The libraries had in priority a simple syntax and an intuitive usage.
Vectors: arbitrary dimensions, value access by indices or letters, angles between two 2D vectors, etc...
Most operations implicitely supports using a vector with another vector, scalars, lists or matrices.
Matrices: discriminants, inverse, Euler matrices (by vector or individual x;y;z axis), removing rows, removing columns, rotates a matrix with a given axis and angle (degrees or radians), indentities.
Other data-structures written are binary trees, stacks, queue, transforms, linked lists.
Given the context of a code written in Python, the goal of this library was not sheer performance, but the ease of use and educative value it offers.
They have been used in educational settings, where the introduction of data structures is done in Python, but previously used archaic libraries.