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branches : [ master ]
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pull_request :
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branches : [ master ]
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+ workflow_dispatch :
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+ inputs :
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+ nipype_branch :
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+ description : ' Build specific Nipype branch'
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+ required : true
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+ default : ' master'
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jobs :
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steps :
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- uses : actions/checkout@v2
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- name : generate the Dockerfile from generate.sh
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- run : bash generate.sh
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+ run : |
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+ BRANCH=${{ github.event.inputs.nipype_branch }}
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+ BRANCH=${BRANCH:-"master"}
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+ bash generate.sh $BRANCH
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# In this step, this action saves a list of existing images,
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# the cache is created without them in the post run.
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# It also restores the cache if it exists.
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set -e
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+ NIPYPE_BRANCH=${1:- " master" }
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+ case $NIPYPE_BRANCH in
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+ master)
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+ NIPYPE_URL=" https://github.com/nipy/nipype/tarball/master"
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+ ;;
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+ * )
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+ NIPYPE_URL=" git+https://github.com/nipy/nipype.git@${NIPYPE_BRANCH} "
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+ ;;
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+ esac
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+
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# Generate Dockerfile
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generate_docker () {
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docker run --rm kaczmarj/neurodocker:master generate docker \
@@ -17,7 +27,7 @@ generate_docker() {
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--miniconda \
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conda_install=" python=3.8 pytest jupyter jupyterlab jupyter_contrib_nbextensions
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traits pandas matplotlib scikit-learn scikit-image seaborn nbformat nb_conda" \
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- pip_install=" https://github.com/nipy/nipype/tarball/master
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+ pip_install=" $NIPYPE_URL
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pybids==0.13.1
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nilearn datalad[full] nipy duecredit nbval niflow-nipype1-workflows" \
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create_env=" neuro" \
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--user=neuro \
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--workdir /home/neuro \
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--miniconda \
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- conda_install=" python=3.7 pytest jupyter jupyterlab jupyter_contrib_nbextensions
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+ conda_install=" python=3.8 pytest jupyter jupyterlab jupyter_contrib_nbextensions
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traits pandas matplotlib scikit-learn scikit-image seaborn nbformat nb_conda" \
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- pip_install=" https://github.com/nipy/nipype/tarball/master
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+ pip_install=" $NIPYPE_URL
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pybids==0.13.1
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nilearn datalad[full] nipy duecredit nbval niflow-nipype1-workflows" \
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create_env=" neuro" \
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