JOSS review: Improve installation about pymccrgb HOT 7 OPEN

I am working on a conda recipe for this package. When it's accepted, I will change the install instructions to something like:

This package is developed for Linux/OS X and Python 3.6+. It depends on common Python packages like sklearn, numpy, the LibLAS C API, and MCC Python bindings.

You can install this package with conda:

conda env create -n pymcc python=3.6
conda activate pymcc
conda install pymccrgb -y -c conda-forge

from pymccrgb.

The conda recipe can't be built because of the dependency on LibLAS. I am adding this in the PR, but it's a blocking issue until I add liblas to conda-forge.

See conda-forge/staged-recipes#9923

from pymccrgb.

It's great that you are adding LibLAS to conda-forge. I wonder if this repo is of any help:
https://github.com/osgeo-forge/liblas-feedstock

from pymccrgb.

Thanks! Really helpful to see their recipe. Wish it was actually on conda-forge...

from pymccrgb.

@martibosch The libLAS and wrapper conda recipes are ready to merge, but the main recipe is running into some fairly extensive dependency issues that will take time to resolve.

Is this a necessary step for your review, or could I work to resolve the conda packaging difficulties as the paper moves towards publication? Thanks.

from pymccrgb.

Hello @rmsare! I understand that pushing recipes to conda-forge takes time and can easily get messy. I believe that all my other comments have been addressed and therefore, from my side, the paper can now move to publication (without having to wait for the conda recipe part).
Cheers!

from pymccrgb.

Thanks! With a little debugging effort it will be up soon.

from pymccrgb.