The recipes here create conda packages for scientific and numerical software components associated with the omnia
project.
The packages built from these recipes are shared with the community on anaconda.org.
To install a package
# Add the omnia channel
$ conda config --add channels omnia
# Install the 'mdtraj' a package
$ conda install mdtraj
Python packages are built against latest two releases of python (3.5 and 3.6) and python 2.7. Packages which have a binary dependency on numpy are built against the latest two releases of numpy (1.10 and 1.11).
WARNING: Python 3.4 support will be phased out now that python 3.6 has been released.
WARNING: Numpy 1.09 support will be phased out now that numpy 1.11 has been released.
The recipes here are automatically built using Travis-CI for linux
and osx
and Appveyor-CI for win
.
For linux
builds, we use a modified version of the Holy Build Box, available here, to ensure that the packages are fully compatible across multiple linux distributions and versions.
This build image contains the additional tools:
- clang 3.8.1
- TeXLive 2015
- The CUDA Toolkit version 8.0
- The AMD APP SDK 3.0
To build a package yourself, run conda build <package_name>
, or ./conda-build-all ./*
to build multiple packages across each of the supported python/numpy configurations.
- Fork this repo
- Add your
conda
recipe for building your packagepackagename
in a subdirectory calledpackagename
. Feel free to use other recipes here as examples. - Open a pull request to merge your branch into this master repo.
- It will automatically be tested to make sure it compiles.
- We will discuss the recipe and give suggestions about how to fix any issues.
- The recipe will be merged and our automated build framework will build
and deploy the packages to the
omnia
anaconda channel under therc
label. - Test the binaries by using
conda install -c omnia/label/rc packagename
- When you're sure the binaries are ready for a full release, comment on the
original pull request and a maintainer will move the package from the
rc
label to the main label.
Q: Should I include an md5
hash in my source:
section if using a Github compressed archive url:
?
A: No. Github compressed archives are frequently regenerated with different compression settings, etc., so md5
hashes cannot be trusted to be invariant. (#699)