Match Semantics

The match statement first evaluates the subject expression. If a comma is present a tuple is constructed using the standard rules.

The resulting subject value is then used to select the first case block whose patterns succeeds matching it and whose guard condition (if present) is “truthy”. If no case blocks qualify the match statement is complete; otherwise, the block of the selected case block is executed. The usual rules for executing a block nested inside a compound statement apply (e.g. an if statement).

Name bindings made during a successful pattern match outlive the executed block and can be used after the match statement.

During failed pattern matches, some subpatterns may succeed. For example, while matching the pattern (0, x, 1) with the value [0, 1, 2], the subpattern x may succeed if the list elements are matched from left to right. The implementation may choose to either make persistent bindings for those partial matches or not. User code including a match statement should not rely on the bindings being made for a failed match, but also shouldn’t assume that variables are unchanged by a failed match. This part of the behavior is left intentionally unspecified so different implementations can add optimizations, and to prevent introducing semantic restrictions that could limit the extensibility of this feature.

The precise pattern binding rules vary per pattern type and are specified below.

Guards

If a guard is present on a case block, once the pattern or patterns in the case block succeed, the expression in the guard is evaluated. If this raises an exception, the exception bubbles up. Otherwise, if the condition is “truthy” the case block is selected; if it is “falsy” the case block is not selected.

Since guards are expressions they are allowed to have side effects. 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., even if determining whether those patterns succeed may happen out of order, guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected.

Irrefutable case blocks

A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. In particular, capture patterns and wildcard patterns are irrefutable, and so are AS patterns whose left-hand side is irrefutable, OR patterns containing at least one irrefutable pattern, and parenthesized irrefutable patterns.

A case block is considered irrefutable if it has no guard and its pattern is irrefutable.

A match statement may have at most one irrefutable case block, and it must be last.

AS Patterns

Syntax:

as_pattern: or_pattern 'as' capture_pattern

(Note: the name on the right may not be _.)

An AS pattern matches the OR pattern on the left of the as keyword against the subject. If this fails, the AS pattern fails. Otherwise, the AS pattern binds the subject to the name on the right of the as keyword and succeeds.

OR Patterns

Syntax:

or_pattern: '|'.closed_pattern+

When two or more patterns are separated by vertical bars (|), this is called an OR pattern. (A single closed pattern is just that.)

Only the final subpattern may be irrefutable.

Each subpattern must bind the same set of names.

An OR pattern matches each of its subpatterns in turn to the subject, until one succeeds. The OR pattern is then deemed to succeed. If none of the subpatterns succeed the OR pattern fails.

Literal Patterns

Syntax:

literal_pattern:
    | signed_number
    | signed_number '+' NUMBER
    | signed_number '-' NUMBER
    | strings
    | 'None'
    | 'True'
    | 'False'
signed_number: 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 only permitted to express complex numbers; they require a real number on the left and an imaginary number on the right.

A literal pattern succeeds if the subject value compares equal to the value expressed by the literal, using the following comparisons rules:

• Numbers and strings are compared using the == operator.
• The singleton literals None, True and False are compared using the is operator.

Capture Patterns

Syntax:

capture_pattern: !"_" NAME

The single underscore (_) is not a capture pattern (this is what !"_" expresses). It is treated as a wildcard pattern.

A capture pattern always succeeds. It binds the subject value to the name using the scoping rules for name binding established for the walrus operator in PEP 572. (Summary: the name becomes a local variable in the closest containing function scope unless there’s an applicable nonlocal or global statement.)

In a given pattern, a given name may be bound only once. This disallows for example case x, x: ... but allows case [x] | x: ....

Wildcard Pattern

Syntax:

wildcard_pattern: "_"

A wildcard pattern always succeeds. It binds no name.

Value Patterns

Syntax:

value_pattern: attr
attr: name_or_attr '.' NAME
name_or_attr: attr | NAME

The dotted name in the pattern is looked up using the standard Python name resolution rules. However, when the same value pattern 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. (To clarify, this cache is strictly tied to a given execution of a given match statement.)

The pattern succeeds if the value found thus compares equal to the subject value (using the == operator).

Group Patterns

Syntax:

group_pattern: '(' pattern ')'

(For the syntax of pattern, see Patterns above. Note that it contains no comma – a parenthesized series of items with at least one comma is a sequence pattern, as is ().)

A parenthesized pattern has no additional syntax. It allows users to add parentheses around patterns to emphasize the intended grouping.

Sequence Patterns

Syntax:

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)

(Note that a single parenthesized pattern without a trailing comma is a group pattern, not a sequence pattern. However a single pattern enclosed in [...] is still a sequence pattern.)

There is no semantic difference between a sequence pattern using [...], a sequence pattern using (...), and an open sequence pattern.

A sequence pattern may contain at most one star subpattern. 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.

For a sequence pattern to succeed the subject must be a sequence, where being a sequence is defined as its class being one of the following:

• a class that inherits from collections.abc.Sequence
• a Python class that has been registered as a collections.abc.Sequence
• a builtin class that has its Py_TPFLAGS_SEQUENCE bit set
• a class that inherits from any of the above (including classes defined before a parent’s Sequence registration)

The following standard library classes will have their Py_TPFLAGS_SEQUENCE bit set:

• array.array
• collections.deque
• list
• memoryview
• range
• tuple

A fixed-length sequence pattern fails if the length of the subject sequence is not equal to the number of subpatterns.

A variable-length sequence pattern fails if the length of the subject sequence is less than the number of non-star subpatterns.

The length of the subject sequence is obtained using the builtin len() function (i.e., via the __len__ protocol). However, the interpreter may cache this value in a similar manner as described for value patterns.

A fixed-length sequence pattern matches the subpatterns to corresponding items of the subject sequence, from left to right. Matching stops (with a failure) as soon as a subpattern fails. If all subpatterns succeed in matching their corresponding item, the sequence pattern succeeds.

A variable-length sequence pattern first matches the leading non-star subpatterns to the corresponding items of the subject sequence, as for a fixed-length sequence. If this succeeds, the star subpattern matches a list formed of the remaining subject items, with items removed from the end corresponding to the non-star subpatterns following the star subpattern. The remaining non-star subpatterns are then matched to the corresponding subject items, as for a fixed-length sequence.

Mapping Patterns

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

(Note that **_ is disallowed by this syntax.)

A mapping pattern may contain at most one double star pattern, and it must be last.

A mapping pattern may not contain duplicate key values. (If all key patterns are literal patterns this is considered a syntax error; otherwise this is a runtime error and will raise ValueError.)

For a mapping pattern to succeed the subject must be a mapping, where being a mapping is defined as its class being one of the following:

• a class that inherits from collections.abc.Mapping
• a Python class that has been registered as a collections.abc.Mapping
• a builtin class that has its Py_TPFLAGS_MAPPING bit set
• a class that inherits from any of the above (including classes defined before a parent’s Mapping registration)

The standard library classes dict and mappingproxy will have their Py_TPFLAGS_MAPPING bit set.

A mapping pattern succeeds 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. Keys are always compared with the == operator. If a '**' NAME form is present, that name is bound to a dict containing remaining key-value pairs from the subject mapping.

If duplicate keys are detected in the mapping pattern, the pattern is considered invalid, and a ValueError is raised.

Key-value pairs are matched using the two-argument form of the subject’s get() method. As a consequence, matched key-value pairs must already be present in the mapping, and not created on-the-fly by __missing__ or __getitem__. For example, collections.defaultdict instances will only be matched by patterns with keys that were already present when the match statement was entered.

Class Patterns

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

A class pattern may not repeat the same keyword multiple times.

If name_or_attr is not an instance of the builtin type, TypeError is raised.

A class pattern fails if the subject is not an instance of name_or_attr. This is tested using isinstance().

If no arguments are present, the pattern succeeds if the isinstance() check succeeds. Otherwise:

• If only keyword patterns are present, they are processed as follows, one by one:
  • 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 fails.
    • Otherwise, the subpattern associated with the keyword is matched against the attribute value. If this fails, the class pattern fails. If it succeeds, the match proceeds to the next keyword.
  • If all keyword patterns succeed, the class pattern as a whole succeeds.
• If any positional patterns are present, they are converted to keyword patterns (see below) and treated as additional keyword patterns, preceding the syntactic keyword patterns (if any).

Positional patterns are converted to keyword patterns using the __match_args__ attribute on the class designated by name_or_attr, as follows:

• For a number of built-in types (specified below), a single positional subpattern is accepted which will match the entire subject. (Keyword patterns work as for other types here.)
• 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 the length of __match_args__ (as obtained using len()), TypeError is raised.
• Otherwise, positional pattern i is converted to a keyword pattern using __match_args__[i] as the keyword, provided it the latter is a string; if it is not, TypeError is raised.
• For duplicate keywords, TypeError is raised.

Once the positional patterns have been converted to keyword patterns, the match proceeds as if there were only keyword patterns.

As mentioned above, for the following built-in types the handling of positional subpatterns is different: bool, bytearray, bytes, dict, float, frozenset, int, list, set, str, and tuple.

This behavior is roughly equivalent to the following:

class C:
    __match_args__ = ("__match_self_prop__",)
    @property
    def __match_self_prop__(self):
        return self