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Add icechunk conda env
First step toward #5. It was interesting to see that icechunk itself is rather light-weight, with minimal dependencies.
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environment_icechunk.yml

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name: icechunk
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channels:
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- conda-forge
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# - nodefaults # Speeds solving env, by limiting the number of options
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dependencies:
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- python =3.12
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# Data Engine
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- icechunk # installs zarr3
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# Data processing
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- geopandas # installs shapely, pyarrow, pyogrio, libgdal, networkx
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- xarray
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- rioxarray
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- dask
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# Remote Access
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- fsspec
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- s3fs # Access to Amazon S3 filesystem
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- cdsapi # Access to Copernicus Data System for ERA5
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# # HyRiver packages for data fetching
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# - pygeoogc # Retrieve Data from RESTful, WMS, and WFS Services
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# - async-retriever # Asynchronous requests with persistent caching
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# # Visualization (optional)
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# - hvplot # hvPlot installs most HoloViz libs, https://holoviz.org
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# - geoviews
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# - contextily # for static plotting
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# # Interactivity via Jupyter Notebooks
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# - jupyterlab
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# - nodejs # required for many extensions
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# - ipympl # jupyter-matplotlib, https://github.com/matplotlib/ipympl
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# - ipywidgets # Interactive HTML widgets for Jupyter
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# - ipywidgets_bokeh
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# - jupyter_bokeh # Renders Holviz / Bokeh objects in Jupyter
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# - pyviz_comms # bidirectional communication between Python & JavaScript for Jupyter
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# Dev tools: Language Server Protocol (LSP) (Optional)
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- python-lsp-server # LSP extension for Python (pylsp), including:
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- pylsp-mypy # MyPy type checking for Python >=3.7.
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# - jupyterlab-lsp # Provides both server extension and lab extension
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# Environment and package management
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- conda
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- conda-build
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- conda-libmamba-solver # Faster env solver, https://conda.github.io/conda-libmamba-solver/
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- pip
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- git # for pip installing directly from GitHub
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# PIP install requirements only if it is not possible with conda
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- pip:
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# -

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