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Ma accept str for datetime #14517

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Oct 16, 2020
Merged

Ma accept str for datetime #14517

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accept str for datetime
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14 changes: 14 additions & 0 deletions sdk/metricsadvisor/azure-ai-metricsadvisor/azure/ai/metricsadvisor/_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -187,3 +187,17 @@ def convert_to_sub_feedback(feedback):
if feedback.feedback_type == "Period":
return PeriodFeedback._from_generated(feedback) # type: ignore
raise HttpResponseError("Invalid feedback type returned in the response.")

def convert_datetime(date_time):
# type: (Union[str, datetime.datetime]) -> datetime.datetime
if isinstance(date_time, datetime.datetime):
return date_time
if isinstance(date_time, six.string_types):
try:
return datetime.datetime.strptime(date_time, "%Y-%m-%d")
except ValueError:
try:
return datetime.datetime.strptime(date_time, "%Y-%m-%dT%H:%M:%SZ")
except ValueError:
return datetime.datetime.strptime(date_time, "%Y-%m-%d %H:%M:%S")
raise TypeError("Bad datetime type")
31 changes: 18 additions & 13 deletions ...azure-ai-metricsadvisor/azure/ai/metricsadvisor/_metrics_advisor_administration_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,8 @@
construct_alert_config_dict,
construct_detection_config_dict,
construct_hook_dict,
construct_data_feed_dict
construct_data_feed_dict,
convert_datetime
)
from .models._models import (
DataFeed,
Expand Down Expand Up @@ -556,8 +557,8 @@ def get_data_feed_ingestion_progress(
def refresh_data_feed_ingestion(
self,
data_feed_id, # type: str
start_time, # type: datetime.datetime
end_time, # type: datetime.datetime
start_time, # type: Union[str, datetime.datetime]
end_time, # type: Union[str, datetime.datetime]
**kwargs # type: Any
):
# type: (...) -> None
Expand All @@ -566,9 +567,9 @@ def refresh_data_feed_ingestion(
:param data_feed_id: The data feed unique id.
:type data_feed_id: str
:param start_time: The start point of time range to refresh data ingestion.
:type start_time: ~datetime.datetime
:type start_time: Union[str, ~datetime.datetime]
:param end_time: The end point of time range to refresh data ingestion.
:type end_time: ~datetime.datetime
:type end_time: Union[str, ~datetime.datetime]
:return: None
:rtype: None
:raises ~azure.core.exceptions.HttpResponseError:
Expand All @@ -582,11 +583,13 @@ def refresh_data_feed_ingestion(
:dedent: 4
:caption: Refresh data feed ingestion over a period of time
"""
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)
self._client.reset_data_feed_ingestion_status(
data_feed_id,
body=_IngestionProgressResetOptions(
start_time=start_time,
end_time=end_time
start_time=converted_start_time,
end_time=converted_end_time
),
**kwargs
)
Expand Down Expand Up @@ -1171,18 +1174,18 @@ def list_metric_anomaly_detection_configurations(
def list_data_feed_ingestion_status(
self,
data_feed_id, # type: str
start_time, # type: datetime.datetime
end_time, # type: datetime.datetime
start_time, # type: Union[str, datetime.datetime]
end_time, # type: Union[str, datetime.datetime]
**kwargs # type: Any
):
# type: (...) -> ItemPaged[DataFeedIngestionStatus]
"""Get data ingestion status by data feed.

:param str data_feed_id: The data feed unique id.
:param start_time: Required. the start point of time range to query data ingestion status.
:type start_time: ~datetime.datetime
:type start_time: Union[str, ~datetime.datetime]
:param end_time: Required. the end point of time range to query data ingestion status.
:type end_time: ~datetime.datetime
:type end_time: Union[str, ~datetime.datetime]
:keyword int skip:
:return: Pageable of DataFeedIngestionStatus
:rtype: ~azure.core.paging.ItemPaged[~azure.ai.metricsadvisor.models.DataFeedIngestionStatus]
Expand All @@ -1199,12 +1202,14 @@ def list_data_feed_ingestion_status(
"""

skip = kwargs.pop("skip", None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)

return self._client.get_data_feed_ingestion_status( # type: ignore
data_feed_id=data_feed_id,
body=_IngestionStatusQueryOptions(
start_time=start_time,
end_time=end_time
start_time=converted_start_time,
end_time=converted_end_time
),
skip=skip,
**kwargs
Expand Down
105 changes: 64 additions & 41 deletions ...metricsadvisor/azure-ai-metricsadvisor/azure/ai/metricsadvisor/_metrics_advisor_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@
# pylint: disable=protected-access

from typing import List, Union, Dict, Any, cast, TYPE_CHECKING
import datetime # pylint:disable=unused-import

from azure.core.tracing.decorator import distributed_trace
from ._metrics_advisor_key_credential import MetricsAdvisorKeyCredential
Expand All @@ -27,7 +26,7 @@
FeedbackDimensionFilter,
)
from ._generated import AzureCognitiveServiceMetricsAdvisorRESTAPIOpenAPIV2
from ._helpers import convert_to_sub_feedback
from ._helpers import convert_to_sub_feedback, convert_datetime
from .models._models import (
Incident,
Anomaly,
Expand All @@ -38,6 +37,7 @@
from ._version import SDK_MONIKER

if TYPE_CHECKING:
import datetime
from ._generated.models import (
SeriesResult,
EnrichmentStatus,
Expand Down Expand Up @@ -175,8 +175,8 @@ def list_feedbacks(self, metric_id, **kwargs):
:keyword feedback_type: filter feedbacks by type. Possible values include: "Anomaly",
"ChangePoint", "Period", "Comment".
:paramtype feedback_type: str or ~azure.ai.metricsadvisor.models.FeedbackType
:keyword ~datetime.datetime start_time: start time filter under chosen time mode.
:keyword ~datetime.datetime end_time: end time filter under chosen time mode.
:keyword Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:keyword Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:keyword time_mode: time mode to filter feedback. Possible values include: "MetricTimestamp",
"FeedbackCreatedTime".
:paramtype time_mode: str or ~azure.ai.metricsadvisor.models.FeedbackQueryTimeMode
Expand All @@ -203,13 +203,15 @@ def list_feedbacks(self, metric_id, **kwargs):
feedback_type = kwargs.pop('feedback_type', None)
start_time = kwargs.pop('start_time', None)
end_time = kwargs.pop('end_time', None)
converted_start_time = convert_datetime(start_time) if start_time else None
converted_end_time = convert_datetime(end_time) if end_time else None
time_mode = kwargs.pop('time_mode', None)
feedback_filter = MetricFeedbackFilter(
metric_id=metric_id,
dimension_filter=dimension_filter,
feedback_type=feedback_type,
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
time_mode=time_mode,
)

Expand Down Expand Up @@ -249,8 +251,8 @@ def list_incident_root_causes(self, detection_configuration_id, incident_id, **k
def list_metric_enriched_series_data(
self, detection_configuration_id, # type: str
series, # type: Union[List[SeriesIdentity], List[Dict[str, str]]]
start_time, # type: datetime.datetime
end_time, # type: datetime.datetime
start_time, # type: Union[str, datetime.datetime]
end_time, # type: Union[str, datetime.datetime]
**kwargs # type: Any
):
# type: (...) -> ItemPaged[SeriesResult]
Expand All @@ -259,8 +261,8 @@ def list_metric_enriched_series_data(
:param str detection_configuration_id: anomaly alerting configuration unique id.
:param series: List of dimensions specified for series.
:type series: ~azure.ai.metricsadvisor.models.SeriesIdentity or list[dict[str, str]]
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:return: Pageable of SeriesResult
:rtype: ~azure.core.paging.ItemPaged[~azure.ai.metricsadvisor.models.SeriesResult]
:raises ~azure.core.exceptions.HttpResponseError:
Expand All @@ -273,9 +275,11 @@ def list_metric_enriched_series_data(
] or series

series_list = cast(List[SeriesIdentity], series_list)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)
detection_series_query = DetectionSeriesQuery(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
series=series_list
)

Expand All @@ -292,8 +296,8 @@ def list_alerts_for_alert_configuration(self, alert_configuration_id, start_time

:param alert_configuration_id: anomaly alert configuration unique id.
:type alert_configuration_id: str
:param ~datetime.datetime start_time: start time.
:param ~datetime.datetime end_time: end time.
:param Union[str, ~datetime.datetime] start_time: start time.
:param Union[str, ~datetime.datetime] end_time: end time.
:param time_mode: time mode. Possible values include: "AnomalyTime", "CreatedTime",
"ModifiedTime".
:type time_mode: str or ~azure.ai.metricsadvisor.models.TimeMode
Expand All @@ -313,10 +317,12 @@ def list_alerts_for_alert_configuration(self, alert_configuration_id, start_time
"""

skip = kwargs.pop('skip', None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)

alerting_result_query = AlertingResultQuery(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
time_mode=time_mode,
)

Expand Down Expand Up @@ -369,8 +375,8 @@ def list_anomalies_for_detection_configuration(self, detection_configuration_id,

:param detection_configuration_id: anomaly detection configuration unique id.
:type detection_configuration_id: str
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:keyword int skip:
:keyword filter:
:paramtype filter: ~azure.ai.metricsadvisor.models.DetectionAnomalyFilterCondition
Expand All @@ -381,9 +387,11 @@ def list_anomalies_for_detection_configuration(self, detection_configuration_id,

skip = kwargs.pop('skip', None)
filter_condition = kwargs.pop('filter', None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)
detection_anomaly_result_query = DetectionAnomalyResultQuery(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
filter=filter_condition,
)

Expand All @@ -402,15 +410,15 @@ def list_dimension_values_for_detection_configuration(
end_time,
**kwargs
):
# type: (str, str, datetime.datetime, datetime.datetime, Any) -> ItemPaged[str]
# type: (str, str, Union[str, datetime.datetime], Union[str, datetime.datetime], Any) -> ItemPaged[str]

"""Query dimension values of anomalies.

:param detection_configuration_id: anomaly detection configuration unique id.
:type detection_configuration_id: str
:param str dimension_name: dimension to query.
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:keyword int skip:
:keyword str dimension_name: The dimension name to query.
:paramtype dimension_filter: ~azure.ai.metricsadvisor.models.DimensionGroupIdentity
Expand All @@ -421,9 +429,11 @@ def list_dimension_values_for_detection_configuration(

skip = kwargs.pop('skip', None)
dimension_filter = kwargs.pop('dimension_filter', None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)
anomaly_dimension_query = AnomalyDimensionQuery(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
dimension_name=dimension_name,
dimension_filter=dimension_filter,
)
Expand Down Expand Up @@ -461,14 +471,14 @@ def list_incidents_for_alert(self, alert_configuration_id, alert_id, **kwargs):

@distributed_trace
def list_incidents_for_detection_configuration(self, detection_configuration_id, start_time, end_time, **kwargs):
# type: (str, datetime.datetime, datetime.datetime, Any) -> ItemPaged[Incident]
# type: (str, Union[str, datetime.datetime], Union[str, datetime.datetime], Any) -> ItemPaged[Incident]

"""Query incidents under a specific alert.

:param detection_configuration_id: anomaly detection configuration unique id.
:type detection_configuration_id: str
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:keyword filter:
:paramtype filter: ~azure.ai.metricsadvisor.models.DetectionIncidentFilterCondition
:return: Incidents under a specific alert.
Expand All @@ -477,10 +487,12 @@ def list_incidents_for_detection_configuration(self, detection_configuration_id,
"""

filter_condition = kwargs.pop('filter', None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)

detection_incident_result_query = DetectionIncidentResultQuery(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
filter=filter_condition,
)

Expand Down Expand Up @@ -523,25 +535,34 @@ def list_metric_dimension_values(self, metric_id, dimension_name, **kwargs):
**kwargs)

@distributed_trace
def list_metrics_series_data(self, metric_id, start_time, end_time, series_to_filter, **kwargs):
# type: (str, datetime.datetime, datetime.datetime, List[Dict[str, str]], Any) -> ItemPaged[MetricSeriesData]
def list_metrics_series_data(self,
metric_id, # type: str
start_time, # type: Union[str, datetime.datetime]
end_time, # type: Union[str, datetime.datetime]
series_to_filter, # type: List[Dict[str, str]]
**kwargs # type: Any
):
# type: (...) -> ItemPaged[MetricSeriesData]

"""Get time series data from metric.

:param metric_id: metric unique id.
:type metric_id: str
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:param series_to_filter: query specific series.
:type series_to_filter: list[dict[str, str]]
:return: Time series data from metric.
:rtype: ~azure.core.paging.ItemPaged[~azure.ai.metricsadvisor.models.MetricSeriesData]
:raises ~azure.core.exceptions.HttpResponseError:
"""

converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)

metric_data_query_options = MetricDataQueryOptions(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
series=series_to_filter,
)

Expand Down Expand Up @@ -588,24 +609,26 @@ def list_metric_series_definitions(self, metric_id, active_since, **kwargs):

@distributed_trace
def list_metric_enrichment_status(self, metric_id, start_time, end_time, **kwargs):
# type: (str, datetime.datetime, datetime.datetime, Any) -> ItemPaged[EnrichmentStatus]
# type: (str, Union[str, datetime.datetime], Union[str, datetime.datetime], Any) -> ItemPaged[EnrichmentStatus]

"""Query anomaly detection status.

:param metric_id: filter feedbacks by metric id.
:type metric_id: str
:param ~datetime.datetime start_time: start time filter under chosen time mode.
:param ~datetime.datetime end_time: end time filter under chosen time mode.
:param Union[str, ~datetime.datetime] start_time: start time filter under chosen time mode.
:param Union[str, ~datetime.datetime] end_time: end time filter under chosen time mode.
:keyword int skip:
:return: Anomaly detection status.
:rtype: ~azure.core.paging.ItemPaged[~azure.ai.metricsadvisor.models.EnrichmentStatus]
:raises ~azure.core.exceptions.HttpResponseError:
"""

skip = kwargs.pop('skip', None)
converted_start_time = convert_datetime(start_time)
converted_end_time = convert_datetime(end_time)
enrichment_status_query_option = EnrichmentStatusQueryOption(
start_time=start_time,
end_time=end_time,
start_time=converted_start_time,
end_time=converted_end_time,
)

return self._client.get_enrichment_status_by_metric( # type: ignore
Expand Down
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