6. 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
                   | print_stmt
                   | return_stmt
                   | yield_stmt
                   | raise_stmt
                   | break_stmt
                   | continue_stmt
                   | import_stmt
                   | future_stmt
                   | global_stmt
                   | exec_stmt


6.1. 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 (see section The print statement) on a
line by itself.  (Expression statements yielding "None" are not
written, so that procedure calls do not cause any output.)


6.2. 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

(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 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.

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" 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 current global
    namespace.

  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 a plain 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).

* 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 (small) 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


6.2.1. 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.


6.3. 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.


6.4. 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)


6.5. The "del" statement
========================

   del_stmt ::= "del" target_list

Deletion is recursively defined very similar to the way assignment is
defined. Rather than 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.

It is illegal to delete a name from the local namespace if it occurs
as a free variable in a nested block.

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).


6.6. The "print" statement
==========================

   print_stmt ::= "print" ([expression ("," expression)* [","]]
                  | ">>" expression [("," expression)+ [","]])

"print" evaluates each expression in turn and writes the resulting
object to standard output (see below).  If an object is not a string,
it is first converted to a string using the rules for string
conversions.  The (resulting or original) string is then written.  A
space is written before each object is (converted and) written, unless
the output system believes it is positioned at the beginning of a
line.  This is the case (1) when no characters have yet been written
to standard output, (2) when the last character written to standard
output is a whitespace character except "' '", or (3) when the last
write operation on standard output was not a "print" statement. (In
some cases it may be functional to write an empty string to standard
output for this reason.)

Note:

  Objects which act like file objects but which are not the built-in
  file objects often do not properly emulate this aspect of the file
  object’s behavior, so it is best not to rely on this.

A "'\n'" character is written at the end, unless the "print" statement
ends with a comma.  This is the only action if the statement contains
just the keyword "print".

Standard output is defined as the file object named "stdout" in the
built-in module "sys".  If no such object exists, or if it does not
have a "write()" method, a "RuntimeError" exception is raised.

"print" also has an extended form, defined by the second portion of
the syntax described above. This form is sometimes referred to as
“"print" chevron.” In this form, the first expression after the ">>"
must evaluate to a “file-like” object, specifically an object that has
a "write()" method as described above.  With this extended form, the
subsequent expressions are printed to this file object.  If the first
expression evaluates to "None", then "sys.stdout" is used as the file
for output.


6.7. 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.


6.8. 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 generator’s "next()"
method 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.

As of Python version 2.5, the "yield" statement is now 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.

For full details of "yield" semantics, refer to the Yield expressions
section.

Note:

  In Python 2.2, the "yield" statement was only allowed when the
  "generators" feature has been enabled.  This "__future__" import
  statement was used to enable the feature:

     from __future__ import generators

See also:

  **PEP 255** - Simple Generators
     The proposal for adding generators and the "yield" statement to
     Python.

  **PEP 342** - Coroutines via Enhanced Generators
     The proposal that, among other generator enhancements, proposed
     allowing "yield" to appear inside a "try" … "finally" block.


6.9. The "raise" statement
==========================

   raise_stmt ::= "raise" [expression ["," expression ["," 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 expressions to get three objects,
using "None" as the value of omitted expressions.  The first two
objects are used to determine the *type* and *value* of the exception.

If the first object is an instance, the type of the exception is the
class of the instance, the instance itself is the value, and the
second object must be "None".

If the first object is a class, it becomes the type of the exception.
The second object is used to determine the exception value: If it is
an instance of the class, the instance becomes the exception value. If
the second object is a tuple, it is used as the argument list for the
class constructor; if it is "None", an empty argument list is used,
and any other object is treated as a single argument to the
constructor.  The instance so created by calling the constructor is
used as the exception value.

If a third object is present and not "None", it must be a traceback
object (see section The standard type hierarchy), and it is
substituted instead of the current location as the place where the
exception occurred.  If the third object is present and not a
traceback object or "None", a "TypeError" exception is raised.  The
three-expression form of "raise" is useful to re-raise an exception
transparently in an except clause, but "raise" with no expressions
should be preferred if the exception to be re-raised was the most
recently active exception in the current scope.

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


6.10. 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.


6.11. 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.


6.12. 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.

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.

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.

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.  If the
wild card form of import — "import *" — is used in a function and the
function contains or is a nested block with free variables, the
compiler 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.


6.12.1. 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 2.6 are "unicode_literals",
"print_function", "absolute_import", "division", "generators",
"nested_scopes" and "with_statement".  "generators", "with_statement",
"nested_scopes" are redundant in Python version 2.6 and above because
they are always enabled.

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 an "exec" statement or calls to the built-in
functions "compile()" and "execfile()" 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, starting
with Python 2.2 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.


6.13. 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:** "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 an "exec"
statement does not affect the code block *containing* the "exec"
statement, and code contained in an "exec" statement is unaffected by
"global" statements in the code containing the "exec" statement.  The
same applies to the "eval()", "execfile()" and "compile()" functions.


6.14. The "exec" statement
==========================

   exec_stmt ::= "exec" or_expr ["in" expression ["," expression]]

This statement supports dynamic execution of Python code.  The first
expression should evaluate to either a Unicode string, a *Latin-1*
encoded string, an open file object, a code object, or a tuple.  If it
is a string, the string is parsed as a suite of Python statements
which is then executed (unless a syntax error occurs). [1] If it is an
open file, the file is parsed until EOF and executed. If it is a code
object, it is simply executed.  For the interpretation of a tuple, see
below.  In all cases, the code that’s executed is expected to be valid
as file input (see section File input).  Be aware that the "return"
and "yield" statements may not be used outside of function definitions
even within the context of code passed to the "exec" statement.

In all cases, if the optional parts are omitted, the code is executed
in the current scope.  If only the first expression after "in" is
specified, it should be a dictionary, which will be used for both the
global and the local variables.  If two expressions are given, they
are used for the global and local variables, respectively. If
provided, *locals* can be any mapping object. Remember that at module
level, globals and locals are the same dictionary. If two separate
objects are given as *globals* and *locals*, the code will be executed
as if it were embedded in a class definition.

The first expression may also be a tuple of length 2 or 3.  In this
case, the optional parts must be omitted.  The form "exec(expr,
globals)" is equivalent to "exec expr in globals", while the form
"exec(expr, globals, locals)" is equivalent to "exec expr in globals,
locals".  The tuple form of "exec" provides compatibility with Python
3, where "exec" is a function rather than a statement.

Changed in version 2.4: Formerly, *locals* was required to be a
dictionary.

As a side effect, an implementation may insert additional keys into
the dictionaries given besides those corresponding to variable names
set by the executed code.  For example, the current implementation may
add a reference to the dictionary of the built-in module "__builtin__"
under the key "__builtins__" (!).

**Programmer’s hints:** dynamic evaluation of expressions is supported
by the built-in function "eval()".  The built-in functions "globals()"
and "locals()" return the current global and local dictionary,
respectively, which may be useful to pass around for use by "exec".

-[ Footnotes ]-

[1] Note that the parser only accepts the Unix-style end of line
    convention. If you are reading the code from a file, make sure to
    use *universal newlines* mode to convert Windows or Mac-style
    newlines.
