gamla

README

λamla is a performant functional programming library for python which supports mixing async and regular functions.

Installation: pip install gamla

API reference: https://gamla.readthedocs.io/

Basic example

gamla can help you turn this:

import dataclasses

@dataclasses.dataclass
class Person:
    age: int
    name: str

    def is_eligible(self):
        return self.age > 9


def get_names_eligible_for_vaccine(people):
    result = []
    for person in people:
        if person.is_eligible():
            result.append(person.name)
    return result

into this:

import dataclasses
from gamla import attrgetter, greater_than, compose_left, filter, map

@dataclasses.dataclass(frozen=True)
class Person:
    age: int
    name: str

is_eligible = compose_left(attrgetter("age"), greater_than(9))
get_names_eligible_for_vaccine = compose_left(filter(is_eligible), map(attrgetter("name")), list)

Is this a good thing? that's for you to decide.

The upside:

Functional programming is mainly about how to split your code into composable parts. Composability means that things are easy to move, replace or combine together like lego. It helps you identify recurring patterns (e.g. filter), factor them out and reuse them. If your generalizations are good, they free your mind to focus on the new logic. Concretely it saves a lot of code and helps a reader understand what a piece of code is doing. For example, if you are familiar with what filter is, you don't have to squint and realize that an if and a for actually do a filtering pattern.

The downside:

Programming in this style in python means some tools won't be so useful (e.g. your debugger, static analysis tools).

Debugging anonymous compositions

gamla.debug

Classic breakpoints are less useful when working with compositions, as there isn't always a line of code to place the breakpoint on. Instead one can use gamla.debug and gamla.debug_exception.

gamla.debug can be used within pipelines and will provide a pdb breakpoint prompt where the value at this position can be referenced by x.

def increment(x):
    return x + 1

increment_twice = gamla.compose_left(increment, gamla.debug, increment)

increment_twice(1)

The above code will break with x being 2.

When you have a long pipeline and want to debug at each step of the way, you can use gamla.debug_compose and gamla.debug_compose_left.

gamla.debug_exception

In some cases tracking down an exception involves inspecting code that runs many times. Consider the following example:

def increment(x):
    return x + 1

def sometimes_has_a_bug(x):
    if x == 666:
        raise Exception
    return x

increment_with_bug = gamla.map(gamla.compose_left(increment, sometimes_has_a_bug))

tuple(increment_with_bug(range(1000)))

Adding a gamla.debug here can be quite tedious, because the code will break many times.

Instead we can use gamla.debug_exception to break only in the case the inner function raises, at which case we would get a breakpoint prompt, and be able to inspect the value causing the exception, use the name x. This would like this:

increment_with_bug = gamla.map(gamla.compose_left(increment, gamla.debug_exception(sometimes_has_a_bug)))

One can also use gamla.debug_exception using a decorator.

@gamla.debug_exception
def sometimes_has_a_bug(x):
    if x == 666:
        raise Exception
    return x

Mixing asynchronous and synchronous code

Most functions in this lib will work seamlessly with async and regular functions, and allow the developer to focus on the logic instead of deciding where to place an await.

For example:

import asyncio

import gamla


def increment(i):
    return i + 1


async def increment_async(i):
    await asyncio.sleep(1)
    return i + 1


async def run():
    mixed_composition = gamla.compose_left(increment, increment_async, increment)
    return await mixed_composition(0)  # returns 3!

Releasing a new version

Increment the version in master, and pypi will automatically update.

Updating documentation after change in README.md

While in gamla directory:

1. Install md-to-rst converter: pip install m2r
2. Convert README.md to README.rst: m2r README.md
3. Move README.rst to docs/source folder instead of existing one: mv README.rst docs/source