rowangaffney/data_science_im_rs repository overview

⁠data_science_im_rs    

• Includes three geospatial environments, Python (py_geo and py_geo_gpu) and R (r_geo). Each contain a set of geospatial packages and parallel/distributed computing packages
• Will include the IDL (with ENVI API) if correct folders are bind-mounted on container execution (not in example below) and the ENVI licensed in active / "checked-out".
• Built with a proxy to RStudio⁠, VSCode⁠, and Panel⁠ (will launch in seperate tabs).
• Built from Jupyter Minimal-notebook Stack⁠
• Docker Hub Link⁠
• To build locally with singularity:

  singularity pull docker://rowangaffney/data_science_im_rs:latest
  

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  or

  singularity pull docker://rowangaffney/data_science_im_rs:vX.X.X
  

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To launch this container with singularity on the USDA ARS Ceres HPC and use Dask Distributed + Dask Jobqueue⁠, you need to bind the following directories:

--bind /etc/munge --bind /var/log/munge --bind /var/run/munge --bind /usr/bin/squeue --bind /usr/bin/scancel --bind /usr/bin/sbatch --bind /usr/bin/scontrol --bind /usr/bin/sinfo --bind /system/slurm:/etc/slurm --bind /run/munge --bind /usr/lib64/libslurm.so --bind /usr/lib64/libmunge.so.2 --bind /usr/lib64/slurm --bind /project --bind /lustre