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DSS users will be able to spawn sessions with one of the environments summarised in the table below. This can be selected from the "Select an Environment" dropdown selector on the JupyterHub Launcher, and depending on the environment, additional options may be configurable.
Name | Use case | RAM | CPU | Duration |
|---|---|---|---|---|
ECMWF Data Store Service - SMALL | Downloading, inspecting and plotting data products found on the Data-Stores | 2 | 1 | 12 hours |
ECMWF Data Store Service - MEDIUM | Some small data processing, e.g. data averaging of small files | 4 | 2 | 3 hours |
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In the first deployment smaller (and shorter) sessions will be prioritised to ensure fair usage of the platform. These priorities are to be monitored closely and will evolve as the project develops. |
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stashincludebyfilepath
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| repoSlug | ecmwf-jupyterhub-docker | |||
| branchId | refs/heads/main | |||
| projectKey | JUP | |||
| filepath | singleuser/ecmwf/ecmwf-env.yml |
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name: base
channels:
- conda-forge
dependencies:
- python
- pip
- jupyterlab-git
- ipywidgets
- nodejs
- git
- yaml
- pyyaml
- beautifulsoup4
- jupyter-server-proxy
- numpy
- pandas
- xarray
- numexpr
- scipy
- seaborn
- dask
- cartopy
- shapely
- plotly
- netcdf4
- cf-units
- Markdown
- toolz
- tqdm
- adjustText
- aws-requests-auth
- bokeh
- voila
- docstring_parser
- filelock
- metview-batch
- metview-python
- cdsapi
- ecmwf-api-client
- ecmwf-opendata
- pip:
- earthkit |
You can install additional packages from the (open-source) conda-forge channel (`conda install PACKAGE-NAME`), or from PyPi (`pip install PACKAGE-NAME`). This packages will be installed in your local storage and will be available next time you create a session.
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