Selectivity makes it our choice for user space installation.Īnaconda is the most popular Python distribution. Packages need to be installed manually (described below). This makes the base installation rather small, at 0.3 GB. Miniconda is a minimal Anaconda distribution, which ships with base Python and the conda package manager. Is offered in a form of a Docker container, which can be imported and loaded in our HPC environment using Singularity. In those cases, we recommend to research if the particular stack Python library stack is difficult to install, mostly when there are conflicts betweenĭependent libraries. However, please, be aware that there are some corner cases when Anaconda/Miniconda Peformance improvements and are comparable or better to hand tuned Python builds.įor these reasons we are deprecating centrally maintained Python distributions and Space Python distributions, and specifically Anaconda/Miniconda, are actively incorporating On specific versions of modules which may be incompatible with others. Maintained Python distributions up to date. The Python ecosystem is growing rapidly and it has become difficult to keep centrally Why are we moving away from a central Python installation? Parallel machine learning environment with Tensorflow, Keras and Horovod.Interactive machine learning environment with Tensorflow, Keras and Jupyter Lab.Why are we moving away from a central Python installation?.Therefore weĮncourage users to maintain their own Python stack as described below. Increasingly difficult to support the Python distribution centrally. Current Page: Python3: Setup of a virtual environmentĪs Python libraries evolve rapidly and may have specific dependencies, it is becoming.University Application Heath Summary - NOC.Narwhal User Guide (Protected Environment Statistics).
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