4. Execution model
******************


4.1. Structure of a program
===========================

A Python program is constructed from code blocks. A *block* is a piece
of Python program text that is executed as a unit. The following are
blocks: a module, a function body, and a class definition. Each
command typed interactively is a block.  A script file (a file given
as standard input to the interpreter or specified as a command line
argument to the interpreter) is a code block.  A script command (a
command specified on the interpreter command line with the "-c"
option) is a code block. A module run as a top level script (as module
"__main__") from the command line using a "-m" argument is also a code
block. The string argument passed to the built-in functions "eval()"
and "exec()" is a code block.

A code block is executed in an *execution frame*.  A frame contains
some administrative information (used for debugging) and determines
where and how execution continues after the code block’s execution has
completed.


4.2. Naming and binding
=======================


4.2.1. Binding of names
-----------------------

*Names* refer to objects.  Names are introduced by name binding
operations.

The following constructs bind names:

* formal parameters to functions,

* class definitions,

* function definitions,

* assignment expressions,

* targets that are identifiers if occurring in an assignment:

  * "for" loop header,

  * after "as" in a "with" statement, "except" clause, "except*"
    clause, or in the as-pattern in structural pattern matching,

  * in a capture pattern in structural pattern matching

* "import" statements.

* "type" statements.

* type parameter lists.

The "import" statement of the form "from ... import *" binds all names
defined in the imported module, except those beginning with an
underscore. This form may only be used at the module level.

A target occurring in a "del" statement is also considered bound for
this purpose (though the actual semantics are to unbind the name).

Each assignment or import statement occurs within a block defined by a
class or function definition or at the module level (the top-level
code block).

If a name is bound in a block, it is a local variable of that block,
unless declared as "nonlocal" or "global".  If a name is bound at the
module level, it is a global variable.  (The variables of the module
code block are local and global.)  If a variable is used in a code
block but not defined there, it is a *free variable*.

Each occurrence of a name in the program text refers to the *binding*
of that name established by the following name resolution rules.


4.2.2. Resolution of names
--------------------------

A *scope* defines the visibility of a name within a block.  If a local
variable is defined in a block, its scope includes that block.  If the
definition occurs in a function block, the scope extends to any blocks
contained within the defining one, unless a contained block introduces
a different binding for the name.

When a name is used in a code block, it is resolved using the nearest
enclosing scope.  The set of all such scopes visible to a code block
is called the block’s *environment*.

When a name is not found at all, a "NameError" exception is raised. If
the current scope is a function scope, and the name refers to a local
variable that has not yet been bound to a value at the point where the
name is used, an "UnboundLocalError" exception is raised.
"UnboundLocalError" is a subclass of "NameError".

If a name binding operation occurs anywhere within a code block, all
uses of the name within the block are treated as references to the
current block.  This can lead to errors when a name is used within a
block before it is bound.  This rule is subtle.  Python lacks
declarations and allows name binding operations to occur anywhere
within a code block.  The local variables of a code block can be
determined by scanning the entire text of the block for name binding
operations. See the FAQ entry on UnboundLocalError for examples.

If the "global" statement occurs within a block, all uses of the names
specified in the statement refer to the bindings of those names in the
top-level namespace.  Names are resolved in the top-level namespace by
searching the global namespace, i.e. the namespace of the module
containing the code block, and the builtins namespace, the namespace
of the module "builtins".  The global namespace is searched first.  If
the names are not found there, the builtins namespace is searched
next. If the names are also not found in the builtins namespace, new
variables are created in the global namespace. The global statement
must precede all uses of the listed names.

The "global" statement has the same scope as a name binding operation
in the same block.  If the nearest enclosing scope for a free variable
contains a global statement, the free variable is treated as a global.

The "nonlocal" statement causes corresponding names to refer to
previously bound variables in the nearest enclosing function scope.
"SyntaxError" is raised at compile time if the given name does not
exist in any enclosing function scope. Type parameters cannot be
rebound with the "nonlocal" statement.

The namespace for a module is automatically created the first time a
module is imported.  The main module for a script is always called
"__main__".

Class definition blocks and arguments to "exec()" and "eval()" are
special in the context of name resolution. A class definition is an
executable statement that may use and define names. These references
follow the normal rules for name resolution with an exception that
unbound local variables are looked up in the global namespace. The
namespace of the class definition becomes the attribute dictionary of
the class. The scope of names defined in a class block is limited to
the class block; it does not extend to the code blocks of methods.
This includes comprehensions and generator expressions, but it does
not include annotation scopes, which have access to their enclosing
class scopes. This means that the following will fail:

   class A:
       a = 42
       b = list(a + i for i in range(10))

However, the following will succeed:

   class A:
       type Alias = Nested
       class Nested: pass

   print(A.Alias.__value__)  # <type 'A.Nested'>


4.2.3. Annotation scopes
------------------------

Type parameter lists and "type" statements introduce *annotation
scopes*, which behave mostly like function scopes, but with some
exceptions discussed below. *Annotations* currently do not use
annotation scopes, but they are expected to use annotation scopes in
Python 3.13 when **PEP 649** is implemented.

Annotation scopes are used in the following contexts:

* Type parameter lists for generic type aliases.

* Type parameter lists for generic functions. A generic function’s
  annotations are executed within the annotation scope, but its
  defaults and decorators are not.

* Type parameter lists for generic classes. A generic class’s base
  classes and keyword arguments are executed within the annotation
  scope, but its decorators are not.

* The bounds, constraints, and default values for type parameters
  (lazily evaluated).

* The value of type aliases (lazily evaluated).

Annotation scopes differ from function scopes in the following ways:

* Annotation scopes have access to their enclosing class namespace. If
  an annotation scope is immediately within a class scope, or within
  another annotation scope that is immediately within a class scope,
  the code in the annotation scope can use names defined in the class
  scope as if it were executed directly within the class body. This
  contrasts with regular functions defined within classes, which
  cannot access names defined in the class scope.

* Expressions in annotation scopes cannot contain "yield", "yield
  from", "await", or ":=" expressions. (These expressions are allowed
  in other scopes contained within the annotation scope.)

* Names defined in annotation scopes cannot be rebound with "nonlocal"
  statements in inner scopes. This includes only type parameters, as
  no other syntactic elements that can appear within annotation scopes
  can introduce new names.

* While annotation scopes have an internal name, that name is not
  reflected in the *qualified name* of objects defined within the
  scope. Instead, the "__qualname__" of such objects is as if the
  object were defined in the enclosing scope.

Added in version 3.12: Annotation scopes were introduced in Python
3.12 as part of **PEP 695**.

Changed in version 3.13: Annotation scopes are also used for type
parameter defaults, as introduced by **PEP 696**.


4.2.4. Lazy evaluation
----------------------

The values of type aliases created through the "type" statement are
*lazily evaluated*. The same applies to the bounds, constraints, and
default values of type variables created through the type parameter
syntax. This means that they are not evaluated when the type alias or
type variable is created. Instead, they are only evaluated when doing
so is necessary to resolve an attribute access.

Example:

   >>> type Alias = 1/0
   >>> Alias.__value__
   Traceback (most recent call last):
     ...
   ZeroDivisionError: division by zero
   >>> def func[T: 1/0](): pass
   >>> T = func.__type_params__[0]
   >>> T.__bound__
   Traceback (most recent call last):
     ...
   ZeroDivisionError: division by zero

Here the exception is raised only when the "__value__" attribute of
the type alias or the "__bound__" attribute of the type variable is
accessed.

This behavior is primarily useful for references to types that have
not yet been defined when the type alias or type variable is created.
For example, lazy evaluation enables creation of mutually recursive
type aliases:

   from typing import Literal

   type SimpleExpr = int | Parenthesized
   type Parenthesized = tuple[Literal["("], Expr, Literal[")"]]
   type Expr = SimpleExpr | tuple[SimpleExpr, Literal["+", "-"], Expr]

Lazily evaluated values are evaluated in annotation scope, which means
that names that appear inside the lazily evaluated value are looked up
as if they were used in the immediately enclosing scope.

Added in version 3.12.


4.2.5. Builtins and restricted execution
----------------------------------------

**CPython implementation detail:** Users should not touch
"__builtins__"; it is strictly an implementation detail.  Users
wanting to override values in the builtins namespace should "import"
the "builtins" module and modify its attributes appropriately.

The builtins namespace associated with the execution of a code block
is actually found by looking up the name "__builtins__" in its global
namespace; this should be a dictionary or a module (in the latter case
the module’s dictionary is used).  By default, when in the "__main__"
module, "__builtins__" is the built-in module "builtins"; when in any
other module, "__builtins__" is an alias for the dictionary of the
"builtins" module itself.


4.2.6. Interaction with dynamic features
----------------------------------------

Name resolution of free variables occurs at runtime, not at compile
time. This means that the following code will print 42:

   i = 10
   def f():
       print(i)
   i = 42
   f()

The "eval()" and "exec()" functions do not have access to the full
environment for resolving names.  Names may be resolved in the local
and global namespaces of the caller.  Free variables are not resolved
in the nearest enclosing namespace, but in the global namespace.  [1]
The "exec()" and "eval()" functions have optional arguments to
override the global and local namespace.  If only one namespace is
specified, it is used for both.


4.3. Exceptions
===============

Exceptions are a means of breaking out of the normal flow of control
of a code block in order to handle errors or other exceptional
conditions.  An exception is *raised* at the point where the error is
detected; it may be *handled* by the surrounding code block or by any
code block that directly or indirectly invoked the code block where
the error occurred.

The Python interpreter raises an exception when it detects a run-time
error (such as division by zero).  A Python program can also
explicitly raise an exception with the "raise" statement. Exception
handlers are specified with the "try" … "except" statement.  The
"finally" clause of such a statement can be used to specify cleanup
code which does not handle the exception, but is executed whether an
exception occurred or not in the preceding code.

Python uses the “termination” model of error handling: an exception
handler can find out what happened and continue execution at an outer
level, but it cannot repair the cause of the error and retry the
failing operation (except by re-entering the offending piece of code
from the top).

When an exception is not handled at all, the interpreter terminates
execution of the program, or returns to its interactive main loop.  In
either case, it prints a stack traceback, except when the exception is
"SystemExit".

Exceptions are identified by class instances.  The "except" clause is
selected depending on the class of the instance: it must reference the
class of the instance or a *non-virtual base class* thereof. The
instance can be received by the handler and can carry additional
information about the exceptional condition.

Note:

  Exception messages are not part of the Python API.  Their contents
  may change from one version of Python to the next without warning
  and should not be relied on by code which will run under multiple
  versions of the interpreter.

See also the description of the "try" statement in section The try
statement and "raise" statement in section The raise statement.

-[ Footnotes ]-

[1] This limitation occurs because the code that is executed by these
    operations is not available at the time the module is compiled.
