VScode development container for writing and data analyses in the Subramaniam lab
108
Useful for:
To use this container, create a .devcontainer.json file with the following contents and open the corresponding folder in VScode that is set up for remote development (see here).
{
"image": "rasilab/default:1.0.0"
}
This image was created using the following Dockerfile:
FROM qmcgaw/latexdevcontainer:latest
USER root
WORKDIR /tmp
# Install pandoc
RUN wget https://github.com/jgm/pandoc/releases/download/2.17/pandoc-2.17-1-amd64.deb
RUN dpkg -i pandoc-2.17-1-amd64.deb
# Install conda and python
# Install conda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh -O miniconda.sh
RUN bash miniconda.sh -b -p /opt/conda
# Put conda in PATH
ENV CONDA_DIR /opt/conda
ENV PATH=$CONDA_DIR/bin:$PATH
# Set up shell for conda activation
RUN eval "$(conda shell.bash hook)"
# Install pandoc filter extension
RUN conda run -n base pip install pandocfilters
# Update Latex installer
RUN tlmgr update --self
# Install Xelatex
RUN apt install -y libfontconfig1
# to prevent error messages during xetex install
RUN tlmgr update texlive-scripts
RUN tlmgr install xetex
# Latex packages
RUN tlmgr install setspace \
unicode-math \
xcolor \
booktabs \
etoolbox \
lineno \
caption \
float \
enumitem
# copy Helvetica font
COPY .install/fonts/ /usr/share/fonts/truetype/helvetica/
# Install Python conda environment
COPY .install/python_environment.yml /tmp/
RUN conda env create -f /tmp/python_environment.yml
# Install R conda environment
COPY .install/R_environment.yml /tmp/
RUN conda env create -f /tmp/R_environment.yml
# Set up R jupyter kernel and make it visible to python
ENV PATH="$PATH:/opt/conda/envs/py/bin"
RUN /opt/conda/envs/R/bin/R -s -e "IRkernel::installspec()"
Content type
Image
Digest
Size
2.1 GB
Last updated
over 4 years ago
docker pull rasilab/default:1.0.0