- Add initial support for Numba compilation: asm, demangling, execution
Numba wraps Python functions in `Dispatcher` objects. Each dispatcher
contains zero or more compiled argument-type-indexed overloads of its
function. We import the user's code as a module, and emit the code from
all overloads of all dispatchers that the module publicly exposes.
Name mangling is odd in Numba. It uses a similar mangling syntax to C++,
but also encodes non-symbol (`r"[^a-z0-9_]"`) characters as `_%02x`.
This encoding yields valid identifier names, so it is not strictly
invertible. Here, I have hard-coded some replacements to decode some
common cases at the cost of possible clashes with ugly user-defined
names.
Screenshot captured via `make dev EXTRA_ARGS="--debug --language numba"`
## To do
- [x] Answer questions of #5591.
- [x] Acquire a python environment.
- [ ] Automatically run the python test?
Locally, I have installed a virtual environment with python 3.12.3 with
```shell
path/to/python -m venv venv_numba
path/to/venv_numba/bin/python -m pip install numba==0.61.0 scipy>=0.16
```
and configured its use with
```properties
# compiler-explorer/etc/config/numba.local.properties
compilers=&numba
defaultCompiler=numba_0_61_0
group.numba.compilers=numba_0_61_0
group.numba.baseName=Numba
compiler.numba_0_61_0.exe=/path/to/python3.13
compiler.numba_0_61_0.semver=0.61.0
```
I run this python-side test file with
```python
path/to/venv_numba/bin/python -m unittest etc/scripts/test_numba_wrapper.py
```
---------
Co-authored-by: Mats Jun Larsen <mats@jun.codes>
