Closed angelosnm closed 2 years ago
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I found the solution to the above by adding the commands below from section "System tweaks for Rstudio integration with geospatial packages" in my Dockerfile! (I am running jupyter/datascience-notebook:ubuntu-20.04
as a base image)
RUN cd /tmp && \ wget https://download2.rstudio.org/server/bionic/amd64/rstudio-server-2022.07.1-554-amd64.deb && \ gdebi -n rstudio-server-2022.07.1-554-amd64.deb
ENV PATH=$PATH:/usr/lib/rstudio-server/bin
USER jovyan
RUN conda install -c conda-forge gdal r-rgdal r-raster r-terra r-sp r-sf
RUN sudo rm /usr/lib/x86_64-linux-gnu/libstdc++.so.6 RUN sudo ln -s /opt/conda/lib/libstdc++.so.6.0.30 /usr/lib/x86_64-linux-gnu/libstdc++.so.6
RUN python3 -m pip install jupyter-rsession-proxy RUN cd /tmp/ && \ git clone --depth 1 https://github.com/jupyterhub/jupyter-server-proxy && \ cd jupyter-server-proxy/jupyterlab-server-proxy && \ npm install && npm run build && jupyter labextension link . && \ npm run build && jupyter lab build
It is not an actual issue with this project but one related to GDAL and the general difficulty of it to be intergrated to a system and I open this issue in case anyone faced such issues.
I have installed some geospatial R packages in my notebook such as r-raster, r-terra, r-sp and others using "conda install". Those work fine inside pure Jupyter environment but when one tries to import them from Rstudio environment the below comes up:
It is clear that GDAL which is installed under the hood cannot recognize the runtime as conda one.
P.S: I have installed other packages (not related with GDAL) with the same way and those can be loaded normally into Rstudio as expected.