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The recipes here create conda packages that are uploaded to Binstar.org and shared with the community.

For IOOS python users, the Anaconda Scientific Python Distribution is the easiest way to get custom packages needed to run the IOOS system tests. Using Anaconda users can conda install, which installs not only binary packages for their platform, but the binary libraries they depend on. So easier than pip install and, thanks to binary relocation, more powerful than python wheels. System-level installation of libraries and admin privileges are not required. Check out Travis Oliphant's blog piece for more info.

The recipes here are automatically built using Travis-CI with the assistance of Obvious-CI.

Some bugs, like hard-coded paths, might surface when using these packages. If you encounter one,raise an issue.

Some bullets points:

• The numpy version is controlled by the environment variable CONDA_NPY (e.g.: export CONDA_NPY=18).
• The python version is controlled by the environment variable CONDA_PY (e.g.: export CONDA_PY=27).
• When rebuilding something with the same version we need to increment the build number in the meta.yaml. That will ensure the installation of the new version, rather than just what is sitting around in their cache.
• To avoid the package cache we can add a -f to the install to force downloading, like: conda install iris -f
• There is no need for subdirs like np18py27.
• conda build iris will automatically build all the other dependencies (biggus, pyke, cartopy) if it finds a recipe for the requirement at the same directory level.
• That is a strong incentive to set: conda config --set binstar_upload yes and have all packages uploaded with one "build".