When referring to namespaces, always say "namespaces" instead of

"name spaces".

Inconsistency noted by Keith Briggs <keith.briggs@bt.com>.
This commit is contained in:
Fred Drake 2000-09-12 16:23:48 +00:00
parent 81cccb7563
commit 1349437e4c
4 changed files with 54 additions and 53 deletions

View File

@ -3242,18 +3242,18 @@ subject is useful for any advanced Python programmer.
Let's begin with some definitions.
A \emph{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 \function{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.
A \emph{namespace} 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 (functions such as \function{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 \emph{attribute} for any name following a
dot --- for example, in the expression \code{z.real}, \code{real} is
@ -3262,12 +3262,12 @@ names in modules are attribute references: in the expression
\code{modname.funcname}, \code{modname} is a module object and
\code{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!\footnote{
global names defined in the module: they share the same namespace!
\footnote{
Except for one thing. Module objects have a secret read-only
attribute called \code{__dict__} which returns the dictionary
attribute called \member{__dict__} which returns the dictionary
used to implement the module's namespace; the name
\code{__dict__} is an attribute but not a global name.
\member{__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.
@ -3297,10 +3297,10 @@ 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.
A \emph{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.
A \emph{scope} is 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, exactly three nested scopes are in use
@ -3316,13 +3316,13 @@ the same name space as the global scope: the module's name space.
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 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.)
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 assignments always go into the
innermost scope. Assignments do not copy data --- they just
@ -3766,9 +3766,10 @@ code that is byte-compiled together. The same restriction applies to
when referencing \code{__dict__} directly.
Here's an example of a class that implements its own
\code{__getattr__} and \code{__setattr__} methods and stores all
attributes in a private variable, in a way that works in Python 1.4 as
well as in previous versions:
\method{__getattr__()} and \method{__setattr__()} methods and stores
all attributes in a private variable, in a way that works in all
versions of Python, including those available before this feature was
added:
\begin{verbatim}
class VirtualAttributes: