def test_search(self, mock_seq_response):
res = SEQ_API.search(filter=SequenceFilter(external_id_prefix="e"))
assert mock_seq_response.calls[0].response.json()["items"] == res.dump(camel_case=True)
assert {
"search": {"name": None, "description": None, "query": None},
"filter": {"externalIdPrefix": "e"},
"limit": None,
} == jsgz_load(mock_seq_response.calls[0].request.body)
def __call__(
self,
chunk_size: int = None,
name: str = None,
external_id_prefix: str = None,
metadata: Dict[str, str] = None,
asset_ids: List[int] = None,
root_asset_ids: List[int] = None,
asset_subtree_ids: List[int] = None,
asset_subtree_external_ids: List[str] = None,
created_time: Dict[str, Any] = None,
last_updated_time: Dict[str, Any] = None,
limit: int = None,
) -> Generator[Union[Sequence, SequenceList], None, None]:
"""Iterate over sequences
Fetches sequences as they are iterated over, so you keep a limited number of objects in memory.
Args:
chunk_size (int, optional): Number of sequences to return in each chunk. Defaults to yielding one event a time.
name (str): Filter out sequences that do not have this *exact* name.
external_id_prefix (str): Filter out sequences that do not have this string as the start of the externalId
metadata (Dict[str, Any]): Filter out sequences that do not match these metadata fields and values (case-sensitive). Format is {"key1":"value1","key2":"value2"}.
asset_ids (List[int]): Filter out sequences that are not linked to any of these assets.
root_asset_ids (List[int]): Filter out sequences not linked to assets with one of these assets as the root asset.
asset_subtree_ids (List[int]): List of asset subtrees ids to filter on.
asset_subtree_external_ids (List[str]): List of asset subtrees external ids to filter on.
created_time (Union[Dict[str, int], TimestampRange]): Range between two timestamps. Possible keys are `min` and `max`, with values given as time stamps in ms.
last_updated_time (Union[Dict[str, int], TimestampRange]): Range between two timestamps. Possible keys are `min` and `max`, with values given as time stamps in ms.
limit (int, optional): Max number of sequences to return. Defaults to return all items.
Yields:
Union[Sequence, SequenceList]: yields Sequence one by one if chunk is not specified, else SequenceList objects.
"""
if asset_subtree_ids or asset_subtree_external_ids:
asset_subtree_ids = self._process_ids(asset_subtree_ids,
asset_subtree_external_ids,
wrap_ids=True)
filter = SequenceFilter(
name=name,
metadata=metadata,
external_id_prefix=external_id_prefix,
asset_ids=asset_ids,
root_asset_ids=root_asset_ids,
asset_subtree_ids=asset_subtree_ids,
created_time=created_time,
last_updated_time=last_updated_time,
).dump(camel_case=True)
return self._list_generator(method="GET",
chunk_size=chunk_size,
filter=filter,
limit=limit)
def test_search_with_filter(self, mock_seq_response):
res = SEQ_API.search(
name="n",
description="d",
query="q",
filter=SequenceFilter(last_updated_time={"max": 42}))
assert mock_seq_response.calls[0].response.json()["items"] == res.dump(
camel_case=True)
req_body = jsgz_load(mock_seq_response.calls[0].request.body)
assert 42 == req_body["filter"]["lastUpdatedTime"]["max"]
assert {
"name": "n",
"description": "d",
"query": "q"
} == req_body["search"]
def list(
self,
name: str = None,
external_id_prefix: str = None,
metadata: Dict[str, str] = None,
asset_ids: List[int] = None,
root_asset_ids: List[int] = None,
asset_subtree_ids: List[int] = None,
asset_subtree_external_ids: List[str] = None,
data_set_ids: List[int] = None,
data_set_external_ids: List[str] = None,
created_time: (Union[Dict[str, Any], TimestampRange]) = None,
last_updated_time: (Union[Dict[str, Any], TimestampRange]) = None,
limit: Optional[int] = 25,
) -> SequenceList:
"""`Iterate over sequences <https://docs.cognite.com/api/v1/#operation/advancedListSequences>`_
Fetches sequences as they are iterated over, so you keep a limited number of objects in memory.
Args:
name (str): Filter out sequences that do not have this *exact* name.
external_id_prefix (str): Filter out sequences that do not have this string as the start of the externalId
metadata (Dict[str, Any]): Filter out sequences that do not match these metadata fields and values (case-sensitive). Format is {"key1":"value1","key2":"value2"}.
asset_ids (List[int]): Filter out sequences that are not linked to any of these assets.
root_asset_ids (List[int]): Filter out sequences not linked to assets with one of these assets as the root asset.
asset_subtree_ids (List[int]): List of asset subtrees ids to filter on.
asset_subtree_external_ids (List[str]): List of asset subtrees external ids to filter on.
data_set_ids (List[int]): Return only events in the specified data sets with these ids.
data_set_external_ids (List[str]): Return only events in the specified data sets with these external ids.
created_time (Union[Dict[str, int], TimestampRange]): Range between two timestamps. Possible keys are `min` and `max`, with values given as time stamps in ms.
last_updated_time (Union[Dict[str, int], TimestampRange]): Range between two timestamps. Possible keys are `min` and `max`, with values given as time stamps in ms.
limit (int, optional): Max number of sequences to return. Defaults to 25. Set to -1, float("inf") or None
to return all items.
Returns:
SequenceList: The requested sequences.
Examples:
List sequences::
>>> from cognite.client import CogniteClient
>>> c = CogniteClient()
>>> res = c.sequences.list(limit=5)
Iterate over sequences::
>>> from cognite.client import CogniteClient
>>> c = CogniteClient()
>>> for seq in c.sequences:
... seq # do something with the sequences
Iterate over chunks of sequences to reduce memory load::
>>> from cognite.client import CogniteClient
>>> c = CogniteClient()
>>> for seq_list in c.sequences(chunk_size=2500):
... seq_list # do something with the sequences
"""
if asset_subtree_ids or asset_subtree_external_ids:
asset_subtree_ids = self._process_ids(asset_subtree_ids,
asset_subtree_external_ids,
wrap_ids=True)
if data_set_ids or data_set_external_ids:
data_set_ids = self._process_ids(data_set_ids,
data_set_external_ids,
wrap_ids=True)
filter = SequenceFilter(
name=name,
metadata=metadata,
external_id_prefix=external_id_prefix,
asset_ids=asset_ids,
root_asset_ids=root_asset_ids,
asset_subtree_ids=asset_subtree_ids,
created_time=created_time,
last_updated_time=last_updated_time,
data_set_ids=data_set_ids,
).dump(camel_case=True)
return self._list(method="POST", filter=filter, limit=limit)
def test_search(self):
res = COGNITE_CLIENT.sequences.search(
name="42", filter=SequenceFilter(created_time={"min": 0}))
assert len(res) > 0
def test_aggregate(self):
res = COGNITE_CLIENT.sequences.aggregate(filter=SequenceFilter(
name="42"))
assert res[0].count > 0
def list(
self,
name: str = None,
external_id_prefix: str = None,
metadata: Dict[str, Any] = None,
asset_ids: List[int] = None,
root_asset_ids: List[int] = None,
created_time: Dict[str, Any] = None,
last_updated_time: Dict[str, Any] = None,
limit: Optional[int] = 25,
) -> SequenceList:
"""Iterate over sequences
Fetches sequences as they are iterated over, so you keep a limited number of objects in memory.
Args:
name (str): Filter out sequences that do not have this *exact* name.
external_id_prefix (str): Filter out sequences that do not have this string as the start of the externalId
metadata (Dict[str, Any]): Filter out sequences that do not match these metadata fields and values (case-sensitive). Format is {"key1":"value1","key2":"value2"}.
asset_ids (List[int]): Filter out sequences that are not linked to any of these assets.
root_asset_ids (List[int]): Filter out sequences not linked to assets with one of these assets as the root asset.
created_time (Dict[str, Any]): Filter out sequences with createdTime outside this range.
last_updated_time (Dict[str, Any]): Filter out sequences with lastUpdatedTime outside this range.
limit (int, optional): Max number of sequences to return. Defaults to 25. Set to -1, float("inf") or None
to return all items.
Returns:
SequenceList: The requested sequences.
Examples:
List sequences::
>>> from cognite.client.experimental import CogniteClient
>>> c = CogniteClient()
>>> res = c.sequences.list(limit=5)
Iterate over sequences::
>>> from cognite.client.experimental import CogniteClient
>>> c = CogniteClient()
>>> for seq in c.sequences:
... seq # do something with the sequences
Iterate over chunks of sequences to reduce memory load::
>>> from cognite.client.experimental import CogniteClient
>>> c = CogniteClient()
>>> for seq_list in c.sequences(chunk_size=2500):
... seq_list # do something with the sequences
"""
filter = SequenceFilter(
name=name,
metadata=metadata,
external_id_prefix=external_id_prefix,
asset_ids=asset_ids,
root_asset_ids=root_asset_ids,
created_time=created_time,
last_updated_time=last_updated_time,
).dump(camel_case=True)
return self._list(method="POST", filter=filter, limit=limit)