Brandon T. Willard

Some links: * [Making kernels for Jupyter](https://jupyter-client.readthedocs.io/en/stable/kernels.html) * [Making simple Python wrapper kernels](https://jupyter-client.readthedocs.io/en/latest/wrapperkernels.html) * [A simple example kernel for Jupyter](https://github.com/jupyter/echo_kernel) _Originally posted by @brandonwillard in https://github.com/gilch/hissp/issues/25#issuecomment-518285190_

GitHub Actions for stale issues/PRs and package deployment

8

Should we try setting up GitHub Actions for PyPi deployment and automatically managing stale issues and PRs?

Make the `inspect` module compatible with Hy

2

The `inspect` module isn't compatible with some Hy-derived objects, and code that implicitly uses `inspect` (including other standard library modules) is generally error-prone because of this. In particular, debuggers are...

In order for a compiler instance to—for example—simply [re]use itself when calling `hy_eval` (e.g. during `eval-and-compile`), we need to make the compiler "stateless". Current `HyASTCompiler` class members `imports` and `temp_if`...

Scope of functions resulting from a macro expansion

3

Would we ever want functions resulting from the expansion of an imported macro to share the macro's namespace and/or `require`s? Of course a macro can be made to `import`/`require` its...

Add vectorized overloads for array arguments

2

This PR dynamically creates Python functions in order to `vectorize` the functions exposed by `numba-scipy`. This can serve as a stand-in until https://github.com/numba/numba/issues/6954 is addressed. Closes #56.

Closes #1094 - [ ] Inspect the types of graphs produced by the broadcasting used in this approach and make sure they're fully reduced. - [ ] Investigate the effects...

Fix cache versioning of empty `Op.__props__`

1

This PR closes #1101 by fixing the way C cache version tuples are generated when `Op.__props__` is empty. More specifically, these changes prevent the addition of empty tuples to the...

Here's a MWE: ```python import aesara import aesara.tensor as at from aesara.raise_op import assert_op x = at.vector("x") x_a = assert_op(x, at.gt(x.shape[0], 1)) y = x_a.shape[0] aesara.dprint(y, print_type=True) # Subtensor{int64} [id...

[`Elemwise` appears to store its `ufunc` objects in `Apply.tag`](https://github.com/aesara-devs/aesara/blob/fd50f36b404d1c89a841907d3682537d5f7719ab/aesara/tensor/elemwise.py#L673) in certain cases, and we absolutely do not want this—especially since this poor choice has already caused its concerns to leak...