pykell 0.0.2

Python functional programming library inspired by Haskell.

Pykell

Python functional programming library inspired by Haskell.

This is a personal project to deepen my understanding of functional programming by implementing this DSL in python.

It is open-source, so feel free to open issues and pull requests!

Installing

We have a stable release under pypi:

pip install pykell

Features

This DSL makes it easy to write functional programming patters with a clean syntax.

Functions

This is an abstraction layer on top of Python regular functions and lambdas.

from pykell.typing import Function
from pykell.functions import F

# Via a decorator pattern
@F
def f(x: int, y: float) -> float: return x + y

# via a lambda (with type hints support)
g = F[float, str](lambda x: f"This is a float: {x}")


# automatic curying:
f # Function[int, Function[float, float]]
f2 = f |2 # application via | operator
f2_ = f(2) # works just as fine!
my_float = f2 |1.5


# composition
h = f2 >> g # this will return ⃘⃘⃘⃘f ∘ g
h | 1.2 # This is a float: 3.2

# Chaining
x = f |2 |1.5

Containers

These are well known containers that can make your life easyer when programming.

from pykell.typing import Maybe, Just, Nothing, Error, Result

def f(x: int) -> Maybe[int]:
    return Just(x + 10) if x < 10 else Nothing()

def f(x: int) -> Result[int, Exception]:
    return Just(x + 10) if x < 10 else Error(Exception("This  is too big!!!"))

Functors

This is some syntatic sugar to use functors in python.

from pykell.typing import Function
from pykell.functors import Functor

@Functor
def int_to_str(f: Function[int, float]) -> Function[str, str]:
    return lambda x: str(f(int(x)))


# some functions
f = F[int, float](lambda x: x / 7)
g = F[int, float](lambda x: x * 8)

new_f: Function[str, str] = int_to_str(f) # this works

# But this is cleaner!
with int_to_str:
    # inside here all | calls go through the functor
    x = f |"1" # "0.14285714285714285"
    y = f |"3" # "24"
    z = f(7) # when calling with (), no functor is applied

Containers

These are well known containers that can make your life easyer when programming.

from pykell.typing import Maybe, Just, Nothing, Error, Result

def f(x: int) -> Maybe[int]:
    return Just(x + 10) if x < 10 else Nothing()

def f(x: int) -> Result[int, Exception]:
    return Just(x + 10) if x < 10 else Error(Exception("This  is too big!!!"))

Arrays

This is inspired by other array language features but use haskells lazyness to do computations.

from pykell.arrays import arr

result = (
    arr([1, 2, 3])
    .map(lambda x: x + 1)
    .filter(lambda x: x % 2 != 0)
    .fold(0, lambda acc, cur: cur + acc)
)

print(result._) # evaluates the expression:


# you can do infinite calculations with it!
def naturals(): 
    i = 0
    while True: 
        yield (i := i + 1)


result = (
    arr(naturals())
    .map(lambda x: x + 1)
    .filter(lambda x: x % 2 != 0)
    .take(10)
)

print(result._) # 3, 5, 7, ...

Monads

This is a good one.

from pykell.monads import MaybeMonad
from pykell.functions import F
from pykell.typing import Maybe, Just, Nothing

# define some functions we want to compose ...
f = F[int, Maybe[int]](lambda x: Just(x + 10) if x < 10 else Nothing())
g = F[int, Maybe[float]](lambda x: Just(x / 7) if x < 10 else Nothing())

# Play inside the monadic environment!
@MaybeMonad.do
def calculate(x):
    y: int = yield f(x)  # yield calls with the bind. 
                    # Think of it like the let! in f# or x <- ... in Haskell. 
    if y < 5: # besides the yield everything works as normal!
        return y + 5

    z: float = yield g(z)
    return z - 1.5

calculate(-10) # Just(5)
calculate(4)   # Just(2.0)
calculate(11)  # Nothing()

Contributions

This is just an experiment. If you have any ideas of features you want to see in here please reach out!