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README.md
Pampy: Pattern Matching for Python
Pampy is pretty small, reasonably fast, and often makes your code more readable, and easier to reason about.
You can write many patterns
Patterns are evaluated in the order they appear.
You can write Fibonacci
The operator _ means "any other case I didn't think of".
from pampy import match, _ def fibonacci(n): return match(n, 1, 1, 2, 1, _, lambda x: fibonacci(x-1) + fibonacci(x-2) )
You can write a Lisp calculator in 5 lines
from pampy import match, REST, _ def lisp(exp): return match(exp, int, lambda x: x, callable, lambda x: x, (callable, REST), lambda f, rest: f(*map(lisp, rest)), tuple, lambda t: list(map(lisp, t)), ) plus = lambda a, b: a + b minus = lambda a, b: a - b from functools import reduce lisp((plus, 1, 2)) # => 3 lisp((plus, 1, (minus, 4, 2))) # => 3 lisp((reduce, plus, (1, 2, 3)) # => 6
You can match so many things!
match(x, 3, "this matches the number 3", int, "matches any integer", (str, int), lambda a, b: "a tuple (a, b) you can use in a function", [1, 2, _], "any list of 3 elements that begins with [1, 2]", {'x': _}, "any dict with a key 'x' and any value associated", _, "anthing else" )
You can match [HEAD, TAIL]
from pampy import match, HEAD, TAIL, _ x = [1, 2, 3] match(x, [1, TAIL], lambda t: t) # => [2, 3] match(x, [HEAD, TAIL], lambda h, t: (h, t)) # => (1, [2, 3])
TAIL
and REST
actually mean the same thing.
You can nest lists and tuples
from pampy import match, _ x = [1, [2, 3], 4] match(x, [1, [_, 3], _], lambda a, b: [1, [a, 3], b]) # => [1, [2, 3], 4]
You can nest dicts. And you can use _ as key!
pet = { 'type': 'dog', 'details': { 'age': 3 } } match(pet, { 'details': { 'age': _ } }, lambda age: age) # => 3 match(pet, { _ : { 'age': _ } }, lambda a, b: (a, b)) # => ('details', 3)
It feels like putting multiple _ inside dicts shouldn't work. Isn't ordering in dicts not guaranteed ? But it does because in Python 3.7, dict is an OrderedDict by default
All the things you can match
As Pattern you can use any Python type, any class, or any Python value.
The operator _
and types like int
or str
, extract variables that are passed to functions.
Types and Classes are matched via instanceof(value, pattern)
.
Iterable
Patterns match recursively through all their elements. The same goes for dictionaries.
Pattern Example
What it means
Matched Example
Arguments Passed to function
NOT Matched Example
"hello"
only the string "hello"
matches
"hello"
"hello"
any other value
int
Any integer
42
42
any other value
float
Any float number
2.35
2.35
any other value
str
Any string
"hello"
"hello"
any other value
tuple
Any tuple
(1, 2)
(1, 2)
any other value
list
Any list
[1, 2]
[1, 2]
any other value
MyClass
Any instance of MyClass
MyClass()
that instance
any other object instance
_
Any object (even None)
ANY
The same as _
(int, int)
A tuple made of any two integers
(1, 2)
[1, 2, _]
A list that starts with 1, 2 and ends with any value
[1, 2, 3]
3
[1, 2, 3, 4]
[1, 2, TAIL]
A list that start with 1, 2 and ends with any sequence
[1, 2, 3, 4]
[3, 4]
[1, 7, 7, 7]
{'type':'dog', age: _ }
Any dict with type: "dog"
and with an age
{"type":"dog", "age": 3}
3
{"type":"cat", "age":2}
{'type':'dog', age: int }
Any dict with type: "dog"
and with an int
age
{"type":"dog", "age": 3}
3
{"type":"dog", "age":2.3}
Using strict=False
By default match()
is strict. If no pattern matches, it raises a MatchError
.
You can prevent it using strict=False
. In this case match
just returns False
if nothing matches.
>>> match([1, 2], [1, 2, 3], "whatever") MatchError: '_' not provided. This case is not handled: >>> match([1, 2], [1, 2, 3], "whatever", strict=False) False
Install
Currently it works only in Python > 3.6 Because dict matching can work only in the latest Pythons.
I'm currently working on a backport with some minor syntax changes for Python2.
To install it:
$ pip install pampy
or
$ pip3 install pampy
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