Python 3.6.5 Documentation >  Compound statements

Compound statements
*******************

Compound statements contain (groups of) other statements; they affect
or control the execution of those other statements in some way. In
general, compound statements span multiple lines, although in simple
incarnations a whole compound statement may be contained in one line.

The "if", "while" and "for" statements implement traditional control
flow constructs. "try" specifies exception handlers and/or cleanup
code for a group of statements, while the "with" statement allows the
execution of initialization and finalization code around a block of
code. Function and class definitions are also syntactically compound
statements.

A compound statement consists of one or more ‘clauses.’ A clause
consists of a header and a ‘suite.’ The clause headers of a
particular compound statement are all at the same indentation level.
Each clause header begins with a uniquely identifying keyword and ends
with a colon. A suite is a group of statements controlled by a
clause. A suite can be one or more semicolon-separated simple
statements on the same line as the header, following the header’s
colon, or it can be one or more indented statements on subsequent
lines. Only the latter form of a suite can contain nested compound
statements; the following is illegal, mostly because it wouldn’t be
clear to which "if" clause a following "else" clause would belong:

if test1: if test2: print(x)

Also note that the semicolon binds tighter than the colon in this
context, so that in the following example, either all or none of the
"print()" calls are executed:

if x < y < z: print(x); print(y); print(z)

Summarizing:

compound_stmt ::= if_stmt
| while_stmt
| for_stmt
| try_stmt
| with_stmt
| funcdef
| classdef
| async_with_stmt
| async_for_stmt
| async_funcdef
suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT
statement ::= stmt_list NEWLINE | compound_stmt
stmt_list ::= simple_stmt (";" simple_stmt)* [";"]

Note that statements always end in a "NEWLINE" possibly followed by a
"DEDENT". Also note that optional continuation clauses always begin
with a keyword that cannot start a statement, thus there are no
ambiguities (the ‘dangling "else"’ problem is solved in Python by
requiring nested "if" statements to be indented).

The formatting of the grammar rules in the following sections places
each clause on a separate line for clarity.

The "if" statement
==================

The "if" statement is used for conditional execution:

if_stmt ::= "if" expression ":" suite
( "elif" expression ":" suite )*
["else" ":" suite]

It selects exactly one of the suites by evaluating the expressions one
by one until one is found to be true (see section Boolean operations
for the definition of true and false); then that suite is executed
(and no other part of the "if" statement is executed or evaluated).
If all expressions are false, the suite of the "else" clause, if
present, is executed.

The "while" statement
=====================

The "while" statement is used for repeated execution as long as an
expression is true:

while_stmt ::= "while" expression ":" suite
["else" ":" suite]

This repeatedly tests the expression and, if it is true, executes the
first suite; if the expression is false (which may be the first time
it is tested) the suite of the "else" clause, if present, is executed
and the loop terminates.

A "break" statement executed in the first suite terminates the loop
without executing the "else" clause’s suite. A "continue" statement
executed in the first suite skips the rest of the suite and goes back
to testing the expression.

The "for" statement
===================

The "for" statement is used to iterate over the elements of a sequence
(such as a string, tuple or list) or other iterable object:

for_stmt ::= "for" target_list "in" expression_list ":" suite
["else" ":" suite]

The expression list is evaluated once; it should yield an iterable
object. An iterator is created for the result of the
"expression_list". The suite is then executed once for each item
provided by the iterator, in the order returned by the iterator. Each
item in turn is assigned to the target list using the standard rules
for assignments (see Assignment statements), and then the suite is
executed. When the items are exhausted (which is immediately when the
sequence is empty or an iterator raises a "StopIteration" exception),
the suite in the "else" clause, if present, is executed, and the loop
terminates.

A "break" statement executed in the first suite terminates the loop
without executing the "else" clause’s suite. A "continue" statement
executed in the first suite skips the rest of the suite and continues
with the next item, or with the "else" clause if there is no next
item.

The for-loop makes assignments to the variables(s) in the target list.
This overwrites all previous assignments to those variables including
those made in the suite of the for-loop:

for i in range(10):
print(i)
i = 5 # this will not affect the for-loop
# because i will be overwritten with the next
# index in the range

Names in the target list are not deleted when the loop is finished,
but if the sequence is empty, they will not have been assigned to at
all by the loop. Hint: the built-in function "range()" returns an
iterator of integers suitable to emulate the effect of Pascal’s "for i
:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".

Note: There is a subtlety when the sequence is being modified by the
loop (this can only occur for mutable sequences, i.e. lists). An
internal counter is used to keep track of which item is used next,
and this is incremented on each iteration. When this counter has
reached the length of the sequence the loop terminates. This means
that if the suite deletes the current (or a previous) item from the
sequence, the next item will be skipped (since it gets the index of
the current item which has already been treated). Likewise, if the
suite inserts an item in the sequence before the current item, the
current item will be treated again the next time through the loop.
This can lead to nasty bugs that can be avoided by making a
temporary copy using a slice of the whole sequence, e.g.,

for x in a[:]:
if x < 0: a.remove(x)

The "try" statement
===================

The "try" statement specifies exception handlers and/or cleanup code
for a group of statements:

try_stmt ::= try1_stmt | try2_stmt
try1_stmt ::= "try" ":" suite
("except" [expression ["as" identifier]] ":" suite)+
["else" ":" suite]
["finally" ":" suite]
try2_stmt ::= "try" ":" suite
"finally" ":" suite

The "except" clause(s) specify one or more exception handlers. When no
exception occurs in the "try" clause, no exception handler is
executed. When an exception occurs in the "try" suite, a search for an
exception handler is started. This search inspects the except clauses
in turn until one is found that matches the exception. An expression-
less except clause, if present, must be last; it matches any
exception. For an except clause with an expression, that expression
is evaluated, and the clause matches the exception if the resulting
object is “compatible” with the exception. An object is compatible
with an exception if it is the class or a base class of the exception
object or a tuple containing an item compatible with the exception.

If no except clause matches the exception, the search for an exception
handler continues in the surrounding code and on the invocation stack.
[1]

If the evaluation of an expression in the header of an except clause
raises an exception, the original search for a handler is canceled and
a search starts for the new exception in the surrounding code and on
the call stack (it is treated as if the entire "try" statement raised
the exception).

When a matching except clause is found, the exception is assigned to
the target specified after the "as" keyword in that except clause, if
present, and the except clause’s suite is executed. All except
clauses must have an executable block. When the end of this block is
reached, execution continues normally after the entire try statement.
(This means that if two nested handlers exist for the same exception,
and the exception occurs in the try clause of the inner handler, the
outer handler will not handle the exception.)

When an exception has been assigned using "as target", it is cleared
at the end of the except clause. This is as if

except E as N:
foo

was translated to

except E as N:
try:
foo
finally:
del N

This means the exception must be assigned to a different name to be
able to refer to it after the except clause. Exceptions are cleared
because with the traceback attached to them, they form a reference
cycle with the stack frame, keeping all locals in that frame alive
until the next garbage collection occurs.

Before an except clause’s suite is executed, details about the
exception are stored in the "sys" module and can be accessed via
"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the
exception class, the exception instance and a traceback object (see
section The standard type hierarchy) identifying the point in the
program where the exception occurred. "sys.exc_info()" values are
restored to their previous values (before the call) when returning
from a function that handled an exception.

The optional "else" clause is executed if and when control flows off
the end of the "try" clause. [2] Exceptions in the "else" clause are
not handled by the preceding "except" clauses.

If "finally" is present, it specifies a ‘cleanup’ handler. The "try"
clause is executed, including any "except" and "else" clauses. If an
exception occurs in any of the clauses and is not handled, the
exception is temporarily saved. The "finally" clause is executed. If
there is a saved exception it is re-raised at the end of the "finally"
clause. If the "finally" clause raises another exception, the saved
exception is set as the context of the new exception. If the "finally"
clause executes a "return" or "break" statement, the saved exception
is discarded:

>>> def f():
... try:
... 1/0
... finally:
... return 42
...
>>> f()
42

The exception information is not available to the program during
execution of the "finally" clause.

When a "return", "break" or "continue" statement is executed in the
"try" suite of a "try"…"finally" statement, the "finally" clause is
also executed ‘on the way out.’ A "continue" statement is illegal in
the "finally" clause. (The reason is a problem with the current
implementation — this restriction may be lifted in the future).

The return value of a function is determined by the last "return"
statement executed. Since the "finally" clause always executes, a
"return" statement executed in the "finally" clause will always be the
last one executed:

>>> def foo():
... try:
... return 'try'
... finally:
... return 'finally'
...
>>> foo()
'finally'

Additional information on exceptions can be found in section
Exceptions, and information on using the "raise" statement to generate
exceptions may be found in section The raise statement.

The "with" statement
====================

The "with" statement is used to wrap the execution of a block with
methods defined by a context manager (see section With Statement
Context Managers). This allows common "try"…"except"…"finally" usage
patterns to be encapsulated for convenient reuse.

with_stmt ::= "with" with_item ("," with_item)* ":" suite
with_item ::= expression ["as" target]

The execution of the "with" statement with one “item” proceeds as
follows:

1. The context expression (the expression given in the "with_item")
is evaluated to obtain a context manager.

2. The context manager’s "__exit__()" is loaded for later use.

3. The context manager’s "__enter__()" method is invoked.

4. If a target was included in the "with" statement, the return
value from "__enter__()" is assigned to it.

Note: The "with" statement guarantees that if the "__enter__()"
method returns without an error, then "__exit__()" will always be
called. Thus, if an error occurs during the assignment to the
target list, it will be treated the same as an error occurring
within the suite would be. See step 6 below.

5. The suite is executed.

6. The context manager’s "__exit__()" method is invoked. If an
exception caused the suite to be exited, its type, value, and
traceback are passed as arguments to "__exit__()". Otherwise, three
"None" arguments are supplied.

If the suite was exited due to an exception, and the return value
from the "__exit__()" method was false, the exception is reraised.
If the return value was true, the exception is suppressed, and
execution continues with the statement following the "with"
statement.

If the suite was exited for any reason other than an exception, the
return value from "__exit__()" is ignored, and execution proceeds
at the normal location for the kind of exit that was taken.

With more than one item, the context managers are processed as if
multiple "with" statements were nested:

with A() as a, B() as b:
suite

is equivalent to

with A() as a:
with B() as b:
suite

Changed in version 3.1: Support for multiple context expressions.

See also:

**PEP 343** - The “with” statement
The specification, background, and examples for the Python "with"
statement.

Function definitions
====================

A function definition defines a user-defined function object (see
section The standard type hierarchy):

funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite
decorators ::= decorator+
decorator ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE
dotted_name ::= identifier ("." identifier)*
parameter_list ::= defparameter ("," defparameter)* ["," [parameter_list_starargs]]
| parameter_list_starargs
parameter_list_starargs ::= "*" [parameter] ("," defparameter)* ["," ["**" parameter [","]]]
| "**" parameter [","]
parameter ::= identifier [":" expression]
defparameter ::= parameter ["=" expression]
funcname ::= identifier

A function definition is an executable statement. Its execution binds
the function name in the current local namespace to a function object
(a wrapper around the executable code for the function). This
function object contains a reference to the current global namespace
as the global namespace to be used when the function is called.

The function definition does not execute the function body; this gets
executed only when the function is called. [3]

A function definition may be wrapped by one or more *decorator*
expressions. Decorator expressions are evaluated when the function is
defined, in the scope that contains the function definition. The
result must be a callable, which is invoked with the function object
as the only argument. The returned value is bound to the function name
instead of the function object. Multiple decorators are applied in
nested fashion. For example, the following code

@f1(arg)
@f2
def func(): pass

is roughly equivalent to

def func(): pass
func = f1(arg)(f2(func))

except that the original function is not temporarily bound to the name
"func".

When one or more *parameters* have the form *parameter* "="
*expression*, the function is said to have “default parameter values.”
For a parameter with a default value, the corresponding *argument* may
be omitted from a call, in which case the parameter’s default value is
substituted. If a parameter has a default value, all following
parameters up until the “"*"” must also have a default value — this is
a syntactic restriction that is not expressed by the grammar.

**Default parameter values are evaluated from left to right when the
function definition is executed.** This means that the expression is
evaluated once, when the function is defined, and that the same “pre-
computed” value is used for each call. This is especially important
to understand when a default parameter is a mutable object, such as a
list or a dictionary: if the function modifies the object (e.g. by
appending an item to a list), the default value is in effect modified.
This is generally not what was intended. A way around this is to use
"None" as the default, and explicitly test for it in the body of the
function, e.g.:

def whats_on_the_telly(penguin=None):
if penguin is None:
penguin = []
penguin.append("property of the zoo")
return penguin

Function call semantics are described in more detail in section Calls.
A function call always assigns values to all parameters mentioned in
the parameter list, either from position arguments, from keyword
arguments, or from default values. If the form “"*identifier"” is
present, it is initialized to a tuple receiving any excess positional
parameters, defaulting to the empty tuple. If the form
“"**identifier"” is present, it is initialized to a new ordered
mapping receiving any excess keyword arguments, defaulting to a new
empty mapping of the same type. Parameters after “"*"” or
“"*identifier"” are keyword-only parameters and may only be passed
used keyword arguments.

Parameters may have annotations of the form “": expression"” following
the parameter name. Any parameter may have an annotation even those
of the form "*identifier" or "**identifier". Functions may have
“return” annotation of the form “"-> expression"” after the parameter
list. These annotations can be any valid Python expression and are
evaluated when the function definition is executed. Annotations may
be evaluated in a different order than they appear in the source code.
The presence of annotations does not change the semantics of a
function. The annotation values are available as values of a
dictionary keyed by the parameters’ names in the "__annotations__"
attribute of the function object.

It is also possible to create anonymous functions (functions not bound
to a name), for immediate use in expressions. This uses lambda
expressions, described in section Lambdas. Note that the lambda
expression is merely a shorthand for a simplified function definition;
a function defined in a “"def"” statement can be passed around or
assigned to another name just like a function defined by a lambda
expression. The “"def"” form is actually more powerful since it
allows the execution of multiple statements and annotations.

**Programmer’s note:** Functions are first-class objects. A “"def"”
statement executed inside a function definition defines a local
function that can be returned or passed around. Free variables used
in the nested function can access the local variables of the function
containing the def. See section Naming and binding for details.

See also:

**PEP 3107** - Function Annotations
The original specification for function annotations.

Class definitions
=================

A class definition defines a class object (see section The standard
type hierarchy):

classdef ::= [decorators] "class" classname [inheritance] ":" suite
inheritance ::= "(" [argument_list] ")"
classname ::= identifier

A class definition is an executable statement. The inheritance list
usually gives a list of base classes (see Metaclasses for more
advanced uses), so each item in the list should evaluate to a class
object which allows subclassing. Classes without an inheritance list
inherit, by default, from the base class "object"; hence,

class Foo:
pass

is equivalent to

class Foo(object):
pass

The class’s suite is then executed in a new execution frame (see
Naming and binding), using a newly created local namespace and the
original global namespace. (Usually, the suite contains mostly
function definitions.) When the class’s suite finishes execution, its
execution frame is discarded but its local namespace is saved. [4] A
class object is then created using the inheritance list for the base
classes and the saved local namespace for the attribute dictionary.
The class name is bound to this class object in the original local
namespace.

The order in which attributes are defined in the class body is
preserved in the new class’s "__dict__". Note that this is reliable
only right after the class is created and only for classes that were
defined using the definition syntax.

Class creation can be customized heavily using metaclasses.

Classes can also be decorated: just like when decorating functions,

@f1(arg)
@f2
class Foo: pass

is roughly equivalent to

class Foo: pass
Foo = f1(arg)(f2(Foo))

The evaluation rules for the decorator expressions are the same as for
function decorators. The result is then bound to the class name.

**Programmer’s note:** Variables defined in the class definition are
class attributes; they are shared by instances. Instance attributes
can be set in a method with "self.name = value". Both class and
instance attributes are accessible through the notation “"self.name"”,
and an instance attribute hides a class attribute with the same name
when accessed in this way. Class attributes can be used as defaults
for instance attributes, but using mutable values there can lead to
unexpected results. Descriptors can be used to create instance
variables with different implementation details.

See also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -
Class Decorators

Coroutines
==========

New in version 3.5.

Coroutine function definition
-----------------------------

async_funcdef ::= [decorators] "async" "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite

Execution of Python coroutines can be suspended and resumed at many
points (see *coroutine*). In the body of a coroutine, any "await" and
"async" identifiers become reserved keywords; "await" expressions,
"async for" and "async with" can only be used in coroutine bodies.

Functions defined with "async def" syntax are always coroutine
functions, even if they do not contain "await" or "async" keywords.

It is a "SyntaxError" to use "yield from" expressions in "async def"
coroutines.

An example of a coroutine function:

async def func(param1, param2):
do_stuff()
await some_coroutine()

The "async for" statement
-------------------------

async_for_stmt ::= "async" for_stmt

An *asynchronous iterable* is able to call asynchronous code in its
*iter* implementation, and *asynchronous iterator* can call
asynchronous code in its *next* method.

The "async for" statement allows convenient iteration over
asynchronous iterators.

The following code:

async for TARGET in ITER:
BLOCK
else:
BLOCK2

Is semantically equivalent to:

iter = (ITER)
iter = type(iter).__aiter__(iter)
running = True
while running:
try:
TARGET = await type(iter).__anext__(iter)
except StopAsyncIteration:
running = False
else:
BLOCK
else:
BLOCK2

See also "__aiter__()" and "__anext__()" for details.

It is a "SyntaxError" to use "async for" statement outside of an
"async def" function.

The "async with" statement
--------------------------

async_with_stmt ::= "async" with_stmt

An *asynchronous context manager* is a *context manager* that is able
to suspend execution in its *enter* and *exit* methods.

The following code:

async with EXPR as VAR:
BLOCK

Is semantically equivalent to:

mgr = (EXPR)
aexit = type(mgr).__aexit__
aenter = type(mgr).__aenter__(mgr)

VAR = await aenter
try:
BLOCK
except:
if not await aexit(mgr, *sys.exc_info()):
raise
else:
await aexit(mgr, None, None, None)

See also "__aenter__()" and "__aexit__()" for details.

It is a "SyntaxError" to use "async with" statement outside of an
"async def" function.

See also: **PEP 492** - Coroutines with async and await syntax

-[ Footnotes ]-

[1] The exception is propagated to the invocation stack unless
there is a "finally" clause which happens to raise another
exception. That new exception causes the old one to be lost.

[2] Currently, control “flows off the end” except in the case of
an exception or the execution of a "return", "continue", or
"break" statement.

[3] A string literal appearing as the first statement in the
function body is transformed into the function’s "__doc__"
attribute and therefore the function’s *docstring*.

[4] A string literal appearing as the first statement in the class
body is transformed into the namespace’s "__doc__" item and
therefore the class’s *docstring*.