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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.

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

use of self argument

I am a newcomer to Python. I don't understand how/why the self argument is used:
class Person:
def __init__(self, name):
self.name = name
def sayHi(self):
print 'Hello, my name is', self.name
p = Person('Swaroop')
p.sayHi()
This code is from a Byte of Python. This code could have just as easily been written as:
def sayHi(self, name):
print 'Hello, my name is', name
p = Person('Swaroop')
p.sayHi()
...right? What is the purpose of making name a field of self?

It seems you are oversimplifying a not so simple thing.
In object-oriented programming, a Class is a Declarative Construct which gives a blueprint as to what an object (a manifestation of this blueprint) would contain (properties) and how it would behave (members).
Every manifestation of such a Class is called an Object which has a defined and specific instance. From an object via any of this behavioral attributes called member functions/methods we need somehow to refer to that instance of the object and remember individual elements within it and make a clear distinction with the other non member entities.
Consider Your example
class Person:
def __init__(self, name):
self.name = name
def sayHi(self):
print 'Hello, my name is', self.name
Every Instance of this Person (Tom, Dick, Harry) is unique and within each instance, to refer back to itself we need some idiom like (self in Python, this ptr is C++ or this in Java).
So in the __init__ method when you need to demarcate between the name attribute of Person with the name parameter we can easily do so with self. Not only that, at any instance we can keep on referring back to this name via the self.
Making an instance of Person p=Person('Swaroop') and then invoking sayHi contrasting to calling just a function sayHi which is not a part of an object has two implications
The Function is transient, has no state, no instance and its like Saying this Guy "Hey Mr. who ever you are say 'Hello, my name is Swaroop'". It's like on every run you have to make an imbecile make aware of his name who will forget the next moment you will meet him. It's like this Guy is suffering from Anterograde_amnesia. Calling sayHi of the instance of Person named Swaroop on the other hand would mean something like a physically existing Swaroop greeting back his Name who has a persistent memory and would never forget unless he adopts a new name.
The Function never remembers but forgets every time the call ends. The Person object will remember the name until you explicitly or implicitly Kill That Person.
If you have a background of C++ and might be wondering why on earth do we need to add that extra parameter to the function call where as in C++ this pointer is never passed.
Well Candidly speaking it does. If you read the C++ calling convention, whether X86 or X64, the this pointer is passed through the register ecx to the method to give an handle to itself. This is more explicit here where we deliberately pass the handle to the current instance to the method.

Have a look at the new method sayHiTo:
class Person:
def __init__(self, name):
self.name = name
def sayHi(self):
print 'Hello, my name is', self.name
def sayHiTo(self, other):
print 'Hello', other.name, ' my name is', self.name
p1 = Person('Swaroop')
p2 = Person('codeninja')
p1.sayHiTo(p2)
p2.sayHiTo(p1)

Actually no. Your second example is not correct.
The 'self' keyword is a special reference that is passed to instance methods of a class. It represents the actual instance of the class at that scope. When you make a class it is just a general definition. Then you create instances of that class. Each instance is unique and thus the methods have to be able to work on that instance. You have no way of knowing them until they are made so 'self' passes them in for you.
For instance, if you created two instances of your person class:
p1 = Person("john")
p2 = Person("sam")
self.name value is different for each of those. And when you call sayHi() on each instance:
p1.sayHi()
> Hello, my name is john
p2. sayHi()
> Hello, my name is sam
You would not use the self keyword for unbound functions. That is, just general functions like what you have written as your second example. You would instead have to write it like this;
def sayHi(name):
print 'Hello, my name is', name
p = Person('Swaroop')
p.sayHi()
> sayHi("john")
But that would basically just pass a name string to a Person class and call its method. The idea here is that you create unique instances of Person with their own properties.

The purpose is to store the reference to the name so you can reference it in another method of the class e.g. def sayHi (self)

You can't compare a function in a class to just a function. Sure you can pass in name, but the idea of using a class is that you are encapsulating data. Having vars linked to self means you can pass around an object, and that object can always have access to its 'member variables'. Some other class can use an instance of Person and not need to know that persons name in order to say hi.

What is meant by "classes themselves are objects"?

I was just reading the Python documentation about classes; it says, in Python "classes themselves are objects". How is that different from classes in C#, Java, Ruby, or Smalltalk?
What advantages and disadvantages does this type of classes have compared with those other languages?

In Python, classes are objects in the sense that you can assign them to variables, pass them to functions, etc. just like any other objects. For example
>>> t = type(10)
>>> t
<type 'int'>
>>> len(t.__dict__)
55
>>> t() # construct an int
0
>>> t(10)
10
Java has Class objects which provide some information about a class, but you can't use them in place of explicit class names. They aren't really classes, just class information structures.
Class C = x.getClass();
new C(); // won't work

Declaring a class is simply declaring a variable:
class foo(object):
def bar(self): pass
print foo # <class '__main__.foo'>
They can be assigned and stored like any variable:
class foo(object):
pass
class bar(object):
pass
baz = bar # simple variable assignment
items = [foo, bar]
my_foo = items[0]() # creates a foo
for x in (foo, bar): # create one of each type
print x()
and passed around as a variable:
class foo(object):
def __init__(self):
print "created foo"
def func(f):
f()
func(foo)
They can be created by functions, including the base class list:
def func(base_class, var):
class cls(base_class):
def g(self):
print var
return cls
class my_base(object):
def f(self): print "hello"
new_class = func(my_base, 10)
obj = new_class()
obj.f() # hello
obj.g() # 10
By contrast, while classes in Java have objects representing them, eg. String.class, the class name itself--String--isn't an object and can't be manipulated as one. That's inherent to statically-typed languages.

In C# and Java the classes are not objects. They are types, in the sense in which those languages are statically typed. True you can get an object representing a specific class - but that's not the same as the class itself.
In python what looks like a class is actually an object too.
It's exlpained here much better than I can ever do :)

The main difference is that they mean you can easily manipulate the class as an object. The same facility is available in Java, where you can use the methods of Class to get at information about the class of an object. In languages like Python, Ruby, and Smalltalk, the more dynamic nature of the language lets you "open" the class and change it, which is sometimes called "monkey patching".
Personally I don't think the differences are all that much of a big deal, but I'm sure we can get a good religious war started about it.

Classes are objects in that they are manipulable in Python code just like any object. Others have shown how you can pass them around to functions, allowing them to be operated upon like any object. Here is how you might do this:
class Foo(object):
pass
f = Foo()
f.a = "a" # assigns attribute on instance f
Foo.b = "b" # assigns attribute on class Foo, and thus on all instances including f
print f.a, f.b
Second, like all objects, classes are instantiated at runtime. That is, a class definition is code that is executed rather than a structure that is compiled before anything runs. This means a class can "bake in" things that are only known when the program is run, such as environment variables or user input. These are evaluated once when the class is declared and then become a part of the class. This is different from compiled languages like C# which require this sort of behavior to be implemented differently.
Finally, classes, like any object, are built from classes. Just as an object is built from a class, so is a class built from a special kind of class called a metaclass. You can write your own metaclasses to change how classes are defined.

Another advantage of classes being objects is that objects can change their class at runtime:
>>> class MyClass(object):
... def foo(self):
... print "Yo There! I'm a MyCLass-Object!"
...
>>> class YourClass(object):
... def foo(self):
... print "Guess what?! I'm a YourClass-Object!"
...
>>> o = MyClass()
>>> o.foo()
Yo There! I'm a MyCLass-Object!
>>> o.__class__ = YourClass
>>> o.foo()
Guess what?! I'm a YourClass-Object!
Objects have a special attribute __class__ that points to the class of which they are an instance. This is possible only because classes are objects themself, and therefore can be bound to an attribute like __class__.

As this question has a Smalltalk tag, this answer is from a Smalltalk perspective. In Object-Oriented programming, things get done through message-passing. You send a message to an object, if the object understands that message, it executes the corresponding method and returns a value. But how is the object created in the first place? If special syntax is introduced for creating objects that will break the simple syntax based on message passing. This is what happens in languages like Java:
p = new Point(10, 20); // Creates a new Point object with the help of a special keyword - new.
p.draw(); // Sends the message `draw` to the Point object.
As it is evident from the above code, the language has two ways to get things done - one imperative and the other Object Oriented. In contrast, Smalltalk has a consistent syntax based only on messaging:
p := Point new: 10 y: 20.
p draw.
Here new is a message send to a singleton object called Point which is an instance of a Metaclass. In addition to giving the language a consistent model of computation, metaclasses allow dynamic modification of classes. For instance, the following statement will add a new instance variable to the Point class without requiring a recompilation or VM restart:
Point addInstVarName: 'z'.
The best reading on this subject is The Art of the Metaobject Protocol.