The overall plan for the coming releases is to:

  • Consolidate the existing generic functionality.

  • Add missing generic functionality to provide a more complex toolbox.

  • Weed out usability hurdles, to ensure the library’s interface is easy to use.

At this point we do not have a fixed release cycle. Instead we publish new releases when major feature additions or breaking changes have gone into Scipp.

Upcoming milestones#

We are currently consolidating and simplifying Scipp’s core data structures. In particular:

  • scipp.Dataset will be restricted to items of matching dimensionality (scipp.DataGroup can be used for other applications).

  • Support for attributes will be removed from scipp.DataArray due to conceptual consistency issues.

Future direction and plans#

We have a number of improvements in mind which we would like to consider and potentially introduce to Scipp. At this point we have not prioritized, scheduled, or funded any of these:

  • dask support.

  • Support for numpy’s array-function API, for better interoperability.

  • Experiment with moving more high-level functionality from C++ to Python. Could we wrap NumPy (or similar) arrays, or is the performance penalty too high?

  • Better support for structured dtypes and spatial dtypes.