Hi Thomas, This is great news!
FYI, the traitlets module has been undergoing significant refactoring lately, improving the API to favor a broader usage in the community. One reason for this is that several projects outside of the Jupyter organization are considering adopting traitlets. You can find a summary of the ongoing work and API changes here: https://github.com/ipython/traitlets/issues/48 One of the items in this discussion is about what would be the best place for a repository of trait types for standard data structures of the scipy stack (numpy array, pandas series and dataframes, etc...) It is unlikely that such trait types would be accepted in those libraries at this moment, and the main traitlets package might not be the right place for it either - hence the need for another repo. However, if we don't work on a centralized project, we will probably see a number of competing implementations in different libraries that are clients of traitlets. Hence the idea would be to propose a new project in the Jupyter incubator with a reference implementation. What would be cool would be to join forces and work on a specification or start a discussion of what the ideal implementation for such trait types would look like. Cheers, Sylvain On Wed, Sep 23, 2015 at 12:39 PM, Thomas Robitaille < thomas.robitai...@gmail.com> wrote: > Hi everyone, > > We have released a small experimental package called numtraits that > builds on top of the traitlets package and provides a NumericalTrait > class that can be used to validate properties such as: > > * number of dimension (for arrays) > * shape (for arrays) > * domain (e.g. positive, negative, range of values) > * units (with support for astropy.units, pint, and quantities) > > The idea is to be able to write a class like: > > class Sphere(HasTraits): > > radius = NumericalTrait(domain='strictly-positive', ndim=0) > position = NumericalTrait(shape=(3,)) > > and all the validation will then be done automatically when the user > sets 'radius' or 'position'. > > In addition, tuples and lists can get automatically converted to > arrays, and default values can be specified. You can read more about > the package and see examples of it in use here: > > https://github.com/astrofrog/numtraits > > and it can be easily installed with > > pip install numtraits > > The package supports both Python 3.3+ and Legacy Python (2.7) :) > > At this point, we would be very interested in feedback - the package > is still very young and we can still change the API if needed. Please > open issues with suggestions! > > Cheers, > > Tom and Francesco > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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