TDA environment

Creating and saving a Nextjournal environment

Each Nextjournal code cell runs in a runtime, and each runtime has an environment, which is a Docker container with its own filesystem.  In any environment we can install whatever system or language packages we need, modify configuration files, and set up directory and data file structures however we like.  Then, we can save and export the environment as a whole for future reproducibility, as well as use by others.

pip freeze

1.1s

When we need additional Python packages, they can be installed in multiple ways.  The easiest way is to use conda, which will attempt to install all packages and dependencies in a consistent manner, including system packages and libraries.  The Anaconda Cloud has a searchable database of packages and channels—by default we will select only from the anaconda channel.

conda install -y \
  descartes pysal scikit-learn netcdf4 \
  basemap pyproj Cython

201.8s

conda install -y -c jjhelmus \
  trmm_rsl pyglpk cvxopt

27.0s

For packages and versions unavailable via conda, or for installing packages in wheel files, pip is available.  For any packages that require compilation, we can install gcc first.

apt-get update > /dev/null
apt-get install -y build-essential gcc gfortran git

30.8s

Finally, if a package has a setup.py, we can download and install with that.  

rm -rf PyTDA pyart
git clone https://github.com/ARM-DOE/pyart
git clone https://github.com/nasa/PyTDA

6.4s

export RSL_PATH=/opt/conda
cd pyart && python setup.py install

72.7s

cd PyTDA && python setup.py install

1.9s