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Add version numbers to all packages in environment.yml file
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fperez committed Nov 25, 2022
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Expand Up @@ -4,104 +4,104 @@ channels:
- conda-forge

dependencies:
- python=3.10
- python==3.10.8
# Required until https://github.com/jupyterhub/repo2docker/pull/1196 is merged
- jupyterhub-singleuser>=3.0,<4.0
# nbgitpuller is very helpful when distributing user content
- nbgitpuller
- nbgitpuller==1.1.1
# Specify major version of jupyterlab to use. Manually bump it when you want to upgrade
# jupyterlab version
- jupyterlab>=3.0,<4.0
# This provides memory usage stats on JupyterLab and classic notebook
- jupyter-resource-usage
- jupyter-resource-usage==0.6.4
# https://syncthing.net/ provides a dropbox-like interface for syncing directories across users,
# hubs and machines. Used along with `jupyter-syncthing-proxy` from pip.
- syncthing
- syncthing==1.22.1
# gh-scoped-creds allows users to securely push to GitHub from their repo.
# https://blog.jupyter.org/securely-pushing-to-github-from-a-jupyterhub-3ee42dfdc54f has
# some more information
- gh-scoped-creds
- gh-scoped-creds==4.1

# Cloud access tools and libraries
# Access S3 easily from python
- s3fs
- s3fs==2022.11.0
# handle login and similar details for accessing earthdata protected data
# https://github.com/nsidc/earthaccess
- earthdata
- earthdata==0.4.1
# Access datasets exposed via STAC
- pystac-client
- pystac-client==0.5.1
# Access datasets exposed via intake catalogs
- intake
- intake-esm
- intake-xarray
- intake==0.6.6
- intake-esm==2022.9.18
- intake-xarray==0.6.1

# Core scientific python stack
- numpy
- scipy
- matplotlib
- pandas
- networkx
- scikit-image
- scikit-learn
- sympy
- statsmodels
- xarray
- hypothesis # needed by numpy testing tools
- cython # optimization, C API access
- numba # high-performance numerics
- numpy==1.23.5
- scipy==1.9.3
- matplotlib==3.6.2
- pandas==1.5.2
- networkx==2.8.8
- scikit-image==0.19.3
- scikit-learn==1.1.3
- sympy==1.11.1
- statsmodels==0.13.5
- xarray==2022.11.0
- hypothesis==6.58.0 # needed by numpy testing tools
- cython==0.29.32 # optimization, C API access
- numba==0.56.4 # high-performance numerics

# Jupyter tools
- ipython
- ipywidgets
- jupyterlab-favorites
- jupyterlab-geojson
- jupyterlab-git
- jupyter-book
- nbconvert
- nbdime
- ipython==8.6.0
- ipywidgets==7.7.2
- jupyterlab-favorites==3.1.0
- jupyterlab-geojson==3.3.1
- jupyterlab-git==0.39.3
- jupyter-book==0.13.1
- nbconvert==6.5.3
- nbdime==3.1.1

# Visualization packages
- cartopy # geospatial plotting with matplotlib
- seaborn # statistical plotting with matplotlib
- ipympl # This enables matplotlib interaction with jupyter widgets
- ipyleaflet
- bokeh
- plotly
- cartopy==0.20.2 # geospatial plotting with matplotlib
- seaborn==0.12.1 # statistical plotting with matplotlib
- ipympl==0.9.2 # This enables matplotlib interaction with jupyter widgets
- ipyleaflet==0.17.2
- bokeh==3.0.2
- plotly==5.11.0

# Geospatial data packages
- geopandas
- rasterio
- rioxarray
- xarray-datatree
- geopandas==0.12.1
- rasterio==1.2.10
- rioxarray==0.13.1
- xarray-datatree==0.0.9

# File formats and file management, download, dataset caching
- h5py
- hdf5
- h5netcdf
- pooch
- h5py==3.7.0
- hdf5==1.12.1
- h5netcdf==1.1.0
- pooch==1.6.0

# Distributed computing
- dask
- dask-labextension
- dask==2022.11.0
- dask-labextension==6.0.0

# Other useful generic python packages
- pillow # Python imaging library, useful for many image-related tasks
- tqdm # progress bars, with notebook support
- pytest
- pytest-cov
- pep8
- flake8
- pillow==9.2.0 # Python imaging library, useful for many image-related tasks
- tqdm==4.64.1 # progress bars, with notebook support
- pytest==7.2.0
- pytest-cov==4.0.0
- pep8==1.7.1
- flake8==5.0.4

# Packages specific to cryo work
- icepyx
- icepyx==0.6.4

# Desktop tools whose versions are more recent on conda-forge than ubuntu
- qgis
- qgis==3.18.3

# Not all packages will be available from conda-forge, we install from pip when we need to.
- pip
- pip==22.3.1
- pip:
- jupyter-syncthing-proxy
- jupyter-syncthing-proxy

# Access linux desktop from inside JupyterHub
- jupyter-desktop-server
- jupyter-desktop-server

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