astrojuanlu
commented
2 years ago I arrived here after trying to figure out what conda develop is because it's mentioned in the SciPy developer documentation. If it's not maintained, the best thing to do is indeed to deprecate and remove it.
The logical solution is to use whatever is the equivalent of
pip install -e in conda.
This was my go-to solution too, but as mentioned by @rgommers in this scipy-dev thread, one needs to be careful with at least two things:
- Build isolation. The presence of a
pyproject.tomltriggers build isolation, and this can interfere with the carefully created environment (for example, through conda). The solution is to opt out by adding--no-build-isolation, as explained in the docs. - Dependency installation. pip is an installer, and its default behavior is, naturally, to install the dependencies of a project. However,
pip installmight meddle with the development environment by upgrading or downgrading some of the dependencies. Traditionally,setup.py develophas covered the use case of "build extensions in-place + create an editable install" without adding dependencies, but directsetup.pyinvocations are now deprecated. The solution, then, is to add the--no-depsflag, as explained in this somewhat hidden corner of the pip docs.
In sum, the closest replacement to python setup.py develop or conda develop . these days is probably:
pip install --no-build-isolation --no-deps -e .(I might be missing other deviations from setup.py develop but I think I have captured the two most important ones)
EricThomson
maximlt
rgommers
Nodd
chbrandt
b4rlw
mbaudin47
jezdez
jaimergp
JeanChristopheMorinPerso
dholth
The
conda developcommand has been informally deprecated multiple times:But it is still present in the code and in the documentation. That is very likely misleading to anyone trying to learn best practices for scientific computing.
Example scenario: As soon as a new scientific programmer gets comfortable enough with Python to start working on multiple projects, the next logical step is to learn how to manage environments and dependencies. They'll start by adding a
setup.pywith dependencies to each project, and most likely they'll start using conda to manage environments. (That's what I recommend to users of the servers I manage.) They'll create a conda environment, activate it, and then runpip install -e ., and the code from their project and all its dependencies will be available to anything they run in that environment. If they use Jupyter, they'll install that environment as a kernel.And then, as development progresses, they'll add more stuff. They'll
conda installmore packages. And now they have a problem: as described in the current documentation, it's dangerous to interleaveconda installandpip install. Inevitably they'll end up with an environment that's inconsistent, un-upgradeable and unusable.On their next project, they'll try to avoid that problem. The logical solution is to use whatever is the equivalent of
pip install -ein conda. Which will lead them toconda develop, which looks like the solution to their problem. They will then waste a day or more trying to getconda developto work, eventually stumbling across #1992 or #2633. And then they will curse the name of the person who exhorted them to use conda and follow best practices. Which in several cases has been me.Please deprecate or remove
conda develop.