8. 복합문(Compound statements)¶
복합문은 다른 문장들(의 그룹들)을 포함합니다; 어떤 방법으로 그 다른 문장들의 실행에 영향을 주거나 제어합니다. 간단하게 표현할 때, 전체 복합문을 한 줄로 쓸 수 있기는 하지만, 일반적으로 복합문은 여러 줄에 걸칩니다.
if
, while
, for
문장은 전통적인 제어 흐름 구조를 구현합니다. 문장들의 그룹에 대해 try
는 예외 처리기나 정리(cleanup) 코드 또는 그 둘 모두를 지정하는 반면, with
문은 코드 블록 주변으로 초기화와 파이널리제이션 코드를 실행할 수 있도록 합니다. 함수와 클래스 정의 또한 문법적으로 복합문입니다.
복합문은 하나나 그 이상의 ‘절’로 구성됩니다. 절은 헤더와 ‘스위트(suite)’로 구성됩니다. 특정 복합문의 절 헤더들은 모두 같은 들여쓰기 수준을 갖습니다. 각 절 헤더는 특별하게 식별되는 키워드로 시작하고 콜론으로 끝납니다. 스위트는 절에 의해 제어되는 문장들의 그룹입니다. 스위트는 헤더의 콜론 뒤에서 같은 줄에 세미콜론으로 분리된 하나나 그 이상의 단순문일 수 있습니다. 또는 그다음 줄에 들여쓰기 된 하나나 그 이상의 문장들일 수도 있습니다. 오직 후자의 형태만 중첩된 복합문을 포함할 수 있습니다; 다음과 같은 것은 올바르지 않은데, 대체로 뒤따르는 else
절이 있다면 어떤 if
절에 속하는지 명확하지 않기 때문입니다.
if test1: if test2: print(x)
또한, 이 문맥에서 세미콜론이 콜론보다 더 강하게 결합해서, 다음과 같은 예에서, print()
호출들은 모두 실행되거나 어느 하나도 실행되지 않습니다는 것에 주의해야 합니다:
if x < y < z: print(x); print(y); print(z)
요약하면:
compound_stmt ::=if_stmt
|while_stmt
|for_stmt
|try_stmt
|with_stmt
|match_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
)* [";"]
문장들이 항상 NEWLINE
으로 끝나고 DEDENT
가 그 뒤를 따를 수 있음에 주목해야 합니다. 또한, 생략 가능한 연결 절들이 항상 문장을 시작시킬 수 없는 키워드로 시작하기 때문에, 모호함이 없다는 것도 주목하세요 (파이썬에서는 중첩된 if
문이 들여쓰기 되는 것을 요구함으로써 ‘매달린(dangling) else
’ 문제를 해결합니다).
명확함을 위해 다음에 오는 절들에서 나오는 문법 규칙들은 각 절을 별도의 줄에 놓도록 포매팅합니다.
8.1. if
문¶
if
문은 조건부 실행에 사용됩니다:
if_stmt ::= "if"assignment_expression
":"suite
("elif"assignment_expression
":"suite
)* ["else" ":"suite
]
참이 되는 것을 발견할 때까지 표현식들의 값을 하나씩 차례대로 구해서 정확히 하나의 스위트를 선택합니다 (참과 거짓의 정의는 논리 연산(Boolean operations) 섹션을 보세요); 그런 다음 그 스위트를 실행합니다 (그리고는 if
문의 다른 어떤 부분도 실행되거나 값이 구해지지 않습니다). 모든 표현식들이 거짓이면 else
절의 스위트가 (있다면) 실행됩니다.
8.2. while
문¶
while
문은 표현식이 참인 동안 실행을 반복하는 데 사용됩니다:
while_stmt ::= "while"assignment_expression
":"suite
["else" ":"suite
]
이것은 표현식을 반복적으로 검사하고, 참이면, 첫 번째 스위트를 실행합니다; 표현식이 거짓이면 (처음부터 거짓일 수도 있습니다) else
절의 스위트가 (있다면) 실행되고 루프를 종료합니다.
첫 번째 스위트에서 실행되는 break
문은 else
절을 실행하지 않고 루프를 종료합니다. 첫 번째 스위트에서 실행되는 continue
문은 스위트의 나머지 부분을 건너뛰고 표현식의 검사로 돌아갑니다.
8.3. for
문¶
for
문은 (문자열, 튜플, 리스트 같은) 시퀀스 나 다른 이터러블 객체의 요소들을 이터레이트하는데 사용됩니다:
for_stmt ::= "for"target_list
"in"starred_list
":"suite
["else" ":"suite
]
The starred_list
expression is evaluated once; it should yield an
iterable object. An iterator is created for that iterable.
The first item provided
by the iterator is then assigned to the target list using the standard
rules for assignments (see 대입문), and the suite is executed. This
repeats for each item provided by the iterator. When the iterator is exhausted,
the suite in the else
clause,
if present, is executed, and the loop terminates.
첫 번째 스위트에서 실행되는 break
문은 else
절을 실행하지 않고 루프를 종료합니다. 첫 번째 스위트에서 실행되는 continue
문은 스위트의 나머지 부분을 건너뛰고 다음 항목으로 넘어가거나, 다음 항목이 없으면 else
절로 갑니다.
for-루프는 타깃 목록의 변수들에 대입합니다. for-루프의 스위트에서 이루어진 것들도 포함해서, 그 변수에 앞서 대입된 값들을 모두 덮어씁니다:
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 type range()
represents immutable arithmetic sequences of integers.
For instance, iterating range(3)
successively yields 0, 1, and then 2.
버전 3.11에서 변경: Starred elements are now allowed in the expression list.
8.4. try
문¶
The try
statement specifies exception handlers and/or cleanup code
for a group of statements:
try_stmt ::=try1_stmt
|try2_stmt
|try3_stmt
try1_stmt ::= "try" ":"suite
("except" [expression
["as"identifier
]] ":"suite
)+ ["else" ":"suite
] ["finally" ":"suite
] try2_stmt ::= "try" ":"suite
("except" "*"expression
["as"identifier
] ":"suite
)+ ["else" ":"suite
] ["finally" ":"suite
] try3_stmt ::= "try" ":"suite
"finally" ":"suite
예외에 관한 추가의 정보는 예외 섹션에서 찾을 수 있고, 예외를 일으키기 위해 raise
문을 사용하는 것에 관한 정보는 raise 문 섹션에서 찾을 수 있습니다.
8.4.1. except
clause¶
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, the
expression must evaluate to an exception type or a tuple of exception types.
The raised exception matches an except
clause whose expression evaluates
to the class or a non-virtual base class of the exception object,
or to a tuple that contains such a class.
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
가 이렇게 변환되는 것과 같습니다
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,
the exception is stored in the sys
module, where it can be accessed
from within the body of the except
clause by calling
sys.exception()
. When leaving an exception handler, the exception
stored in the sys
module is reset to its previous value:
>>> print(sys.exception())
None
>>> try:
... raise TypeError
... except:
... print(repr(sys.exception()))
... try:
... raise ValueError
... except:
... print(repr(sys.exception()))
... print(repr(sys.exception()))
...
TypeError()
ValueError()
TypeError()
>>> print(sys.exception())
None
8.4.2. except*
clause¶
The except*
clause(s) are used for handling
ExceptionGroup
s. The exception type for matching is interpreted as in
the case of except
, but in the case of exception groups we can have
partial matches when the type matches some of the exceptions in the group.
This means that multiple except*
clauses can execute,
each handling part of the exception group.
Each clause executes at most once and handles an exception group
of all matching exceptions. Each exception in the group is handled by at most
one except*
clause, the first that matches it.
>>> try:
... raise ExceptionGroup("eg",
... [ValueError(1), TypeError(2), OSError(3), OSError(4)])
... except* TypeError as e:
... print(f'caught {type(e)} with nested {e.exceptions}')
... except* OSError as e:
... print(f'caught {type(e)} with nested {e.exceptions}')
...
caught <class 'ExceptionGroup'> with nested (TypeError(2),)
caught <class 'ExceptionGroup'> with nested (OSError(3), OSError(4))
+ Exception Group Traceback (most recent call last):
| File "<stdin>", line 2, in <module>
| ExceptionGroup: eg
+-+---------------- 1 ----------------
| ValueError: 1
+------------------------------------
Any remaining exceptions that were not handled by any except*
clause are re-raised at the end, along with all exceptions that were
raised from within the except*
clauses. If this list contains
more than one exception to reraise, they are combined into an exception
group.
If the raised exception is not an exception group and its type matches
one of the except*
clauses, it is caught and wrapped by an
exception group with an empty message string.
>>> try:
... raise BlockingIOError
... except* BlockingIOError as e:
... print(repr(e))
...
ExceptionGroup('', (BlockingIOError()))
An except*
clause must have a matching expression; it cannot be except*:
.
Furthermore, this expression cannot contain exception group types, because that would
have ambiguous semantics.
It is not possible to mix except
and except*
in the same try
.
break
, continue
and return
cannot appear in an except*
clause.
8.4.3. else
clause¶
생략 가능한 else
절은 제어 흐름이 try
스위트를 빠져나가고, 예외가 발생하지 않았고, return
, continue
또는 break
문이 실행되지 않으면 실행됩니다. else
절에서 발생하는 예외는 앞에 나오는 except
절에서 처리되지 않습니다.
8.4.4. finally
clause¶
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.’
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'
버전 3.8에서 변경: Prior to Python 3.8, a continue
statement was illegal in the
finally
clause due to a problem with the implementation.
8.5. with
문¶
with
문은 블록의 실행을 컨텍스트 관리자 (with 문 컨텍스트 관리자 섹션을 보세요) 가 정의한 메서드들로 감싸는 데 사용됩니다. 이것은 흔한 try
…except
…finally
사용 패턴을 편리하게 재사용할 수 있도록 캡슐화할 수 있도록 합니다.
with_stmt ::= "with" ( "("with_stmt_contents
","? ")" |with_stmt_contents
) ":"suite
with_stmt_contents ::=with_item
(","with_item
)* with_item ::=expression
["as"target
]
하나의 “item” 을 사용하는 with
문의 실행은 다음과 같이 진행됩니다:
The context expression (the expression given in the
with_item
) is evaluated to obtain a context manager.The context manager’s
__enter__()
is loaded for later use.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.참고
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 7 below.스위트가 실행됩니다.
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.
다음과 같은 코드는:
with EXPRESSION as TARGET:
SUITE
의미상으로 다음과 동등합니다:
manager = (EXPRESSION)
enter = type(manager).__enter__
exit = type(manager).__exit__
value = enter(manager)
hit_except = False
try:
TARGET = value
SUITE
except:
hit_except = True
if not exit(manager, *sys.exc_info()):
raise
finally:
if not hit_except:
exit(manager, None, None, None)
하나 보다 많은 항목을 주면, 컨텍스트 관리자는 with
문이 중첩된 것처럼 진행합니다:
with A() as a, B() as b:
SUITE
의미상으로 다음과 동등합니다:
with A() as a:
with B() as b:
SUITE
You can also write multi-item context managers in multiple lines if the items are surrounded by parentheses. For example:
with (
A() as a,
B() as b,
):
SUITE
버전 3.1에서 변경: 다중 컨텍스트 표현식의 지원
버전 3.10에서 변경: Support for using grouping parentheses to break the statement in multiple lines.
8.6. The match
statement¶
Added in version 3.10.
The match statement is used for pattern matching. Syntax:
match_stmt ::= 'match'subject_expr
":" NEWLINE INDENTcase_block
+ DEDENT subject_expr ::=star_named_expression
","star_named_expressions
? |named_expression
case_block ::= 'case'patterns
[guard
] ":"block
참고
This section uses single quotes to denote soft keywords.
Pattern matching takes a pattern as input (following case
) and a subject
value (following match
). The pattern (which may contain subpatterns) is
matched against the subject value. The outcomes are:
A match success or failure (also termed a pattern success or failure).
Possible binding of matched values to a name. The prerequisites for this are further discussed below.
The match
and case
keywords are soft keywords.
더 보기
8.6.1. Overview¶
Here’s an overview of the logical flow of a match statement:
The subject expression
subject_expr
is evaluated and a resulting subject value obtained. If the subject expression contains a comma, a tuple is constructed using the standard rules.Each pattern in a
case_block
is attempted to match with the subject value. The specific rules for success or failure are described below. The match attempt can also bind some or all of the standalone names within the pattern. The precise pattern binding rules vary per pattern type and are specified below. Name bindings made during a successful pattern match outlive the executed block and can be used after the match statement.참고
During failed pattern matches, some subpatterns may succeed. Do not rely on bindings being made for a failed match. Conversely, do not rely on variables remaining unchanged after a failed match. The exact behavior is dependent on implementation and may vary. This is an intentional decision made to allow different implementations to add optimizations.
If the pattern succeeds, the corresponding guard (if present) is evaluated. In this case all name bindings are guaranteed to have happened.
If the guard evaluates as true or is missing, the
block
insidecase_block
is executed.Otherwise, the next
case_block
is attempted as described above.If there are no further case blocks, the match statement is completed.
참고
Users should generally never rely on a pattern being evaluated. Depending on implementation, the interpreter may cache values or use other optimizations which skip repeated evaluations.
A sample match statement:
>>> flag = False
>>> match (100, 200):
... case (100, 300): # Mismatch: 200 != 300
... print('Case 1')
... case (100, 200) if flag: # Successful match, but guard fails
... print('Case 2')
... case (100, y): # Matches and binds y to 200
... print(f'Case 3, y: {y}')
... case _: # Pattern not attempted
... print('Case 4, I match anything!')
...
Case 3, y: 200
In this case, if flag
is a guard. Read more about that in the next section.
8.6.2. Guards¶
guard ::= "if" named_expression
A guard
(which is part of the case
) must succeed for code inside
the case
block to execute. It takes the form: if
followed by an
expression.
The logical flow of a case
block with a guard
follows:
Check that the pattern in the
case
block succeeded. If the pattern failed, theguard
is not evaluated and the nextcase
block is checked.If the pattern succeeded, evaluate the
guard
.If the
guard
condition evaluates as true, the case block is selected.If the
guard
condition evaluates as false, the case block is not selected.If the
guard
raises an exception during evaluation, the exception bubbles up.
Guards are allowed to have side effects as they are expressions. Guard evaluation must proceed from the first to the last case block, one at a time, skipping case blocks whose pattern(s) don’t all succeed. (I.e., guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected.
8.6.3. Irrefutable Case Blocks¶
An irrefutable case block is a match-all case block. A match statement may have at most one irrefutable case block, and it must be last.
A case block is considered irrefutable if it has no guard and its pattern is irrefutable. A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. Only the following patterns are irrefutable:
AS Patterns whose left-hand side is irrefutable
OR Patterns containing at least one irrefutable pattern
parenthesized irrefutable patterns
8.6.4. Patterns¶
참고
This section uses grammar notations beyond standard EBNF:
the notation
SEP.RULE+
is shorthand forRULE (SEP RULE)*
the notation
!RULE
is shorthand for a negative lookahead assertion
The top-level syntax for patterns
is:
patterns ::=open_sequence_pattern
|pattern
pattern ::=as_pattern
|or_pattern
closed_pattern ::= |literal_pattern
|capture_pattern
|wildcard_pattern
|value_pattern
|group_pattern
|sequence_pattern
|mapping_pattern
|class_pattern
The descriptions below will include a description “in simple terms” of what a pattern does for illustration purposes (credits to Raymond Hettinger for a document that inspired most of the descriptions). Note that these descriptions are purely for illustration purposes and may not reflect the underlying implementation. Furthermore, they do not cover all valid forms.
8.6.4.1. OR Patterns¶
An OR pattern is two or more patterns separated by vertical
bars |
. Syntax:
or_pattern ::= "|".closed_pattern
+
Only the final subpattern may be irrefutable, and each subpattern must bind the same set of names to avoid ambiguity.
An OR pattern matches each of its subpatterns in turn to the subject value, until one succeeds. The OR pattern is then considered successful. Otherwise, if none of the subpatterns succeed, the OR pattern fails.
In simple terms, P1 | P2 | ...
will try to match P1
, if it fails it will try to
match P2
, succeeding immediately if any succeeds, failing otherwise.
8.6.4.2. AS Patterns¶
An AS pattern matches an OR pattern on the left of the as
keyword against a subject. Syntax:
as_pattern ::=or_pattern
"as"capture_pattern
If the OR pattern fails, the AS pattern fails. Otherwise, the AS pattern binds
the subject to the name on the right of the as keyword and succeeds.
capture_pattern
cannot be a _
.
In simple terms P as NAME
will match with P
, and on success it will
set NAME = <subject>
.
8.6.4.3. Literal Patterns¶
A literal pattern corresponds to most literals in Python. Syntax:
literal_pattern ::=signed_number
|signed_number
"+" NUMBER |signed_number
"-" NUMBER |strings
| "None" | "True" | "False" signed_number ::= ["-"] NUMBER
The rule strings
and the token NUMBER
are defined in the
standard Python grammar. Triple-quoted strings are
supported. Raw strings and byte strings are supported. f-strings are
not supported.
The forms signed_number '+' NUMBER
and signed_number '-' NUMBER
are
for expressing complex numbers; they require a real number
on the left and an imaginary number on the right. E.g. 3 + 4j
.
In simple terms, LITERAL
will succeed only if <subject> == LITERAL
. For
the singletons None
, True
and False
, the is
operator is used.
8.6.4.4. Capture Patterns¶
A capture pattern binds the subject value to a name. Syntax:
capture_pattern ::= !'_' NAME
A single underscore _
is not a capture pattern (this is what !'_'
expresses). It is instead treated as a
wildcard_pattern
.
In a given pattern, a given name can only be bound once. E.g.
case x, x: ...
is invalid while case [x] | x: ...
is allowed.
Capture patterns always succeed. The binding follows scoping rules
established by the assignment expression operator in PEP 572; the
name becomes a local variable in the closest containing function scope unless
there’s an applicable global
or nonlocal
statement.
In simple terms NAME
will always succeed and it will set NAME = <subject>
.
8.6.4.5. Wildcard Patterns¶
A wildcard pattern always succeeds (matches anything) and binds no name. Syntax:
wildcard_pattern ::= '_'
_
is a soft keyword within any pattern,
but only within patterns. It is an identifier, as usual, even within
match
subject expressions, guard
s, and case
blocks.
In simple terms, _
will always succeed.
8.6.4.6. Value Patterns¶
A value pattern represents a named value in Python. Syntax:
value_pattern ::=attr
attr ::=name_or_attr
"." NAME name_or_attr ::=attr
| NAME
The dotted name in the pattern is looked up using standard Python
name resolution rules. The pattern succeeds if the
value found compares equal to the subject value (using the ==
equality
operator).
In simple terms NAME1.NAME2
will succeed only if <subject> == NAME1.NAME2
참고
If the same value occurs multiple times in the same match statement, the interpreter may cache the first value found and reuse it rather than repeat the same lookup. This cache is strictly tied to a given execution of a given match statement.
8.6.4.7. Group Patterns¶
A group pattern allows users to add parentheses around patterns to emphasize the intended grouping. Otherwise, it has no additional syntax. Syntax:
group_pattern ::= "(" pattern
")"
In simple terms (P)
has the same effect as P
.
8.6.4.8. Sequence Patterns¶
A sequence pattern contains several subpatterns to be matched against sequence elements. The syntax is similar to the unpacking of a list or tuple.
sequence_pattern ::= "[" [maybe_sequence_pattern
] "]" | "(" [open_sequence_pattern
] ")" open_sequence_pattern ::=maybe_star_pattern
"," [maybe_sequence_pattern
] maybe_sequence_pattern ::= ",".maybe_star_pattern
+ ","? maybe_star_pattern ::=star_pattern
|pattern
star_pattern ::= "*" (capture_pattern
|wildcard_pattern
)
There is no difference if parentheses or square brackets
are used for sequence patterns (i.e. (...)
vs [...]
).
참고
A single pattern enclosed in parentheses without a trailing comma
(e.g. (3 | 4)
) is a group pattern.
While a single pattern enclosed in square brackets (e.g. [3 | 4]
) is
still a sequence pattern.
At most one star subpattern may be in a sequence pattern. The star subpattern may occur in any position. If no star subpattern is present, the sequence pattern is a fixed-length sequence pattern; otherwise it is a variable-length sequence pattern.
The following is the logical flow for matching a sequence pattern against a subject value:
If the subject value is not a sequence [2], the sequence pattern fails.
If the subject value is an instance of
str
,bytes
orbytearray
the sequence pattern fails.The subsequent steps depend on whether the sequence pattern is fixed or variable-length.
If the sequence pattern is fixed-length:
If the length of the subject sequence is not equal to the number of subpatterns, the sequence pattern fails
Subpatterns in the sequence pattern are matched to their corresponding items in the subject sequence from left to right. Matching stops as soon as a subpattern fails. If all subpatterns succeed in matching their corresponding item, the sequence pattern succeeds.
Otherwise, if the sequence pattern is variable-length:
If the length of the subject sequence is less than the number of non-star subpatterns, the sequence pattern fails.
The leading non-star subpatterns are matched to their corresponding items as for fixed-length sequences.
If the previous step succeeds, the star subpattern matches a list formed of the remaining subject items, excluding the remaining items corresponding to non-star subpatterns following the star subpattern.
Remaining non-star subpatterns are matched to their corresponding subject items, as for a fixed-length sequence.
참고
The length of the subject sequence is obtained via
len()
(i.e. via the__len__()
protocol). This length may be cached by the interpreter in a similar manner as value patterns.
In simple terms [P1, P2, P3,
… , P<N>]
matches only if all the following
happens:
check
<subject>
is a sequencelen(subject) == <N>
P1
matches<subject>[0]
(note that this match can also bind names)P2
matches<subject>[1]
(note that this match can also bind names)… and so on for the corresponding pattern/element.
8.6.4.9. Mapping Patterns¶
A mapping pattern contains one or more key-value patterns. The syntax is similar to the construction of a dictionary. Syntax:
mapping_pattern ::= "{" [items_pattern
] "}" items_pattern ::= ",".key_value_pattern
+ ","? key_value_pattern ::= (literal_pattern
|value_pattern
) ":"pattern
|double_star_pattern
double_star_pattern ::= "**"capture_pattern
At most one double star pattern may be in a mapping pattern. The double star pattern must be the last subpattern in the mapping pattern.
Duplicate keys in mapping patterns are disallowed. Duplicate literal keys will
raise a SyntaxError
. Two keys that otherwise have the same value will
raise a ValueError
at runtime.
The following is the logical flow for matching a mapping pattern against a subject value:
If the subject value is not a mapping [3],the mapping pattern fails.
If every key given in the mapping pattern is present in the subject mapping, and the pattern for each key matches the corresponding item of the subject mapping, the mapping pattern succeeds.
If duplicate keys are detected in the mapping pattern, the pattern is considered invalid. A
SyntaxError
is raised for duplicate literal values; or aValueError
for named keys of the same value.
참고
Key-value pairs are matched using the two-argument form of the mapping
subject’s get()
method. Matched key-value pairs must already be present
in the mapping, and not created on-the-fly via __missing__()
or
__getitem__()
.
In simple terms {KEY1: P1, KEY2: P2, ... }
matches only if all the following
happens:
check
<subject>
is a mappingKEY1 in <subject>
P1
matches<subject>[KEY1]
… and so on for the corresponding KEY/pattern pair.
8.6.4.10. Class Patterns¶
A class pattern represents a class and its positional and keyword arguments (if any). Syntax:
class_pattern ::=name_or_attr
"(" [pattern_arguments
","?] ")" pattern_arguments ::=positional_patterns
[","keyword_patterns
] |keyword_patterns
positional_patterns ::= ",".pattern
+ keyword_patterns ::= ",".keyword_pattern
+ keyword_pattern ::= NAME "="pattern
The same keyword should not be repeated in class patterns.
The following is the logical flow for matching a class pattern against a subject value:
If
name_or_attr
is not an instance of the builtintype
, raiseTypeError
.If the subject value is not an instance of
name_or_attr
(tested viaisinstance()
), the class pattern fails.If no pattern arguments are present, the pattern succeeds. Otherwise, the subsequent steps depend on whether keyword or positional argument patterns are present.
For a number of built-in types (specified below), a single positional subpattern is accepted which will match the entire subject; for these types keyword patterns also work as for other types.
If only keyword patterns are present, they are processed as follows, one by one:
I. The keyword is looked up as an attribute on the subject.
If this raises an exception other than
AttributeError
, the exception bubbles up.If this raises
AttributeError
, the class pattern has failed.Else, the subpattern associated with the keyword pattern is matched against the subject’s attribute value. If this fails, the class pattern fails; if this succeeds, the match proceeds to the next keyword.
II. If all keyword patterns succeed, the class pattern succeeds.
If any positional patterns are present, they are converted to keyword patterns using the
__match_args__
attribute on the classname_or_attr
before matching:I. The equivalent of
getattr(cls, "__match_args__", ())
is called.If this raises an exception, the exception bubbles up.
If the returned value is not a tuple, the conversion fails and
TypeError
is raised.If there are more positional patterns than
len(cls.__match_args__)
,TypeError
is raised.Otherwise, positional pattern
i
is converted to a keyword pattern using__match_args__[i]
as the keyword.__match_args__[i]
must be a string; if notTypeError
is raised.If there are duplicate keywords,
TypeError
is raised.
- II. Once all positional patterns have been converted to keyword patterns,
the match proceeds as if there were only keyword patterns.
For the following built-in types the handling of positional subpatterns is different:
These classes accept a single positional argument, and the pattern there is matched against the whole object rather than an attribute. For example
int(0|1)
matches the value0
, but not the value0.0
.
In simple terms CLS(P1, attr=P2)
matches only if the following happens:
isinstance(<subject>, CLS)
convert
P1
to a keyword pattern usingCLS.__match_args__
For each keyword argument
attr=P2
:hasattr(<subject>, "attr")
P2
matches<subject>.attr
… and so on for the corresponding keyword argument/pattern pair.
8.7. 함수 정의¶
함수 정의는 사용자 정의 함수 객체 (표준형 계층 섹션을 보세요) 를 정의합니다:
funcdef ::= [decorators
] "def"funcname
[type_params
] "(" [parameter_list
] ")" ["->"expression
] ":"suite
decorators ::=decorator
+ decorator ::= "@"assignment_expression
NEWLINE 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 ::= "*" [star_parameter
] (","defparameter
)* ["," ["**"parameter
[","]]] | "**"parameter
[","] parameter ::=identifier
[":"expression
] star_parameter ::=identifier
[":" ["*"]expression
] defparameter ::=parameter
["="expression
] funcname ::=identifier
함수 정의는 실행할 수 있는 문장입니다. 실행하면 현재 지역 이름 공간의 함수 이름을 함수 객체 (함수의 실행 가능한 코드를 둘러싼 래퍼(wrapper)). 이 함수 객체는 현재의 이름 공간에 대한 참조를 포함하는데, 함수가 호출될 때 전역 이름 공간으로 사용됩니다.
함수 정의는 함수의 바디를 실행하지 않습니다. 함수가 호출될 때 실행됩니다. [4]
함수 정의는 하나나 그 이상의 데코레이터 표현식으로 감싸질 수 있습니다. 데코레이터 표현식은 함수가 정의될 때, 함수 정의를 포함하는 스코프에서 값을 구합니다. 그 결과는 콜러블이어야 하는데, 함수 객체만을 인자로 사용해서 호출됩니다. 반환 값이 함수 객체 대신 함수의 이름에 연결됩니다. 여러 개의 데코레이터는 중첩되는 방식으로 적용됩니다. 예를 들어, 다음과 같은 코드
@f1(arg)
@f2
def func(): pass
는 대략 다음과 동등합니다
def func(): pass
func = f1(arg)(f2(func))
원래의 함수가 임시로 이름 func
에 연결되지 않는다는 점만 다릅니다.
버전 3.9에서 변경: Functions may be decorated with any valid
assignment_expression
. Previously, the grammar was
much more restrictive; see PEP 614 for details.
A list of type parameters may be given in square brackets
between the function’s name and the opening parenthesis for its parameter list.
This indicates to static type checkers that the function is generic. At runtime,
the type parameters can be retrieved from the function’s
__type_params__
attribute. See Generic functions for more.
버전 3.12에서 변경: Type parameter lists are new in Python 3.12.
하나나 그 이상의 매개변수 들이 parameter =
expression 형태를 가질 때, 함수가 “기본 매개변수 값”을 갖는다고 말합니다. 기본값이 있는 매개변수의 경우, 호출할 때 대응하는 인자 를 생략할 수 있고, 그럴 때 매개변수의 기본값이 적용됩니다. 만약 매개변수가 기본값을 가지면, “*
” 까지 그 뒤를 따르는 모든 매개변수도 기본값을 가져야 합니다 — 이것은 문법 규칙에서 표현되지 않는 문법적 제약입니다.
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 value 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 parameter 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 호출. A
function call always assigns values to all parameters mentioned in the parameter
list, either from positional 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
by keyword arguments. Parameters before “/
” are positional-only parameters
and may only be passed by positional arguments.
버전 3.8에서 변경: The /
function parameter syntax may be used to indicate positional-only
parameters. See PEP 570 for details.
Parameters may have an annotation of the form “: expression
”
following the parameter name. Any parameter may have an annotation, even those of the form
*identifier
or **identifier
. (As a special case, parameters of the form
*identifier
may have an annotation “: *expression
”.) Functions may have “return” annotation of
the form “-> expression
” after the parameter list. These annotations can be
any valid Python expression. 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. If the annotations
import from
__future__
is used, annotations are preserved as strings at runtime which
enables postponed evaluation. Otherwise, they are evaluated when the function
definition is executed. In this case annotations may be evaluated in
a different order than they appear in the source code.
버전 3.11에서 변경: Parameters of the form “*identifier
” may have an annotation
“: *expression
”. See PEP 646.
표현식에서 즉시 사용하기 위해, 이름 없는 함수(이름에 연결되지 않은 함수)를 만드는 것도 가능합니다. 이것은 람다 표현식을 사용하는데, 람다(Lambdas) 섹션에서 설명합니다. 람다 표현식은 단순화된 함수 정의를 위한 줄임 표현에 지나지 않는다는 것에 주의하세요; “def
” 문장에서 정의된 함수는 람다 표현식으로 정의된 함수처럼 전달되거나 다른 이름에 대입될 수 있습니다. 여러 개의 문장을 실행하는 것과 어노테이션을 허락하기 때문에, “def
” 형태가 사실 더 강력합니다.
프로그래머 유의 사항: 함수는 퍼스트 클래스(first-class) 객체다. 함수 정의 안에서 실행되는 “def
” 문은 돌려주거나 전달할 수 있는 지역 함수를 정의합니다. 중첩된 함수에서 사용되는 자유 변수들은 그 def 를 포함하는 함수의 지역 변수들을 액세스할 수 있습니다. 더 자세한 내용은 이름과 연결(binding) 섹션을 보세요.
더 보기
- PEP 3107 - 함수 어노테이션
함수 어노테이션의 최초 규격.
- PEP 484 - 형 힌트
어노테이션에 대한 표준 의미 정의: 형 힌트.
- PEP 526 - 변수 어노테이션 문법
Ability to type hint variable declarations, including class variables and instance variables.
- PEP 563 - 어노테이션의 지연된 평가
즉시 평가하는 대신 실행시간에 어노테이션을 문자열 형식으로 보존하여 어노테이션 내에서의 전방 참조를 지원합니다.
- PEP 318 - Decorators for Functions and Methods
Function and method decorators were introduced. Class decorators were introduced in PEP 3129.
8.8. 클래스 정의¶
클래스 정의는 클래스 객체(표준형 계층 섹션을 보세요)를 정의합니다:
classdef ::= [decorators
] "class"classname
[type_params
] [inheritance
] ":"suite
inheritance ::= "(" [argument_list
] ")" classname ::=identifier
클래스 정의는 실행 가능한 문장입니다. 계승(inheritance) 목록은 보통 베이스 클래스들의 목록을 제공하는데 (더 고급 사용에 대해서는 메타 클래스 를 보세요), 목록의 각 항목은 값을 구할 때 서브 클래싱을 허락하는 클래스 객체가 되어야 합니다. 계승 목록이 없는 클래스는, 기본적으로, 베이스 클래스 object
를 계승합니다; 그래서
class Foo:
pass
는 다음과 동등합니다
class Foo(object):
pass
클래스의 스위트는 새로 만들어진 지역 이름 공간과 원래의 전역 이름 공간을 사용하는 새 실행 프레임 (이름과 연결(binding) 을 보세요)에서 실행됩니다. (보통, 스위트는 대부분 함수 정의들을 포함합니다.) 클래스의 스위트가 실행을 마치면, 실행 프레임은 파기하지만, 그것의 지역 이름 공간은 보존합니다. [5] 그런 다음, 계승 목록을 베이스 클래스들로, 보존된 지역 이름 공간을 어트리뷰트 딕셔너리로 사용해서 새 클래스 객체를 만듭니다. 클래스의 이름은 원래의 지역 이름 공간에서 이 클래스 객체와 연결됩니다.
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.
클래스 생성은 메타 클래스 를 사용해서 심하게 커스터마이즈할 수 있습니다.
클래스 역시 함수를 데코레이팅할 때처럼 테코레이트할 수 있습니다,
@f1(arg)
@f2
class Foo: pass
는 대략 다음과 동등합니다
class Foo: pass
Foo = f1(arg)(f2(Foo))
데코레이터 표현식의 값을 구하는 규칙은 함수 데코레이터와 같습니다. 그런 다음 그 결과가 클래스 이름에 연결됩니다.
버전 3.9에서 변경: Classes may be decorated with any valid
assignment_expression
. Previously, the grammar was
much more restrictive; see PEP 614 for details.
A list of type parameters may be given in square brackets
immediately after the class’s name.
This indicates to static type checkers that the class is generic. At runtime,
the type parameters can be retrieved from the class’s
__type_params__
attribute. See Generic classes for more.
버전 3.12에서 변경: Type parameter lists are new in Python 3.12.
프로그래머 유의 사항: 클래스 정의에서 정의되는 변수들은 클래스 어트리뷰트입니다; 이것들은 인스턴스 간에 공유됩니다. 인스턴스 어트리뷰트는 메서드에서 self.name = value
로 설정될 수 있습니다. 클래스와 인스턴스 어트리뷰트 모두 “self.name
” 표기법으로 액세스할 수 있고, 이런 식으로 액세스할 때 인스턴스 어트리뷰트는 같은 이름의 클래스 어트리뷰트를 가립니다. 클래스 어트리뷰트는 인스턴스 어트리뷰트의 기본값으로 사용될 수 있지만, 가변 값을 사용하는 것은 예상하지 않은 결과를 줄 수 있습니다. 디스크립터 를 다른 구현 상세를 갖는 인스턴스 변수를 만드는데 사용할 수 있습니다.
8.9. 코루틴¶
Added in version 3.5.
8.9.1. 코루틴 함수 정의¶
async_funcdef ::= [decorators
] "async" "def"funcname
"(" [parameter_list
] ")" ["->"expression
] ":"suite
Execution of Python coroutines can be suspended and resumed at many points
(see coroutine). await
expressions, async for
and
async with
can only be used in the body of a coroutine function.
async def
문법으로 정의된 함수는 항상 코루틴 함수인데, await
나 async
키워드를 포함하지 않는 경우도 그렇습니다.
코루틴 함수의 바디 안에서 yield from
표현식을 사용하는 것은 SyntaxError
입니다.
코루틴 함수의 예:
async def func(param1, param2):
do_stuff()
await some_coroutine()
버전 3.7에서 변경: await
and async
are now keywords; previously they were only
treated as such inside the body of a coroutine function.
8.9.2. async for
문¶
async_for_stmt ::= "async" for_stmt
비동기 이터러블 은 비동기 이터레이터 를 직접 반환하는 __aiter__
메서드를 제공하고, 비동기 이터레이터는 자신의 __anext__
메서드에서 비동기 코드를 호출할 수 있습니다.
async for
문은 비동기 이터러블에 대한 편리한 이터레이션을 허락합니다.
다음과 같은 코드는:
async for TARGET in ITER:
SUITE
else:
SUITE2
의미상으로 다음과 동등합니다:
iter = (ITER)
iter = type(iter).__aiter__(iter)
running = True
while running:
try:
TARGET = await type(iter).__anext__(iter)
except StopAsyncIteration:
running = False
else:
SUITE
else:
SUITE2
See also __aiter__()
and __anext__()
for details.
코루틴 함수의 바디 밖에서 async for
문을 사용하는 것은 SyntaxError
입니다.
8.9.3. async with
문¶
async_with_stmt ::= "async" with_stmt
비동기 컨텍스트 관리자 는 enter 와 exit 메서드에서 실행을 일시 중지할 수 있는 컨텍스트 관리자 입니다.
다음과 같은 코드는:
async with EXPRESSION as TARGET:
SUITE
의미상으로 다음과 동등합니다:
manager = (EXPRESSION)
aenter = type(manager).__aenter__
aexit = type(manager).__aexit__
value = await aenter(manager)
hit_except = False
try:
TARGET = value
SUITE
except:
hit_except = True
if not await aexit(manager, *sys.exc_info()):
raise
finally:
if not hit_except:
await aexit(manager, None, None, None)
See also __aenter__()
and __aexit__()
for details.
코루틴 함수의 바디 밖에서 async with
문을 사용하는 것은 SyntaxError
입니다.
더 보기
- PEP 492 - async 와 await 문법을 사용하는 코루틴
코루틴을 파이썬에서 적절한 독립적인 개념으로 만들고, 문법 지원을 추가한 제안.
8.10. Type parameter lists¶
Added in version 3.12.
버전 3.13에서 변경: Support for default values was added (see PEP 696).
type_params ::= "["type_param
(","type_param
)* "]" type_param ::=typevar
|typevartuple
|paramspec
typevar ::=identifier
(":"expression
)? ("="expression
)? typevartuple ::= "*"identifier
("="expression
)? paramspec ::= "**"identifier
("="expression
)?
Functions (including coroutines), classes and type aliases may contain a type parameter list:
def max[T](args: list[T]) -> T:
...
async def amax[T](args: list[T]) -> T:
...
class Bag[T]:
def __iter__(self) -> Iterator[T]:
...
def add(self, arg: T) -> None:
...
type ListOrSet[T] = list[T] | set[T]
Semantically, this indicates that the function, class, or type alias is generic over a type variable. This information is primarily used by static type checkers, and at runtime, generic objects behave much like their non-generic counterparts.
Type parameters are declared in square brackets ([]
) immediately
after the name of the function, class, or type alias. The type parameters
are accessible within the scope of the generic object, but not elsewhere.
Thus, after a declaration def func[T](): pass
, the name T
is not available in
the module scope. Below, the semantics of generic objects are described
with more precision. The scope of type parameters is modeled with a special
function (technically, an annotation scope) that
wraps the creation of the generic object.
Generic functions, classes, and type aliases have a
__type_params__
attribute listing their type parameters.
Type parameters come in three kinds:
typing.TypeVar
, introduced by a plain name (e.g.,T
). Semantically, this represents a single type to a type checker.typing.TypeVarTuple
, introduced by a name prefixed with a single asterisk (e.g.,*Ts
). Semantically, this stands for a tuple of any number of types.typing.ParamSpec
, introduced by a name prefixed with two asterisks (e.g.,**P
). Semantically, this stands for the parameters of a callable.
typing.TypeVar
declarations can define bounds and constraints with
a colon (:
) followed by an expression. A single expression after the colon
indicates a bound (e.g. T: int
). Semantically, this means
that the typing.TypeVar
can only represent types that are a subtype of
this bound. A parenthesized tuple of expressions after the colon indicates a
set of constraints (e.g. T: (str, bytes)
). Each member of the tuple should be a
type (again, this is not enforced at runtime). Constrained type variables can only
take on one of the types in the list of constraints.
For typing.TypeVar
s declared using the type parameter list syntax,
the bound and constraints are not evaluated when the generic object is created,
but only when the value is explicitly accessed through the attributes __bound__
and __constraints__
. To accomplish this, the bounds or constraints are
evaluated in a separate annotation scope.
typing.TypeVarTuple
s and typing.ParamSpec
s cannot have bounds
or constraints.
All three flavors of type parameters can also have a default value, which is used
when the type parameter is not explicitly provided. This is added by appending
a single equals sign (=
) followed by an expression. Like the bounds and
constraints of type variables, the default value is not evaluated when the
object is created, but only when the type parameter’s __default__
attribute
is accessed. To this end, the default value is evaluated in a separate
annotation scope. If no default value is specified
for a type parameter, the __default__
attribute is set to the special
sentinel object typing.NoDefault
.
The following example indicates the full set of allowed type parameter declarations:
def overly_generic[
SimpleTypeVar,
TypeVarWithDefault = int,
TypeVarWithBound: int,
TypeVarWithConstraints: (str, bytes),
*SimpleTypeVarTuple = (int, float),
**SimpleParamSpec = (str, bytearray),
](
a: SimpleTypeVar,
b: TypeVarWithDefault,
c: TypeVarWithBound,
d: Callable[SimpleParamSpec, TypeVarWithConstraints],
*e: SimpleTypeVarTuple,
): ...
8.10.1. Generic functions¶
Generic functions are declared as follows:
def func[T](arg: T): ...
This syntax is equivalent to:
annotation-def TYPE_PARAMS_OF_func():
T = typing.TypeVar("T")
def func(arg: T): ...
func.__type_params__ = (T,)
return func
func = TYPE_PARAMS_OF_func()
Here annotation-def
indicates an annotation scope,
which is not actually bound to any name at runtime. (One
other liberty is taken in the translation: the syntax does not go through
attribute access on the typing
module, but creates an instance of
typing.TypeVar
directly.)
The annotations of generic functions are evaluated within the annotation scope used for declaring the type parameters, but the function’s defaults and decorators are not.
The following example illustrates the scoping rules for these cases, as well as for additional flavors of type parameters:
@decorator
def func[T: int, *Ts, **P](*args: *Ts, arg: Callable[P, T] = some_default):
...
Except for the lazy evaluation of the
TypeVar
bound, this is equivalent to:
DEFAULT_OF_arg = some_default
annotation-def TYPE_PARAMS_OF_func():
annotation-def BOUND_OF_T():
return int
# In reality, BOUND_OF_T() is evaluated only on demand.
T = typing.TypeVar("T", bound=BOUND_OF_T())
Ts = typing.TypeVarTuple("Ts")
P = typing.ParamSpec("P")
def func(*args: *Ts, arg: Callable[P, T] = DEFAULT_OF_arg):
...
func.__type_params__ = (T, Ts, P)
return func
func = decorator(TYPE_PARAMS_OF_func())
The capitalized names like DEFAULT_OF_arg
are not actually
bound at runtime.
8.10.2. Generic classes¶
Generic classes are declared as follows:
class Bag[T]: ...
This syntax is equivalent to:
annotation-def TYPE_PARAMS_OF_Bag():
T = typing.TypeVar("T")
class Bag(typing.Generic[T]):
__type_params__ = (T,)
...
return Bag
Bag = TYPE_PARAMS_OF_Bag()
Here again annotation-def
(not a real keyword) indicates an
annotation scope, and the name
TYPE_PARAMS_OF_Bag
is not actually bound at runtime.
Generic classes implicitly inherit from typing.Generic
.
The base classes and keyword arguments of generic classes are
evaluated within the type scope for the type parameters,
and decorators are evaluated outside that scope. This is illustrated
by this example:
@decorator
class Bag(Base[T], arg=T): ...
This is equivalent to:
annotation-def TYPE_PARAMS_OF_Bag():
T = typing.TypeVar("T")
class Bag(Base[T], typing.Generic[T], arg=T):
__type_params__ = (T,)
...
return Bag
Bag = decorator(TYPE_PARAMS_OF_Bag())
8.10.3. Generic type aliases¶
The type
statement can also be used to create a generic type alias:
type ListOrSet[T] = list[T] | set[T]
Except for the lazy evaluation of the value, this is equivalent to:
annotation-def TYPE_PARAMS_OF_ListOrSet():
T = typing.TypeVar("T")
annotation-def VALUE_OF_ListOrSet():
return list[T] | set[T]
# In reality, the value is lazily evaluated
return typing.TypeAliasType("ListOrSet", VALUE_OF_ListOrSet(), type_params=(T,))
ListOrSet = TYPE_PARAMS_OF_ListOrSet()
Here, annotation-def
(not a real keyword) indicates an
annotation scope. The capitalized names
like TYPE_PARAMS_OF_ListOrSet
are not actually bound at runtime.
각주