Beap aka biparental heap (https://en.wikipedia.org/wiki/Beap) is an implicit data structure which allows efficient insertion and searching of elements, while not requiring any more space than the data elements themselves. Efficient searching and insertion are supported by clever arrangement of elements in the array which backs the beap structure, and clever algorithms utilizing this arrangement.
Beap is further elaboration of the ideas of heap data structure (which allows for efficient insertion and finding minimum/maximum, but not efficient searching for an arbitrary element). It was originally described by researchers Ian Munro and Hendra Suwanda. Howerver, it's quite hard to find an implementation of this data structure. Nor it's easy to implement it based on the original paper, because, following a good academic tradition, the paper is rather terse, incomplete, inconsistent and has errata.
This project is an implementation of Beap using Python3, written by Paul Sokolovsky and distributed under the terms of OpenSource MIT license. It's intended to be a reference implementation, i.e. written more for clarity and testability rather than optimized. It's accompanied by detailed unit tests. The idea is that this implementation can serve as the basis for more efficient implementation, if such is needed.
For more information on implicit data structures, see https://github.com/pfalcon/awesome-implicit-data-structures .