7. Simple statements
********************

A simple statement is 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
                | annotated_assignment_stmt
                | pass_stmt
                | del_stmt
                | return_stmt
                | yield_stmt
                | raise_stmt
                | break_stmt
                | continue_stmt
                | import_stmt
                | future_stmt
                | global_stmt
                | nonlocal_stmt
                | type_stmt


7.1. 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: starred_expression

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.)


7.2. 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 "=")+ (starred_expression | yield_expression)
   target_list:     target ("," target)* [","]
   target:          identifier
                    | "(" [target_list] ")"
                    | "[" [target_list] "]"
                    | attributeref
                    | subscription
                    | slicing
                    | "*" target

(See section Primaries for the syntax definitions for *attributeref*,
*subscription*, and *slicing*.)

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 with no trailing comma,
  optionally in parentheses, the object is assigned to that target.

* Else:

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

  * Else: 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" 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 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 right-hand side
  expression, "a.x" can access either an instance attribute or (if no
  instance attribute exists) a class attribute.  The left-hand side
  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 right-hand side expression
  refers to a class attribute, the left-hand side 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/value 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 target
  sequence 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.

Although the definition of assignment implies that overlaps between
the left-hand side and the right-hand side are 'simultaneous' (for
example "a, b = b, a" swaps two variables), overlaps *within* the
collection of assigned-to variables occur left-to-right, sometimes
resulting in confusion.  For instance, the following program prints
"[0, 2]":

   x = [0, 1]
   i = 0
   i, x[i] = 1, 2         # i is updated, then x[i] is updated
   print(x)

See also:

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


7.2.1. 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 of 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 statement 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.

Unlike normal assignments, augmented assignments evaluate the left-
hand side *before* evaluating the right-hand side.  For example, "a[i]
+= f(x)" first looks-up "a[i]", then it evaluates "f(x)" and performs
the addition, and lastly, it writes the result back to "a[i]".

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.


7.2.2. Annotated assignment statements
--------------------------------------

*Annotation* assignment is the combination, in a single statement, of
a variable or attribute annotation and an optional assignment
statement:

   annotated_assignment_stmt: augtarget ":" expression
                              ["=" (starred_expression | yield_expression)]

The difference from normal Assignment statements is that only a single
target is allowed.

The assignment target is considered "simple" if it consists of a
single name that is not enclosed in parentheses. For simple assignment
targets, if in class or module scope, the annotations are gathered in
a lazily evaluated annotation scope. The annotations can be evaluated
using the "__annotations__" attribute of a class or module, or using
the facilities in the "annotationlib" module.

If the assignment target is not simple (an attribute, subscript node,
or parenthesized name), the annotation is never evaluated.

If a name is annotated in a function scope, then this name is local
for that scope. Annotations are never evaluated and stored in function
scopes.

If the right hand side is present, an annotated assignment performs
the actual assignment as if there was no annotation present. If the
right hand side is not present for an expression target, then the
interpreter evaluates the target except for the last "__setitem__()"
or "__setattr__()" call.

See also:

  **PEP 526** - Syntax for Variable Annotations
     The proposal that added syntax for annotating the types of
     variables (including class variables and instance variables),
     instead of expressing them through comments.

  **PEP 484** - Type hints
     The proposal that added the "typing" module to provide a standard
     syntax for type annotations that can be used in static analysis
     tools and IDEs.

Changed in version 3.8: Now annotated assignments allow the same
expressions in the right hand side as regular assignments. Previously,
some expressions (like un-parenthesized tuple expressions) caused a
syntax error.

Changed in version 3.14: Annotations are now lazily evaluated in a
separate annotation scope. If the assignment target is not simple,
annotations are never evaluated.


7.3. 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.


7.4. 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)


7.5. 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.  Trying to delete an unbound name
raises a "NameError" exception.

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: Previously it was illegal to delete a name
from the local namespace if it occurs as a free variable in a nested
block.


7.6. 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 indicates that the
generator is done and will cause "StopIteration" to be raised. The
returned value (if any) is used as an argument to construct
"StopIteration" and becomes the "StopIteration.value" attribute.

In an asynchronous generator function, an empty "return" statement
indicates that the asynchronous generator is done and will cause
"StopAsyncIteration" to be raised.  A non-empty "return" statement is
a syntax error in an asynchronous generator function.


7.7. The "yield" statement
==========================

   yield_stmt: yield_expression

A "yield" statement is semantically equivalent to a yield expression.
The "yield" statement can be used to omit the parentheses that would
otherwise be required in the equivalent yield expression statement.
For example, the yield statements

   yield <expr>
   yield from <expr>

are equivalent to the yield expression statements

   (yield <expr>)
   (yield from <expr>)

Yield expressions and statements are only used when defining a
*generator* function, and are only used in the body of the generator
function.  Using "yield" in a function definition is sufficient to
cause that definition to create a generator function instead of a
normal function.

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


7.8. The "raise" statement
==========================

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

If no expressions are present, "raise" re-raises the exception that is
currently being handled, which is also known as the *active
exception*. If there isn't currently an active exception, a
"RuntimeError" exception is raised indicating that this is an error.

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. 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. If the
second expression is an exception instance, it will be attached to the
raised exception as the "__cause__" attribute (which is writable). If
the expression is an exception class, the class will be instantiated
and the resulting exception instance will be attached to the raised
exception as the "__cause__" attribute. 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>
       print(1 / 0)
             ~~^~~
   ZeroDivisionError: division by zero

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

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

A similar mechanism works implicitly if a new exception is raised when
an exception is already being handled.  An exception may be handled
when an "except" or "finally" clause, or a "with" statement, is used.
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>
       print(1 / 0)
             ~~^~~
   ZeroDivisionError: division by zero

   During handling of the above exception, another exception occurred:

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

Exception chaining can be explicitly suppressed by specifying "None"
in the "from" clause:

   >>> try:
   ...     print(1 / 0)
   ... except:
   ...     raise RuntimeError("Something bad happened") from None
   ...
   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.

Changed in version 3.3: "None" is now permitted as "Y" in "raise X
from Y".Added the "__suppress_context__" attribute to suppress
automatic display of the exception context.

Changed in version 3.11: If the traceback of the active exception is
modified in an "except" clause, a subsequent "raise" statement re-
raises the exception with the modified traceback. Previously, the
exception was re-raised with the traceback it had when it was caught.


7.9. 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.


7.10. 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 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.


7.11. The "import" statement
============================

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

The basic import statement (no "from" clause) is executed in two
steps:

1. find a module, loading and initializing it if necessary

2. define a name or names in the local namespace for the scope where
   the "import" statement occurs.

When the statement contains multiple clauses (separated by commas) the
two steps are carried out separately for each clause, just as though
the clauses had been separated out into individual import statements.

The details of the first step, finding and loading modules, are
described in greater detail in the section on the import system, which
also describes the various types of packages and modules that can be
imported, as well as all the hooks that can be used to customize the
import system. Note that failures in this step may indicate either
that the module could not be located, *or* that an error occurred
while initializing the module, which includes execution of the
module's code.

If the requested module is retrieved successfully, it will be made
available in the local namespace in one of three ways:

* If the module name is followed by "as", then the name following "as"
  is bound directly to the imported module.

* If no other name is specified, and the module being imported is a
  top level module, the module's name is bound in the local namespace
  as a reference to the imported module

* If the module being imported is *not* a top level module, then the
  name of the top level package that contains the module is bound in
  the local namespace as a reference to the top level package. The
  imported module must be accessed using its full qualified name
  rather than directly

The "from" form uses a slightly more complex process:

1. find the module specified in the "from" clause, loading and
   initializing it if necessary;

2. for each of the identifiers specified in the "import" clauses:

   1. check if the imported module has an attribute by that name

   2. if not, attempt to import a submodule with that name and then
      check the imported module again for that attribute

   3. if the attribute is not found, "ImportError" is raised.

   4. otherwise, a reference to that value is stored in the local
      namespace, using the name in the "as" clause if it is present,
      otherwise using the attribute name

Examples:

   import foo                 # foo imported and bound locally
   import foo.bar.baz         # foo, foo.bar, and foo.bar.baz imported, foo bound locally
   import foo.bar.baz as fbb  # foo, foo.bar, and foo.bar.baz imported, foo.bar.baz bound as fbb
   from foo.bar import baz    # foo, foo.bar, and foo.bar.baz imported, foo.bar.baz bound as baz
   from foo import attr       # foo imported and foo.attr bound as attr

If the list of identifiers is replaced by a star ("'*'"), all public
names defined in the module are bound in the local namespace for the
scope where the "import" statement occurs.

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 wild card form of import --- "from module 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 in the Package
Relative Imports section.

"importlib.import_module()" is provided to support applications that
determine dynamically the modules to be loaded.

Raises an auditing event "import" with arguments "module", "filename",
"sys.path", "sys.meta_path", "sys.path_hooks".


7.11.1. 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 where the feature
becomes standard.

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_stmt: "from" "__future__" "import" feature ["as" identifier]
                ("," feature ["as" identifier])*
                | "from" "__future__" "import" "(" feature ["as" identifier]
                ("," feature ["as" identifier])* [","] ")"
   feature:     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 only feature that requires using the future statement is
"annotations" (see **PEP 563**).

All historical features enabled by the future statement are still
recognized by Python 3.  The list includes "absolute_import",
"division", "generators", "generator_stop", "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.


7.12. The "global" statement
============================

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

The "global" statement causes the listed identifiers 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.

The "global" statement applies to the entire current scope (module,
function body or class definition). A "SyntaxError" is raised if a
variable is used or assigned to prior to its global declaration in the
scope.

At the module level, all variables are global, so a "global" statement
has no effect. However, variables must still not be used or assigned
to prior to their "global" declaration. This requirement is relaxed in
the interactive prompt (*REPL*).

**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 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.


7.13. The "nonlocal" statement
==============================

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

When the definition of a function or class is nested (enclosed) within
the definitions of other functions, its nonlocal scopes are the local
scopes of the enclosing functions. The "nonlocal" statement causes the
listed identifiers to refer to names previously bound in nonlocal
scopes. It allows encapsulated code to rebind such nonlocal
identifiers.  If a name is bound in more than one nonlocal scope, the
nearest binding is used. If a name is not bound in any nonlocal scope,
or if there is no nonlocal scope, a "SyntaxError" is raised.

The "nonlocal" statement applies to the entire scope of a function or
class body. A "SyntaxError" is raised if a variable is used or
assigned to prior to its nonlocal declaration in the scope.

See also:

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

**Programmer's note:** "nonlocal" is a directive to the parser and
applies only to code parsed along with it.  See the note for the
"global" statement.


7.14. The "type" statement
==========================

   type_stmt: 'type' identifier [type_params] "=" expression

The "type" statement declares a type alias, which is an instance of
"typing.TypeAliasType".

For example, the following statement creates a type alias:

   type Point = tuple[float, float]

This code is roughly equivalent to:

   annotation-def VALUE_OF_Point():
       return tuple[float, float]
   Point = typing.TypeAliasType("Point", VALUE_OF_Point())

"annotation-def" indicates an annotation scope, which behaves mostly
like a function, but with several small differences.

The value of the type alias is evaluated in the annotation scope. It
is not evaluated when the type alias is created, but only when the
value is accessed through the type alias's "__value__" attribute (see
Lazy evaluation). This allows the type alias to refer to names that
are not yet defined.

Type aliases may be made generic by adding a type parameter list after
the name. See Generic type aliases for more.

"type" is a soft keyword.

Added in version 3.12.

See also:

  **PEP 695** - Type Parameter Syntax
     Introduced the "type" statement and syntax for generic classes
     and functions.
