Democritus Algorithms (a.k.a. d8s-algorithms)

Democritus functions^[1] for working with algorithms.

[1] Democritus functions are simple, effective, modular, well-tested, and well-documented Python functions.

We use d8s (pronounced "dee-eights") as an abbreviation for democritus (you can read more about this here).

Installation

pip install d8s-algorithms

Usage

You import the library like:

from d8s_algorithms import *

Once imported, you can use any of the functions listed below.

Functions

def amb(validation_function: Callable[..., bool], *args: Any) -> Iterable[Any]:
    """."""

def depth_first_traverse(
    data: Any,
    get_children_function: Callable[[Any], Optional[Iterable]],
    *,
    collect_items_function: Optional[Callable[[Any], Any]] = None
) -> Iterable[Any]:
    """Traverse the data in a depth-first manner.

The get_children_function specifies how children will be identified from each node of the data.
The collect_items_function, if provided, allows you to collect items from the data by...
 returning them from the collect_items_function."""

def breadth_first_traverse(
    data: Any,
    get_children_function: Callable[[Any], Optional[Iterable]],
    *,
    collect_items_function: Optional[Callable[[Any], Any]] = None
) -> Iterable[Any]:
    """Traverse the data in a breadth-first manner.

The get_children_function specifies how children will be identified from each node of the data.
The collect_items_function, if provided, allows you to collect items from the data by...
 returning them from the collect_items_function."""

def genetic_algorithm_run(
    data: Iterable[Any],
    scoring_function: Callable[[Any], Union[int, float]],
    selection_function: Callable[[Dict[Any, Union[int, float]]], Iterable[Any]],
    mutation_function: Callable[[Iterable[Any]], Iterable[Any]],
    max_epochs: int,
) -> Dict[Any, Union[int, float]]:
    """."""

def genetic_algorithm_best_mutation_function(
    starting_values: Iterable[Any],
    generations: int,
    scoring_function: Callable[[Any], Union[int, float]],
    mutation_functions: List[Callable[[Any], Any]],
):
    """Find the best mutation function.

The best function is the one which produces values from the starting values...
 that score the highest (as measured by the scoring_function) after generations."""

Development

👋 If you want to get involved in this project, we have some short, helpful guides below:

If you have any questions or there is anything we did not cover, please raise an issue and we'll be happy to help.

Credits