RFC CLI Tool Proposal

## Introduction
Other OSS projects such as `scipy` and `numpy` have made use of development CLI tools such as `runtests.py` and `dev.py` to provide a collected and singular entry point into development tasks for contributors. I find these tools very helpful personally, and think they add a large amount of value, especially for onboarding new contributors. Recently Pandas has also begun discussion and implementation of their own development CLI tool. @noatamir has made a great writeup on some of the benefits and justifications for such a tool (see: https://github.com/pandas-dev/pandas/issues/47700). I highly recommend taking the time to read their writeup. 

Some of the benefits of such a tool include:
1. Increased discoverability of tools, decreasing time spent jumping around documentation. This is especially helpful for those who may not read every single word of documentation (such is my bad habit 😅).
2. Consistency for CI and development. We can establish a 1-1 between CI checks and `dev.py` commands, e.g. `dev.py lint` which could then impose both `black` and `isort` (cf. https://github.com/scikit-learn/scikit-learn/issues/22853)
3. Ease of installation. Users could install whatever dependencies are necessary depending on what workflow they want enabled. A call to `dev.py doc build` could check for the presence of the necessary dependencies and install if needed (or optionally prompt).
4. Reduced barrier to entry. Quite frankly, having to run various commands for tasks, anywhere from linting to building C sources, can be overwhelming, especially to new developers.

Recently `scipy` explored a new solution for developing a unified development CLI tool (cf. https://github.com/scipy/scipy/issues/15489) based on [`do.it`](https://pydoit.org/). Pandas is also exploring a `do.it` based [solution](https://github.com/pandas-dev/pandas/issues/47700). There's been good feedback on this framework and I would propose the same.

## Encompassed Actions
Some actions which would be wrapped by such a development CLI include:
- Dependency installation (could be per-workflow)
- Testing
- Linting
- Extension building
- Documentation building
- Pre-commit installation

## Considerations
As with all things, the question is whether the benefits outweigh the maintenance cost. While projects like scipy with many complex workflows benefit the most from such a tool, personally I think anything to decrease the barrier to entry for scikit-learn development is worth considering.

If we do opt to build such a tool, we can make use of the work already done in scipy as well as the recently released separate [`dev.py` package](https://github.com/scientific-python/dev.py). Either way, the largest modification we'd need to make is alter the `build` command to use `setuptools` instead of `meson`, though that shouldn't be too problematic.

COMMENT:
I still don't have a strong opinion on the matter. I would need to sleep on it. I would like to like the CLI proposal :)

On the downside first, I would be under the impression that we are going to wrap up commands from Python tools, that we use in scikit-learn. In the end, it would be cumbersome for newcomers because they will have to learn a new set of commands for every project to which they want to contribute to. So why not directly learn, the `pytest`, `sphinx`, etc, commands?

> Consistency for CI and development. We can establish a 1-1 between CI checks and dev.py commands, e.g. dev.py lint which could then impose both black and isort (cf. https://github.com/scikit-learn/scikit-learn/issues/22853)

I assume that the comment of @jorisvandenbossche is valid for the 1-1 CI checks: https://github.com/pandas-dev/pandas/issues/47700#issuecomment-1186836950. For the linting, it could be OK but further than that, it would be too optimistic.

But I see an upside: if we get a unified CLI for the pydata ecosystem and even if in scikit-learn, we would use a subset of the complex CLI required for SciPy or Pandas, then it starts to be interesting. A newcomer is learning a CLI interface allowing them to contribute to any pydata project.

Also, we created in the past a `Makefile` with the exact same intention. However, it was not cross-platform. So a CLI based on Python commands would probably unlock some of those issues.

Labels: RFC, workflow