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SURF Research Cloud config (#104)
* Classroom jupyter environment config * Update SURF conda deps #104 (comment)
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# For the classroom, virtualship is deployed using Jupyter Notebook instances on
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# SURF Research Cloud. Custom environments (aka. iPython kernels) can be created
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# by populating a configuration YAML file as done below, and following the process documented here:
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# https://gitlab.com/rsc-surf-nl/plugins/plugin-custom-packages/-/blob/main/README.md
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# The original example config can be found here:
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# https://gitlab.com/rsc-surf-nl/plugins/plugin-custom-packages/-/blob/main/files/sample-requirements.yml
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# Using the SURF Research Cloud dashboard, you can look at the metadata for the Jupyter instance.
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# In general, you can look at the miniconda section of this YAML file to see which dependencies
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# are used in addition to virtualship for analysis.
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---
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apt:
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repo_keys: []
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# # for example: key for mongodb repo
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# - 9DA31620334BD75D9DCB49F368818C72E52529D4
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# # or for R-repo
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# - E298A3A825C0D65DFD57CBB651716619E084DAB9
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repos:
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- "deb http://archive.ubuntu.com/ubuntu focal main multiverse universe restricted"
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- "deb http://archive.ubuntu.com/ubuntu focal-security main multiverse universe restricted"
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# - 'deb [arch=amd64] https://repo.mongodb.org/apt/ubuntu bionic/mongodb-org/4.0 multiverse'
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# - 'deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/'
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packages:
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- ncdu
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# deb:
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# # xxdiff
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# - 'http://nl.archive.ubuntu.com/ubuntu/pool/universe/x/xxdiff/xxdiff_4.0.1+hg487+dfsg-1_amd64.deb'
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# # libnetcdf
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# - 'http://nl.archive.ubuntu.com/ubuntu/pool/universe/n/netcdf-cxx/libnetcdf-c++4-1_4.3.1-2build1_amd64.deb'
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# # - 'https://download2.rstudio.org/server/bionic/amd64/rstudio-server-2021.09.0-351-amd64.deb'
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miniconda:
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name: custom-kernel
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channels:
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- conda-forge
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- defaults
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dependencies:
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- python=3.10
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- virtualship
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- xarray
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- numpy
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- scipy
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- pandas
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- matplotlib
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- cartopy
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- cmocean
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- geopy
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- gsw
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# to create ipython-kernels you will always need the package ipykernel
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- ipykernel
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# After conda-packages pip-packages can still be installed
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# so install pip ...
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- pip
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# ... and tell conda to use it:
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# - pip:
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# - requests
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# - ...
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prefix: /etc/miniconda/envs

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