A while ago, I stumbled across a talk in an archive of a developer conference introducing a thin wrapper around the Numpy library that makes it more intuitive and "pythonic", especially when it comes to array operations involving multiple dimensions, appending/concatenating and axis arguments to various functions.

Unfortunately, I cannot remember the name of the library or the conference - it may have been FOSDEM, but I was unable to find it via a search there or on the internet.

I have seen JAX which does have slightly different/better indexing semantics than plain Numpy but is too rich/heavy for my needs.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Browse other questions tagged or ask your own question.