ok, I start understanding the logic... I performed the steps of the documentation but the dss-local-packages.txt was empty. I added inside the list of package of my custum env to "install" them in the built-in environment. The the training is still crahing because numpy is not found. When I run "DATA_DIR/bin/pip list", I get a full list of packages that includes "numpy". thanks for your help 😉 Salvatore ps: I am on archlinux
The dss-local-packages.txt can be empty, it lists the _additional_ packages that you installed on top of the base packages. The DSS installer takes care of installing the base packages under the hood. You should not manually specify the packages from your repository, as it will override the base packages with different versions that may not expected in the built-in python env. Can you try with just the instructions from the documentation?
ArchLinux is not officially supported, but quick tests seem to show that we can't reproduce your issue. With a base ArchLinux from AWS, DSS starts normally and Pandas is functional after: - installing the packages extra/jdk8-openjdk, extra/nginx, extra/freetype2, community/gcc54 - adding /usr/lib/gcc/x86_64-pc-linux-gnu/5.4.1 to DSS' LD_LIBRARY_PATH
If you can't solve this, you can continue with your code env as long as it's not blocking you, or try either installing the builtin code env using conda https://doc.dataiku.com/dss/latest/installation/python.html#using-anaconda-python or a fully custom python environment https://doc.dataiku.com/dss/latest/installation/python.html#advanced-using-a-fully-custom-python-environment Also, providing full installation logs may help us have other ideas.