def test_create_deprecated(self, vector_client):
attributes = dict(name='name',
title='title',
description='description',
owners=['owners'],
readers=['readers'],
writers=None)
FeatureCollection.create(vector_client=vector_client, **attributes)
vector_client.create_product.assert_called_once_with(
description='description',
product_id='name',
owners=['owners'],
readers=['readers'],
title='title',
writers=None)
def test_create_deprecated(self, vector_client):
attributes = dict(
name="name",
title="title",
description="description",
owners=["owners"],
readers=["readers"],
writers=None,
)
FeatureCollection.create(vector_client=vector_client, **attributes)
vector_client.create_product.assert_called_once_with(
description="description",
product_id="name",
owners=["owners"],
readers=["readers"],
title="title",
writers=None,
)
You can use wildcards to search for properties in the Vector service.
The API reference for these methods and classes is at :py:mod:`descarteslabs.vectors`.
"""
from descarteslabs.vectors import Feature, FeatureCollection, properties as p
import uuid
################################################
# Let's make a test :class:`FeatureCollection <descarteslabs.vectors.featurecollection.FeatureCollection>`
# use :meth:`FeatureCollection.create <descarteslabs.vectors.featurecollection.FeatureCollection.create>`.
id_suffix = str(uuid.uuid4())
fc = FeatureCollection.create(
product_id="my_test_product" + id_suffix,
title="My Test Product",
description="This product was created using an example file.",
)
print("Created Feature Collection with id {}".format(fc.id))
################################################
# Establish the geometry
polygon = {
"type":
"Polygon",
"coordinates": [[
[-105.86975097656249, 36.94550173495345],
[-104.930419921875, 36.94550173495345],
[-104.930419921875, 37.70120736474139],
[-105.86975097656249, 37.70120736474139],
