8. 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.


8.1. "if" 语句
==============

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. "while" 语句
=================

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

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

这将重复地检验表达式，并且如果其值为真就执行第一个子句体；如果表达式值
为假（这可能在第一次检验时就发生）则如果 "else" 子句体存在就会被执行并
终止循环。

第一个子句体中的 "break" 语句在执行时将终止循环且不执行 "else" 子句体
。 第一个子句体中的 "continue" 语句在执行时将跳过子句体中的剩余部分并
返回检验表达式。


8.3. "for" 语句
===============

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]

表达式列表会被求值一次；它应该产生一个可迭代对象。 系统将为
"expression_list" 的结果创建一个迭代器，然后将为迭代器所提供的每一项执
行一次子句体，具体次序与迭代器的返回顺序一致。 每一项会按标准赋值规则
(参见 Assignment statements) 被依次赋值给目标列表，然后子句体将被执行
。 当所有项被耗尽时 (这会在序列为空或迭代器引发 "StopIteration" 异常时
立刻发生)，"else" 子句的子句体如果存在将会被执行，并终止循环。

第一个子句体中的 "break" 语句在执行时将终止循环且不执行 "else" 子句体
。 第一个子句体中的 "continue" 语句在执行时将跳过子句体中的剩余部分并
转往下一项继续执行，或者在没有下一项时转往 "else" 子句执行。

The for-loop makes assignments to the variables 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]".

備註: 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. "try" 语句
===============

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

"except" 子句指定一个或多个异常处理器。 当 "try" 子句中没有发生异常时
，没有异常处理器会被执行。 当 "try" 子句中发生异常时，将启动对异常处理
器的搜索。 此搜索会依次检查 except 子句，直至找到与该异常相匹配的子句
。 如果存在无表达式的 except 子句，它必须是最后一个；它将匹配任何异常
。 对于带有表达式的 except 子句，该表达式会被求值，如果结果对象与发生
的异常“兼容”则该子句将匹配该异常。 一个对象如果是异常对象所属的类或基
类，或者是包含有兼容该异常的项的元组则两者就是兼容的。

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).

当找到一个匹配的 except 子句时，该异常将被赋值给该 except 子句在 "as"
关键字之后指定的目标，如果存在此关键字的话，并且该 except 子句体将被执
行。 所有 except 子句都必须有可执行的子句体。 当到达子句体的末尾时，通
常会转向整个 try 语句之后继续执行。 （这意味着如果对于同一异常存在有嵌
套的两个处理器，而异常发生于内层处理器的 try 子句中，则外层处理器将不
会处理该异常。）

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.

如果控制流离开 "try" 子句体时没有引发异常，并且没有执行 "return",
"continue" 或 "break" 语句，可选的 "else" 子句将被执行。  "else" 语句
中的异常不会由之前的 "except" 子句处理。

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", "break" or "continue" 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.'

函数的返回值是由最后被执行的 "return" 语句所决定的。 由于 "finally" 子
句总是被执行，因此在 "finally" 子句中被执行的 "return" 语句总是最后被
执行的:

   >>> 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 raise 语句.

3.8 版更變: Prior to Python 3.8, a "continue" statement was illegal in
the "finally" clause due to a problem with the implementation.


8.5. "with" 语句
================

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.

   備註: 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

3.1 版更變: Support for multiple context expressions.

也參考:

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


8.6. 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_no_posonly]]
                        | parameter_list_no_posonly
   parameter_list_no_posonly ::= 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.

形参可以带有 *标注*，其形式为在形参名称后加上 "": expression""。 任何
形参都可以带有标注，甚至 "*identifier" 或 "**identifier" 这样的形参也
可以。 函数可以带有“返回”标注，其形式为在形参列表后加上 ""->
expression""。 这些标注可以是任何有效的 Python 表达式。 标注的存在不会
改变函数的语义。 标注值可以作为函数对象的 "__annotations__" 属性中以对
应形参名称为键的字典值被访问。 如果使用了 "annotations" import from
"__future__" 的方式，则标注会在运行时保存为字符串以启用延迟求值特性。
否则，它们会在执行函数定义时被求值。 在这种情况下，标注的求值顺序可能
与它们在源代码中出现的顺序不同。

创建匿名函数（未绑定到一个名称的函数）以便立即在表达式中使用也是可能的
。 这需要使用 lambda 表达式，具体描述见 Lambdas 一节。 请注意 lambda
只是简单函数定义的一种简化写法；在 ""def"" 语句中定义的函数也可以像用
lambda 表达式定义的函数一样被传递或赋值给其他名称。 ""def"" 形式实际上
更为强大，因为它允许执行多条语句和使用标注。

**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.

也參考:

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

  **PEP 484** - Type Hints
     Definition of a standard meaning for annotations: type hints.

  **PEP 526** - Syntax for Variable Annotations
     Ability to type hint variable declarations, including class
     variables and instance variables

  **PEP 563** - Postponed Evaluation of Annotations
     Support for forward references within annotations by preserving
     annotations in a string form at runtime instead of eager
     evaluation.


8.7. 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. [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.

也參考:

  **PEP 3115** - Metaclasses in 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
===============

3.5 版新加入.


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*).  Inside the body of a coroutine function,
"await" and "async" identifiers become reserved keywords; "await"
expressions, "async for" and "async with" can only be used in
coroutine function 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 a "yield from" expression inside the body
of a coroutine function.

An example of a coroutine function:

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


8.8.2. "async for" 语句
-----------------------

   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 an "async for" statement outside the body
of a coroutine function.


8.8.3. "async with" 语句
------------------------

   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 an "async with" statement outside the
body of a coroutine function.

也參考:

  **PEP 492** - Coroutines with async and await syntax
     The proposal that made coroutines a proper standalone concept in
     Python, and added supporting syntax.

-[ 註解 ]-

[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*.
