#sci-wms

COPYRIGHT 2010 Alexander Crosby

####A Python WMS service for geospatial gridded data

##System Requirements

• = 4GB RAM But it depends directly on the size and extents of the datasets you will be visualizing.

• 2 CPU (> 4 CPU Better)

• Python 2.7.x with sqlite
• LibGeos (https://download.osgeo.org/geos/)
• LibSpatialIndex (https://libspatialindex.github.com)
• netCDF4 C library (with opendap enabled, if opendap/remote functionality is desired)
• libhdf5 C library (dependency of netCDF4)
• libcurl (required for opendap)

Your system may have already installed the following dependencies, but they are required by some of the module dependencies installed in the next section.

• libpng
• libfreetype
• libjpeg
• libevent

##Community

We have started a Google Group for the sci-wms project located here.

##Installation

Download the compressed project and unpack anywhere. This is where the installation will live.

Install the following Python dependencies using pip, easy_install, or equivalent. If you are using virtualenv, just make sure you have the environment activated before you try to install the packages or point to the environment with pip on the install command.

pip install numpy
pip install django==1.4
pip install gunicorn
pip install gevent
pip install matplotlib>=1.2.0
pip install netCDF4
pip install shapely
pip install rtree

You also need to ensure that you have basemap matplotlib toolkit installed, which isn't available from pypi.

wget https://sourceforge.net/projects/matplotlib/files/matplotlib-toolkits/basemap-1.0.6/basemap-1.0.6.tar.gz
pip install basemap-1.0.6.tar.gz

If your version of the HDF5 C libraries is >=1.8.10, you may have to install the netCDF4 Python module from the source repository in order for it to work properly. This requires an SVN client to be installed on your system. (Please let us know if you have problems importing netCDF4 in Python after running this command.)

pip install -e svn+https://netcdf4-python.googlecode.com/svn/trunk#egg=netCDF4

If your NetCDF4 and HDF5 libraries are in non-typical locations, you will need to pass the locations to the pip command:

NETCDF4_DIR=path HDF5_DIR=path pip install netCDF4

If there is problem with gevent or greenlet, or if you would like gunicorn to use an alternative worker, you can install the eventlet worker. With some configuration of the sci-wms gunicorn configuration files, you can also use tornado workers.

pip install eventlet
pip install tornado

##Test To make sure that dependencies have been installed correctly, and that sci-wms is fully functional. Run the following command to run the tests.

cd sci-wms/src/pywms && python manage.py test

##Start the services You can start the services on port 7000 from the command line by using the following commands. Learn about gunicorn wsgi server configuration by clicking here.

cd sci-wms/src/pywms && gunicorn_django -c config_public.py

##Caveats:

Look at https://github.com/acrosby/sci-wms/issues?state=open for a list of known issues and problems.