pipette

pipette is a lightweight, expressive Python library designed to enable clean, functional-style data processing pipelines with intuitive syntax and powerful composition.

Note that due to the limitations of Python's static typing, some features may not provide type hints as expected. However, the library is designed to be flexible and easy to use, even without strict type enforcement.

Features

pipette is currently in early development, but it already includes:

• Lazy evaluation for efficient data processing.
• Support for custom transformations using the @pipette decorator.
• Core functional utilities like select, where, reduce, sort_by, and more.
• Currying support for partial function application.
• Basic monad implementation for chaining operations with error handling.

Installation

pipette can be installed via pip from the Python Package Index (PyPI):

pip install pipette-fp

Alternatively, you can install the latest development version of pipette directly from GitHub:

pip install git+https://github.com/chriso345/pipette

Usage

pipette aims to make functional pipelines clear and concise.

from pipette import where, select, into

data = [
    {"active": True, "value": 10},
    {"active": False, "value": 5},
    {"active": True, "value": 7},
]

result = (
    data
    | where(lambda x: x["active"])
    | select(lambda x: x["value"])
    | into(list)
)

print(result)  # Output: [10, 7]

Custom transformations can easily be added to extend functionality:

from pipette import pipette

@pipette
def double(x):
    return builtins.map(lambda n: n * 2, x)

result = (
    [1, 2, 3, 4]
    | double
    | into(list)
)

print(result)  # Output: [2, 4, 6, 8]

Curry

pipette provides a submodule for easy currying of functions:

from pipette.curry import curry

@curry
def add(x: int, y: int) -> int:
    return x + y

result = add(2)(3)
print(result) # Output: 5

result = add(2)
print(result(3)) # Output: 5

Note, however, that python's static typing does not support currying and the type hints will error.

Monads

pipette also includes a simple monad implementation for chaining operations:

from pipette.monad import Maybe, Some, Nothing

def safe_divide(x, y) -> Maybe[float]:
    if y == 0:
        return Nothing()
    else:
        return Some(x / y)

s = Some(10) >> (lambda x: safe_divide(x, 2)) | (lambda x: x + 1)
print(s) # Output: Some(6.0)

n = Some(10) >> (lambda x: safe_divide(x, 0)) | (lambda x: x + 1)
print(n) # Output: Nothing

Here >> binds the monad value to the function, and | provides a simple way to map the result to another function.

License

This project is licensed under the MIT License. See the LICENSE file for details.