bynning

Python library for sorting arbitrary data into bins.

Core Classes/Concepts

This section provides an explanation of the core classes and concepts that underpin the bynning model.

Binnable

from wai.bynning import Binnable

An object is Binnable if it conforms to the wai.bynning.Binnable interface. The interface provides a bin_key
property, which can be of any type, and represents the data used to decide which bin the object belongs in.

BinItem

from wai.bynning import BinItem

A BinItem is a wrapper for objects that aren’t inherently binnable. This allows arbitrary objects to be sorted
using the bynning system. A BinItem is initialised with a payload object (the object being binned) and a
provided bin-key object. Static methods are provided for bulk wrapping/unwrapping of objects with BinItem
wrappers.

Bin

from wai.bynning import Bin

A Bin represents a collection of objects that have been sorted into a group based on their bin-key. Each bin
has a Label, which is the ‘name’ of the Bin. Bins can be iterated through, and retain the order in which
they were filled.

Binning

from wai.bynning import Binning

A Binning is the result of sorting a collection of items into a number of Bins. A Binning can be iterated
over the Bins it contains, or over the items in those Bins.

Binner

from wai.bynning.binners import Binner

A Binner is an algorithm for determining which Bin an object should go into based on its bin-key. The
wai.bynning.binners package provides many implementations of common binning algorithms. Binners support one
public method, bin, which takes an iterable of Binnable objects to bin and returns the resulting Binning.

Extractor

from wai.bynning.extraction import Extractor

Extractors are used in a few places to determine which information is relevant to a given operation. For example,
determining the bin-key of a non-Binnable object when wrapping it in a BinItem.

Examples

Grouping Containers by Size

from typing import Sized, Iterable, Dict, List
# The containers we want to group
containers: Iterable[Sized] = ...
# Wrap the containers in BinItems, keyed by their size
from wai.bynning import BinItem
from wai.bynning.extraction import SizeExtractor
binnable_containers: Iterable[BinItem] = BinItem.extract_from(SizeExtractor(), containers)
# As the bin-key is the containers size, just need to bin by bin-key
from wai.bynning import Binning
from wai.bynning.binners import KeyBinner
container_binning: Binning = KeyBinner().bin(binnable_containers)
# Create a dictionary from container-size to containers
containers_by_size: Dict[int, List[Sized]] = {
    bin.label: list(BinItem.unwrapping_iterator(bin))
    for bin in container_binning
}