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9.2 Python Scopes and Name Spaces

Before introducing classes, I first have to tell you something about Python's scope rules. Class definitions play some neat tricks with name spaces, and you need to know how scopes and name spaces work to fully understand what's going on. Incidentally, knowledge about this subject is useful for any advanced Python programmer.

Let's begin with some definitions.

A name space is a mapping from names to objects. Most name spaces 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 name spaces are: the set of built-in names (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 name space. The important thing to know about name spaces is that there is absolutely no relation between names in different name spaces; 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 object `z`. Strictly speaking, references to names in modules are attribute references: in the expression `modname.funcname`, `modname` is a module object and `funcname` is 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 name space!9.1

Attributes may be read-only or writable. In the latter case, assignment to attributes is possible. Module attributes are writable: you can write "`modname.the_answer = 42`". Writable attributes may also be deleted with the `del` statement, e.g. "`del modname.the_answer`".

Name spaces are created at different moments and have different lifetimes. The name space containing the built-in names is created when the Python interpreter starts up, and is never deleted. The global name space for a module is created when the module definition is read in; normally, module name spaces 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 name space. (The built-in names actually also live in a module; this is called `__builtin__`.)

The local name space 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 name space.

A scope is a textual region of a Python program where a name space is directly accessible. ``Directly accessible'' here means that an unqualified reference to a name attempts to find the name in the name space.

Although scopes are determined statically, they are used dynamically. At any time during execution, exactly three nested scopes are in use (i.e., exactly three name spaces are directly accessible): the innermost scope, which is searched first, contains the local names, the middle scope, searched next, contains the current module's global names, and the outermost scope (searched last) is the name space containing built-in names.

Usually, the local scope references the local names of the (textually) current function. Outside of functions, the local scope references the same name space as the global scope: the module's name space. Class definitions place yet another name space 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 name space, 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 assignments always go into the innermost scope. Assignments do not copy data -- they just bind names to objects. The same is true for deletions: the statement "`del x`" removes the binding of `x` from the name space referenced by the local scope. In fact, all operations that introduce new names use the local scope: in particular, import statements and function definitions bind the module or function name in the local scope. (The `global` statement can be used to indicate that particular variables live in the global scope.)

#### Footnotes

... space!9.1
  Except for one thing. Module objects have a secret read-only attribute called `__dict__` which returns the dictionary used to implement the module's name space; the name `__dict__` is an attribute but not a global name. Obviously, using this violates the abstraction of name space implementation, and should be restricted to things like post-mortem debuggers.