Jupyter Lab, Calysto Hy, Archimedes… oh my

I recently came across a really nifty looking set of tools, namely: Jupyter Lab and Calysto Hy. Former is continuation of IPython, a notebook based Python authoring tool. It lets you write notebooks online and mix in Python. As such it’s really nice for writing reports, while doing compations required for that report at the same time. Calypso Hy is metakernel, that allows Jupyter Lab (and Jupyter in general) use Hy.

Here I’m going to give Jupyter Lab and Calysto Hy a little test drive, using some familiar libraries: Hypothesis and Archimedes.

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Archimedes

I decided to split off macros used for Hypothesis into their own library called Archimedes. The package isn’t in PyPi yet and might never be there, since it’s not particularly useful as a Python library. One major thing that is still lacking is support for settings, but I don’t foresee that to be too difficult to implement. After that I’ll probably do a little bit cleaning up and call the library finished for now.

Hy, Nose and Hypothesis

I recently came across a tool called Hypothesis that immediately sparked my interest. Their documentation describe it as:

Hypothesis is a Python library for creating unit tests which are simpler to write and more powerful when run, finding edge cases in your code you wouldn’t have thought to look for. It is stable, powerful and easy to add to any existing test suite.

Stable, powerful and easy to add are all words that I like. And if you know me, you quickly guessed that I wanted a Hy interface for this new shiny tool.

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