8. Declarações compostas¶
Declarações compostas contém (grupos de) outras declarações; Elas afetam ou controlam a execução dessas outras declarações de alguma maneira. Em geral, declarações compostas abrangem múltiplas linhas, no entanto em algumas manifestações simples uma declaração composta inteira pode estar contida em uma linha.
As instruções if
, while
e for
implementam construções tradicionais de controle do fluxo de execução. try
especifica tratadores de exceções e/ou código de limpeza para um grupo de instruções, enquanto a palavra reservada with
permite a execução de código de inicialização e finalização em volta de um bloco de código. Definições de função e classe também são sintaticamente instruções compostas.
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 INDENTstatement
+ DEDENT statement ::=stmt_list
NEWLINE |compound_stmt
stmt_list ::=simple_stmt
(";"simple_stmt
)* [";"]
Note que instruções sempre terminam em uma NEWLINE
possivelmente seguida por uma DEDENT
. Note também que cláusulas de continuação sempre começam com uma palavra reservada que não pode iniciar uma instrução, desta forma não há ambiguidades (o problema do else
’ pendurado é resolvido em Python obrigando que instruções if
aninhadas tenham indentação)
A formatação das regras de gramática nas próximas seções põe cada cláusula em uma linha separada para as tornar mais claras.
8.1. 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.
8.2. 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.
8.3. 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]
.
Nota
There is a subtlety when the sequence is being modified by the loop (this can only occur for mutable sequences, e.g. 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)
8.4. 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 A hierarquia de tipos padrão) 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 the control flow leaves the
try
suite, no exception was raised, and no return
,
continue
, or break
statement was executed. 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 Exceções,
and information on using the raise
statement to generate exceptions
may be found in section The raise statement.
8.5. The with
statement¶
The with
statement is used to wrap the execution of a block with
methods defined by a context manager (see section Com gerenciadores de contexto de instruções).
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:
The context expression (the expression given in the
with_item
) is evaluated to obtain a context manager.The context manager’s
__exit__()
is loaded for later use.The context manager’s
__enter__()
method is invoked.If a target was included in the
with
statement, the return value from__enter__()
is assigned to it.Nota
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.The suite is executed.
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, threeNone
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 thewith
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
é equivalente a:
with A() as a:
with B() as b:
suite
Alterado na versão 3.1: Support for multiple context expressions.
8.6. Definições de função¶
A function definition defines a user-defined function object (see section A hierarquia de tipos padrão):
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. 2
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
Nomeação e ligação for details.
Ver também
- PEP 3107 - Function Annotations
The original specification for function annotations.
8.7. Definições de classe¶
A class definition defines a class object (see section A hierarquia de tipos padrão):
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
é equivalente a:
class Foo(object):
pass
The class’s suite is then executed in a new execution frame (see Nomeação e ligação), 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. 3 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.
Ver também
- PEP 3115 - Metaclasses no Python 3000
The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed.
- PEP 3129 - Class Decorators
The proposal that added class decorators. Function and method decorators were introduced in PEP 318.
8.8. Coroutines¶
Novo na versão 3.5.
8.8.1. 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()
8.8.2. 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.
8.8.3. 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.
Ver também
- PEP 492 - Coroutines with async and await syntax
The proposal that made coroutines a proper standalone concept in Python, and added supporting syntax.
Notas de rodapé
- 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
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.- 3
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.