Solar tomography has progressed rapidly in recent years thanks to thedevelopment of robust algorithms and the availability of more powerfulcomputers. It can today provide crucial insights in solving issuesrelated to the line-of-sight integration present in the data of solarimagers and coronagraphs. However, there remain challenges such as theincrease of the available volume of data, the handling of the temporalevolution of the observed structures, and the heterogeneity of thedata in multi-spacecraft studies. We present a generic softwarepackage that can perform fast tomographic inversions that scaleslinearly with the number of measurements, linearly with the length ofthe reconstruction cube (and not the number of voxels) and linearlywith the number of cores and can use data from different sources andwith a variety of physical models: TomograPy
, an open-source software freelyavailable on the Python Package Index. For performance, TomograPy usesa parallelized-projection algorithm. It relies on the World CoordinateSystem standard to manage various data sources. A variety of inversionalgorithms are provided to perform the tomographic-map estimation. Atest suite is provided along with the code to ensure software quality.Since it makes use of the Siddon algorithm it is restricted torectangular parallelepiped voxels but the spherical geometry of thecorona can be handled through proper use of priors. We describe themain features of the code and show three practical examples ofmulti-spacecraft tomographic inversions using STEREO/EUVI andSTEREO/COR1 data. Static and smoothly varying temporal evolutionmodels are presented.