namespace for class inside of class in python - python

I am trying to understand the nesting of namespaces in python 2.7.
Consider the following not-working code:
class c(object):
def debug(self):
print globals(),locals()
print x,y
class a(object):
x=7
def __init__(self):
self.y=9
class b(object):
def debug(self):
print globals(),locals()
print x,y
class d(c):
pass
How do I access to the variables x and y, from the calls
a().b().debug()
a.b().debug()
a().d().debug()
a.d().debug()
None of them seems able to see either x nor y.
EDIT after discussion, it seems that what I want (avoid reference to globals) can be reached only by explicitly extending the information on the nested classes. For instance
class a(object):
#
#classmethod
def _initClass(cls):
for v in dir(cls):
if type(cls.__dict__[v])==type:
setattr(cls.__dict__[v],'vader',cls)
#
x=7
class b(object):
def debug(self):
print b.vader.x
class d(c):
pass
a._initClass()
And even this technique does not seem useful to access an instance variable, as intended in the a().d().debug sequence.

class objects do not create a scope; class bodies are executed just once and discarded, the local namespace producing the class attributes. Class bodies never participate in nested scopes; they are ignored entirely when resolving non-local names.
As such, your x = 7 is not a name that the nested b class (or its methods) could ever access. Instead, it is a class attribute on a. Accessing a.x will work. y is an instance attribute, and you'll have to have a reference to the instance for it to be accessible anywhere else.
Note that this applies to class b as well; it is a class attribute on a now, just like x is a class attribute.
There is nothing special about your class b other than how you reference the class object. Just because you created an instance of a does not mean that b has any privileged access to it; a().b() does not create a relationship between the instances. You could do:
b = a.b
b_instance = b()
and there would be no difference. You could even do:
a.b.a = a
a.b.a()
and the world will not implode! (fancy that).

Martijn already gave a good answer, but I'll take a stab at my own.
As Martijn said, class declarations are executed rather like one-off functions, with their own local scope, when their module is first imported. Whatever's left over in this local scope, after everything in the class declaration has been executed, is used as the class's dictionary. So x, __init__, b, and d all end up being attributes on the a class object. The same is true of your classes b and d; their bodies are executed when the module is imported and the local scopes left over are used as their dictionaries as well.
The reason your code isn't working is that, by the time the debug method executes, the only scopes it's aware of are the global scope and its own local scope. In python, methods do not implicitly include a class instance's dictionary as part of their scope as they do in languages like C++. The class instance is available explicitly as the self argument which appears in the argument list (hence, Python's zen "explicit is better than implicit" -- try import this in the python console).
Also, it doesn't matter whether or not you instantiate a before accessing and instantiating the other classes b and d on a since b and d are both class attributes on a. Therefore, python can successfully retrieve b and d from either an instance of a or a direct reference to the a class object.

Related

How do I create an instance of a nested class from within that class in Python?

class ExampleClass():
def Example(self):
self.nestedinstance = self.NestedClass()
self.nestedinstance.makenew()
class NestedClass():
def makenew(self):
newclass = NestedClass()
ExampleClass().Example()
When I run the above code I get the exception: name 'NestedClass' is not defined
Is there a different way to do this with a nested class or have I done something wrong?
You ideally want to be using classmethods if creating a new instance, this is an example of how you'd do it:
class NestedClass():
#classmethod
def makenew(cls):
newclass = cls()
Alternatively if you wanted to create an instance using the current instance (for example if you needed to pass in some arguments), then you can get the class by using type(self) or self.__class__.
class NestedClass():
def makenew(self):
newclass = type(self)()
Without knowing your use case though, this may not be what you're after.
Your error comes from how python handles classes.
When it encounters a class statement, the body of the class is run, and the names it defines are placed in a separate namespace, which will eventually become the class __dict__. The class object is not created and bound to its name until (well) after the body has run. That means that when you put class NestedClass: inside the body of class ExampleClass:, ExampleClass does not exist yet, and neither does NestedClass. Indirectly because of this, all the new class namespaces live in the top level available namespace (e.g. global or function), and are not actually nested within one another.
As a consequence of this order of operations, class bodies are not aware of the namespaces of surrounding classes at all. So the namespace of NestedClass looks out to the global namespace, not to the __dict__ of ExampleClass, as you might expect coming from say Java. A class defined in a function would be able to see the functions local namespace before globals, but still not that of an enclosing class.
And so, the line newclass = NestedClass() raises an error. The name NestedClass does not exist in the function's namespace, or in the global namespace. There are three simple workarounds available:
Use the staticly scoped __class__:
newclass = __class__()
Refer to the class by its global name:
newclass = ExampleClass.NestedClass()
Don't use nested classes in Python. This is generally the preferred approach. Just move NestedClass to the top level. Then your makenew method will work without modification, and ExampleClass.Example can refer to NestedClass directly instead of as self.NestedClass.

Properties seem to set to the same value for all objects (Python) [duplicate]

What is the difference between class and instance variables in Python?
class Complex:
a = 1
and
class Complex:
def __init__(self):
self.a = 1
Using the call: x = Complex().a in both cases assigns x to 1.
A more in-depth answer about __init__() and self will be appreciated.
When you write a class block, you create class attributes (or class variables). All the names you assign in the class block, including methods you define with def become class attributes.
After a class instance is created, anything with a reference to the instance can create instance attributes on it. Inside methods, the "current" instance is almost always bound to the name self, which is why you are thinking of these as "self variables". Usually in object-oriented design, the code attached to a class is supposed to have control over the attributes of instances of that class, so almost all instance attribute assignment is done inside methods, using the reference to the instance received in the self parameter of the method.
Class attributes are often compared to static variables (or methods) as found in languages like Java, C#, or C++. However, if you want to aim for deeper understanding I would avoid thinking of class attributes as "the same" as static variables. While they are often used for the same purposes, the underlying concept is quite different. More on this in the "advanced" section below the line.
An example!
class SomeClass:
def __init__(self):
self.foo = 'I am an instance attribute called foo'
self.foo_list = []
bar = 'I am a class attribute called bar'
bar_list = []
After executing this block, there is a class SomeClass, with 3 class attributes: __init__, bar, and bar_list.
Then we'll create an instance:
instance = SomeClass()
When this happens, SomeClass's __init__ method is executed, receiving the new instance in its self parameter. This method creates two instance attributes: foo and foo_list. Then this instance is assigned into the instance variable, so it's bound to a thing with those two instance attributes: foo and foo_list.
But:
print instance.bar
gives:
I am a class attribute called bar
How did this happen? When we try to retrieve an attribute through the dot syntax, and the attribute doesn't exist, Python goes through a bunch of steps to try and fulfill your request anyway. The next thing it will try is to look at the class attributes of the class of your instance. In this case, it found an attribute bar in SomeClass, so it returned that.
That's also how method calls work by the way. When you call mylist.append(5), for example, mylist doesn't have an attribute named append. But the class of mylist does, and it's bound to a method object. That method object is returned by the mylist.append bit, and then the (5) bit calls the method with the argument 5.
The way this is useful is that all instances of SomeClass will have access to the same bar attribute. We could create a million instances, but we only need to store that one string in memory, because they can all find it.
But you have to be a bit careful. Have a look at the following operations:
sc1 = SomeClass()
sc1.foo_list.append(1)
sc1.bar_list.append(2)
sc2 = SomeClass()
sc2.foo_list.append(10)
sc2.bar_list.append(20)
print sc1.foo_list
print sc1.bar_list
print sc2.foo_list
print sc2.bar_list
What do you think this prints?
[1]
[2, 20]
[10]
[2, 20]
This is because each instance has its own copy of foo_list, so they were appended to separately. But all instances share access to the same bar_list. So when we did sc1.bar_list.append(2) it affected sc2, even though sc2 didn't exist yet! And likewise sc2.bar_list.append(20) affected the bar_list retrieved through sc1. This is often not what you want.
Advanced study follows. :)
To really grok Python, coming from traditional statically typed OO-languages like Java and C#, you have to learn to rethink classes a little bit.
In Java, a class isn't really a thing in its own right. When you write a class you're more declaring a bunch of things that all instances of that class have in common. At runtime, there's only instances (and static methods/variables, but those are really just global variables and functions in a namespace associated with a class, nothing to do with OO really). Classes are the way you write down in your source code what the instances will be like at runtime; they only "exist" in your source code, not in the running program.
In Python, a class is nothing special. It's an object just like anything else. So "class attributes" are in fact exactly the same thing as "instance attributes"; in reality there's just "attributes". The only reason for drawing a distinction is that we tend to use objects which are classes differently from objects which are not classes. The underlying machinery is all the same. This is why I say it would be a mistake to think of class attributes as static variables from other languages.
But the thing that really makes Python classes different from Java-style classes is that just like any other object each class is an instance of some class!
In Python, most classes are instances of a builtin class called type. It is this class that controls the common behaviour of classes, and makes all the OO stuff the way it does. The default OO way of having instances of classes that have their own attributes, and have common methods/attributes defined by their class, is just a protocol in Python. You can change most aspects of it if you want. If you've ever heard of using a metaclass, all that is is defining a class that is an instance of a different class than type.
The only really "special" thing about classes (aside from all the builtin machinery to make them work they way they do by default), is the class block syntax, to make it easier for you to create instances of type. This:
class Foo(BaseFoo):
def __init__(self, foo):
self.foo = foo
z = 28
is roughly equivalent to the following:
def __init__(self, foo):
self.foo = foo
classdict = {'__init__': __init__, 'z': 28 }
Foo = type('Foo', (BaseFoo,) classdict)
And it will arrange for all the contents of classdict to become attributes of the object that gets created.
So then it becomes almost trivial to see that you can access a class attribute by Class.attribute just as easily as i = Class(); i.attribute. Both i and Class are objects, and objects have attributes. This also makes it easy to understand how you can modify a class after it's been created; just assign its attributes the same way you would with any other object!
In fact, instances have no particular special relationship with the class used to create them. The way Python knows which class to search for attributes that aren't found in the instance is by the hidden __class__ attribute. Which you can read to find out what class this is an instance of, just as with any other attribute: c = some_instance.__class__. Now you have a variable c bound to a class, even though it probably doesn't have the same name as the class. You can use this to access class attributes, or even call it to create more instances of it (even though you don't know what class it is!).
And you can even assign to i.__class__ to change what class it is an instance of! If you do this, nothing in particular happens immediately. It's not earth-shattering. All that it means is that when you look up attributes that don't exist in the instance, Python will go look at the new contents of __class__. Since that includes most methods, and methods usually expect the instance they're operating on to be in certain states, this usually results in errors if you do it at random, and it's very confusing, but it can be done. If you're very careful, the thing you store in __class__ doesn't even have to be a class object; all Python's going to do with it is look up attributes under certain circumstances, so all you need is an object that has the right kind of attributes (some caveats aside where Python does get picky about things being classes or instances of a particular class).
That's probably enough for now. Hopefully (if you've even read this far) I haven't confused you too much. Python is neat when you learn how it works. :)
What you're calling an "instance" variable isn't actually an instance variable; it's a class variable. See the language reference about classes.
In your example, the a appears to be an instance variable because it is immutable. It's nature as a class variable can be seen in the case when you assign a mutable object:
>>> class Complex:
>>> a = []
>>>
>>> b = Complex()
>>> c = Complex()
>>>
>>> # What do they look like?
>>> b.a
[]
>>> c.a
[]
>>>
>>> # Change b...
>>> b.a.append('Hello')
>>> b.a
['Hello']
>>> # What does c look like?
>>> c.a
['Hello']
If you used self, then it would be a true instance variable, and thus each instance would have it's own unique a. An object's __init__ function is called when a new instance is created, and self is a reference to that instance.

Conditional statements in a class, but outside of scope of the function

We know that with notation:
class Foo(object):
a = 1
def __init__(self):
self.b = 2
def c(self):
print('c')
we can create static variable Foo.a, 'normal' variable b, which will be available after creating and instance of Foo, and method c
Today I was really surprised, that I can use conditional statements in a class, but outside of scope of the function
class C():
if True:
a = 1
b = 2
Languages like C++/Java, taught me that legal notation is similar to:
class Name():
variable = <expression>
Could you describe other rules, which refer to this specific scope? How I should name this scope?
The class body is just Python code. It has specific scope rules, but anything goes otherwise. This means you can create functions conditionally:
class C:
if some_condition:
def optional_method(self):
pass
or pull methods from elsewhere:
import some_module
class D:
method_name = some_module.function_that_accepts_self
etc.
The Python documentation for class definitions states:
A class definition is an executable statement.
and
The class’s suite is then executed in a new execution frame (see section Naming and binding), using a newly created local namespace and the original global namespace. (Usually, the suite contains only function definitions.) When the class’s suite finishes execution, its execution frame is discarded but its local namespace is saved. A class object is then created using the inheritance list for the base classes and the saved local namespace for the attribute dictionary.
Note the usually in that text. Essentially, the class body is executed as a function would, and anything you put in the body namespace becomes an attribute on the class.
The Naming and binding section then tells you:
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
so names you define in this block cannot be directly accessed in methods; you'd use class.name or self.name instead.
In java everything is classes and object, classes are container but in python everything is object.
Classes are also objects. like functions(also objects) so when you use conditional statement in function then python allows you to do same in Classes.
like:-
def A():
if condition:
do something
elif condition:
do somethig
else:
do something
is same
Class A()
if condition:
do something
elif condition:
do somethig
else:
do something
you can assign functions even to store in a variable like you do for classes
def A():
pass
a = A # is valid
while in java you can't define function outside the classes.

How should I choose between using instance vs. class attributes?

I tried this example code:
class testclass:
classvar = 'its classvariable LITERAL'
def __init__(self,x,y):
self.z = x
self.classvar = 'its initvariable LITERAL'
self.test()
def test(self):
print('class var',testclass.classvar)
print('instance var',self.classvar)
if __name__ == '__main__':
x = testclass(2,3)
I need some clarification. In both cases, I'm able to access the class attribute and instance in the test method.
So, suppose if I have to define a literal that needs to be used across all function, which would be the better way to define it: an instance attribute or a class attribute?
I found this in an old presentation made by Guido van Rossum in 1999 ( http://legacy.python.org/doc/essays/ppt/acm-ws/sld001.htm ) and I think it explains the topic beautifully:
Instance variable rules
On use via instance (self.x), search order:
(1) instance, (2) class, (3) base classes
this also works for method lookup
On assigment via instance (self.x = ...):
always makes an instance variable
Class variables "default" for instance variables
But...!
mutable class variable: one copy shared by all
mutable instance variable: each instance its own
Class variables are quite good for "constants" used by all the instances (that's all methods are technically). You could use module globals, but using a class variable makes it more clearly associated with the class.
There are often uses for class variables that you actually change, too, but it's usually best to stay away from them for the same reason you stay away from having different parts of your program communicate by altering global variables.
Instance variables are for data that is actually part of the instance. They could be different for each particular instance, and they often change over the lifetime of a single particular instance. It's best to use instance variables for data that is conceptually part of an instance, even if in your program you happen to only have one instance, or you have a few instances that in practice always have the same value.
It's good practice to only use class attributes if they are going to remain fixed, and one great thing about them is that they can be accessed outside of an instance:
class MyClass():
var1 = 1
def __init__(self):
self.var2 = 2
MyClass.var1 # 1 (you can reference var1 without instantiating)
MyClass.var2 # AttributeError: class MyClass has no attribute 'var2'
If MyClass.var is defined, it should be the same in every instance of MyClass, otherwise you get the following behaviour which is considered confusing.
a = MyClass()
b = MyClass()
a.var1, a.var2 # (1,2)
a.var1, a.var2 = (3,4) # you can change these variables
a.var1, a.var2 # (3,4)
b.var1, b.var2 # (1,2) # but they don't change in b
MyClass.var1 # 1 nor in MyClass
You should define it as a class attribute if you want it to be shared among all instances. You should define it as an instance variable if you want a separate one for each instance (e.g., if different instances might have different values for the variable).

Python weird class variables usage

Suppose we have the following code:
class A:
var = 0
a = A()
I do understand that a.var and A.var are different variables, and I think I understand why this thing happens. I thought it was just a side effect of python's data model, since why would someone want to modify a class variable in an instance?
However, today I came across a strange example of such a usage: it is in google app engine db.Model reference. Google app engine datastore assumes we inherit db.Model class and introduce keys as class variables:
class Story(db.Model):
title = db.StringProperty()
body = db.TextProperty()
created = db.DateTimeProperty(auto_now_add=True)
s = Story(title="The Three Little Pigs")
I don't understand why do they expect me to do like that? Why not introduce a constructor and use only instance variables?
The db.Model class is a 'Model' style class in classic Model View Controller design pattern.
Each of the assignments in there are actually setting up columns in the database, while also giving an easy to use interface for you to program with. This is why
title="The Three Little Pigs"
will update the object as well as the column in the database.
There is a constructor (no doubt in db.Model) that handles this pass-off logic, and it will take a keyword args list and digest it to create this relational model.
This is why the variables are setup the way they are, so that relation is maintained.
Edit: Let me describe that better. A normal class just sets up the blue print for an object. It has instance variables and class variables. Because of the inheritence to db.Model, this is actually doing a third thing: Setting up column definitions in a database. In order to do this third task it is making EXTENSIVE behinds the scenes changes to things like attribute setting and getting. Pretty much once you inherit from db.Model you aren't really a class anymore, but a DB template. Long story short, this is a VERY specific edge case of the use of a class
If all variables are declared as instance variables then the classes using Story class as superclass will inherit nothing from it.
From the Model and Property docs, it looks like Model has overridden __getattr__ and __setattr__ methods so that, in effect, "Story.title = ..." does not actually set the instance attribute; instead it sets the value stored with the instance's Property.
If you ask for story.__dict__['title'], what does it give you?
I do understand that a.var and A.var are different variables
First off: as of now, no, they aren't.
In Python, everything you declare inside the class block belongs to the class. You can look up attributes of the class via the instance, if the instance doesn't already have something with that name. When you assign to an attribute of an instance, the instance now has that attribute, regardless of whether it had one before. (__init__, in this regard, is just another function; it's called automatically by Python's machinery, but it simply adds attributes to an object, it doesn't magically specify some kind of template for the contents of all instances of the class - there's the magic __slots__ class attribute for that, but it still doesn't do quite what you might expect.)
But right now, a has no .var of its own, so a.var refers to A.var. And you can modify a class attribute via an instance - but note modify, not replace. This requires, of course, that the original value of the attribute is something modifiable - a list qualifies, a str doesn't.
Your GAE example, though, is something totally different. The class Story has attributes which specifically are "properties", which can do assorted magic when you "assign to" them. This works by using the class' __getattr__, __setattr__ etc. methods to change the behaviour of the assignment syntax.
The other answers have it mostly right, but miss one critical thing.
If you define a class like this:
class Foo(object):
a = 5
and an instance:
myinstance = Foo()
Then Foo.a and myinstance.a are the very same variable. Changing one will change the other, and if you create multiple instances of Foo, the .a property on each will be the same variable. This is because of the way Python resolves attribute access: First it looks in the object's dict, and if it doesn't find it there, it looks in the class's dict, and so forth.
That also helps explain why assignments don't work the way you'd expect given the shared nature of the variable:
>>> bar = Foo()
>>> baz = Foo()
>>> Foo.a = 6
>>> bar.a = 7
>>> bar.a
7
>>> baz.a
6
What happened here is that when we assigned to Foo.a, it modified the variable that all instance of Foo normally resolve when you ask for instance.a. But when we assigned to bar.a, Python created a new variable on that instance called a, which now masks the class variable - from now on, that particular instance will always see its own local value.
If you wanted each instance of your class to have a separate variable initialized to 5, the normal way to do it would be like this:
class Foo(object);
def __init__(self):
self.a = 5
That is, you define a class with a constructor that sets the a variable on the new instance to 5.
Finally, what App Engine is doing is an entirely different kind of black magic called descriptors. In short, Python allows objects to define special __get__ and __set__ methods. When an instance of a class that defines these special methods is attached to a class, and you create an instance of that class, attempts to access the attribute will, instead of setting or returning the instance or class variable, they call the special __get__ and __set__ methods. A much more comprehensive introduction to descriptors can be found here, but here's a simple demo:
class MultiplyDescriptor(object):
def __init__(self, multiplicand, initial=0):
self.multiplicand = multiplicand
self.value = initial
def __get__(self, obj, objtype):
if obj is None:
return self
return self.multiplicand * self.value
def __set__(self, obj, value):
self.value = value
Now you can do something like this:
class Foo(object):
a = MultiplyDescriptor(2)
bar = Foo()
bar.a = 10
print bar.a # Prints 20!
Descriptors are the secret sauce behind a surprising amount of the Python language. For instance, property is implemented using descriptors, as are methods, static and class methods, and a bunch of other stuff.
These class variables are metadata to Google App Engine generate their models.
FYI, in your example, a.var == A.var.
>>> class A:
... var = 0
...
... a = A()
... A.var = 3
... a.var == A.var
1: True

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