Metadata-Version: 2.1
Name: pygeoutils
Version: 0.1.8
Summary: A set of utilities for manipulating (Geo)JSON and GeoTIFF data.
Home-page: https://github.com/cheginit/pygeoutils
Author: Taher Chegini
Author-email: cheginit@gmail.com
License: MIT license
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Requires-Dist: geopandas
Requires-Dist: rasterio
Requires-Dist: setuptools
Requires-Dist: shapely
Requires-Dist: simplejson
Requires-Dist: xarray

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🚨 **This package is under heavy development and breaking changes are likely to happen.** 🚨

Features
--------

Hydrodata is a stack of Python libraries designed to aid in watershed analysis through
web services. Currently, it only includes hydrology and climatology data within the US.
Hydrodata software stack is shown in the table below.

=========== ===========================================================================
Package     Description
=========== ===========================================================================
Hydrodata_  Access NWIS, HCDN 2009, NLCD, and SSEBop databases
PyGeoOGC_   Query data from any ArcGIS RESTful-, WMS-, and WFS-based services
PyGeoUtils_ Convert responses from PyGeoOGC's supported web services to datasets
PyNHD_      Access NLDI and WaterData web services for navigating the NHDPlus database
Py3DEP_     Access topographic data through the 3D Elevation Program (3DEP) web service
PyDaymet_   Access the Daymet database for daily climate data
=========== ===========================================================================

.. _Hydrodata: https://github.com/cheginit/hydrodata
.. _PyGeoOGC: https://github.com/cheginit/pygeoogc
.. _PyGeoUtils: https://github.com/cheginit/pygeoutils
.. _PyNHD: https://github.com/cheginit/pynhd
.. _Py3DEP: https://github.com/cheginit/py3dep
.. _PyDaymet: https://github.com/cheginit/pydaymet

PyGeoUtils provides utilities for manipulating (Geo)JSON and GeoTIFF data:

- ``json2geodf``: For converting (Geo)JSON objects to GroPandas dataframe.
- ``arcgis2geojson``: For converting ESRIGeoJSON objects to standard GeoJSON format.
- ``gtiff2xarray``: For converting (Geo)TIFF objects to `xarray <https://xarray.pydata.org/>`__
  datasets.
- ``xarray_geomask``: For masking a ``xarray.Dataset`` or ``xarray.DataArray`` using a polygon.

All these function handle all necessary CRS transformations. Moreover, requests for additional
functionalities can be submitted via
`issue tracker <https://github.com/cheginit/pygeoutils/issues>`__.

Installation
------------

You can install pygeoutils using ``pip`` after installing ``libgdal`` on your system
(for example, in Ubuntu run ``sudo apt install libgdal-dev``):

.. code-block:: console

    $ pip install pygeoutils

Alternatively, pygeoutils can be installed from the ``conda-forge`` repository
using `Conda <https://docs.conda.io/en/latest/>`__:

.. code-block:: console

    $ conda install -c conda-forge pygeoutils

Quickstart
----------

To demonstrate capabilities of PyGeoUtils lets use
`PyGeoOGC <https://github.com/cheginit/pygeoogc>`__ to access
`National Wetlands Inventory <https://www.fws.gov/wetlands/>`__ from WMS, and
`FEMA National Flood Hazard <https://www.fema.gov/national-flood-hazard-layer-nfhl>`__
via WFS, then convert the outpus to ``GeoDataFrame`` and ``xarray.Dataset`` using PyGeoUtils.

.. code-block:: python

    import pygeoutils as geoutils
    from pygeoogc import WFS, WMS
    from shapely.geometry import Polygon


    geometry =  Polygon(
        [
            [-118.72, 34.118],
            [-118.31, 34.118],
            [-118.31, 34.518],
            [-118.72, 34.518],
            [-118.72, 34.118],
        ]
    )

    url_wms = "https://www.fws.gov/wetlands/arcgis/services/Wetlands_Raster/ImageServer/WMSServer"
    wms = WMS(
        url_wms,
        layers="0",
        outformat="image/tiff",
        crs="epsg:3857",
    )
    r_dict = wms.getmap_bybox(
        geometry.bounds,
        1e3,
        box_crs="epsg:4326",
    )
    wetlands = geoutils.gtiff2xarray(r_dict, geometry, "epsg:4326")

    url_wfs = "https://hazards.fema.gov/gis/nfhl/services/public/NFHL/MapServer/WFSServer"
    wfs = WFS(
        url_wfs,
        layer="public_NFHL:Base_Flood_Elevations",
        outformat="esrigeojson",
        crs="epsg:4269",
    )
    r = wfs.getfeature_bybox(geometry.bounds, box_crs="epsg:4326")
    flood = geoutils.json2geodf(r.json(), "epsg:4269", "epsg:4326")

Contributing
------------

Contributions are very welcomed. Please read
`CONTRIBUTING.rst <https://github.com/cheginit/pygeoogc/blob/master/CONTRIBUTING.rst>`__
file for instructions.


