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[ECCO] [SDS] Update to Anaconda Python (2.1.0 -> 4.0.0)

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We have updated the Anaconda Python environment from 2.1.0 to Anaconda 4.0.0.

The key python changes are

  • python 2.7.9 -> 2.7.11
  • python 3.3.4 -> 3.3.5
  • ipython notebook -> jupyter notebook

The full Anaconda changelog (not fully synchronized with what ECCO has) can be found at https://docs.continuum.io/anaconda/changelog.  For what it's worth, environments were created prior to the upgrade:

$ conda info --envs
# conda environments:
#
mkl2.7                   /cac/contrib/anaconda/envs/mkl2.7
mkl3.3                   /cac/contrib/anaconda/envs/mkl3.3
py3_20161111             /cac/contrib/anaconda/envs/py3_20161111
python3.3                /cac/contrib/anaconda/envs/python3.3
root20161111             /cac/contrib/anaconda/envs/root20161111
root                  *  /cac/contrib/anaconda

where the py3_20161111 and root20161111 are the environments prior to the upgrade. As of 2016-11-11, the following python versions are installed in there:

  • root20161111: Python 2.7.9 :: Anaconda 2.1.0 (64-bit)
  • py3_20161111: Python 3.3.5 :: Anaconda 2.1.0 (64-bit)

The mkl2.7, mkl3.3, root, and python3.3 environments have been fully upgraded.

Note: In the core environments, the MKL high-performance libraries no longer require that you obtain a personal academic license. You may have to remove older licenses. See https://docs.continuum.io/mkl-optimizations/ for more information, and let us know if you run into any issues.

Note: For convenience, the core 3.3 environment can be called two ways:

  • by loading the appropriate module:
    module load python/anaconda/3.3
  • by loading the default anaconda module, and then activating the py3.3 environment:
    module load python/anaconda
    source activate py3.3

All other Python environments must be loaded using the second method.

Note: For replicability, you may want to always work with your own local environment. You can fix a particular environment by cloning it into your private Anaconda space (by default, this is your home directory, but it can be put into a group-readable directory as well): conda create -n MyClone --clone=root