State-Monad is a Python library that encapsulates stateful computations into a monadic structure.
- Pragmatic Monad: Implements the core concepts of a state monad in a way that is practical and relevant for a Python developpers. It focus on usability rather than strict adherence to mathematical correctness.
- Object-Orgiented Design: State monad operations are built using Python classes, favoring an object-oriented approach that prioritizes working with objects rather than deeply nested functions.
- Type hinting: The implemented type hinting ensures that types are correctly inferred by type checkers like pyright.
You can install State-Monad using pip:
pip install statemonad
The state object is a Python object that represents the state in your computations. Each operation may modify the state and return a new values based on the updated state. The result is a chain of operations where the state flows through each step, with the State-Monad keeping the flow clean and organized.
In this example, we define the collect_even_numbers operations, which returns a CollectEvenNumbers state monad if the given number is even, or a default state monad encapsulating the value otherwise.
The example function performs monadic operations using the collect_even_numbers operator, resulting in a state monad.
Finally, the constructed state monad is applied with an empty tuple as the initial state.
from dataclassabc import dataclassabc
import statemonad
from statemonad.abc import StateMonadNode
from statemonad.typing import StateMonad
type State = tuple[int, ...]
state = tuple()
def collect_even_numbers(num: int):
"""
This function encapsulates the given number within a state monad
and saves it to the state if the number is even.
"""
if num % 2 == 0:
@dataclassabc(frozen=True)
class CollectEvenNumbers(StateMonadNode[State, int]):
num: int
def apply(self, state: State):
n_state = state + (self.num,)
return n_state, self.num
return statemonad.from_node(CollectEvenNumbers(num=num))
else:
return statemonad.from_[State](num)
# do some monadic operations using `flat_map`
def example(init):
return collect_even_numbers(init + 1).flat_map(
lambda x: collect_even_numbers(x + 1).flat_map(
lambda y: collect_even_numbers(y + 1).flat_map(
lambda z: collect_even_numbers(z + 1)
)
)
)
monad: StateMonad[State, int] = example(3)
# Output will be
# StateMonad(flat_map(CollectEvenNumbers(num=4), <lambda>))
print(monad)
# Output will be
# monad=StateMonadImpl(
# child=FlatMapImpl(
# child=CollectEvenNumbers(num=4),
# func=<function example.<locals>.<lambda> at 0x000001A546B53D80>))
print(f"{monad=}")
state, value = monad.apply(state)
print(f"{value=}") # Output will be value=7
print(f"{state=}") # Output will be state=(4, 6)Defining the CollectEvenNumbers state monad as a class allows for a clean and readable representation of the resulting Python object.
However, some details of this representation is obscured by the lambda function used with the flat_map method.
Using the donotation library, the monadic sequence above can be rewritten with the do-notation as follows:
from donotation import do
@do()
def example(init):
x = yield from collect_even_numbers(init + 1)
y = yield from collect_even_numbers(x + 1)
z = yield from collect_even_numbers(y + 1)
return collect_even_numbers(z + 1)Here are some Python libraries that implement the state monad: