doc-requirements.txt

# NOTE: These requirements are used for developing code on the repo.
# As a standard they include certain formatters and linters.

# local package
# -e ../.

# external requirements (mostly linters and formatters)
pylint              # pylint linter
mypy                # python type checker
black               # automatic formatting provider
pre-commit  	    # for git precommit hooks
isort               # automatic import sorter
python-dotenv       # environment variable manager
pydocstyle          # set pydocstyle

# linear algebra and general data analysis
numpy               # arrays, linear algebra
scipy               # linear algebra and numerical mathematics
numba               # speeding up array operations
pandas              # tabular data analysis

# plotting
matplotlib          # general python plotting
seaborn             # fancier plotting styles
descartes           # geospatial plotting of shapefiles
folium              # plotting maps
ipyleaflet          # plotting ipywidget maps

# interactive computing
jupyterlab          # jupyter notebooks
tqdm                # progress bars

# geospatial analysis requirements
rasterio            # opening and loading raster data
fiona               # manipulating geospatial vector data
geopandas           # manipulating geospatial vector data
shapely             # working with vector shapes
pycrs               # working with coordinate reference systems
geopy               # convenient API requests to geocoders
xarray              # useful data structures
rioxarray           # adaptation of xarray for raterio.
dask[array]         # allows to composite multiple satellite images stored in different shards
dask[dataframe]     # allows more lazy operation for xarray.
dask[dataframe]     # allows more lazy operation for xarray.
dask[distributed]   # allows distributed computing
netCDF4             # makes sure that the default driver is netCDF4.
bottleneck          # needed for fill forward (xarray.DataArray.ffil)

# additional
networkx            # manipulating graph data
rtree               # rtree library

# gdrive functionality
google-api-python-client
google-auth-httplib2
google-auth-oauthlib

# make videos for animating timeseries etc.
imageio
imageio-ffmpeg

# xgboost
xgboost         # gradient boosted regression
sklearn         # sklearn
graphviz        # can plot the decission tree

#
pillow
torch==1.8
torchvision
wandb
pytorch-lightning
git+https://github.com/qubvel/segmentation_models.pytorch
hydra-core

#docs
sphinx
sphinx-autodoc-typehints
nbsphinx
nbsphinx-link