def create(cls,
name,
title,
description,
owners=None,
readers=None,
writers=None,
vector_client=None):
"""
Create a vector product in your catalog.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.create(name='foo',
... title='My Foo Vector Collection',
... description='Just a test') # doctest: +SKIP
"""
params = dict(
name=name,
title=title,
description=description,
owners=owners,
readers=readers,
writers=writers,
)
if vector_client is None:
vector_client = Vector()
return cls._from_jsonapi(
vector_client.create_product(**params).data, vector_client)
def create(cls,
product_id,
title,
description,
owners=None,
readers=None,
writers=None,
vector_client=None):
"""
Create a vector product in your catalog.
Parameters
----------
product_id : str
A unique name for this product. In the created
product a namespace consisting of your user id (e.g.
"ae60fc891312ggadc94ade8062213b0063335a3c:") or your organization id (e.g.,
"yourcompany:") will be prefixed to this, if it doesn't already have one, in
order to make the id globally unique.
title : str
A more verbose and expressive name for display purposes.
description : str
Information about the `FeatureCollection`, why it exists,
and what it provides.
owners : list(str), optional
User, group, or organization IDs that own
the newly created FeatureCollection. Defaults to
[``current user``, ``current org``].
The owner can edit and delete this `FeatureCollection`.
readers : list(str), optional
User, group, or organization IDs that can read
the newly created `FeatureCollection`.
writers : list(str), optional
User, group, or organization IDs that can edit
the newly created `FeatureCollection` (includes read permission).
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.create(product_id='foo',
... title='My Foo Vector Collection',
... description='Just a test') # doctest: +SKIP
"""
params = dict(
product_id=product_id,
title=title,
description=description,
owners=owners,
readers=readers,
writers=writers,
)
if vector_client is None:
vector_client = Vector()
return cls._from_jsonapi(
vector_client.create_product(**params).data, vector_client)
def __init__(self, guid, tuid=None, client=None, result_attrs=None, key=None):
if client is None:
from descarteslabs.client.services.vector import Vector # circular import
client = Vector()
super(ExportTask, self).__init__(guid, tuid, client=client)
self.export_id = tuid
self._task_result = result_attrs
self._set_key(key)
def create(cls,
name,
title,
description,
owners=None,
readers=None,
writers=None,
vector_client=None):
"""
Create a vector product in your catalog.
Parameters
----------
name : str
A short name without spaces (like a handle).
title : str
A more verbose and expressive name for display purposes.
description : str
Information about the `FeatureCollection`, why it exists,
and what it provides.
owners : list(str), optional
User, group, or organization IDs that own
the newly created FeatureCollection. Defaults to
[``current user``, ``current org``].
The owner can edit and delete this `FeatureCollection`.
readers : list(str), optional
User, group, or organization IDs that can read
the newly created `FeatureCollection`.
writers : list(str), optional
User, group, or organization IDs that can edit
the newly created `FeatureCollection` (includes read permission).
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.create(name='foo',
... title='My Foo Vector Collection',
... description='Just a test') # doctest: +SKIP
"""
params = dict(
name=name,
title=title,
description=description,
owners=owners,
readers=readers,
writers=writers,
)
if vector_client is None:
vector_client = Vector()
return cls._from_jsonapi(
vector_client.create_product(**params).data, vector_client)
def __init__(self,
guid,
tuid=None,
client=None,
upload_id=None,
result_attrs=None):
if client is None:
from descarteslabs.client.services.vector import Vector # circular import
client = Vector()
super(UploadTask, self).__init__(guid, tuid, client=client)
self._upload_id = upload_id
self._task_result = result_attrs
def list(cls, vector_client=None):
"""
List all ``FeatureCollection`` products that you have access to.
Returns
-------
list(:class:`FeatureCollection`)
A list of all products that you have access to.
Raises
------
~descarteslabs.client.exceptions.NotFoundError
Raised if subsequent pages cannot be found.
~descarteslabs.client.exceptions.RateLimitError
Raised when too many requests have been made within a given time period.
~descarteslabs.client.exceptions.ServerError
Raised when a unknown error occurred on the server.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.list() # doctest: +SKIP
"""
if vector_client is None:
vector_client = Vector()
list = []
page = 1
# The first page will always succeed...
response = vector_client.list_products(page=page)
while len(response) > 0:
partial_list = [
cls._from_jsonapi(fc, vector_client) for fc in response.data
]
list.extend(partial_list)
page += 1
# Subsequent pages may throw NotFoundError
try:
response = vector_client.list_products(page=page)
except NotFoundError:
response = []
return list
def list(cls, vector_client=None):
"""
List all `FeatureCollection` products that you have access to.
Returns
-------
list(`FeatureCollection`)
A list of all products that you have access to.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.list() # doctest: +SKIP
"""
if vector_client is None:
vector_client = Vector()
list = []
page = 1
# The first page will always succeed...
response = vector_client.list_products(page=page)
while len(response) > 0:
partial_list = [
cls._from_jsonapi(fc, vector_client) for fc in response.data
]
list.extend(partial_list)
page += 1
# Subsequent pages may throw NotFoundError
try:
response = vector_client.list_products(page=page)
except NotFoundError:
response = []
return list
def setUp(self):
self.url = "http://example.vector.com"
self.gcs_url = "http://example.gcs.com"
self.client = Vector(url=self.url,
auth=Auth(jwt_token=public_token,
token_info_path=None))
self.match_url = re.compile(self.url)
self.match_gcs_url = re.compile(self.gcs_url)
self.attrs = {
'geometry': {
'coordinates': [[[-113.40087890624999, 40.069664523297774],
[-111.434326171875, 40.069664523297774],
[-111.434326171875, 41.918628865183045],
[-113.40087890624999, 41.918628865183045],
[-113.40087890624999, 40.069664523297774]]],
'type':
'Polygon'
},
'properties': {
'baz': 1.0,
'foo': 'bar'
}
}
self.product_response = {
'data': {
'attributes': {
'description':
'bar',
'name':
'new-test-product',
'owners': [
'org:descarteslabs',
'user:3d7bf4b0b1f4e6283e5cbeaadddbc6de6f16dea1'
],
'readers': [],
'title':
'Test Product',
'writers': []
},
'id': '2b4552ff4b8a4bb5bb278c94005db50',
'meta': {
'created': '2018-12-27T17:01:16.197369'
},
'type': 'product'
}
}
self.status_response = {
'data': {
'attributes': {
'created': '2019-01-03T20:07:51.720000+00:00',
'started': '2019-01-03T20:07:51.903000+00:00',
'status': 'RUNNING'
},
'id': 'c589d688-3230-4caf-9f9d-18854f71e91d',
'type': 'copy_query'
}
}
def setUp(self):
url = "http://example.com"
self.client = Vector(
url=url, auth=Auth(jwt_token=public_token, token_info_path=None)
)
self.match_url = re.compile(url)
def vector_client(self):
if self._vector_client is None:
self._vector_client = Vector()
return self._vector_client
def create(
cls,
product_id,
title,
description,
owners=None,
readers=None,
writers=None,
vector_client=None,
):
"""
Create a vector product in your catalog.
Parameters
----------
product_id : str
A unique name for this product. In the created
product a namespace consisting of your user id (e.g.
"ae60fc891312ggadc94ade8062213b0063335a3c:") or your organization id (e.g.,
"yourcompany:") will be prefixed to this, if it doesn't already have one, in
order to make the id globally unique.
title : str
A more verbose and expressive name for display purposes.
description : str
Information about the ``FeatureCollection``, why it exists,
and what it provides.
owners : list(str), optional
User, group, or organization IDs that own
the newly created FeatureCollection. Defaults to
[``current user``, ``current org``].
The owner can edit and delete this ``FeatureCollection``.
readers : list(str), optional
User, group, or organization IDs that can read
the newly created ``FeatureCollection``.
writers : list(str), optional
User, group, or organization IDs that can edit
the newly created ``FeatureCollection`` (includes read permission).
Returns
-------
:class:`FeatureCollection`
A new ``FeatureCollection``.
Raises
------
~descarteslabs.client.exceptions.BadRequestError
Raised when the request is malformed, e.g. the supplied product id is already in use.
~descarteslabs.client.exceptions.RateLimitError
Raised when too many requests have been made within a given time period.
~descarteslabs.client.exceptions.ServerError
Raised when a unknown error occurred on the server.
Example
-------
>>> from descarteslabs.vectors import FeatureCollection
>>> FeatureCollection.create(product_id='my-vector-product-id',
... title='My Vector Collection',
... description='Just a test') # doctest: +SKIP
"""
params = dict(
product_id=product_id,
title=title,
description=description,
owners=owners,
readers=readers,
writers=writers,
)
if vector_client is None:
vector_client = Vector()
return cls._from_jsonapi(
vector_client.create_product(**params).data, vector_client)
def setUp(self):
self.url = "http://example.vector.com"
self.gcs_url = "http://example.gcs.com"
self.client = Vector(url=self.url,
auth=Auth(jwt_token=public_token,
token_info_path=None))
self.match_url = re.compile(self.url)
self.match_gcs_url = re.compile(self.gcs_url)
self.attrs = {
"geometry": {
"coordinates": [[
[-113.40087890624999, 40.069664523297774],
[-111.434326171875, 40.069664523297774],
[-111.434326171875, 41.918628865183045],
[-113.40087890624999, 41.918628865183045],
[-113.40087890624999, 40.069664523297774],
]],
"type":
"Polygon",
},
"properties": {
"baz": 1.0,
"foo": "bar"
},
}
self.product_response = {
"data": {
"attributes": {
"description":
"bar",
"name":
"new-test-product",
"owners": [
"org:descarteslabs",
"user:3d7bf4b0b1f4e6283e5cbeaadddbc6de6f16dea1",
],
"readers": [],
"title":
"Test Product",
"writers": [],
},
"id": "2b4552ff4b8a4bb5bb278c94005db50",
"meta": {
"created": "2018-12-27T17:01:16.197369"
},
"type": "product",
}
}
self.status_response = {
"data": {
"attributes": {
"created": "2019-01-03T20:07:51.720000+00:00",
"started": "2019-01-03T20:07:51.903000+00:00",
"status": "RUNNING",
},
"id": "c589d688-3230-4caf-9f9d-18854f71e91d",
"type": "copy_query",
}
}
self.feature_response = {
"data": [{
"attributes": {
"created": "2019-03-28T23:08:24.991729+00:00",
"geometry": {
"coordinates": [[[-95, 42], [-95, 41], [-93, 40],
[-93, 42], [-95, 42]]],
"type":
"Polygon",
},
"properties": {},
},
"id": "7d724ae48d1fab595bc95b6091b005c920327",
"type": "feature",
}]
}