  We present a novel open-source Python framework called NanoNET (Nanoscale
Non-equilibrium Electron Transport) for modelling electronic structure and
transport. Our method is based on the tight-binding method and non-equilibrium
Green's function theory. The core functionality of the framework is providing
facilities for efficient construction of tight-binding Hamiltonian matrices
from a list of atomic coordinates and a lookup table of the two-center
integrals in dense, sparse, or block-tridiagonal forms. The framework
implements a method based on $kd$-tree nearest-neighbour search and is
applicable to isolated atomic clusters and periodic structures. A set of
subroutines for detecting the block-tridiagonal structure of a Hamiltonian
matrix and splitting it into series of diagonal and off-diagonal blocks is
based on a new greedy algorithm with recursion. Additionally the developed
software is equipped with a set of programs for computing complex band
structure, self-energies of elastic scattering processes, and Green's
functions. Examples of usage and capabilities of the computational framework
are illustrated by computing the band structure and transport properties of a
silicon nanowire as well as the band structure of bulk bismuth.
