/datacube-wms

Data Cube Web Map Service

Primary LanguagePythonOtherNOASSERTION

datacube-wms

Datacube Web Map Service

Features

  • TODO

Setup

  • Follow datacube installation instructions

  • The Datacube WMS requires a more recent version of rasterio than is currently packaged with conda. Run the following commands:

    conda config --prepend channels conda-forge/label/dev
    conda update --all
    
  • Datacube WMS requires the scikit-image package: conda install scikit-image

  • Run create_tables.sql database script to create schema and tables used by WMS server.

  • Run python update_ranges.py (in the Datacube Conda environment). This script will need to be re-run every time additional datasets are added to the Datacube.

  • Edit datacube_wms/wms_cfg.py as required (See datacube_wms/wms_cfg_example.py for examples). If you are using git, you should either create a branch first, or use datacube_wms/wms_cfg_local.py instead. (If it exists, wms_cfg_local.py is read in preference to wms_cfg.py, but is explicitly ignored by git.)

  • Launch flask app using your favorite WSGI server. The following approaches have been tested:

Flask Dev Server

  • cd to the directory containing this README file.

  • Set the FLASK_APP environment variable:

    export FLASK_APP=datacube_wms/wms.py
    
  • Run the Flask dev server:

    flask run
    
  • If you want the dev server to listen to external requests (i.e. requests from other computers), use the --host option:

    flask run --host=0.0.0.0
    

Apache2 mod_wsgi

Getting mod_wsgi to work with a Conda virtual environment is not trivial. The following steps worked for me, but will not support connecting your web server to multiple web apps using different virtual environments.

  • Uninstall any previously installed mod_wsgi packages

  • (From the Datacube Conda environment) install mod_wsgi with pip. Take note of the name of the resulting module which is given to you at the end of the install process, you will need it later:

    pip install mod_wsgi
    
  • Find the full path of mod_wsgi-express with which mod_wsgi-express

  • Install mod_wsgi into Apache:

    sudo /full/path/to/installed/mod_wsgi-express install-module
    
  • Ensure the following lines appear somewhere in your Apache2 config (Note they must appear in the "root" of the config, they cannot appear inside a VirtualHost section):

    LoadModule wsgi_module /full/path/to/wsgi/module.so
    WSGIPythonHome /path/to/your/conda/cubeenv
    
  • Add the following to your Apache config (inside the appropriate VirtualHost section):

    WSGIDaemonProcess datacube_wms processes=20 threads=1 user=uuu group=ggg maximum-requests=10000
    WSGIScriptAlias /datacube_wms /path/to/source_code/wms/datacube_wms/wsgi.py
    <Location /datacube_wms>
            WSGIProcessGroup datacube_wms
    </Location>
    <Directory /path/to/source_code/wms/datacube_wms>
            <Files wsgi.py>
                    AllowOverride None
                    Require all granted
            </Files>
    </Directory>
    

    Note that uuu and ggg above are the user and group of the owner of the Conda virtual environment.

  • Edit datacube_wms/wsgi.py to suit your system.

  • Update the url in service_cfg in datacube_wms/wms_cfg.py.

Docker

To run this image, use something like:

docker run \
    --rm \
    opendatacube/wms \
    gunicorn -b '0.0.0.0:8000' -w 5 --timeout 300 datacube_wms:wms

The image comes with the standard ODC installed, including the entrypoint that sets the config from the environment.

Additionally, the image includes another flag that can be used to grab a config file from a URL:

  • WMS_CONFIG_URL

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.