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https://github.com/jupyter/docker-stacks.git
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a866877c45
The `r` channel has been considered part of `defaults` since `conda` version `4.3.0`. So it should already be taken into consideration by `conda` installs without having to explicitly add the channel. Further the `conda-forge` channel has incorporated an ever growing, healthy stack of R packages. As such it appears all of the R packages used in this stack now come from `conda-forge` and not `defaults`. Given all of this, it seems safe to drop the `r` channel from explicit addition to the channel list.
91 lines
3.1 KiB
Docker
91 lines
3.1 KiB
Docker
# Copyright (c) Jupyter Development Team.
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# Distributed under the terms of the Modified BSD License.
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FROM jupyter/scipy-notebook
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LABEL maintainer="Jupyter Project <jupyter@googlegroups.com>"
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# Set when building on Travis so that certain long-running build steps can
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# be skipped to shorten build time.
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ARG TEST_ONLY_BUILD
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USER root
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# R pre-requisites
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RUN apt-get update && \
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apt-get install -y --no-install-recommends \
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fonts-dejavu \
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tzdata \
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gfortran \
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gcc && apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Julia dependencies
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# install Julia packages in /opt/julia instead of $HOME
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ENV JULIA_PKGDIR=/opt/julia
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ENV JULIA_VERSION=0.6.2
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RUN mkdir /opt/julia-${JULIA_VERSION} && \
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cd /tmp && \
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wget -q https://julialang-s3.julialang.org/bin/linux/x64/`echo ${JULIA_VERSION} | cut -d. -f 1,2`/julia-${JULIA_VERSION}-linux-x86_64.tar.gz && \
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echo "dc6ec0b13551ce78083a5849268b20684421d46a7ec46b17ec1fab88a5078580 *julia-${JULIA_VERSION}-linux-x86_64.tar.gz" | sha256sum -c - && \
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tar xzf julia-${JULIA_VERSION}-linux-x86_64.tar.gz -C /opt/julia-${JULIA_VERSION} --strip-components=1 && \
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rm /tmp/julia-${JULIA_VERSION}-linux-x86_64.tar.gz
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RUN ln -fs /opt/julia-*/bin/julia /usr/local/bin/julia
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# Show Julia where conda libraries are \
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RUN mkdir /etc/julia && \
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echo "push!(Libdl.DL_LOAD_PATH, \"$CONDA_DIR/lib\")" >> /etc/julia/juliarc.jl && \
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# Create JULIA_PKGDIR \
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mkdir $JULIA_PKGDIR && \
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chown $NB_USER $JULIA_PKGDIR && \
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fix-permissions $JULIA_PKGDIR
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USER $NB_UID
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# R packages including IRKernel which gets installed globally.
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RUN conda install --quiet --yes \
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'rpy2=2.8*' \
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'r-base=3.4.1' \
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'r-irkernel=0.8*' \
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'r-plyr=1.8*' \
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'r-devtools=1.13*' \
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'r-tidyverse=1.1*' \
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'r-shiny=1.0*' \
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'r-rmarkdown=1.8*' \
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'r-forecast=8.2*' \
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'r-rsqlite=2.0*' \
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'r-reshape2=1.4*' \
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'r-nycflights13=0.2*' \
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'r-caret=6.0*' \
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'r-rcurl=1.95*' \
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'r-crayon=1.3*' \
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'r-randomforest=4.6*' \
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'r-htmltools=0.3*' \
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'r-sparklyr=0.7*' \
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'r-htmlwidgets=1.0*' \
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'r-hexbin=1.27*' && \
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conda clean -tipsy && \
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fix-permissions $CONDA_DIR && \
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fix-permissions /home/$NB_USER
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# Add Julia packages. Only add HDF5 if this is not a test-only build since
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# it takes roughly half the entire build time of all of the images on Travis
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# to add this one package and often causes Travis to timeout.
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#
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# Install IJulia as jovyan and then move the kernelspec out
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# to the system share location. Avoids problems with runtime UID change not
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# taking effect properly on the .local folder in the jovyan home dir.
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RUN julia -e 'Pkg.init()' && \
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julia -e 'Pkg.update()' && \
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(test $TEST_ONLY_BUILD || julia -e 'Pkg.add("HDF5")') && \
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julia -e 'Pkg.add("Gadfly")' && \
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julia -e 'Pkg.add("RDatasets")' && \
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julia -e 'Pkg.add("IJulia")' && \
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# Precompile Julia packages \
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julia -e 'using IJulia' && \
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# move kernelspec out of home \
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mv $HOME/.local/share/jupyter/kernels/julia* $CONDA_DIR/share/jupyter/kernels/ && \
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chmod -R go+rx $CONDA_DIR/share/jupyter && \
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rm -rf $HOME/.local && \
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fix-permissions $JULIA_PKGDIR $CONDA_DIR/share/jupyter
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