• No results found

Python Scopes and Namespaces

In document and the Python development team (Page 73-76)

CHAPTER

NINE

CLASSES

Classes provide a means of bundling data and functionality together. Creating a new class creates a newtype of object, allowing newinstancesof that type to be made. Each class instance can have attributes attached to it for maintaining its state. Class instances can also have methods (defined by its class) for modifying its state.

Compared with other programming languages, Python’s class mechanism adds classes with a minimum of new syntax and semantics. It is a mixture of the class mechanisms found in C++ and Modula-3. Python classes provide all the standard features of Object Oriented Programming: the class inheritance mechanism allows multiple base classes, a derived class can override any methods of its base class or classes, and a method can call the method of a base class with the same name. Objects can contain arbitrary amounts and kinds of data. As is true for modules, classes partake of the dynamic nature of Python: they are created at runtime, and can be modified further after creation.

In C++ terminology, normally class members (including the data members) are public (except see below Private Variables), and all member functions are virtual. As in Modula-3, there are no shorthands for referencing the object’s members from its methods: the method function is declared with an explicit first argument representing the object, which is provided implicitly by the call. As in Smalltalk, classes themselves are objects. This provides semantics for importing and renaming. Unlike C++ and Modula-3, built-in types can be used as base classes for extension by the user. Also, like in C++, most built-in operators with special syntax (arithmetic operators, subscripting etc.) can be redefined for class instances.

(Lacking universally accepted terminology to talk about classes, I will make occasional use of Smalltalk and C++ terms. I would use Modula-3 terms, since its object-oriented semantics are closer to those of Python than C++, but I expect that few readers have heard of it.)

9.1 A Word About Names and Objects

Objects have individuality, and multiple names (in multiple scopes) can be bound to the same object. This is known as aliasing in other languages. This is usually not appreciated on a first glance at Python, and can be safely ignored when dealing with immutable basic types (numbers, strings, tuples). However, aliasing has a possibly surprising effect on the semantics of Python code involving mutable objects such as lists, dictionaries, and most other types. This is usually used to the benefit of the program, since aliases behave like pointers in some respects. For example, passing an object is cheap since only a pointer is passed by the implementation; and if a function modifies an object passed as an argument, the caller will see the change

— this eliminates the need for two different argument passing mechanisms as in Pascal.

understand what’s going on. Incidentally, knowledge about this subject is useful for any advanced Python programmer.

Let’s begin with some definitions.

Anamespace is a mapping from names to objects. Most namespaces are currently implemented as Python dictionaries, but that’s normally not noticeable in any way (except for performance), and it may change in the future. Examples of namespaces are: the set of built-in names (containing functions such as abs(), and built-in exception names); the global names in a module; and the local names in a function invocation.

In a sense the set of attributes of an object also form a namespace. The important thing to know about namespaces is that there is absolutely no relation between names in different namespaces; for instance, two different modules may both define a function maximize without confusion — users of the modules must prefix it with the module name.

By the way, I use the word attribute for any name following a dot — for example, in the expression z.

real, real is an attribute of the objectz. Strictly speaking, references to names in modules are attribute references: in the expressionmodname.funcname,modnameis a module object andfuncnameis an attribute of it. In this case there happens to be a straightforward mapping between the module’s attributes and the global names defined in the module: they share the same namespace!1

Attributes may be read-only or writable. In the latter case, assignment to attributes is possible. Module attributes are writable: you can writemodname.the_answer = 42. Writable attributes may also be deleted with thedelstatement. For example,del modname.the_answerwill remove the attributethe_answerfrom the object named bymodname.

Namespaces are created at different moments and have different lifetimes. The namespace containing the built-in names is created when the Python interpreter starts up, and is never deleted. The global namespace for a module is created when the module definition is read in; normally, module namespaces also last until the interpreter quits. The statements executed by the top-level invocation of the interpreter, either read from a script file or interactively, are considered part of a module called__main__, so they have their own global namespace. (The built-in names actually also live in a module; this is calledbuiltins.)

The local namespace for a function is created when the function is called, and deleted when the function returns or raises an exception that is not handled within the function. (Actually, forgetting would be a better way to describe what actually happens.) Of course, recursive invocations each have their own local namespace.

Ascopeis a textual region of a Python program where a namespace is directly accessible. “Directly accessible”

here means that an unqualified reference to a name attempts to find the name in the namespace.

Although scopes are determined statically, they are used dynamically. At any time during execution, there are at least three nested scopes whose namespaces are directly accessible:

• the innermost scope, which is searched first, contains the local names

• the scopes of any enclosing functions, which are searched starting with the nearest enclosing scope, contains non-local, but also non-global names

• the next-to-last scope contains the current module’s global names

• the outermost scope (searched last) is the namespace containing built-in names

If a name is declared global, then all references and assignments go directly to the middle scope containing the module’s global names. To rebind variables found outside of the innermost scope, the nonlocalstatement can be used; if not declared nonlocal, those variables are read-only (an attempt to write to such a variable will simply create anew local variable in the innermost scope, leaving the identically named outer variable unchanged).

1 Except for one thing. Module objects have a secret read-only attribute called__dict__which returns the dictionary used to implement the module’s namespace; the name__dict__is an attribute but not a global name. Obviously, using this violates the abstraction of namespace implementation, and should be restricted to things like post-mortem debuggers.

Python Tutorial, Release 3.6.4

Usually, the local scope references the local names of the (textually) current function. Outside functions, the local scope references the same namespace as the global scope: the module’s namespace. Class definitions place yet another namespace in the local scope.

It is important to realize that scopes are determined textually: the global scope of a function defined in a module is that module’s namespace, no matter from where or by what alias the function is called. On the other hand, the actual search for names is done dynamically, at run time — however, the language definition is evolving towards static name resolution, at “compile” time, so don’t rely on dynamic name resolution! (In fact, local variables are already determined statically.)

A special quirk of Python is that – if noglobalstatement is in effect – assignments to names always go into the innermost scope. Assignments do not copy data — they just bind names to objects. The same is true for deletions: the statementdel xremoves the binding ofxfrom the namespace referenced by the local scope.

In fact, all operations that introduce new names use the local scope: in particular,importstatements and function definitions bind the module or function name in the local scope.

Theglobalstatement can be used to indicate that particular variables live in the global scope and should be rebound there; thenonlocalstatement indicates that particular variables live in an enclosing scope and should be rebound there.

9.2.1 Scopes and Namespaces Example

This is an example demonstrating how to reference the different scopes and namespaces, and how global andnonlocalaffect variable binding:

def scope_test():

def do_local():

spam = "local spam"

def do_nonlocal():

nonlocal spam

spam = "nonlocal spam"

def do_global():

global spam

spam = "global spam"

spam = "test spam"

do_local()

print("After local assignment:", spam) do_nonlocal()

print("After nonlocal assignment:", spam) do_global()

print("After global assignment:", spam) scope_test()

print("In global scope:", spam)

The output of the example code is:

After local assignment: test spam After nonlocal assignment: nonlocal spam After global assignment: nonlocal spam In global scope: global spam

Note how thelocalassignment (which is default) didn’t changescope_test’s binding ofspam. Thenonlocal assignment changed scope_test’s binding of spam, and the global assignment changed the module-level binding.

9.2. Python Scopes and Namespaces 69

You can also see that there was no previous binding forspambefore theglobalassignment.

In document and the Python development team (Page 73-76)