__(meta, classname, bases, classdict):
d.update(classdict)
return super(WithMixins, meta).__new__(meta, classname, bases, d)
return WithMixins
then use it like:
class Foo(object):
__metaclass__ = add_mixins(Mixin1, Mixin2)
# rest of the stuff
This one is based on the way it's done in ruby as explained by Jörg W Mittag. All of the wall of code after if __name__=='__main__' is test/demo code. There's actually only 13 lines of real code to it.
import inspect
def add_mixins(*mixins):
Dummy = type('Dummy', mixins, {})
d = {}
# Now get all the class attributes. Use reversed so that conflicts
# are resolved with the proper priority. This rules out the possibility
# of the mixins calling methods from their base classes that get overridden
# using super but is necessary for the subclass check to fail. If that wasn't a
# requirement, we would just use Dummy above (or use MI directly and
# forget all the metaclass stuff).
for base in reversed(inspect.getmro(Dummy)):
d.update(base.__dict__)
# Create the mixin class. This should be equivalent to creating the
# anonymous class in Ruby.
Mixin = type('Mixin', (object,), d)
class WithMixins(type):
def __new__(meta, classname, bases, classdict):
# The check below prevents an inheritance cycle from forming which
# leads to a TypeError when trying to inherit from the resulting
# class.
if not any(issubclass(base, Mixin) for base in bases):
# This should be the the equivalent of setting the superclass
# pointers in Ruby.
bases = (Mixin,) + bases
return super(WithMixins, meta).__new__(meta, classname, bases,
classdict)
return WithMixins
if __name__ == '__main__':
class Mixin1(object):
def b(self): print "b()"
def c(self): print "c()"
class Mixin2(object):
def d(self): print "d()"
def e(self): print "e()"
class Mixin3Base(object):
def f(self): print "f()"
class Mixin3(Mixin3Base): pass
class Foo(object):
__metaclass__ = add_mixins(Mixin1, Mixin2, Mixin3)
def a(self): print "a()"
class Bar(Foo):
def f(self): print "Bar.f()"
def test_class(cls):
print "Testing {0}".format(cls.__name__)
f = cls()
f.a()
f.b()
f.c()
f.d()
f.e()
f.f()
print (issubclass(cls, Mixin1) or
issubclass(cls, Mixin2) or
issubclass(cls, Mixin3))
test_class(Foo)
test_class(Bar)
You could decorate the classes __getattr__ to check in the mixin. The problem is that all methods of the mixin would always require an object the type of the mixin as their first parameter, so you would have to decorate __init__ as well to create a mixin-object. I believe you could achieve this using a class decorator.
from functools import partial
class Mixin(object):
#staticmethod
def b(self): print "b()"
#staticmethod
def c(self): print "c()"
class Foo(object):
def __init__(self, mixin_cls):
self.delegate_cls = mixin_cls
def __getattr__(self, attr):
if hasattr(self.delegate_cls, attr):
return partial(getattr(self.delegate_cls, attr), self)
def a(self): print "a()"
f = Foo(Mixin)
f.a()
f.b()
f.c()
print issubclass(Foo, Mixin)
This basically uses the Mixin class as a container to hold ad-hoc functions (not methods) that behave like methods by taking an object instance (self) as the first argument. __getattr__ will redirect missing calls to these methods-alike functions.
This passes your simple tests as shown below. But I cannot guarantee it will do all the things you want. Make more thorough test to make sure.
$ python mixin.py
a()
b()
c()
False
Composition? It seems like that would be the simplest way to handle this: either wrap your object in a decorator or just import the methods as an object into your class definition itself. This is what I usually do: put the methods that I want to share between classes in a file and then import the file. If I want to override some behavior I import a modified file with the same method names as the same object name. It's a little sloppy, but it works.
For example, if I want the init_covers behavior from this file (bedg.py)
import cove as cov
def init_covers(n):
n.covers.append(cov.Cover((set([n.id]))))
id_list = []
for a in n.neighbors:
id_list.append(a.id)
n.covers.append(cov.Cover((set(id_list))))
def update_degree(n):
for a in n.covers:
a.degree = 0
for b in n.covers:
if a != b:
a.degree += len(a.node_list.intersection(b.node_list))
In my bar class file I would do: import bedg as foo
and then if I want to change my foo behaviors in another class that inherited bar, I write
import bild as foo
Like I say, it is sloppy.