@@ -4,48 +4,104 @@ name: AnomalyDetectorClient
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fullName : azure.ai.anomalydetector.aio.AnomalyDetectorClient
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module : azure.ai.anomalydetector.aio
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inheritances :
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- - azure.ai.anomalydetector.aio.operations._anomaly_detector_client_operations.AnomalyDetectorClientOperationsMixin
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- summary : The Anomaly Detector API detects anomalies automatically in time series data.
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- It supports two kinds of mode, one is for stateless using, another is for stateful
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- using. In stateless mode, there are three functionalities. Entire Detect is for
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- detecting the whole series with model trained by the time series, Last Detect is
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- detecting last point with model trained by points before. ChangePoint Detect is
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- for detecting trend changes in time series. In stateful mode, user can store time
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- series, the stored time series will be used for detection anomalies. Under this
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- mode, user can still use the above three functionalities by only giving a time range
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- without preparing time series in client side. Besides the above three functionalities,
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- stateful model also provide group based detection and labeling service. By leveraging
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- labeling service user can provide labels for each detection result, these labels
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- will be used for retuning or regenerating detection models. Inconsistency detection
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- is a kind of group based detection, this detection will find inconsistency ones
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- in a set of time series. By using anomaly detector service, business customers can
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- discover incidents and establish a logic flow for root cause analysis.
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+ - azure.ai.anomalydetector.aio._operations._operations.AnomalyDetectorClientOperationsMixin
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+ summary : ' The Anomaly Detector API detects anomalies automatically in time series
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+ data.
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+
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+ It supports two kinds of mode, one is for stateless using, another is for
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+
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+ stateful using. In stateless mode, there are three functionalities. Entire
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+
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+ Detect is for detecting the whole series with model trained by the time series,
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+
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+ Last Detect is detecting last point with model trained by points before.
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+
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+ ChangePoint Detect is for detecting trend changes in time series. In stateful
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+
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+ mode, user can store time series, the stored time series will be used for
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+
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+ detection anomalies. Under this mode, user can still use the above three
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+
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+ functionalities by only giving a time range without preparing time series in
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+
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+ client side. Besides the above three functionalities, stateful model also
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+
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+ provide group based detection and labeling service. By leveraging labeling
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+
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+ service user can provide labels for each detection result, these labels will be
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+
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+ used for retuning or regenerating detection models. Inconsistency detection is
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+
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+ a kind of group based detection, this detection will find inconsistency ones in
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+
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+ a set of time series. By using anomaly detector service, business customers can
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+
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+ discover incidents and establish a logic flow for root cause analysis.'
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constructor :
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- syntax : ' AnomalyDetectorClient(credential: azure.core.credentials.AzureKeyCredential,
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- endpoint: str, **kwargs: Any)'
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+ syntax : ' AnomalyDetectorClient(endpoint: str, credential: azure.core.credentials.AzureKeyCredential,
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+ **kwargs: Any)'
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parameters :
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- - name : credential
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- description : Credential needed for the client to connect to Azure.
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- isRequired : true
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- types :
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- - <xref:azure.core.credentials.AzureKeyCredential>
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- name : endpoint
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description : ' Supported Cognitive Services endpoints (protocol and hostname, for
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example:
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- [https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).'
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+ [https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).
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+ Required.'
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isRequired : true
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types :
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- <xref:str>
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+ - name : credential
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+ description : Credential needed for the client to connect to Azure. Required.
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+ isRequired : true
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+ types :
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+ - <xref:azure.core.credentials.AzureKeyCredential>
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- name : api_version
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- description : ' Anomaly Detector API version (for example, v1.0). The default value
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- is
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+ description : ' Api Version. Default value is " v1.1". Note that overriding this
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+ default
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- "v1.1-preview.1". Note that overriding this default value may result in unsupported
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- behavior.'
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+ value may result in unsupported behavior.'
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types :
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- <xref:str>
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methods :
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- uid : azure.ai.anomalydetector.aio.AnomalyDetectorClient.close
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name : close
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signature : async close() -> None
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+ - uid : azure.ai.anomalydetector.aio.AnomalyDetectorClient.send_request
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+ name : send_request
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+ summary : ' Runs the network request through the client'' s chained policies.
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+
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+
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+ ```
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+
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+
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+ >>> from azure.core.rest import HttpRequest
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+
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+ >>> request = HttpRequest("GET", "https://www.example.org/")
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+
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+ <HttpRequest [GET], url: '' https://www.example.org/'' >
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+
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+ >>> response = await client.send_request(request)
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+
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+ <AsyncHttpResponse: 200 OK>
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+
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+ ```
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+
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+
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+ For more information on this code flow, see [https://aka.ms/azsdk/dpcodegen/python/send_request](https://aka.ms/azsdk/dpcodegen/python/send_request)'
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+ signature : ' send_request(request: azure.core.rest._rest_py3.HttpRequest, **kwargs:
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+ Any) -> Awaitable[azure.core.rest._rest_py3.AsyncHttpResponse]'
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+ parameters :
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+ - name : request
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+ description : The network request you want to make. Required.
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+ isRequired : true
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+ types :
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+ - <xref:azure.core.rest.HttpRequest>
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+ - name : stream
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+ description : Whether the response payload will be streamed. Defaults to False.
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+ types :
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+ - <xref:bool>
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+ return :
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+ description : The response of your network call. Does not do error handling on
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+ your response.
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+ types :
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+ - <xref:azure.core.rest.AsyncHttpResponse>
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