pyfuncpatmatch 0.1.0

Pattern matching (like haskell) for python fonctions

pyfuncpatmatch

Pattern matching (like haskell) for python fonctions

Install

pip install pyfuncpatmatch

Usage

Exemples

For a full list of exemples and tests done, see: main

eq

from pyfuncpatmatch import pm, _eq

@pm(lambda _: 0, _eq(0))
@pm(lambda _: 1, _eq(1))
def fib_rec(n: int):
    return fib_rec(n - 1) + fib_rec(n - 2)

gte, lte

from pyfuncpatmatch import pm, _gte, _lte

@pm(lambda x: f"You are not a teen ({x})", _gte(18))
@pm(lambda x: f"You are not a teen ({x})", _lte(11))
def is_teen(x):
    return f"You are a teen ({x})"

and, lambda

from pyfuncpatmatch import pm, _and, _lambda

@pm(
    lambda _: "FizzBuzz",
    _and(_lambda(lambda x: x % 3 == 0), _lambda(lambda x: x % 5 == 0)),
)
@pm(lambda _: "Fizz", _lambda(lambda x: x % 3 == 0))
@pm(lambda _: "Buzz", _lambda(lambda x: x % 5 == 0))
def fizzbuzz(x):
    return f"{x}"

empty, all, extract

from pyfuncpatmatch import pm, pm_raise, _empty, __, _extract

# pm_raise is a function that raise the exception being passed
# -> lambda can't raise the expression directly
@pm(lambda _: pm_raise(ValueError("empty iterable")), _empty())
@pm(lambda splited: splited[0], _extract(__(), __()))
def head(x):
    raise SyntaxError(f"{x} is not iterable")

@pm(lambda splited: splited[1], _extract(__(), __()))
def tail(x):
    raise ValueError(f"{x} is not iterable")

Keyword Matching

Arguments and Keyword Arguments are passed to the callback the same way they would have be passed to the initial function.

But when the callback is a lambda, it automatically transform keywords arguments as arguments (because passing keyword arguments to lambda raise an exception).

This ensure that you can keep calling the initial function with arguments and keywords arguments.

from pyfuncpatmatch import pm, __, _or, _eq

@pm(lambda x, z: (x,z), x=__(), z=_or(_eq(2), _eq(5)))
@pm(lambda x, z: (x,z), __(), z=_eq(10))
def select(x, y, z):
    return (x, y, z)

# >>> select(1, 2, z=3)
# (1, 2, 3)
# >>> select(0, 1, 2)
# (0, 2)
# >>> select(1, 3, 10)
# (1, 10)