I just started programming in Python, and there's something OOP-related that I'm not quite clear on. So in Python, you can create and assign value to a new variable without needing to first declare it. So with that, is there any difference between creating and assigning a new variable for self (eg. self.variable = 5) inside a function (eg. __init__()) vs. creating and assigning a new private member variable? It seems to me like there is no difference at all.
class Foo:
__var_A = 5;
def __init__(self):
self.__var_B = 5;
self.printVars()
def printVars(self):
print(self.__var_A)
print(self.__var_B)
foo = Foo()
There is in fact a difference between those two variables:
Since __var_A is defined in class Foo instead of an individual member-function like __init__, you can change it for all instances at once like this:
Foo._Foo__var_A = 2
This will not work for __var_B since you define it individually per instance.
Note though, that changing __var_A on an instance will not change it for everyone else, it will instead put a local override into the object itself:
foo2 = Foo()
foo2._Foo__var_A = 1
Foo._Foo__var_A = 2
(foo2._Foo__var_A, foo._Foo__var_A) # Returns: (1, 2)
It seems to me like there is no difference at all.
That is correct.
But remember that Python does not have 'private' members. That is only a convention.
The difference between protected and public is a matter of convention. And class or member variable prefixed by one _ indicates to a developer "don't use this unless you know what you're doing." Private is a SLIGHTLY different case, however: they require two _ and they cannot be suffixed by more than one _. Here are the docs:
“Private” instance variables that cannot be accessed except from inside an object don’t exist in Python. However, there is a convention that is followed by most Python code: a name prefixed with an underscore (e.g. _spam) should be treated as a non-public part of the API (whether it is a function, a method or a data member). It should be considered an implementation detail and subject to change without notice.
Name mangling is an important part of Python inheritence. It allows classes to protect API calls from accidental manipulation of descendants (see above docs). However, if necessary you can still access them via _<class-name><var name>. Eg:
class Foo:
def __init__(self):
self.__bar = 1
print(Foo()._Foo__bar)
# 1
There is no difference if the variable is declared under class foo: of within the __init__(self). Both methods accomplish the same thing.
However, this is slight a twist if the variable (e.g. self.bar) is declared from a method other than __init__. Using
def bar(self):
self.bar = 'test'
creates a variable within the object that is not part of the default class. You can do this, but it is not good programming practice for python.
There is a difference. Consider following example:
foo = Foo()
foo.__dict__
This will return:
{'_Foo__var_B': 5}
But, following code:
bar = Foo
bar.__dict__
will return
{'_Foo__var_A': 5,
'__doc__': None,
'__init__': <function __main__.__init__>,
'__module__': '__main__',
'printVars': <function __main__.printVars>}
This leads to conclusion that __var_A will be accessible even if Foo is not instantiated, while __var_B will not be.
Related
Forgive me if this question is obvious, but from what I've read on Python's OOP tutorials none of them mention how to have a static variable store a static method. In my code I tried:
class Features:
a_static_variable = 1
a_static_variable_that_references_a_static_function = Features.func1
#staticmethod
def func1(blah):
print(blah)
When trying to run this I received:
NameError: name 'Features' is not defined
Is it possible for a class method to reference a static method in its own class? If so, how do I do this. I tried replacing Features with nothing and self but as I expected those made no sense as well.
This is simply a case of func1 not being defined yet.
It should work if you reorder:
class Features:
a_static_variable = 1
#staticmethod
def func1(blah):
print(blah)
a_static_variable_that_references_a_static_function = func1
Yes, just define the function first:
class Features:
#staticmethod
def func1(blah):
print(blah)
a_static_variable = 1
a_static_variable_that_references_a_static_function = func1
Features.a_static_variable_that_references_a_static_function('test')
Your code has two errors (explained in the other answers). This example may help you understand what's going on.
class Example:
class_variable = 'class_variable'
#staticmethod
def static_method():
print('static_method')
class_method = static_method
print(locals())
def instance_method(self):
print(instance_method)
print(locals())
When this code is run, without instantiating a member of this class, the output is:
creating the class:
{'class_variable': 'class_variable',
'__module__': '__main__',
'static_method': <staticmethod object at 0x0135E5F0>,
'class_method': <staticmethod object at 0x0135E5F0>
}
So, while creating the class, a scope is created in which all of the names in that dictionary are accessible.
Now let's look at what happens when we do this:
example = Example()
example.instance_method()
Nothing happens when you instantiate an object, but calling instance_method will print the local variable(s) accessible to that scope.
instance_method
{'self': <__main__.Example instance at 0x01810210>}
Now, you are probably used to creating instance methods that reference class variables.
def other_instance_method(self):
print(Example.class_variable)
Here, Example is not present in the local scope. In order to find it, the global scope needs to be searched (i.e. globals). Note that instead of explicitly referencing Example, we could access the the class variable from the self object itself.
def other_instance_method(self):
print(self.class_variable)
You can do some testing yourself by printing locals() and globals() from various places to get a grip on how the scope changes.
Python (3 and 2) doesn't allow you to reference a class inside its body (except in methods):
class A:
static_attribute = A()
This raises a NameError in the second line because 'A' is not defined, while this
class A:
def method(self):
return A('argument')
works fine.
In other languages, for example Java, the former is no problem and it is advantageous in many situations, like implementing singletons.
Why isn't this possible in Python? What are the reasons for this decision?
EDIT:
I edited my other question so it asks only for ways to "circumvent" this restriction, while this questions asks for its motivation / technical details.
Python is a dynamically typed language, and executes statements as you import the module. There is no compiled definition of a class object, the object is created by executing the class statement.
Python essentially executes the class body like a function, taking the resulting local namespace to form the body. Thus the following code:
class Foo(object):
bar = baz
translates roughly to:
def _Foo_body():
bar = baz
return locals()
Foo = type('Foo', (object,), _Foo_body())
As a result, the name for the class is not assigned to until the class statement has completed executing. You can't use the name inside the class statement until that statement has completed, in the same way that you can't use a function until the def statement has completed defining it.
This does mean you can dynamically create classes on the fly:
def class_with_base(base_class):
class Foo(base_class):
pass
return Foo
You can store those classes in a list:
classes = [class_with_base(base) for base in list_of_bases]
Now you have a list of classes with no global names referring to them anywhere. Without a global name, I can't rely on such a name existing in a method either; return Foo won't work as there is no Foo global for that to refer to.
Next, Python supports a concept called a metaclass, which produces classes just like a class produces instances. The type() function above is the default metaclass, but you are free to supply your own for a class. A metaclass is free to produce whatever it likes really, even things that are bit classes! As such Python cannot, up front, know what kind of object a class statement will produce and can't make assumptions about what it'll end up binding the name used to. See What is a metaclass in Python?
All this is not something you can do in a statically typed language like Java.
A class statement is executed just like any other statement. Your first example is (roughly) equivalent to
a = A()
A = type('A', (), {'static_attribute': a})
The first line obviously raises a NameError, because A isn't yet bound to anything.
In your second example, A isn't referenced until method is actually called, by which time A does refer to the class.
Essentially, a class does not exist until its entire definition is compiled in its entirety. This is similar to end blocks that are explicitly written in other languages, and Python utilizes implicit end blocks which are determined by indentation.
The other answers are great at explaining why you can't reference the class by name within the class, but you can use class methods to access the class.
The #classmethod decorator annotes a method that will be passed the class type, instead of the usual class instance (self). This is similar to Java's static method (there's also a #staticmethod decorator, which is a little different).
For a singleton, you can access a class instance to store an object instance (Attributes defined at the class level are the fields defined as static in a Java class):
class A(object):
instance = None
#classmethod
def get_singleton(cls):
if cls.instance is None:
print "Creating new instance"
cls.instance = cls()
return cls.instance
>>> a1 = A.get_singleton()
Creating new instance
>>> a2 = A.get_singleton()
>>> print a1 is a2
True
You can also use class methods to make java-style "static" methods:
class Name(object):
def __init__(self, name):
self.name = name
#classmethod
def make_as_victoria(cls):
return cls("Victoria")
#classmethod
def make_as_stephen(cls):
return cls("Stephen")
>>> victoria = Name.make_as_victoria()
>>> stephen = Name.make_as_stephen()
>>> print victoria.name
Victoria
>>> print stephen.name
Stephen
The answer is "just because".
It has nothing to do with the type system of Python, or it being dynamic. It has to do with the order in which a newly introduced type is initialized.
Some months ago I developed an object system for the language TXR, in which this works:
1> (defstruct foo nil (:static bar (new foo)))
#
2> (new foo)
#S(foo)
3> *2.bar
#S(foo)
Here, bar is a static slot ("class variable") in foo. It is initialized by an expression which constructs a foo.
Why that works can be understood from the function-based API for the instantiation of a new type, where the static class initialization is performed by a function which is passed in. The defstruct macro compiles a call to make-struct-type in which the (new foo) expression ends up in the body of the anonymous function that is passed for the static-initfun argument. This function is called after the type is registered under the foo symbol already.
We could easily patch the C implementation of make_struct_type so that this breaks. The last few lines of that function are:
sethash(struct_type_hash, name, stype);
if (super) {
mpush(stype, mkloc(su->dvtypes, super));
memcpy(st->stslot, su->stslot, sizeof (val) * su->nstslots);
}
call_stinitfun_chain(st, stype);
return stype;
}
The call_stinifun_chain does the initialization which ends up evaluating (new foo) and storing it in the bar static slot, and the sethash call is what registers the type under its name.
If we simply reverse the order in which these functions are called, the language and type system will still be the same, and almost everything will work as before. Yet, the (:static bar (new foo)) slot specifier will fail.
I put the calls in that order because I wanted the language-controlled aspects of the type to be as complete as possible before exposing it to the user-definable initializations.
I can't think of any reason for foo not to be known at the time when that struct type is being initialized, let alone a good reason. It is legitimate for static construction to create an instance. For example, we could use it to create a "singleton".
This looks like a bug in Python.
I want to clarify how variables are declared in Python.
I have seen variable declaration as
class writer:
path = ""
sometimes, there is no explicit declaration but just initialization using __init__:
def __init__(self, name):
self.name = name
I understand the purpose of __init__, but is it advisable to declare variable in any other functions?
How can I create a variable to hold a custom type?
class writer:
path = "" # string value
customObj = ??
Okay, first things first.
There is no such thing as "variable declaration" or "variable initialization" in Python.
There is simply what we call "assignment", but should probably just call "naming".
Assignment means "this name on the left-hand side now refers to the result of evaluating the right-hand side, regardless of what it referred to before (if anything)".
foo = 'bar' # the name 'foo' is now a name for the string 'bar'
foo = 2 * 3 # the name 'foo' stops being a name for the string 'bar',
# and starts being a name for the integer 6, resulting from the multiplication
As such, Python's names (a better term than "variables", arguably) don't have associated types; the values do. You can re-apply the same name to anything regardless of its type, but the thing still has behaviour that's dependent upon its type. The name is simply a way to refer to the value (object). This answers your second question: You don't create variables to hold a custom type. You don't create variables to hold any particular type. You don't "create" variables at all. You give names to objects.
Second point: Python follows a very simple rule when it comes to classes, that is actually much more consistent than what languages like Java, C++ and C# do: everything declared inside the class block is part of the class. So, functions (def) written here are methods, i.e. part of the class object (not stored on a per-instance basis), just like in Java, C++ and C#; but other names here are also part of the class. Again, the names are just names, and they don't have associated types, and functions are objects too in Python. Thus:
class Example:
data = 42
def method(self): pass
Classes are objects too, in Python.
So now we have created an object named Example, which represents the class of all things that are Examples. This object has two user-supplied attributes (In C++, "members"; in C#, "fields or properties or methods"; in Java, "fields or methods"). One of them is named data, and it stores the integer value 42. The other is named method, and it stores a function object. (There are several more attributes that Python adds automatically.)
These attributes still aren't really part of the object, though. Fundamentally, an object is just a bundle of more names (the attribute names), until you get down to things that can't be divided up any more. Thus, values can be shared between different instances of a class, or even between objects of different classes, if you deliberately set that up.
Let's create an instance:
x = Example()
Now we have a separate object named x, which is an instance of Example. The data and method are not actually part of the object, but we can still look them up via x because of some magic that Python does behind the scenes. When we look up method, in particular, we will instead get a "bound method" (when we call it, x gets passed automatically as the self parameter, which cannot happen if we look up Example.method directly).
What happens when we try to use x.data?
When we examine it, it's looked up in the object first. If it's not found in the object, Python looks in the class.
However, when we assign to x.data, Python will create an attribute on the object. It will not replace the class' attribute.
This allows us to do object initialization. Python will automatically call the class' __init__ method on new instances when they are created, if present. In this method, we can simply assign to attributes to set initial values for that attribute on each object:
class Example:
name = "Ignored"
def __init__(self, name):
self.name = name
# rest as before
Now we must specify a name when we create an Example, and each instance has its own name. Python will ignore the class attribute Example.name whenever we look up the .name of an instance, because the instance's attribute will be found first.
One last caveat: modification (mutation) and assignment are different things!
In Python, strings are immutable. They cannot be modified. When you do:
a = 'hi '
b = a
a += 'mom'
You do not change the original 'hi ' string. That is impossible in Python. Instead, you create a new string 'hi mom', and cause a to stop being a name for 'hi ', and start being a name for 'hi mom' instead. We made b a name for 'hi ' as well, and after re-applying the a name, b is still a name for 'hi ', because 'hi ' still exists and has not been changed.
But lists can be changed:
a = [1, 2, 3]
b = a
a += [4]
Now b is [1, 2, 3, 4] as well, because we made b a name for the same thing that a named, and then we changed that thing. We did not create a new list for a to name, because Python simply treats += differently for lists.
This matters for objects because if you had a list as a class attribute, and used an instance to modify the list, then the change would be "seen" in all other instances. This is because (a) the data is actually part of the class object, and not any instance object; (b) because you were modifying the list and not doing a simple assignment, you did not create a new instance attribute hiding the class attribute.
This might be 6 years late, but in Python 3.5 and above, you can give a hint about a variable type like this:
variable_name: type_name
or this:
variable_name # type: shinyType
This hint has no effect in the core Python interpreter, but many tools will use it to aid the programmer in writing correct code.
So in your case(if you have a CustomObject class defined), you can do:
customObj: CustomObject
See this or that for more info.
There's no need to declare new variables in Python. If we're talking about variables in functions or modules, no declaration is needed. Just assign a value to a name where you need it: mymagic = "Magic". Variables in Python can hold values of any type, and you can't restrict that.
Your question specifically asks about classes, objects and instance variables though. The idiomatic way to create instance variables is in the __init__ method and nowhere else — while you could create new instance variables in other methods, or even in unrelated code, it's just a bad idea. It'll make your code hard to reason about or to maintain.
So for example:
class Thing(object):
def __init__(self, magic):
self.magic = magic
Easy. Now instances of this class have a magic attribute:
thingo = Thing("More magic")
# thingo.magic is now "More magic"
Creating variables in the namespace of the class itself leads to different behaviour altogether. It is functionally different, and you should only do it if you have a specific reason to. For example:
class Thing(object):
magic = "Magic"
def __init__(self):
pass
Now try:
thingo = Thing()
Thing.magic = 1
# thingo.magic is now 1
Or:
class Thing(object):
magic = ["More", "magic"]
def __init__(self):
pass
thing1 = Thing()
thing2 = Thing()
thing1.magic.append("here")
# thing1.magic AND thing2.magic is now ["More", "magic", "here"]
This is because the namespace of the class itself is different to the namespace of the objects created from it. I'll leave it to you to research that a bit more.
The take-home message is that idiomatic Python is to (a) initialise object attributes in your __init__ method, and (b) document the behaviour of your class as needed. You don't need to go to the trouble of full-blown Sphinx-level documentation for everything you ever write, but at least some comments about whatever details you or someone else might need to pick it up.
For scoping purpose, I use:
custom_object = None
Variables have scope, so yes it is appropriate to have variables that are specific to your function. You don't always have to be explicit about their definition; usually you can just use them. Only if you want to do something specific to the type of the variable, like append for a list, do you need to define them before you start using them. Typical example of this.
list = []
for i in stuff:
list.append(i)
By the way, this is not really a good way to setup the list. It would be better to say:
list = [i for i in stuff] # list comprehension
...but I digress.
Your other question.
The custom object should be a class itself.
class CustomObject(): # always capitalize the class name...this is not syntax, just style.
pass
customObj = CustomObject()
As of Python 3, you can explicitly declare variables by type.
For instance, to declare an integer one can do it as follows:
x: int = 3
or:
def f(x: int):
return x
see this question for more detailed info about it:
Explicitly declaring a variable type in Python
Reading the documentation I came across the following paragraph:
A scope defines the visibility of a name within a block. If a local
variable is defined in a block, its scope includes that block. If the
definition occurs in a function block, the scope extends to any blocks
contained within the defining one, unless a contained block introduces
a different binding for the name. The scope of names defined in a
class block is limited to the class block; it does not extend to the
code blocks of methods – this includes comprehensions and generator
expressions since they are implemented using a function scope.
I decided to try accessing class variable from a method myself:
>>> class A():
i = 1
def f(self):
print(i)
>>> a = A()
>>> a.i
1
>>> a.f()
Traceback (most recent call last):
File "<pyshell#7>", line 1, in <module>
a.f()
File "<pyshell#4>", line 4, in f
print(i)
NameError: global name 'i' is not defined
I know that the variable i may be accessed by explicitly pointing to the class name A.i:
>>> a = A()
>>> class A():
i = 1
def f(self):
print(A.i)
>>> a = A()
>>> a.f()
1
The question is why the developers of the language made class variables not visible from methods? What is the rationale behind it?
A class block is syntactic sugar for building a dictionary, which is then passed to the metaclass (usually type) to construct the class object.
class A:
i = 1
def f(self):
print(i)
Is roughly equivalent to:
def f(self):
print(i)
attributes = {"f": f, "i": 1}
A = type("A", (object,), attributes)
Seen that way, there is no outer scope the i name to come from. However there obviously is a temporary scope for you to execute the statements in the class block. It would be possible for that class block to desugar to something more like:
def attributes():
i = 1
def f(self):
print(i)
return locals()
A = type('A', (object,), attributes())
In this case the outer reference to i would work. However, this would be going "against the grain" of Python's object system philosophy.
Python has objects, which contain attributes. There's not really any concept of "variables" other than local variables in functions (which can be nested to create a scope chain). A bare name is looked up as a local variable, then in outer scopes (which come from functions). Attributes are looked up, using the dotted name syntax, on other objects, and you always specify which object to look in.
There is a protocol for resolving attribute references, which says that when attribute is not found on obj, obj.attribute can be resolved by looking in the class of obj (and its base classes, using the method resolution order). This is actually how methods are found; when in your example you executed a.f(), the a object contains no attribute f, so the class of a (which is A) is searched, and the method definition is found.
Having class attributes automatically available in an outer scope for all methods would be weird, because no other attribute works this way. It would also have the following drawbacks:
Functions defined outside the class and assigned to it later would have to use different syntax to refer to the class attribute than functions defined as part of a class.
Because it's shorter, it would encourage reference to class attributes including staticmethods and classmethods as bare names: thing rather than using Class.thing or self.thing. This makes them look like module globals when they're not (method definitions are usually short enough that you can easily see they're not defined locally).
Note that looking for the attributes on self allows them to play nicer with subclasses, as it allows subclasses to override the attribute. That probably isn't as big a deal for "class constants", but it's very important for staticmethods and classmethods.
Those are the main reasons I see, but ultimately it's just a choice the designers of Python made. You find it weird that you don't have this implicit ability to reference class variables, but I find implicit class and instance variable access in languages like C++ and Java to be weird. Different people have different opinions.
This seems to be related to the use of an explicit self parameter, and the requirement that all method calls and instance attribute accesses explicitly use self. It would be at least strange if the uncommon case of accessing a class scope function as a normal function would be much easier than the common case of accessing it as a method via self. Class variables are usually also accessed via the instance in Python.
In C++, in contrast, the class scope is visibile in all methods, but calling a method implicitly passes this. This seems to be the other sane choice.
I haven't found anything. I want to do this without passing the name inside the constructor.
class foo:
pass
something = foo()
I want each instance of foo to be aware of its initial identifier name. In this case the instance of foo() I created should be aware that its identifier is the string "something"
I am working on a small api and this would be a very elegant approach, unfortunately I haven't seen anything like this done.
Thanks,
Even if you could do this—which you can't—it would be an abuse of the language. For the sanity of whoever reads your code, please avoid hidden "magic" behavior. Python programmers would not expect their local variable names to be meaningful and actually be exposed to outside code.
You can't. Creation of an object is totally independent from assigning a reference to that object to some named variable.
foo().doSomething() — an instance of foo is not bound to any name and probably gets garbage collected right after the call.
a[1].moo = foo() — what's the name, again?
a = foo()
b = a # is name of foo 'a' or 'b'? both point to the same instance
a = None # but 'a' is gone, so now the name is 'b'?..
OTOH, passing a name to the constructor is painless:
my_foos = {}
for name in ('a', 'b', 'c'):
my_foos[name] = foo(name)
You may even rudely assign an instance attribute, if you won't change the constructor for some reason:
my_foos = {}
for name in ('a', 'b', 'c'):
a_foo = foo()
a_foo.my_mame = name # here
my_foos[name] = a_foo
And if you're into the dark side, you finally can add your foos to global namespace:
globals().update(my_foos) — now you have global names a, b and c, each referring to an aptly-named foo.
And, for foo's sake, name your classes with a capital initial letter :)
As far as I know, in Python a variable is just a name referring to some object instance. You can have many names pointing to the same instance; the instance is not aware of its names (nor should be, IMHO); the same name can be reused later to point to other instance from a complete different class.
Given the Python data model is hard to see why would be useful for the object to know how it is named in some namespace.
You can store references to your instances in a class variable or another container, but it is not very common in Python - because namespaces are such natural and elegant containers.