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docs-ref-autogen/azure-datalake-store/azure.datalake.store.lib.DatalakeRESTInterface.yml

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -125,18 +125,18 @@ attributes:
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name: session
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- uid: azure.datalake.store.lib.DatalakeRESTInterface.ends
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name: ends
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signature: 'ends = {''APPEND'': (''post'', set(), {''filesessionid'', ''offset'',
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''leaseid'', ''append'', ''syncFlag''}), ''CHECKACCESS'': (''get'', set(), {''fsaction''}),
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signature: 'ends = {''APPEND'': (''post'', set(), {''offset'', ''syncFlag'', ''filesessionid'',
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''append'', ''leaseid''}), ''CHECKACCESS'': (''get'', set(), {''fsaction''}),
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''CONCAT'': (''post'', {''sources''}, {''sources''}), ''CREATE'': (''put'', set(),
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{''write'', ''overwrite'', ''filesessionid'', ''leaseid'', ''syncFlag''}), ''DELETE'':
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{''syncFlag'', ''filesessionid'', ''overwrite'', ''write'', ''leaseid''}), ''DELETE'':
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(''delete'', set(), {''recursive''}), ''GETCONTENTSUMMARY'': (''get'', set(),
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set()), ''GETFILESTATUS'': (''get'', set(), set()), ''LISTSTATUS'': (''get'',
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set(), {''listAfter'', ''listSize''}), ''MKDIRS'': (''put'', set(), set()), ''MODIFYACLENTRIES'':
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(''put'', {''aclSpec''}, {''aclSpec''}), ''MSCONCAT'': (''post'', set(), {''deleteSourceDirectory''}),
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''MSGETACLSTATUS'': (''get'', set(), set()), ''OPEN'': (''get'', set(), {''offset'',
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''read'', ''filesessionid'', ''length''}), ''REMOVEACL'': (''put'', set(), set()),
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''MSGETACLSTATUS'': (''get'', set(), set()), ''OPEN'': (''get'', set(), {''read'',
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''filesessionid'', ''length'', ''offset''}), ''REMOVEACL'': (''put'', set(), set()),
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''REMOVEACLENTRIES'': (''put'', {''aclSpec''}, {''aclSpec''}), ''REMOVEDEFAULTACL'':
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(''put'', set(), set()), ''RENAME'': (''put'', {''destination''}, {''destination''}),
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''SETACL'': (''put'', {''aclSpec''}, {''aclSpec''}), ''SETEXPIRY'': (''put'',
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{''expiryOption''}, {''expiryOption'', ''expireTime''}), ''SETOWNER'': (''put'',
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set(), {''group'', ''owner''}), ''SETPERMISSION'': (''put'', set(), {''permission''})}'
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{''expiryOption''}, {''expireTime'', ''expiryOption''}), ''SETOWNER'': (''put'',
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set(), {''owner'', ''group''}), ''SETPERMISSION'': (''put'', set(), {''permission''})}'

preview/docs-ref-autogen/azure-ai-anomalydetector/azure.ai.anomalydetector.AnomalyDetectorClient.yml

Lines changed: 84 additions & 28 deletions
Original file line numberDiff line numberDiff line change
@@ -4,48 +4,104 @@ name: AnomalyDetectorClient
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fullName: azure.ai.anomalydetector.AnomalyDetectorClient
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module: azure.ai.anomalydetector
66
inheritances:
7-
- azure.ai.anomalydetector.operations._anomaly_detector_client_operations.AnomalyDetectorClientOperationsMixin
8-
summary: The Anomaly Detector API detects anomalies automatically in time series data.
9-
It supports two kinds of mode, one is for stateless using, another is for stateful
10-
using. In stateless mode, there are three functionalities. Entire Detect is for
11-
detecting the whole series with model trained by the time series, Last Detect is
12-
detecting last point with model trained by points before. ChangePoint Detect is
13-
for detecting trend changes in time series. In stateful mode, user can store time
14-
series, the stored time series will be used for detection anomalies. Under this
15-
mode, user can still use the above three functionalities by only giving a time range
16-
without preparing time series in client side. Besides the above three functionalities,
17-
stateful model also provide group based detection and labeling service. By leveraging
18-
labeling service user can provide labels for each detection result, these labels
19-
will be used for retuning or regenerating detection models. Inconsistency detection
20-
is a kind of group based detection, this detection will find inconsistency ones
21-
in a set of time series. By using anomaly detector service, business customers can
22-
discover incidents and establish a logic flow for root cause analysis.
7+
- azure.ai.anomalydetector._operations._operations.AnomalyDetectorClientOperationsMixin
8+
summary: 'The Anomaly Detector API detects anomalies automatically in time series
9+
data.
10+
11+
It supports two kinds of mode, one is for stateless using, another is for
12+
13+
stateful using. In stateless mode, there are three functionalities. Entire
14+
15+
Detect is for detecting the whole series with model trained by the time series,
16+
17+
Last Detect is detecting last point with model trained by points before.
18+
19+
ChangePoint Detect is for detecting trend changes in time series. In stateful
20+
21+
mode, user can store time series, the stored time series will be used for
22+
23+
detection anomalies. Under this mode, user can still use the above three
24+
25+
functionalities by only giving a time range without preparing time series in
26+
27+
client side. Besides the above three functionalities, stateful model also
28+
29+
provide group based detection and labeling service. By leveraging labeling
30+
31+
service user can provide labels for each detection result, these labels will be
32+
33+
used for retuning or regenerating detection models. Inconsistency detection is
34+
35+
a kind of group based detection, this detection will find inconsistency ones in
36+
37+
a set of time series. By using anomaly detector service, business customers can
38+
39+
discover incidents and establish a logic flow for root cause analysis.'
2340
constructor:
24-
syntax: 'AnomalyDetectorClient(credential: AzureKeyCredential, endpoint: str, **kwargs:
25-
Any)'
41+
syntax: 'AnomalyDetectorClient(endpoint: str, credential: azure.core.credentials.AzureKeyCredential,
42+
**kwargs: Any)'
2643
parameters:
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- name: credential
28-
description: Credential needed for the client to connect to Azure.
29-
isRequired: true
30-
types:
31-
- <xref:azure.core.credentials.AzureKeyCredential>
3244
- name: endpoint
3345
description: 'Supported Cognitive Services endpoints (protocol and hostname, for
3446
example:
3547
36-
[https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).'
48+
[https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).
49+
Required.'
3750
isRequired: true
3851
types:
3952
- <xref:str>
53+
- name: credential
54+
description: Credential needed for the client to connect to Azure. Required.
55+
isRequired: true
56+
types:
57+
- <xref:azure.core.credentials.AzureKeyCredential>
4058
- name: api_version
41-
description: 'Anomaly Detector API version (for example, v1.0). The default value
42-
is
59+
description: 'Api Version. Default value is "v1.1". Note that overriding this
60+
default
4361
44-
"v1.1-preview.1". Note that overriding this default value may result in unsupported
45-
behavior.'
62+
value may result in unsupported behavior.'
4663
types:
4764
- <xref:str>
4865
methods:
4966
- uid: azure.ai.anomalydetector.AnomalyDetectorClient.close
5067
name: close
5168
signature: close() -> None
69+
- uid: azure.ai.anomalydetector.AnomalyDetectorClient.send_request
70+
name: send_request
71+
summary: 'Runs the network request through the client''s chained policies.
72+
73+
74+
```
75+
76+
77+
>>> from azure.core.rest import HttpRequest
78+
79+
>>> request = HttpRequest("GET", "https://www.example.org/")
80+
81+
<HttpRequest [GET], url: ''https://www.example.org/''>
82+
83+
>>> response = client.send_request(request)
84+
85+
<HttpResponse: 200 OK>
86+
87+
```
88+
89+
90+
For more information on this code flow, see [https://aka.ms/azsdk/dpcodegen/python/send_request](https://aka.ms/azsdk/dpcodegen/python/send_request)'
91+
signature: 'send_request(request: azure.core.rest._rest_py3.HttpRequest, **kwargs:
92+
Any) -> azure.core.rest._rest_py3.HttpResponse'
93+
parameters:
94+
- name: request
95+
description: The network request you want to make. Required.
96+
isRequired: true
97+
types:
98+
- <xref:azure.core.rest.HttpRequest>
99+
- name: stream
100+
description: Whether the response payload will be streamed. Defaults to False.
101+
types:
102+
- <xref:bool>
103+
return:
104+
description: The response of your network call. Does not do error handling on
105+
your response.
106+
types:
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- <xref:azure.core.rest.HttpResponse>

preview/docs-ref-autogen/azure-ai-anomalydetector/azure.ai.anomalydetector.aio.AnomalyDetectorClient.yml

Lines changed: 84 additions & 28 deletions
Original file line numberDiff line numberDiff line change
@@ -4,48 +4,104 @@ name: AnomalyDetectorClient
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fullName: azure.ai.anomalydetector.aio.AnomalyDetectorClient
55
module: azure.ai.anomalydetector.aio
66
inheritances:
7-
- azure.ai.anomalydetector.aio.operations._anomaly_detector_client_operations.AnomalyDetectorClientOperationsMixin
8-
summary: The Anomaly Detector API detects anomalies automatically in time series data.
9-
It supports two kinds of mode, one is for stateless using, another is for stateful
10-
using. In stateless mode, there are three functionalities. Entire Detect is for
11-
detecting the whole series with model trained by the time series, Last Detect is
12-
detecting last point with model trained by points before. ChangePoint Detect is
13-
for detecting trend changes in time series. In stateful mode, user can store time
14-
series, the stored time series will be used for detection anomalies. Under this
15-
mode, user can still use the above three functionalities by only giving a time range
16-
without preparing time series in client side. Besides the above three functionalities,
17-
stateful model also provide group based detection and labeling service. By leveraging
18-
labeling service user can provide labels for each detection result, these labels
19-
will be used for retuning or regenerating detection models. Inconsistency detection
20-
is a kind of group based detection, this detection will find inconsistency ones
21-
in a set of time series. By using anomaly detector service, business customers can
22-
discover incidents and establish a logic flow for root cause analysis.
7+
- azure.ai.anomalydetector.aio._operations._operations.AnomalyDetectorClientOperationsMixin
8+
summary: 'The Anomaly Detector API detects anomalies automatically in time series
9+
data.
10+
11+
It supports two kinds of mode, one is for stateless using, another is for
12+
13+
stateful using. In stateless mode, there are three functionalities. Entire
14+
15+
Detect is for detecting the whole series with model trained by the time series,
16+
17+
Last Detect is detecting last point with model trained by points before.
18+
19+
ChangePoint Detect is for detecting trend changes in time series. In stateful
20+
21+
mode, user can store time series, the stored time series will be used for
22+
23+
detection anomalies. Under this mode, user can still use the above three
24+
25+
functionalities by only giving a time range without preparing time series in
26+
27+
client side. Besides the above three functionalities, stateful model also
28+
29+
provide group based detection and labeling service. By leveraging labeling
30+
31+
service user can provide labels for each detection result, these labels will be
32+
33+
used for retuning or regenerating detection models. Inconsistency detection is
34+
35+
a kind of group based detection, this detection will find inconsistency ones in
36+
37+
a set of time series. By using anomaly detector service, business customers can
38+
39+
discover incidents and establish a logic flow for root cause analysis.'
2340
constructor:
24-
syntax: 'AnomalyDetectorClient(credential: azure.core.credentials.AzureKeyCredential,
25-
endpoint: str, **kwargs: Any)'
41+
syntax: 'AnomalyDetectorClient(endpoint: str, credential: azure.core.credentials.AzureKeyCredential,
42+
**kwargs: Any)'
2643
parameters:
27-
- name: credential
28-
description: Credential needed for the client to connect to Azure.
29-
isRequired: true
30-
types:
31-
- <xref:azure.core.credentials.AzureKeyCredential>
3244
- name: endpoint
3345
description: 'Supported Cognitive Services endpoints (protocol and hostname, for
3446
example:
3547
36-
[https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).'
48+
[https://westus2.api.cognitive.microsoft.com](https://westus2.api.cognitive.microsoft.com)).
49+
Required.'
3750
isRequired: true
3851
types:
3952
- <xref:str>
53+
- name: credential
54+
description: Credential needed for the client to connect to Azure. Required.
55+
isRequired: true
56+
types:
57+
- <xref:azure.core.credentials.AzureKeyCredential>
4058
- name: api_version
41-
description: 'Anomaly Detector API version (for example, v1.0). The default value
42-
is
59+
description: 'Api Version. Default value is "v1.1". Note that overriding this
60+
default
4361
44-
"v1.1-preview.1". Note that overriding this default value may result in unsupported
45-
behavior.'
62+
value may result in unsupported behavior.'
4663
types:
4764
- <xref:str>
4865
methods:
4966
- uid: azure.ai.anomalydetector.aio.AnomalyDetectorClient.close
5067
name: close
5168
signature: async close() -> None
69+
- uid: azure.ai.anomalydetector.aio.AnomalyDetectorClient.send_request
70+
name: send_request
71+
summary: 'Runs the network request through the client''s chained policies.
72+
73+
74+
```
75+
76+
77+
>>> from azure.core.rest import HttpRequest
78+
79+
>>> request = HttpRequest("GET", "https://www.example.org/")
80+
81+
<HttpRequest [GET], url: ''https://www.example.org/''>
82+
83+
>>> response = await client.send_request(request)
84+
85+
<AsyncHttpResponse: 200 OK>
86+
87+
```
88+
89+
90+
For more information on this code flow, see [https://aka.ms/azsdk/dpcodegen/python/send_request](https://aka.ms/azsdk/dpcodegen/python/send_request)'
91+
signature: 'send_request(request: azure.core.rest._rest_py3.HttpRequest, **kwargs:
92+
Any) -> Awaitable[azure.core.rest._rest_py3.AsyncHttpResponse]'
93+
parameters:
94+
- name: request
95+
description: The network request you want to make. Required.
96+
isRequired: true
97+
types:
98+
- <xref:azure.core.rest.HttpRequest>
99+
- name: stream
100+
description: Whether the response payload will be streamed. Defaults to False.
101+
types:
102+
- <xref:bool>
103+
return:
104+
description: The response of your network call. Does not do error handling on
105+
your response.
106+
types:
107+
- <xref:azure.core.rest.AsyncHttpResponse>

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