Table Of Contents
Table Of Contents

THREDDS Engine (Siphon) Reference

Last Updated: December 2019

This guide introduces Siphon, the which is used as the engine for the THREDDS spatial dataset service. Siphon is a 3rd-party library developed by Unidata for interacting with data on remote services, currently focused on THREDDS services. Siphon does not implement the SpatialDatasetEngine pattern.

Example Usage

The get_spatial_dataset_service() method of the app class returns a siphon.catalog.TDSCatalog object when the as_engine=True option is provided. The TDSCatalog object can be used to query the datasets on the THREDDS server.

NCSS Query Time Series

This example is adapted from the Siphon NCSS Time Series Example

import datetime
from netCDF4 import num2date
from my_first_app.app import MyFirstApp as app

# This returns a siphon.catalog.TDSCatalog bound to the THREDDS service
catalog = app.get_spatial_dataset_service('primary_thredds', as_engine=True)

# Retrieve a dataset
datasets = catalog.datasets
a_dataset = datasets[0]

# Get the NCSS access point
ncss = a_dataset.subset()

# Create a new query
query = ncss.query()

# Construct a query at a location specified by the latitude and longitude and time range
# and return it in the NetCDF4 format
now = datetime.utcnow()
query.lonlat_point(-105, 40).time_range(now, now + timedelta(days=7))
query.variables('streamflow').accept('netcdf')

# Execute the query
data = ncss.get_data(query)

# Extract arrays
streamflow = data.variables['streamflow']
time = data.variables['time']

# Convert times to Python datetime objects
time_objects = num2date(time[:].squeeze(), time.units)

Tip

Refer to the Siphon Examples documentation for more example usage.