
Simple statements
*****************

Simple statements are comprised within a single logical line. Several
simple statements may occur on a single line separated by semicolons.
The syntax for simple statements is:

   simple_stmt ::= expression_stmt
                   | assert_stmt
                   | assignment_stmt
                   | augmented_assignment_stmt
                   | pass_stmt
                   | del_stmt
                   | return_stmt
                   | yield_stmt
                   | raise_stmt
                   | break_stmt
                   | continue_stmt
                   | import_stmt
                   | global_stmt
                   | nonlocal_stmt


Expression statements
=====================

Expression statements are used (mostly interactively) to compute and
write a value, or (usually) to call a procedure (a function that
returns no meaningful result; in Python, procedures return the value
``None``).  Other uses of expression statements are allowed and
occasionally useful.  The syntax for an expression statement is:

   expression_stmt ::= expression_list

An expression statement evaluates the expression list (which may be a
single expression).

In interactive mode, if the value is not ``None``, it is converted to
a string using the built-in ``repr()`` function and the resulting
string is written to standard output on a line by itself (except if
the result is ``None``, so that procedure calls do not cause any
output.)


Assignment statements
=====================

Assignment statements are used to (re)bind names to values and to
modify attributes or items of mutable objects:

   assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)
   target_list     ::= target ("," target)* [","]
   target          ::= identifier
              | "(" target_list ")"
              | "[" target_list "]"
              | attributeref
              | subscription
              | slicing
              | "*" target

(See section *Primaries* for the syntax definitions for the last three
symbols.)

An assignment statement evaluates the expression list (remember that
this can be a single expression or a comma-separated list, the latter
yielding a tuple) and assigns the single resulting object to each of
the target lists, from left to right.

Assignment is defined recursively depending on the form of the target
(list). When a target is part of a mutable object (an attribute
reference, subscription or slicing), the mutable object must
ultimately perform the assignment and decide about its validity, and
may raise an exception if the assignment is unacceptable.  The rules
observed by various types and the exceptions raised are given with the
definition of the object types (see section *The standard type
hierarchy*).

Assignment of an object to a target list, optionally enclosed in
parentheses or square brackets, is recursively defined as follows.

* If the target list is a single target: The object is assigned to
  that target.

* If the target list is a comma-separated list of targets: The object
  must be an iterable with the same number of items as there are
  targets in the target list, and the items are assigned, from left to
  right, to the corresponding targets. (This rule is relaxed as of
  Python 1.5; in earlier versions, the object had to be a tuple.
  Since strings are sequences, an assignment like ``a, b = "xy"`` is
  now legal as long as the string has the right length.)

  * If the target list contains one target prefixed with an asterisk,
    called a "starred" target: The object must be a sequence with at
    least as many items as there are targets in the target list, minus
    one.  The first items of the sequence are assigned, from left to
    right, to the targets before the starred target.  The final items
    of the sequence are assigned to the targets after the starred
    target.  A list of the remaining items in the sequence is then
    assigned to the starred target (the list can be empty).

  * Else: The object must be a sequence with the same number of items
    as there are targets in the target list, and the items are
    assigned, from left to right, to the corresponding targets.

Assignment of an object to a single target is recursively defined as
follows.

* If the target is an identifier (name):

  * If the name does not occur in a ``global`` or ``nonlocal``
    statement in the current code block: the name is bound to the
    object in the current local namespace.

  * Otherwise: the name is bound to the object in the global namespace
    or the outer namespace determined by ``nonlocal``, respectively.

  The name is rebound if it was already bound.  This may cause the
  reference count for the object previously bound to the name to reach
  zero, causing the object to be deallocated and its destructor (if it
  has one) to be called.

* If the target is a target list enclosed in parentheses or in square
  brackets: The object must be an iterable with the same number of
  items as there are targets in the target list, and its items are
  assigned, from left to right, to the corresponding targets.

* If the target is an attribute reference: The primary expression in
  the reference is evaluated.  It should yield an object with
  assignable attributes; if this is not the case, ``TypeError`` is
  raised.  That object is then asked to assign the assigned object to
  the given attribute; if it cannot perform the assignment, it raises
  an exception (usually but not necessarily ``AttributeError``).

  Note: If the object is a class instance and the attribute reference
  occurs on both sides of the assignment operator, the RHS expression,
  ``a.x`` can access either an instance attribute or (if no instance
  attribute exists) a class attribute.  The LHS target ``a.x`` is
  always set as an instance attribute, creating it if necessary.
  Thus, the two occurrences of ``a.x`` do not necessarily refer to the
  same attribute: if the RHS expression refers to a class attribute,
  the LHS creates a new instance attribute as the target of the
  assignment:

     class Cls:
         x = 3             # class variable
     inst = Cls()
     inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3

  This description does not necessarily apply to descriptor
  attributes, such as properties created with ``property()``.

* If the target is a subscription: The primary expression in the
  reference is evaluated.  It should yield either a mutable sequence
  object (such as a list) or a mapping object (such as a dictionary).
  Next, the subscript expression is evaluated.

  If the primary is a mutable sequence object (such as a list), the
  subscript must yield an integer.  If it is negative, the sequence's
  length is added to it.  The resulting value must be a nonnegative
  integer less than the sequence's length, and the sequence is asked
  to assign the assigned object to its item with that index.  If the
  index is out of range, ``IndexError`` is raised (assignment to a
  subscripted sequence cannot add new items to a list).

  If the primary is a mapping object (such as a dictionary), the
  subscript must have a type compatible with the mapping's key type,
  and the mapping is then asked to create a key/datum pair which maps
  the subscript to the assigned object.  This can either replace an
  existing key/value pair with the same key value, or insert a new
  key/value pair (if no key with the same value existed).

  For user-defined objects, the ``__setitem__()`` method is called
  with appropriate arguments.

* If the target is a slicing: The primary expression in the reference
  is evaluated.  It should yield a mutable sequence object (such as a
  list).  The assigned object should be a sequence object of the same
  type.  Next, the lower and upper bound expressions are evaluated,
  insofar they are present; defaults are zero and the sequence's
  length.  The bounds should evaluate to integers. If either bound is
  negative, the sequence's length is added to it.  The resulting
  bounds are clipped to lie between zero and the sequence's length,
  inclusive.  Finally, the sequence object is asked to replace the
  slice with the items of the assigned sequence.  The length of the
  slice may be different from the length of the assigned sequence,
  thus changing the length of the target sequence, if the object
  allows it.

**CPython implementation detail:** In the current implementation, the
syntax for targets is taken to be the same as for expressions, and
invalid syntax is rejected during the code generation phase, causing
less detailed error messages.

WARNING: Although the definition of assignment implies that overlaps
between the left-hand side and the right-hand side are 'safe' (for
example ``a, b = b, a`` swaps two variables), overlaps *within* the
collection of assigned-to variables are not safe!  For instance, the
following program prints ``[0, 2]``:

   x = [0, 1]
   i = 0
   i, x[i] = 1, 2
   print(x)

See also:

   **PEP 3132** - Extended Iterable Unpacking
      The specification for the ``*target`` feature.


Augmented assignment statements
-------------------------------

Augmented assignment is the combination, in a single statement, of a
binary operation and an assignment statement:

   augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)
   augtarget                 ::= identifier | attributeref | subscription | slicing
   augop                     ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="
             | ">>=" | "<<=" | "&=" | "^=" | "|="

(See section *Primaries* for the syntax definitions for the last three
symbols.)

An augmented assignment evaluates the target (which, unlike normal
assignment statements, cannot be an unpacking) and the expression
list, performs the binary operation specific to the type of assignment
on the two operands, and assigns the result to the original target.
The target is only evaluated once.

An augmented assignment expression like ``x += 1`` can be rewritten as
``x = x + 1`` to achieve a similar, but not exactly equal effect. In
the augmented version, ``x`` is only evaluated once. Also, when
possible, the actual operation is performed *in-place*, meaning that
rather than creating a new object and assigning that to the target,
the old object is modified instead.

With the exception of assigning to tuples and multiple targets in a
single statement, the assignment done by augmented assignment
statements is handled the same way as normal assignments. Similarly,
with the exception of the possible *in-place* behavior, the binary
operation performed by augmented assignment is the same as the normal
binary operations.

For targets which are attribute references, the same *caveat about
class and instance attributes* applies as for regular assignments.


The ``assert`` statement
========================

Assert statements are a convenient way to insert debugging assertions
into a program:

   assert_stmt ::= "assert" expression ["," expression]

The simple form, ``assert expression``, is equivalent to

   if __debug__:
      if not expression: raise AssertionError

The extended form, ``assert expression1, expression2``, is equivalent
to

   if __debug__:
      if not expression1: raise AssertionError(expression2)

These equivalences assume that ``__debug__`` and ``AssertionError``
refer to the built-in variables with those names.  In the current
implementation, the built-in variable ``__debug__`` is ``True`` under
normal circumstances, ``False`` when optimization is requested
(command line option -O).  The current code generator emits no code
for an assert statement when optimization is requested at compile
time.  Note that it is unnecessary to include the source code for the
expression that failed in the error message; it will be displayed as
part of the stack trace.

Assignments to ``__debug__`` are illegal.  The value for the built-in
variable is determined when the interpreter starts.


The ``pass`` statement
======================

   pass_stmt ::= "pass"

``pass`` is a null operation --- when it is executed, nothing happens.
It is useful as a placeholder when a statement is required
syntactically, but no code needs to be executed, for example:

   def f(arg): pass    # a function that does nothing (yet)

   class C: pass       # a class with no methods (yet)


The ``del`` statement
=====================

   del_stmt ::= "del" target_list

Deletion is recursively defined very similar to the way assignment is
defined. Rather that spelling it out in full details, here are some
hints.

Deletion of a target list recursively deletes each target, from left
to right.

Deletion of a name removes the binding of that name from the local or
global namespace, depending on whether the name occurs in a ``global``
statement in the same code block.  If the name is unbound, a
``NameError`` exception will be raised.

Deletion of attribute references, subscriptions and slicings is passed
to the primary object involved; deletion of a slicing is in general
equivalent to assignment of an empty slice of the right type (but even
this is determined by the sliced object).

Changed in version 3.2.


The ``return`` statement
========================

   return_stmt ::= "return" [expression_list]

``return`` may only occur syntactically nested in a function
definition, not within a nested class definition.

If an expression list is present, it is evaluated, else ``None`` is
substituted.

``return`` leaves the current function call with the expression list
(or ``None``) as return value.

When ``return`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
leaving the function.

In a generator function, the ``return`` statement is not allowed to
include an ``expression_list``.  In that context, a bare ``return``
indicates that the generator is done and will cause ``StopIteration``
to be raised.


The ``yield`` statement
=======================

   yield_stmt ::= yield_expression

The ``yield`` statement is only used when defining a generator
function, and is only used in the body of the generator function.
Using a ``yield`` statement in a function definition is sufficient to
cause that definition to create a generator function instead of a
normal function. When a generator function is called, it returns an
iterator known as a generator iterator, or more commonly, a generator.
The body of the generator function is executed by calling the
``next()`` function on the generator repeatedly until it raises an
exception.

When a ``yield`` statement is executed, the state of the generator is
frozen and the value of ``expression_list`` is returned to
``next()``'s caller.  By "frozen" we mean that all local state is
retained, including the current bindings of local variables, the
instruction pointer, and the internal evaluation stack: enough
information is saved so that the next time ``next()`` is invoked, the
function can proceed exactly as if the ``yield`` statement were just
another external call.

The ``yield`` statement is allowed in the ``try`` clause of a ``try``
...  ``finally`` construct.  If the generator is not resumed before it
is finalized (by reaching a zero reference count or by being garbage
collected), the generator-iterator's ``close()`` method will be
called, allowing any pending ``finally`` clauses to execute.

See also:

   **PEP 0255** - Simple Generators
      The proposal for adding generators and the ``yield`` statement
      to Python.

   **PEP 0342** - Coroutines via Enhanced Generators
      The proposal that, among other generator enhancements, proposed
      allowing ``yield`` to appear inside a ``try`` ... ``finally``
      block.


The ``raise`` statement
=======================

   raise_stmt ::= "raise" [expression ["from" expression]]

If no expressions are present, ``raise`` re-raises the last exception
that was active in the current scope.  If no exception is active in
the current scope, a ``TypeError`` exception is raised indicating that
this is an error (if running under IDLE, a ``queue.Empty`` exception
is raised instead).

Otherwise, ``raise`` evaluates the first expression as the exception
object.  It must be either a subclass or an instance of
``BaseException``. If it is a class, the exception instance will be
obtained when needed by instantiating the class with no arguments.

The *type* of the exception is the exception instance's class, the
*value* is the instance itself.

A traceback object is normally created automatically when an exception
is raised and attached to it as the ``__traceback__`` attribute, which
is writable. You can create an exception and set your own traceback in
one step using the ``with_traceback()`` exception method (which
returns the same exception instance, with its traceback set to its
argument), like so:

   raise Exception("foo occurred").with_traceback(tracebackobj)

The ``from`` clause is used for exception chaining: if given, the
second *expression* must be another exception class or instance, which
will then be attached to the raised exception as the ``__cause__``
attribute (which is writable).  If the raised exception is not
handled, both exceptions will be printed:

   >>> try:
   ...     print(1 / 0)
   ... except Exception as exc:
   ...     raise RuntimeError("Something bad happened") from exc
   ...
   Traceback (most recent call last):
     File "<stdin>", line 2, in <module>
   ZeroDivisionError: int division or modulo by zero

   The above exception was the direct cause of the following exception:

   Traceback (most recent call last):
     File "<stdin>", line 4, in <module>
   RuntimeError: Something bad happened

A similar mechanism works implicitly if an exception is raised inside
an exception handler: the previous exception is then attached as the
new exception's ``__context__`` attribute:

   >>> try:
   ...     print(1 / 0)
   ... except:
   ...     raise RuntimeError("Something bad happened")
   ...
   Traceback (most recent call last):
     File "<stdin>", line 2, in <module>
   ZeroDivisionError: int division or modulo by zero

   During handling of the above exception, another exception occurred:

   Traceback (most recent call last):
     File "<stdin>", line 4, in <module>
   RuntimeError: Something bad happened

Additional information on exceptions can be found in section
*Exceptions*, and information about handling exceptions is in section
*The try statement*.


The ``break`` statement
=======================

   break_stmt ::= "break"

``break`` may only occur syntactically nested in a ``for`` or
``while`` loop, but not nested in a function or class definition
within that loop.

It terminates the nearest enclosing loop, skipping the optional
``else`` clause if the loop has one.

If a ``for`` loop is terminated by ``break``, the loop control target
keeps its current value.

When ``break`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
leaving the loop.


The ``continue`` statement
==========================

   continue_stmt ::= "continue"

``continue`` may only occur syntactically nested in a ``for`` or
``while`` loop, but not nested in a function or class definition or
``finally`` clause within that loop.  It continues with the next cycle
of the nearest enclosing loop.

When ``continue`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
starting the next loop cycle.


The ``import`` statement
========================

   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*
                   | "from" relative_module "import" identifier ["as" name]
                   ( "," identifier ["as" name] )*
                   | "from" relative_module "import" "(" identifier ["as" name]
                   ( "," identifier ["as" name] )* [","] ")"
                   | "from" module "import" "*"
   module          ::= (identifier ".")* identifier
   relative_module ::= "."* module | "."+
   name            ::= identifier

Import statements are executed in two steps: (1) find a module, and
initialize it if necessary; (2) define a name or names in the local
namespace (of the scope where the ``import`` statement occurs). The
statement comes in two forms differing on whether it uses the ``from``
keyword. The first form (without ``from``) repeats these steps for
each identifier in the list. The form with ``from`` performs step (1)
once, and then performs step (2) repeatedly. For a reference
implementation of step (1), see the ``importlib`` module.

To understand how step (1) occurs, one must first understand how
Python handles hierarchical naming of modules. To help organize
modules and provide a hierarchy in naming, Python has a concept of
packages. A package can contain other packages and modules while
modules cannot contain other modules or packages. From a file system
perspective, packages are directories and modules are files. The
original specification for packages is still available to read,
although minor details have changed since the writing of that
document.

Once the name of the module is known (unless otherwise specified, the
term "module" will refer to both packages and modules), searching for
the module or package can begin. The first place checked is
``sys.modules``, the cache of all modules that have been imported
previously. If the module is found there then it is used in step (2)
of import unless ``None`` is found in ``sys.modules``, in which case
``ImportError`` is raised.

If the module is not found in the cache, then ``sys.meta_path`` is
searched (the specification for ``sys.meta_path`` can be found in
**PEP 302**). The object is a list of *finder* objects which are
queried in order as to whether they know how to load the module by
calling their ``find_module()`` method with the name of the module. If
the module happens to be contained within a package (as denoted by the
existence of a dot in the name), then a second argument to
``find_module()`` is given as the value of the ``__path__`` attribute
from the parent package (everything up to the last dot in the name of
the module being imported). If a finder can find the module it returns
a *loader* (discussed later) or returns ``None``.

If none of the finders on ``sys.meta_path`` are able to find the
module then some implicitly defined finders are queried.
Implementations of Python vary in what implicit meta path finders are
defined. The one they all do define, though, is one that handles
``sys.path_hooks``, ``sys.path_importer_cache``, and ``sys.path``.

The implicit finder searches for the requested module in the "paths"
specified in one of two places ("paths" do not have to be file system
paths). If the module being imported is supposed to be contained
within a package then the second argument passed to ``find_module()``,
``__path__`` on the parent package, is used as the source of paths. If
the module is not contained in a package then ``sys.path`` is used as
the source of paths.

Once the source of paths is chosen it is iterated over to find a
finder that can handle that path. The dict at
``sys.path_importer_cache`` caches finders for paths and is checked
for a finder. If the path does not have a finder cached then
``sys.path_hooks`` is searched by calling each object in the list with
a single argument of the path, returning a finder or raises
``ImportError``. If a finder is returned then it is cached in
``sys.path_importer_cache`` and then used for that path entry. If no
finder can be found but the path exists then a value of ``None`` is
stored in ``sys.path_importer_cache`` to signify that an implicit,
file-based finder that handles modules stored as individual files
should be used for that path. If the path does not exist then a finder
which always returns ``None`` is placed in the cache for the path.

If no finder can find the module then ``ImportError`` is raised.
Otherwise some finder returned a loader whose ``load_module()`` method
is called with the name of the module to load (see **PEP 302** for the
original definition of loaders). A loader has several responsibilities
to perform on a module it loads. First, if the module already exists
in ``sys.modules`` (a possibility if the loader is called outside of
the import machinery) then it is to use that module for initialization
and not a new module. But if the module does not exist in
``sys.modules`` then it is to be added to that dict before
initialization begins. If an error occurs during loading of the module
and it was added to ``sys.modules`` it is to be removed from the dict.
If an error occurs but the module was already in ``sys.modules`` it is
left in the dict.

The loader must set several attributes on the module. ``__name__`` is
to be set to the name of the module. ``__file__`` is to be the "path"
to the file unless the module is built-in (and thus listed in
``sys.builtin_module_names``) in which case the attribute is not set.
If what is being imported is a package then ``__path__`` is to be set
to a list of paths to be searched when looking for modules and
packages contained within the package being imported. ``__package__``
is optional but should be set to the name of package that contains the
module or package (the empty string is used for module not contained
in a package). ``__loader__`` is also optional but should be set to
the loader object that is loading the module.

If an error occurs during loading then the loader raises
``ImportError`` if some other exception is not already being
propagated. Otherwise the loader returns the module that was loaded
and initialized.

When step (1) finishes without raising an exception, step (2) can
begin.

The first form of ``import`` statement binds the module name in the
local namespace to the module object, and then goes on to import the
next identifier, if any.  If the module name is followed by ``as``,
the name following ``as`` is used as the local name for the module.

The ``from`` form does not bind the module name: it goes through the
list of identifiers, looks each one of them up in the module found in
step (1), and binds the name in the local namespace to the object thus
found.  As with the first form of ``import``, an alternate local name
can be supplied by specifying "``as`` localname".  If a name is not
found, ``ImportError`` is raised.  If the list of identifiers is
replaced by a star (``'*'``), all public names defined in the module
are bound in the local namespace of the ``import`` statement.

The *public names* defined by a module are determined by checking the
module's namespace for a variable named ``__all__``; if defined, it
must be a sequence of strings which are names defined or imported by
that module.  The names given in ``__all__`` are all considered public
and are required to exist.  If ``__all__`` is not defined, the set of
public names includes all names found in the module's namespace which
do not begin with an underscore character (``'_'``). ``__all__``
should contain the entire public API. It is intended to avoid
accidentally exporting items that are not part of the API (such as
library modules which were imported and used within the module).

The ``from`` form with ``*`` may only occur in a module scope.  The
wild card form of import --- ``import *`` --- is only allowed at the
module level. Attempting to use it in class or function definitions
will raise a ``SyntaxError``.

When specifying what module to import you do not have to specify the
absolute name of the module. When a module or package is contained
within another package it is possible to make a relative import within
the same top package without having to mention the package name. By
using leading dots in the specified module or package after ``from``
you can specify how high to traverse up the current package hierarchy
without specifying exact names. One leading dot means the current
package where the module making the import exists. Two dots means up
one package level. Three dots is up two levels, etc. So if you execute
``from . import mod`` from a module in the ``pkg`` package then you
will end up importing ``pkg.mod``. If you execute ``from ..subpkg2
import mod`` from within ``pkg.subpkg1`` you will import
``pkg.subpkg2.mod``. The specification for relative imports is
contained within **PEP 328**.

``importlib.import_module()`` is provided to support applications that
determine which modules need to be loaded dynamically.


Future statements
-----------------

A *future statement* is a directive to the compiler that a particular
module should be compiled using syntax or semantics that will be
available in a specified future release of Python.  The future
statement is intended to ease migration to future versions of Python
that introduce incompatible changes to the language.  It allows use of
the new features on a per-module basis before the release in which the
feature becomes standard.

   future_statement ::= "from" "__future__" "import" feature ["as" name]
                        ("," feature ["as" name])*
                        | "from" "__future__" "import" "(" feature ["as" name]
                        ("," feature ["as" name])* [","] ")"
   feature          ::= identifier
   name             ::= identifier

A future statement must appear near the top of the module.  The only
lines that can appear before a future statement are:

* the module docstring (if any),

* comments,

* blank lines, and

* other future statements.

The features recognized by Python 3.0 are ``absolute_import``,
``division``, ``generators``, ``unicode_literals``,
``print_function``, ``nested_scopes`` and ``with_statement``.  They
are all redundant because they are always enabled, and only kept for
backwards compatibility.

A future statement is recognized and treated specially at compile
time: Changes to the semantics of core constructs are often
implemented by generating different code.  It may even be the case
that a new feature introduces new incompatible syntax (such as a new
reserved word), in which case the compiler may need to parse the
module differently.  Such decisions cannot be pushed off until
runtime.

For any given release, the compiler knows which feature names have
been defined, and raises a compile-time error if a future statement
contains a feature not known to it.

The direct runtime semantics are the same as for any import statement:
there is a standard module ``__future__``, described later, and it
will be imported in the usual way at the time the future statement is
executed.

The interesting runtime semantics depend on the specific feature
enabled by the future statement.

Note that there is nothing special about the statement:

   import __future__ [as name]

That is not a future statement; it's an ordinary import statement with
no special semantics or syntax restrictions.

Code compiled by calls to the built-in functions ``exec()`` and
``compile()`` that occur in a module ``M`` containing a future
statement will, by default, use the new syntax or semantics associated
with the future statement.  This can be controlled by optional
arguments to ``compile()`` --- see the documentation of that function
for details.

A future statement typed at an interactive interpreter prompt will
take effect for the rest of the interpreter session.  If an
interpreter is started with the *-i* option, is passed a script name
to execute, and the script includes a future statement, it will be in
effect in the interactive session started after the script is
executed.

See also:

   **PEP 236** - Back to the __future__
      The original proposal for the __future__ mechanism.


The ``global`` statement
========================

   global_stmt ::= "global" identifier ("," identifier)*

The ``global`` statement is a declaration which holds for the entire
current code block.  It means that the listed identifiers are to be
interpreted as globals.  It would be impossible to assign to a global
variable without ``global``, although free variables may refer to
globals without being declared global.

Names listed in a ``global`` statement must not be used in the same
code block textually preceding that ``global`` statement.

Names listed in a ``global`` statement must not be defined as formal
parameters or in a ``for`` loop control target, ``class`` definition,
function definition, or ``import`` statement.

**CPython implementation detail:** The current implementation does not
enforce the latter two restrictions, but programs should not abuse
this freedom, as future implementations may enforce them or silently
change the meaning of the program.

**Programmer's note:** the ``global`` is a directive to the parser.
It applies only to code parsed at the same time as the ``global``
statement. In particular, a ``global`` statement contained in a string
or code object supplied to the built-in ``exec()`` function does not
affect the code block *containing* the function call, and code
contained in such a string is unaffected by ``global`` statements in
the code containing the function call.  The same applies to the
``eval()`` and ``compile()`` functions.


The ``nonlocal`` statement
==========================

   nonlocal_stmt ::= "nonlocal" identifier ("," identifier)*

The ``nonlocal`` statement causes the listed identifiers to refer to
previously bound variables in the nearest enclosing scope.  This is
important because the default behavior for binding is to search the
local namespace first.  The statement allows encapsulated code to
rebind variables outside of the local scope besides the global
(module) scope.

Names listed in a ``nonlocal`` statement, unlike to those listed in a
``global`` statement, must refer to pre-existing bindings in an
enclosing scope (the scope in which a new binding should be created
cannot be determined unambiguously).

Names listed in a ``nonlocal`` statement must not collide with pre-
existing bindings in the local scope.

See also:

   **PEP 3104** - Access to Names in Outer Scopes
      The specification for the ``nonlocal`` statement.

-[ Footnotes ]-

[1] It may occur within an ``except`` or ``else`` clause.  The
    restriction on occurring in the ``try`` clause is implementor's
    laziness and will eventually be lifted.
