Alteryx Designer Ideas

Share your Designer product ideas - we're listening!

Using conda (instead/with pip) for managing package dependencies and conda envs

Currently pip is the package manager in place within the Designer. Unfortunately this is something that doesn't fit our requirements as Data Scientists. We prefer using conda due to the following reasons:

  1. conda manages also non-Python library dependencies. This way conda can be used to manage R packages as well which comes in quite handy (even tough not all packages from CRAN Repository are available)
  1. conda provides a very simple way of creating conda envs (similar to virtualenv but with conda one can also install and manage pip packages --> virtualenv cannot install conda packages!) to isolate required packages (with specific versions) used in a workflow (e.g. for a Python Tool in Designer).


So I would like to have conda instead or additionally to pip and would like to create my conda envs where I install the packages I need for a specific task within my workflow. Moreover, if you think about to feature an R jupyter notebook capability (like the Python Tool) it could be beneficial to change from pip to conda for managing packages in both worlds.

5 - Atom
This would be amazing! I love using Pytorch but currently it can't be installed without a Conda install.