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
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