  The minimum spanning tree (MST), a graph constructed from a distribution of
points, draws lines between pairs of points so that all points are linked in a
single skeletal structure that contains no loops and has minimal total edge
length. The MST has been used in a broad range of scientific fields such as
particle physics (to distinguish classes of events in collider collisions), in
astronomy (to detect mass segregation in star clusters) and cosmology (to
search for filaments in the cosmic web). Its success in these fields has been
driven by its sensitivity to the spatial distribution of points and the
patterns within. MiSTree, a public Python package, allows a user to construct
the MST in a variety of coordinates systems, including Celestial coordinates
used in astronomy. The package enables the MST to be constructed quickly by
initially using a k-nearest neighbour graph (kNN, rather than a matrix of
pairwise distances) which is then fed to Kruskal's algorithm to construct the
MST. MiSTree enables a user to measure the statistics of the MST and provides
classes for binning the MST statistics (into histograms) and plotting the
distributions. Applying the MST will enable the inclusion of high-order
statistics information from the cosmic web which can provide additional
information to improve cosmological parameter constraints. This information has
not been fully exploited due to the computational cost of calculating N-point
statistics. MiSTree was designed to be used in cosmology but could be used in
any field which requires extracting non-Gaussian information from point
distributions. The source code for MiSTree is available on GitHub at
https://github.com/knaidoo29/mistree
