PEP 636 – Structural Pattern Matching: Tutorial
- PEP
- 636
- Title
- Structural Pattern Matching: Tutorial
- Author
- Daniel F Moisset <dfmoisset at gmail.com>
- Sponsor
- Guido van Rossum <guido at python.org>
- BDFL-Delegate
- Discussions-To
- Python-Dev <python-dev@python.org>
- Status
- Final
- Type
- Informational
- Created
- 12-Sep-2020
- Python-Version
- 3.10
- Post-History
- 22-Oct-2020, 08-Feb-2021
- Resolution
- https://mail.python.org/archives/list/python-committers@python.org/message/SQC2FTLFV5A7DV7RCEAR2I2IKJKGK7W3
Contents
- Abstract
- Tutorial
- Matching sequences
- Matching multiple patterns
- Matching specific values
- Matching multiple values
- Adding a wildcard
- Composing patterns
- Or patterns
- Capturing matched sub-patterns
- Adding conditions to patterns
- Adding a UI: Matching objects
- Matching positional attributes
- Matching against constants and enums
- Going to the cloud: Mappings
- Matching builtin classes
- Appendix A – Quick Intro
- Copyright
Abstract
This PEP is a tutorial for the pattern matching introduced by PEP 634.
PEP 622 proposed syntax for pattern matching, which received detailed discussion both from the community and the Steering Council. A frequent concern was about how easy it would be to explain (and learn) this feature. This PEP addresses that concern providing the kind of document which developers could use to learn about pattern matching in Python.
This is considered supporting material for PEP 634 (the technical specification for pattern matching) and PEP 635 (the motivation and rationale for having pattern matching and design considerations).
For readers who are looking more for a quick review than for a tutorial, see Appendix A.
Tutorial
As an example to motivate this tutorial, you will be writing a text adventure. That is
a form of interactive fiction where the user enters text commands to interact with a
fictional world and receives text descriptions of what happens. Commands will be
simplified forms of natural language like get sword
, attack dragon
, go north
,
enter shop
or buy cheese
.
Matching sequences
Your main loop will need to get input from the user and split it into words, let’s say a list of strings like this:
command = input("What are you doing next? ")
# analyze the result of command.split()
The next step is to interpret the words. Most of our commands will have two words: an action and an object. So you may be tempted to do the following:
[action, obj] = command.split()
... # interpret action, obj
The problem with that line of code is that it’s missing something: what if the user
types more or fewer than 2 words? To prevent this problem you can either check the length
of the list of words, or capture the ValueError
that the statement above would raise.
You can use a matching statement instead:
match command.split():
case [action, obj]:
... # interpret action, obj
The match statement evaluates the “subject” (the value after the match
keyword), and checks it against the pattern (the code next to case
). A pattern
is able to do two different things:
- Verify that the subject has certain structure. In your case, the
[action, obj]
pattern matches any sequence of exactly two elements. This is called matching - It will bind some names in the pattern to component elements of your subject. In
this case, if the list has two elements, it will bind
action = subject[0]
andobj = subject[1]
.
If there’s a match, the statements inside the case block will be executed with the
bound variables. If there’s no match, nothing happens and the statement after
match
is executed next.
Note that, in a similar way to unpacking assignments, you can use either parenthesis,
brackets, or just comma separation as synonyms. So you could write case action, obj
or case (action, obj)
with the same meaning. All forms will match any sequence (for
example lists or tuples).
Matching multiple patterns
Even if most commands have the action/object form, you might want to have user commands
of different lengths. For example, you might want to add single verbs with no object like
look
or quit
. A match statement can (and is likely to) have more than one
case
:
match command.split():
case [action]:
... # interpret single-verb action
case [action, obj]:
... # interpret action, obj
The match statement will check patterns from top to bottom. If the pattern doesn’t
match the subject, the next pattern will be tried. However, once the first
matching pattern is found, the body of that case is executed, and all further
cases are ignored. This is similar to the way that an if/elif/elif/...
statement works.
Matching specific values
Your code still needs to look at the specific actions and conditionally execute
different logic depending on the specific action (e.g., quit
, attack
, or buy
).
You could do that using a chain of if/elif/elif/...
, or using a dictionary of
functions, but here we’ll leverage pattern matching to solve that task. Instead of a
variable, you can use literal values in patterns (like "quit"
, 42
, or None
).
This allows you to write:
match command.split():
case ["quit"]:
print("Goodbye!")
quit_game()
case ["look"]:
current_room.describe()
case ["get", obj]:
character.get(obj, current_room)
case ["go", direction]:
current_room = current_room.neighbor(direction)
# The rest of your commands go here
A pattern like ["get", obj]
will match only 2-element sequences that have a first
element equal to "get"
. It will also bind obj = subject[1]
.
As you can see in the go
case, we also can use different variable names in
different patterns.
Literal values are compared with the ==
operator except for the constants True
,
False
and None
which are compared with the is
operator.
Matching multiple values
A player may be able to drop multiple items by using a series of commands
drop key
, drop sword
, drop cheese
. This interface might be cumbersome, and
you might like to allow dropping multiple items in a single command, like
drop key sword cheese
. In this case you don’t know beforehand how many words will
be in the command, but you can use extended unpacking in patterns in the same way that
they are allowed in assignments:
match command.split():
case ["drop", *objects]:
for obj in objects:
character.drop(obj, current_room)
# The rest of your commands go here
This will match any sequences having “drop” as its first elements. All remaining
elements will be captured in a list
object which will be bound to the objects
variable.
This syntax has similar restrictions as sequence unpacking: you can not have more than one starred name in a pattern.
Adding a wildcard
You may want to print an error message saying that the command wasn’t recognized when
all the patterns fail. You could use the feature we just learned and write
case [*ignored_words]
as your last pattern. There’s however a much simpler way:
match command.split():
case ["quit"]: ... # Code omitted for brevity
case ["go", direction]: ...
case ["drop", *objects]: ...
... # Other cases
case _:
print(f"Sorry, I couldn't understand {command!r}")
This special pattern which is written _
(and called wildcard) always
matches but it doesn’t bind any variables.
Note that this will match any object, not just sequences. As such, it only makes sense to have it by itself as the last pattern (to prevent errors, Python will stop you from using it before).
Composing patterns
This is a good moment to step back from the examples and understand how the patterns that you have been using are built. Patterns can be nested within each other, and we have been doing that implicitly in the examples above.
There are some “simple” patterns (“simple” here meaning that they do not contain other patterns) that we’ve seen:
- Capture patterns (stand-alone names like
direction
,action
,objects
). We never discussed these separately, but used them as part of other patterns. - Literal patterns (string literals, number literals,
True
,False
, andNone
) - The wildcard pattern
_
Until now, the only non-simple pattern we have experimented with is the sequence pattern.
Each element in a sequence pattern can in fact be
any other pattern. This means that you could write a pattern like
["first", (left, right), _, *rest]
. This will match subjects which are a sequence of at
least three elements, where the first one is equal to "first"
and the second one is
in turn a sequence of two elements. It will also bind left=subject[1][0]
,
right=subject[1][1]
, and rest = subject[3:]
Or patterns
Going back to the adventure game example, you may find that you’d like to have several
patterns resulting in the same outcome. For example, you might want the commands
north
and go north
to be equivalent. You may also desire to have aliases for
get X
, pick up X
and pick X up
for any X.
The |
symbol in patterns combines them as alternatives. You could for example write:
match command.split():
... # Other cases
case ["north"] | ["go", "north"]:
current_room = current_room.neighbor("north")
case ["get", obj] | ["pick", "up", obj] | ["pick", obj, "up"]:
... # Code for picking up the given object
This is called an or pattern and will produce the expected result. Patterns are
tried from left to right; this may be relevant to know what is bound if more than
one alternative matches. An important restriction when writing or patterns is that all
alternatives should bind the same variables. So a pattern [1, x] | [2, y]
is not
allowed because it would make unclear which variable would be bound after a successful
match. [1, x] | [2, x]
is perfectly fine and will always bind x
if successful.
Capturing matched sub-patterns
The first version of our “go” command was written with a ["go", direction]
pattern.
The change we did in our last version using the pattern ["north"] | ["go", "north"]
has some benefits but also some drawbacks in comparison: the latest version allows the
alias, but also has the direction hardcoded, which will force us to actually have
separate patterns for north/south/east/west. This leads to some code duplication, but at
the same time we get better input validation, and we will not be getting into that
branch if the command entered by the user is "go figure!"
instead of a direction.
We could try to get the best of both worlds doing the following (I’ll omit the aliased version without “go” for brevity):
match command.split():
case ["go", ("north" | "south" | "east" | "west")]:
current_room = current_room.neighbor(...)
# how do I know which direction to go?
This code is a single branch, and it verifies that the word after “go” is really a direction. But the code moving the player around needs to know which one was chosen and has no way to do so. What we need is a pattern that behaves like the or pattern but at the same time does a capture. We can do so with an as pattern:
match command.split():
case ["go", ("north" | "south" | "east" | "west") as direction]:
current_room = current_room.neighbor(direction)
The as-pattern matches whatever pattern is on its left-hand side, but also binds the value to a name.
Adding conditions to patterns
The patterns we have explored above can do some powerful data filtering, but sometimes
you may wish for the full power of a boolean expression. Let’s say that you would actually
like to allow a “go” command only in a restricted set of directions based on the possible
exits from the current_room. We can achieve that by adding a guard to our
case. Guards consist of the if
keyword followed by any expression:
match command.split():
case ["go", direction] if direction in current_room.exits:
current_room = current_room.neighbor(direction)
case ["go", _]:
print("Sorry, you can't go that way")
The guard is not part of the pattern, it’s part of the case. It’s only checked if
the pattern matches, and after all the pattern variables have been bound (that’s why the
condition can use the direction
variable in the example above). If the pattern
matches and the condition is truthy, the body of the case executes normally. If the
pattern matches but the condition is falsy, the match statement proceeds to check the
next case as if the pattern hadn’t matched (with the possible side-effect of
having already bound some variables).
Adding a UI: Matching objects
Your adventure is becoming a success and you have been asked to implement a graphical
interface. Your UI toolkit of choice allows you to write an event loop where you can get a new
event object by calling event.get()
. The resulting object can have different type and
attributes according to the user action, for example:
- A
KeyPress
object is generated when the user presses a key. It has akey_name
attribute with the name of the key pressed, and some other attributes regarding modifiers. - A
Click
object is generated when the user clicks the mouse. It has an attributeposition
with the coordinates of the pointer. - A
Quit
object is generated when the user clicks on the close button for the game window.
Rather than writing multiple isinstance()
checks, you can use patterns to recognize
different kinds of objects, and also apply patterns to its attributes:
match event.get():
case Click(position=(x, y)):
handle_click_at(x, y)
case KeyPress(key_name="Q") | Quit():
game.quit()
case KeyPress(key_name="up arrow"):
game.go_north()
...
case KeyPress():
pass # Ignore other keystrokes
case other_event:
raise ValueError(f"Unrecognized event: {other_event}")
A pattern like Click(position=(x, y))
only matches if the type of the event is
a subclass of the Click
class. It will also require that the event has a position
attribute that matches the (x, y)
pattern. If there’s a match, the locals x
and
y
will get the expected values.
A pattern like KeyPress()
, with no arguments will match any object which is an
instance of the KeyPress
class. Only the attributes you specify in the pattern are
matched, and any other attributes are ignored.
Matching positional attributes
The previous section described how to match named attributes when doing an object match. For some objects it could be convenient to describe the matched arguments by position (especially if there are only a few attributes and they have a “standard” ordering). If the classes that you are using are named tuples or dataclasses, you can do that by following the same order that you’d use when constructing an object. For example, if the UI framework above defines their class like this:
from dataclasses import dataclass
@dataclass
class Click:
position: tuple
button: Button
then you can rewrite your match statement above as:
match event.get():
case Click((x, y)):
handle_click_at(x, y)
The (x, y)
pattern will be automatically matched against the position
attribute, because the first argument in the pattern corresponds to the first
attribute in your dataclass definition.
Other classes don’t have a natural ordering of their attributes so you’re required to use explicit names in your pattern to match with their attributes. However, it’s possible to manually specify the ordering of the attributes allowing positional matching, like in this alternative definition:
class Click:
__match_args__ = ("position", "button")
def __init__(self, pos, btn):
self.position = pos
self.button = btn
...
The __match_args__
special attribute defines an explicit order for your attributes
that can be used in patterns like case Click((x,y))
.
Matching against constants and enums
Your pattern above treats all mouse buttons the same, and you have decided that you
want to accept left-clicks, and ignore other buttons. While doing so, you notice that
the button
attribute is typed as a Button
which is an enumeration built with
enum.Enum
. You can in fact match against enumeration values like this:
match event.get():
case Click((x, y), button=Button.LEFT): # This is a left click
handle_click_at(x, y)
case Click():
pass # ignore other clicks
This will work with any dotted name (like math.pi
). However an unqualified name (i.e.
a bare name with no dots) will be always interpreted as a capture pattern, so avoid
that ambiguity by always using qualified constants in patterns.
Going to the cloud: Mappings
You have decided to make an online version of your game. All
of your logic will be in a server, and the UI in a client which will communicate using
JSON messages. Via the json
module, those will be mapped to Python dictionaries,
lists and other builtin objects.
Our client will receive a list of dictionaries (parsed from JSON) of actions to take, each element looking for example like these:
{"text": "The shop keeper says 'Ah! We have Camembert, yes sir'", "color": "blue"}
- If the client should make a pause
{"sleep": 3}
- To play a sound
{"sound": "filename.ogg", "format": "ogg"}
Until now, our patterns have processed sequences, but there are patterns to match mappings based on their present keys. In this case you could use:
for action in actions:
match action:
case {"text": message, "color": c}:
ui.set_text_color(c)
ui.display(message)
case {"sleep": duration}:
ui.wait(duration)
case {"sound": url, "format": "ogg"}:
ui.play(url)
case {"sound": _, "format": _}:
warning("Unsupported audio format")
The keys in your mapping pattern need to be literals, but the values can be any pattern. As in sequence patterns, all subpatterns have to match for the general pattern to match.
You can use **rest
within a mapping pattern to capture additional keys in
the subject. Note that if you omit this, extra keys in the subject will be
ignored while matching, i.e. the message
{"text": "foo", "color": "red", "style": "bold"}
will match the first pattern
in the example above.
Matching builtin classes
The code above could use some validation. Given that messages came from an external source, the types of the field could be wrong, leading to bugs or security issues.
Any class is a valid match target, and that includes built-in classes like bool
str
or int
. That allows us to combine the code above with a class pattern.
So instead of writing {"text": message, "color": c}
we can use
{"text": str() as message, "color": str() as c}
to ensure that message
and c
are both strings. For many builtin classes (see PEP-634 for the whole list), you can
use a positional parameter as a shorthand, writing str(c)
rather than str() as c
.
The fully rewritten version looks like this:
for action in actions:
match action:
case {"text": str(message), "color": str(c)}:
ui.set_text_color(c)
ui.display(message)
case {"sleep": float(duration)}:
ui.wait(duration)
case {"sound": str(url), "format": "ogg"}:
ui.play(url)
case {"sound": _, "format": _}:
warning("Unsupported audio format")
Appendix A – Quick Intro
A match statement takes an expression and compares its value to successive patterns given as one or more case blocks. This is superficially similar to a switch statement in C, Java or JavaScript (and many other languages), but much more powerful.
The simplest form compares a subject value against one or more literals:
def http_error(status):
match status:
case 400:
return "Bad request"
case 404:
return "Not found"
case 418:
return "I'm a teapot"
case _:
return "Something's wrong with the Internet"
Note the last block: the “variable name” _
acts as a wildcard and
never fails to match.
You can combine several literals in a single pattern using |
(“or”):
case 401 | 403 | 404:
return "Not allowed"
Patterns can look like unpacking assignments, and can be used to bind variables:
# point is an (x, y) tuple
match point:
case (0, 0):
print("Origin")
case (0, y):
print(f"Y={y}")
case (x, 0):
print(f"X={x}")
case (x, y):
print(f"X={x}, Y={y}")
case _:
raise ValueError("Not a point")
Study that one carefully! The first pattern has two literals, and can
be thought of as an extension of the literal pattern shown above. But
the next two patterns combine a literal and a variable, and the
variable binds a value from the subject (point
). The fourth
pattern captures two values, which makes it conceptually similar to
the unpacking assignment (x, y) = point
.
If you are using classes to structure your data you can use the class name followed by an argument list resembling a constructor, but with the ability to capture attributes into variables:
from dataclasses import dataclass
@dataclass
class Point:
x: int
y: int
def where_is(point):
match point:
case Point(x=0, y=0):
print("Origin")
case Point(x=0, y=y):
print(f"Y={y}")
case Point(x=x, y=0):
print(f"X={x}")
case Point():
print("Somewhere else")
case _:
print("Not a point")
You can use positional parameters with some builtin classes that provide an
ordering for their attributes (e.g. dataclasses). You can also define a specific
position for attributes in patterns by setting the __match_args__
special
attribute in your classes. If it’s set to (“x”, “y”), the following patterns are all
equivalent (and all bind the y
attribute to the var
variable):
Point(1, var)
Point(1, y=var)
Point(x=1, y=var)
Point(y=var, x=1)
Patterns can be arbitrarily nested. For example, if we have a short list of points, we could match it like this:
match points:
case []:
print("No points")
case [Point(0, 0)]:
print("The origin")
case [Point(x, y)]:
print(f"Single point {x}, {y}")
case [Point(0, y1), Point(0, y2)]:
print(f"Two on the Y axis at {y1}, {y2}")
case _:
print("Something else")
We can add an if
clause to a pattern, known as a “guard”. If the
guard is false, match
goes on to try the next case block. Note
that value capture happens before the guard is evaluated:
match point:
case Point(x, y) if x == y:
print(f"Y=X at {x}")
case Point(x, y):
print(f"Not on the diagonal")
Several other key features:
- Like unpacking assignments, tuple and list patterns have exactly the
same meaning and actually match arbitrary sequences. An important
exception is that they don’t match iterators or strings.
(Technically, the subject must be an instance of
collections.abc.Sequence
.) - Sequence patterns support wildcards:
[x, y, *rest]
and(x, y, *rest)
work similar to wildcards in unpacking assignments. The name after*
may also be_
, so(x, y, *_)
matches a sequence of at least two items without binding the remaining items. - Mapping patterns:
{"bandwidth": b, "latency": l}
captures the"bandwidth"
and"latency"
values from a dict. Unlike sequence patterns, extra keys are ignored. A wildcard**rest
is also supported. (But**_
would be redundant, so it is not allowed.) - Subpatterns may be captured using the
as
keyword:case (Point(x1, y1), Point(x2, y2) as p2): ...
- Most literals are compared by equality, however the singletons
True
,False
andNone
are compared by identity. - Patterns may use named constants. These must be dotted names
to prevent them from being interpreted as capture variable:
from enum import Enum class Color(Enum): RED = 0 GREEN = 1 BLUE = 2 match color: case Color.RED: print("I see red!") case Color.GREEN: print("Grass is green") case Color.BLUE: print("I'm feeling the blues :(")
Copyright
This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.
Source: https://github.com/python/peps/blob/master/pep-0636.rst
Last modified: 2021-11-08 04:12:11 GMT