I was looking through some of the Django source code and came across this. What exactly does: encoding = property(lambda self: self.file.encoding) do?
There's nothing wrong with the other two answers, but they might be a little high-level. So here's the 101 version:
lambda
Although it's in their documentation for C#, I think Microsoft actually has the best explanation of the concept of lambda:
A lambda expression is an anonymous function that can contain
expressions and statements
Most people without an official CS degree trip over lambda, but when you think of it as simply an "anonymous function", I think it becomes much easier to understand. The format for lambda in Python is:
lambda [argument]: [expression]
Where [argument] can be nothing, a single argument or a comma-delimited list of arguments and [expression] is essentially the method body. That's why #Jordan said the code you mentioned is roughly the equivalent of:
def encoding(self):
return self.file.encoding
self is the argument passed into the method and the return value of the method (self.file.encoding) is the expression.
property
The property method allows you to create "getters" and "setters", basically, for an attribute on a class. In traditional OOP, "members", or the attributes of a class, are usually set as protected or private -- you never actually access the attribute directly. Instead, you access methods that in turn retrieve or manipulate the attribute. Chief among those would get the getter and the setter. As their names pretty much describe, they are methods that get and set the value of an attribute, respectively.
Now, Python OOP doesn't really have a concept of protected or private attributes in the truest sense. You are free to follow the rules, but there's nothing stopping you from accessing anything you want on a class. So, getters and setters are most normally, in Python, used in conjunction with property to "fake" an attribute, for lack of a better word. For example:
def get_foo(self):
return self.bar
def set_foo(self, value):
self.bar = value
foo = property(get_foo, set_foo)
With that I can now do things like instance.foo (no parenthesis) and instance.foo = 'something'. And it works just as if foo was a regular attribute on the class.
In the code you mention, they're only setting a getter, but it works the same. encoding will act like an attribute on the class and returns the value of file.encoding.
It's basically shorthand for a fullblown wrapped getter. Expanded would look something like this, although it's not a true 1-1 expansion.
def encoding(self):
return self.file.encoding
It is a property that proxies access from the containing class to it's file.encoding attribute.
Related
This question already has answers here:
What is the purpose of the `self` parameter? Why is it needed?
(26 answers)
Closed 6 months ago.
When defining a method on a class in Python, it looks something like this:
class MyClass(object):
def __init__(self, x, y):
self.x = x
self.y = y
But in some other languages, such as C#, you have a reference to the object that the method is bound to with the "this" keyword without declaring it as an argument in the method prototype.
Was this an intentional language design decision in Python or are there some implementation details that require the passing of "self" as an argument?
I like to quote Peters' Zen of Python. "Explicit is better than implicit."
In Java and C++, 'this.' can be deduced, except when you have variable names that make it impossible to deduce. So you sometimes need it and sometimes don't.
Python elects to make things like this explicit rather than based on a rule.
Additionally, since nothing is implied or assumed, parts of the implementation are exposed. self.__class__, self.__dict__ and other "internal" structures are available in an obvious way.
It's to minimize the difference between methods and functions. It allows you to easily generate methods in metaclasses, or add methods at runtime to pre-existing classes.
e.g.
>>> class C:
... def foo(self):
... print("Hi!")
...
>>>
>>> def bar(self):
... print("Bork bork bork!")
...
>>>
>>> c = C()
>>> C.bar = bar
>>> c.bar()
Bork bork bork!
>>> c.foo()
Hi!
>>>
It also (as far as I know) makes the implementation of the python runtime easier.
I suggest that one should read Guido van Rossum's blog on this topic - Why explicit self has to stay.
When a method definition is decorated, we don't know whether to automatically give it a 'self' parameter or not: the decorator could turn the function into a static method (which has no 'self'), or a class method (which has a funny kind of self that refers to a class instead of an instance), or it could do something completely different (it's trivial to write a decorator that implements '#classmethod' or '#staticmethod' in pure Python). There's no way without knowing what the decorator does whether to endow the method being defined with an implicit 'self' argument or not.
I reject hacks like special-casing '#classmethod' and '#staticmethod'.
Python doesn't force you on using "self". You can give it whatever name you want. You just have to remember that the first argument in a method definition header is a reference to the object.
Also allows you to do this: (in short, invoking Outer(3).create_inner_class(4)().weird_sum_with_closure_scope(5) will return 12, but will do so in the craziest of ways.
class Outer(object):
def __init__(self, outer_num):
self.outer_num = outer_num
def create_inner_class(outer_self, inner_arg):
class Inner(object):
inner_arg = inner_arg
def weird_sum_with_closure_scope(inner_self, num)
return num + outer_self.outer_num + inner_arg
return Inner
Of course, this is harder to imagine in languages like Java and C#. By making the self reference explicit, you're free to refer to any object by that self reference. Also, such a way of playing with classes at runtime is harder to do in the more static languages - not that's it's necessarily good or bad. It's just that the explicit self allows all this craziness to exist.
Moreover, imagine this: We'd like to customize the behavior of methods (for profiling, or some crazy black magic). This can lead us to think: what if we had a class Method whose behavior we could override or control?
Well here it is:
from functools import partial
class MagicMethod(object):
"""Does black magic when called"""
def __get__(self, obj, obj_type):
# This binds the <other> class instance to the <innocent_self> parameter
# of the method MagicMethod.invoke
return partial(self.invoke, obj)
def invoke(magic_self, innocent_self, *args, **kwargs):
# do black magic here
...
print magic_self, innocent_self, args, kwargs
class InnocentClass(object):
magic_method = MagicMethod()
And now: InnocentClass().magic_method() will act like expected. The method will be bound with the innocent_self parameter to InnocentClass, and with the magic_self to the MagicMethod instance. Weird huh? It's like having 2 keywords this1 and this2 in languages like Java and C#. Magic like this allows frameworks to do stuff that would otherwise be much more verbose.
Again, I don't want to comment on the ethics of this stuff. I just wanted to show things that would be harder to do without an explicit self reference.
I think it has to do with PEP 227:
Names in class scope are not accessible. Names are resolved in the
innermost enclosing function scope. If a class definition occurs in a
chain of nested scopes, the resolution process skips class
definitions. This rule prevents odd interactions between class
attributes and local variable access. If a name binding operation
occurs in a class definition, it creates an attribute on the resulting
class object. To access this variable in a method, or in a function
nested within a method, an attribute reference must be used, either
via self or via the class name.
I think the real reason besides "The Zen of Python" is that Functions are first class citizens in Python.
Which essentially makes them an Object. Now The fundamental issue is if your functions are object as well then, in Object oriented paradigm how would you send messages to Objects when the messages themselves are objects ?
Looks like a chicken egg problem, to reduce this paradox, the only possible way is to either pass a context of execution to methods or detect it. But since python can have nested functions it would be impossible to do so as the context of execution would change for inner functions.
This means the only possible solution is to explicitly pass 'self' (The context of execution).
So i believe it is a implementation problem the Zen came much later.
As explained in self in Python, Demystified
anything like obj.meth(args) becomes Class.meth(obj, args). The calling process is automatic while the receiving process is not (its explicit). This is the reason the first parameter of a function in class must be the object itself.
class Point(object):
def __init__(self,x = 0,y = 0):
self.x = x
self.y = y
def distance(self):
"""Find distance from origin"""
return (self.x**2 + self.y**2) ** 0.5
Invocations:
>>> p1 = Point(6,8)
>>> p1.distance()
10.0
init() defines three parameters but we just passed two (6 and 8). Similarly distance() requires one but zero arguments were passed.
Why is Python not complaining about this argument number mismatch?
Generally, when we call a method with some arguments, the corresponding class function is called by placing the method's object before the first argument. So, anything like obj.meth(args) becomes Class.meth(obj, args). The calling process is automatic while the receiving process is not (its explicit).
This is the reason the first parameter of a function in class must be the object itself. Writing this parameter as self is merely a convention. It is not a keyword and has no special meaning in Python. We could use other names (like this) but I strongly suggest you not to. Using names other than self is frowned upon by most developers and degrades the readability of the code ("Readability counts").
...
In, the first example self.x is an instance attribute whereas x is a local variable. They are not the same and lie in different namespaces.
Self Is Here To Stay
Many have proposed to make self a keyword in Python, like this in C++ and Java. This would eliminate the redundant use of explicit self from the formal parameter list in methods. While this idea seems promising, it's not going to happen. At least not in the near future. The main reason is backward compatibility. Here is a blog from the creator of Python himself explaining why the explicit self has to stay.
The 'self' parameter keeps the current calling object.
class class_name:
class_variable
def method_name(self,arg):
self.var=arg
obj=class_name()
obj.method_name()
here, the self argument holds the object obj. Hence, the statement self.var denotes obj.var
There is also another very simple answer: according to the zen of python, "explicit is better than implicit".
I was sure that there'd be an answer to this question somewhere on stack overflow, but I haven't been able to find one; most of them are in regards to passing functions, and not methods, as arguments to functions.
I'm currently working with Python 2.7.5 and I'm trying to define a function like this:
def func(object, method):
object.method()
that when called like so:
some_object_instance = SomeObject()
func(some_object_instance, SomeObject.some_object_method)
using a class defined like this:
class SomeObject:
def some_object_method(self):
# do something
is basically equivalent to doing this:
some_object_instance.some_object_method()
I, however, keep getting an attribute error--something along the lines of
'SomeObject' has no attribute 'method'
I was under the impression that I could legally pass methods as arguments and have them evaluate correctly when used in the aforementioned manner. What am I missing?
That's not the way method calling works. The foo.bar syntax looks for a method named bar on the foo object. If you already have the method, just call it:
def func(object, method):
method(object)
func(some_object_instance, SomeObject.some_object_method)
SomeObject.some_object_method is what's called an "unbound method": it's a method object without a self bound into it, so you have to explicitly pass the self to it.
This might make more sense with a concrete example:
>>> s = 'ABC'
>>> s_lower = s.lower # bound method
>>> s_lower()
'abc'
>>> str_lower = str.lower # unbound method
>>> str_lower(s)
'abc'
By comparison, some_object_instance.some_object_method is a "bound method", you can just call it as-is, and some_object_instance is already "bound in" as the self argument:
def func2(method):
method()
func2(some_object_instance.some_object_method)
Unbound methods aren't explained in detail the tutorial; they're covered in the section on bound methods. So you have to go to the reference manual for documentation (in [standard type hierarchy] (https://docs.python.org/2/reference/datamodel.html#the-standard-type-hierarchy), way down in the subsection "User-defined methods"), which can be a little bit daunting for novices.
Personally, I didn't really get this until I learned how it worked under the covers. About a year ago, I wrote a blog post How methods work to try to explain it to someone else (but in Python 3.x terms, which is slightly different); it may help. To really get it, you have to get through the Descriptor HOWTO, which may take a few read-throughs and a lot of playing around in the interactive interpreter before it really clicks, but hopefully you can understand the basic concepts behind methods before getting to that point.
Since you are passing an unbound method to the function, you need to call it as:
method(object)
Or better pass the name of the method as string and then use getattr:
getattr(object, method)()
In addition to bypassing any instance attributes in the interest of correctness, implicit special method lookup generally also bypasses the __getattribute__() method even of the object’s metaclass.
The docs mention special methods such as __hash__, __repr__ and __len__, and I know from experience it also includes __iter__ for Python 2.7.
To quote an answer to a related question:
"Magic __methods__() are treated specially: They are internally assigned to "slots" in the type data structure to speed up their look-up, and they are only looked up in these slots."
In a quest to improve my answer to another question, I need to know: Which methods, specifically, are we talking about?
You can find an answer in the python3 documentation for object.__getattribute__, which states:
Called unconditionally to implement attribute accesses for instances of the class. If the class also defines __getattr__(), the
latter will not be called unless __getattribute__() either calls it
explicitly or raises an AttributeError. This method should return the
(computed) attribute value or raise an AttributeError exception. In
order to avoid infinite recursion in this method, its implementation
should always call the base class method with the same name to access
any attributes it needs, for example, object.__getattribute__(self,
name).
Note
This method may still be bypassed when looking up special methods as the result of implicit invocation via language syntax or built-in
functions. See Special method lookup.
also this page explains exactly how this "machinery" works. Fundamentally __getattribute__ is called only when you access an attribute with the .(dot) operator(and also by hasattr as Zagorulkin pointed out).
Note that the page does not specify which special methods are implicitly looked up, so I deem that this hold for all of them(which you may find here.
Checked in 2.7.9
Couldn't find any way to bypass the call to __getattribute__, with any of the magical methods that are found on object or type:
# Preparation step: did this from the console
# magics = set(dir(object) + dir(type))
# got 38 names, for each of the names, wrote a.<that_name> to a file
# Ended up with this:
a.__module__
a.__base__
#...
Put this at the beginning of that file, which i renamed into a proper python module (asdf.py)
global_counter = 0
class Counter(object):
def __getattribute__(self, name):
# this will count how many times the method was called
global global_counter
global_counter += 1
return super(Counter, self).__getattribute__(name)
a = Counter()
# after this comes the list of 38 attribute accessess
a.__module__
#...
a.__repr__
#...
print global_counter # you're not gonna like it... it printer 38
Then i also tried to get each of those names by getattr and hasattr -> same result. __getattribute__ was called every time.
So if anyone has other ideas... I was too lazy to look inside C code for this, but I'm sure the answer lies somewhere there.
So either there's something that i'm not getting right, or the docs are lying.
super().method will also bypass __getattribute__. This atrocious code will run just fine (Python 3.11).
class Base:
def print(self):
print("whatever")
def __getattribute__(self, item):
raise Exception("Don't access this with a dot!")
class Sub(Base):
def __init__(self):
super().print()
a = Sub()
# prints 'whatever'
a.print()
# Exception Don't access this with a dot!
I've done some Python but have just now starting to use Ruby
I could use a good explanation of the difference between "self" in these two languages.
Obvious on first glance:
Self is not a keyword in Python, but there is a "self-like" value no matter what you call it.
Python methods receive self as an explicit argument, whereas Ruby does not.
Ruby sometimes has methods explicitly defined as part of self using dot notation.
Initial Googling reveals
http://rubylearning.com/satishtalim/ruby_self.html
http://www.ibiblio.org/g2swap/byteofpython/read/self.html
Python is designed to support more than just object-oriented programming. Preserving the same interface between methods and functions lets the two styles interoperate more cleanly.
Ruby was built from the ground up to be object-oriented. Even the literals are objects (evaluate 1.class and you get Fixnum). The language was built such that self is a reserved keyword that returns the current instance wherever you are.
If you're inside an instance method of one of your class, self is a reference to said instance.
If you're in the definition of the class itself (not in a method), self is the class itself:
class C
puts "I am a #{self}"
def instance_method
puts 'instance_method'
end
def self.class_method
puts 'class_method'
end
end
At class definition time, 'I am a C' will be printed.
The straight 'def' defines an instance method, whereas the 'def self.xxx' defines a class method.
c=C.new
c.instance_method
#=> instance_method
C.class_method
#=> class_method
Despite webmat's claim, Guido wrote that explicit self is "not an implementation hack -- it is a semantic device".
The reason for explicit self in method
definition signatures is semantic
consistency. If you write
class C: def foo(self, x, y): ...
This really is the same as writing
class C: pass
def foo(self, x, y): ... C.foo = foo
This was an intentional design decision, not a result of introducing OO behaviour at a latter date.
Everything in Python -is- an object, including literals.
See also Why must 'self' be used explicitly in method definitions and calls?
self is used only as a convention, you can use spam, bacon or sausage instead of self and get the same result. It's just the first argument passed to bound methods. But stick to using self as it will confuse others and some editors.
Well, I don't know much about Ruby. But the obvious point about Python's "self" is that it's not a "keyword" ...it's just the name of an argument that's sent to your method.
You can use any name you like for this argument. "Self" is just a convention.
For example :
class X :
def __init__(a,val) :
a.x = val
def p(b) :
print b.x
x = X(6)
x.p()
Prints the number 6 on the terminal. In the constructor the self object is actually called a. But in the p() method, it's called b.
Update : In October 2008, Guido pointed out that having an explicit self was also necessary to allow Python decorators to be general enough to work on pure functions, methods or classmethods : http://neopythonic.blogspot.com/2008/10/why-explicit-self-has-to-stay.html
This question already has answers here:
What is the purpose of the `self` parameter? Why is it needed?
(26 answers)
Closed 6 months ago.
When defining a method on a class in Python, it looks something like this:
class MyClass(object):
def __init__(self, x, y):
self.x = x
self.y = y
But in some other languages, such as C#, you have a reference to the object that the method is bound to with the "this" keyword without declaring it as an argument in the method prototype.
Was this an intentional language design decision in Python or are there some implementation details that require the passing of "self" as an argument?
I like to quote Peters' Zen of Python. "Explicit is better than implicit."
In Java and C++, 'this.' can be deduced, except when you have variable names that make it impossible to deduce. So you sometimes need it and sometimes don't.
Python elects to make things like this explicit rather than based on a rule.
Additionally, since nothing is implied or assumed, parts of the implementation are exposed. self.__class__, self.__dict__ and other "internal" structures are available in an obvious way.
It's to minimize the difference between methods and functions. It allows you to easily generate methods in metaclasses, or add methods at runtime to pre-existing classes.
e.g.
>>> class C:
... def foo(self):
... print("Hi!")
...
>>>
>>> def bar(self):
... print("Bork bork bork!")
...
>>>
>>> c = C()
>>> C.bar = bar
>>> c.bar()
Bork bork bork!
>>> c.foo()
Hi!
>>>
It also (as far as I know) makes the implementation of the python runtime easier.
I suggest that one should read Guido van Rossum's blog on this topic - Why explicit self has to stay.
When a method definition is decorated, we don't know whether to automatically give it a 'self' parameter or not: the decorator could turn the function into a static method (which has no 'self'), or a class method (which has a funny kind of self that refers to a class instead of an instance), or it could do something completely different (it's trivial to write a decorator that implements '#classmethod' or '#staticmethod' in pure Python). There's no way without knowing what the decorator does whether to endow the method being defined with an implicit 'self' argument or not.
I reject hacks like special-casing '#classmethod' and '#staticmethod'.
Python doesn't force you on using "self". You can give it whatever name you want. You just have to remember that the first argument in a method definition header is a reference to the object.
Also allows you to do this: (in short, invoking Outer(3).create_inner_class(4)().weird_sum_with_closure_scope(5) will return 12, but will do so in the craziest of ways.
class Outer(object):
def __init__(self, outer_num):
self.outer_num = outer_num
def create_inner_class(outer_self, inner_arg):
class Inner(object):
inner_arg = inner_arg
def weird_sum_with_closure_scope(inner_self, num)
return num + outer_self.outer_num + inner_arg
return Inner
Of course, this is harder to imagine in languages like Java and C#. By making the self reference explicit, you're free to refer to any object by that self reference. Also, such a way of playing with classes at runtime is harder to do in the more static languages - not that's it's necessarily good or bad. It's just that the explicit self allows all this craziness to exist.
Moreover, imagine this: We'd like to customize the behavior of methods (for profiling, or some crazy black magic). This can lead us to think: what if we had a class Method whose behavior we could override or control?
Well here it is:
from functools import partial
class MagicMethod(object):
"""Does black magic when called"""
def __get__(self, obj, obj_type):
# This binds the <other> class instance to the <innocent_self> parameter
# of the method MagicMethod.invoke
return partial(self.invoke, obj)
def invoke(magic_self, innocent_self, *args, **kwargs):
# do black magic here
...
print magic_self, innocent_self, args, kwargs
class InnocentClass(object):
magic_method = MagicMethod()
And now: InnocentClass().magic_method() will act like expected. The method will be bound with the innocent_self parameter to InnocentClass, and with the magic_self to the MagicMethod instance. Weird huh? It's like having 2 keywords this1 and this2 in languages like Java and C#. Magic like this allows frameworks to do stuff that would otherwise be much more verbose.
Again, I don't want to comment on the ethics of this stuff. I just wanted to show things that would be harder to do without an explicit self reference.
I think it has to do with PEP 227:
Names in class scope are not accessible. Names are resolved in the
innermost enclosing function scope. If a class definition occurs in a
chain of nested scopes, the resolution process skips class
definitions. This rule prevents odd interactions between class
attributes and local variable access. If a name binding operation
occurs in a class definition, it creates an attribute on the resulting
class object. To access this variable in a method, or in a function
nested within a method, an attribute reference must be used, either
via self or via the class name.
I think the real reason besides "The Zen of Python" is that Functions are first class citizens in Python.
Which essentially makes them an Object. Now The fundamental issue is if your functions are object as well then, in Object oriented paradigm how would you send messages to Objects when the messages themselves are objects ?
Looks like a chicken egg problem, to reduce this paradox, the only possible way is to either pass a context of execution to methods or detect it. But since python can have nested functions it would be impossible to do so as the context of execution would change for inner functions.
This means the only possible solution is to explicitly pass 'self' (The context of execution).
So i believe it is a implementation problem the Zen came much later.
As explained in self in Python, Demystified
anything like obj.meth(args) becomes Class.meth(obj, args). The calling process is automatic while the receiving process is not (its explicit). This is the reason the first parameter of a function in class must be the object itself.
class Point(object):
def __init__(self,x = 0,y = 0):
self.x = x
self.y = y
def distance(self):
"""Find distance from origin"""
return (self.x**2 + self.y**2) ** 0.5
Invocations:
>>> p1 = Point(6,8)
>>> p1.distance()
10.0
init() defines three parameters but we just passed two (6 and 8). Similarly distance() requires one but zero arguments were passed.
Why is Python not complaining about this argument number mismatch?
Generally, when we call a method with some arguments, the corresponding class function is called by placing the method's object before the first argument. So, anything like obj.meth(args) becomes Class.meth(obj, args). The calling process is automatic while the receiving process is not (its explicit).
This is the reason the first parameter of a function in class must be the object itself. Writing this parameter as self is merely a convention. It is not a keyword and has no special meaning in Python. We could use other names (like this) but I strongly suggest you not to. Using names other than self is frowned upon by most developers and degrades the readability of the code ("Readability counts").
...
In, the first example self.x is an instance attribute whereas x is a local variable. They are not the same and lie in different namespaces.
Self Is Here To Stay
Many have proposed to make self a keyword in Python, like this in C++ and Java. This would eliminate the redundant use of explicit self from the formal parameter list in methods. While this idea seems promising, it's not going to happen. At least not in the near future. The main reason is backward compatibility. Here is a blog from the creator of Python himself explaining why the explicit self has to stay.
The 'self' parameter keeps the current calling object.
class class_name:
class_variable
def method_name(self,arg):
self.var=arg
obj=class_name()
obj.method_name()
here, the self argument holds the object obj. Hence, the statement self.var denotes obj.var
There is also another very simple answer: according to the zen of python, "explicit is better than implicit".