Saravanan666/pypi-org huggingface dataset:
Package: azure-mgmt-streamanalytics
Microsoft Azure SDK for PythonThis is the Microsoft Azure Stream Analytics Management Client Library.
This package has been tested with Python 2.7, 3.6+.
For a more complete view of Azure libraries, see theazure sdk python release.DisclaimerAzure SDK Python packages support for Python 2.7 has ended 01 January 2022. For more information and questions, please refer tohttps://github.com/Azure/azure-sdk-for-python/issues/20691UsageTo learn how to use this package, see thequickstart guideFor docs and references, seePython SDK ReferencesCode samples for this package can be found atStream Analytics Managementon docs.microsoft.com.
Additional code samples for different Azure services are available atSamples RepoProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History1.0.0 (2022-01-06)FeaturesAdded operation StreamingJobsOperations.begin_scaleModel AzureSqlReferenceInputDataSource has a new parameter databaseModel AzureSqlReferenceInputDataSource has a new parameter delta_snapshot_queryModel AzureSqlReferenceInputDataSource has a new parameter full_snapshot_queryModel AzureSqlReferenceInputDataSource has a new parameter passwordModel AzureSqlReferenceInputDataSource has a new parameter refresh_rateModel AzureSqlReferenceInputDataSource has a new parameter refresh_typeModel AzureSqlReferenceInputDataSource has a new parameter serverModel AzureSqlReferenceInputDataSource has a new parameter tableModel AzureSqlReferenceInputDataSource has a new parameter userModel Cluster has a new parameter capacity_allocatedModel Cluster has a new parameter capacity_assignedModel Cluster has a new parameter cluster_idModel Cluster has a new parameter created_dateModel Cluster has a new parameter provisioning_stateModel Operation has a new parameter is_data_actionModel PrivateEndpoint has a new parameter created_dateModel PrivateEndpoint has a new parameter manual_private_link_service_connectionsModel Transformation has a new parameter valid_streaming_unitsBreaking changesModel AzureSqlReferenceInputDataSource no longer has parameter propertiesModel Cluster no longer has parameter propertiesModel FunctionProperties no longer has parameter bindingModel FunctionProperties no longer has parameter inputsModel FunctionProperties no longer has parameter outputModel PrivateEndpoint no longer has parameter propertiesModel StreamingJob no longer has parameter externals1.0.0rc1 (2020-09-18)Initial Release
Package: azure-mgmt-support
Microsoft Azure SDK for PythonThis is the Microsoft Azure Support Management Client Library.
This package has been tested with Python 2.7, 3.5, 3.6, 3.7 and 3.8.
For a more complete view of Azure libraries, see theazure sdk python release.UsageTo learn how to use this package, see thequickstart guideFor docs and references, seePython SDK ReferencesCode samples for this package can be found atSupport Managementon docs.microsoft.com.
Additional code samples for different Azure services are available atSamples RepoProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History6.0.0 (2021-03-29)GA release6.0.0b1 (2020-12-02)This is beta preview version.This version uses a next-generation code generator that introduces important breaking changes, but also important new features (like unified authentication and async programming).General breaking changesCredential system has been completly revamped:azure.common.credentialsormsrestazure.azure_active_directoryinstances are no longer supported, use theazure-identityclasses instead:https://pypi.org/project/azure-identity/credentialsparameter has been renamedcredentialTheconfigattribute no longer exists on a client, configuration should be passed as kwarg. Example:MyClient(credential, subscription_id, enable_logging=True). For a complete set of
supported options, see theparameters accept in init documentation of azure-coreYou can't import aversionmodule anymore, use__version__insteadOperations that used to return amsrest.polling.LROPollernow returns aazure.core.polling.LROPollerand are prefixed withbegin_.Exceptions tree have been simplified and most exceptions are nowazure.core.exceptions.HttpResponseError(CloudErrorhas been removed).Most of the operation kwarg have changed. Some of the most noticeable:rawhas been removed. Equivalent feature can be found usingcls, a callback that will give access to internal HTTP response for advanced userFor a complete set of
supported options, see theparameters accept in Request documentation of azure-coreGeneral new featuresType annotations support usingtyping. SDKs are mypy ready.This client has now stable and official support for async. Check theaionamespace of your package to find the async client.This client now support natively tracing library like OpenCensus or OpenTelemetry. See thistracing quickstartfor an overview.1.0.0 (2020-03-14)FeaturesModel UpdateSupportTicket has a new parameter statusModel Service has a new parameter resource_typesBreaking changesModel SupportTicketDetails no longer has parameter production_outageOperation SupportTicketsOperations.update has a new signature0.1.0 (2020-01-31)Initial Release
Package: azure-mgmt-testbase
Microsoft Azure SDK for PythonThis is the Microsoft Azure Testbase Management Client Library.
This package has been tested with Python 3.7+.
For a more complete view of Azure libraries, see theazure sdk python release.DisclaimerAzure SDK Python packages support for Python 2.7 has ended 01 January 2022. For more information and questions, please refer tohttps://github.com/Azure/azure-sdk-for-python/issues/20691UsageTo learn how to use this package, see thequickstart guideFor docs and references, seePython SDK ReferencesCode samples for this package can be found atTestbase Managementon docs.microsoft.com.
Additional code samples for different Azure services are available atSamples RepoProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History1.0.0b2 (2022-11-04)Features AddedAdded operation PackagesOperations.run_testAdded operation TestResultsOperations.get_console_log_download_urlAdded operation group BillingHubServiceOperationsModel ScriptExecutionResult has a new parameter stderr_log_file_nameModel ScriptExecutionResult has a new parameter stdout_log_file_nameModel TargetOSInfo has a new parameter baseline_o_ssModel Test has a new parameter validation_result_idModel TestResultResource has a new parameter interop_media_typeModel TestResultResource has a new parameter interop_media_versionModel TestSummaryResource has a new parameter package_tags1.0.0b1 (2021-06-17)Initial Release
Package: azure-mgmt-videoanalyzer
Microsoft Azure SDK for PythonWe’re retiring the Azure Video Analyzer preview service; you're advised to transition your applications off of Video Analyzer by 01 December 2022. This SDK is no longer maintained and won’t work after the service is retired. To learn how to transition off, please refer to:Transition from Azure Video Analyzer - Azure Video Analyzer | Microsoft DocsThe complete list of available packages can be found at:https://aka.ms/azsdk/python/allRelease History1.0.0b4 (2022-05-13)Deprecate the package1.0.0b3 (2021-10-25)FeaturesModel ProxyResource has a new parameter system_dataModel Resource has a new parameter system_dataModel TrackedResource has a new parameter system_dataModel VideoAnalyzerUpdate has a new parameter provisioning_stateModel VideoAnalyzerUpdate has a new parameter iot_hubsModel VideoAnalyzerUpdate has a new parameter network_access_controlModel VideoAnalyzerUpdate has a new parameter private_endpoint_connectionsModel VideoAnalyzerUpdate has a new parameter public_network_accessModel VideoAnalyzer has a new parameter provisioning_stateModel VideoAnalyzer has a new parameter iot_hubsModel VideoAnalyzer has a new parameter network_access_controlModel VideoAnalyzer has a new parameter private_endpoint_connectionsModel VideoAnalyzer has a new parameter public_network_accessModel VideoEntity has a new parameter archivalModel VideoEntity has a new parameter content_urlsAdded operation VideoAnalyzersOperations.begin_updateAdded operation VideoAnalyzersOperations.begin_create_or_updateAdded operation VideosOperations.list_content_tokenAdded operation group PrivateEndpointConnectionsOperationsAdded operation group PrivateLinkResourcesOperationsAdded operation group OperationStatusesOperationsAdded operation group PipelineJobsOperationsAdded operation group PipelineTopologiesOperationsAdded operation group VideoAnalyzerOperationStatusesOperationsAdded operation group LivePipelineOperationStatusesOperationsAdded operation group LivePipelinesOperationsAdded operation group OperationResultsOperationsAdded operation group PipelineJobOperationStatusesOperationsAdded operation group VideoAnalyzerOperationResultsOperationsBreaking changesParameter id of model StorageAccount is now requiredOperation EdgeModulesOperations.list has a new signatureOperation EdgeModulesOperations.list has a new signatureModel VideoFlags no longer has parameter is_recordingModel VideoFlags has a new required parameter is_in_useModel VideoEntity no longer has parameter streamingRemoved operation VideoAnalyzersOperations.create_or_updateRemoved operation VideoAnalyzersOperations.updateRemoved operation VideoAnalyzersOperations.sync_storage_keysRemoved operation VideosOperations.list_streaming_token1.0.0b2 (2021-05-24)Update README.md1.0.0b1 (2021-05-11)Initial Release
Package: azure-mgmt-vmwarecloudsimple
Microsoft Azure SDK for PythonThis is the Microsoft Azure MyService Management Client Library.Azure Resource Manager (ARM) is the next generation of management APIs that
replace the old Azure Service Management (ASM).This package has been tested with Python 2.7, 3.5, 3.6 and 3.7.For the older Azure Service Management (ASM) libraries, seeazure-servicemanagement-legacylibrary.For a more complete set of Azure libraries, see theazurebundle package.UsageFor code examples, seeMyService Managementon docs.microsoft.com.Provide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History0.2.0 (2019-10-31)FeaturesModel VirtualNic has a new parameter customizationModel VirtualMachine has a new parameter customizationAdded operation group CustomizationPoliciesOperations0.1.0 (2019-10-08)Initial Release
Package: azure-mgmt-voiceservices
Microsoft Azure SDK for PythonThis is the Microsoft Azure Voiceservices Management Client Library.
This package has been tested with Python 3.7+.
For a more complete view of Azure libraries, see theazure sdk python release.DisclaimerAzure SDK Python packages support for Python 2.7 has ended 01 January 2022. For more information and questions, please refer tohttps://github.com/Azure/azure-sdk-for-python/issues/20691Getting startedPrerequisitesPython 3.7+ is required to use this package.Azure subscriptionInstall the packagepipinstallazure-mgmt-voiceservices
pipinstallazure-identityAuthenticationBy default,Azure Active Directorytoken authentication depends on correct configure of following environment variables.AZURE_CLIENT_IDfor Azure client ID.AZURE_TENANT_IDfor Azure tenant ID.AZURE_CLIENT_SECRETfor Azure client secret.In addition, Azure subscription ID can be configured via environment variableAZURE_SUBSCRIPTION_ID.With above configuration, client can be authenticated by following code:fromazure.identityimportDefaultAzureCredentialfromazure.mgmt.voiceservicesimportVoiceServicesMgmtClientimportossub_id=os.getenv("AZURE_SUBSCRIPTION_ID")client=VoiceServicesMgmtClient(credential=DefaultAzureCredential(),subscription_id=sub_id)ExamplesCode samples for this package can be found at:Search Voiceservices Managementon docs.microsoft.comAzure Python Mgmt SDK Samples RepoTroubleshootingNext stepsProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History1.0.0 (2023-05-19)other changeFirst GA1.0.0b1 (2023-02-20)Initial Release
Package: azure-mgmt-webpubsub
Microsoft Azure SDK for PythonThis is the Microsoft Azure WebPubSub Management Client Library.
This package has been tested with Python 3.7+.
For a more complete view of Azure libraries, see theazure sdk python release.DisclaimerAzure SDK Python packages support for Python 2.7 has ended 01 January 2022. For more information and questions, please refer tohttps://github.com/Azure/azure-sdk-for-python/issues/20691Getting startedPrerequisitesPython 3.7+ is required to use this package.Azure subscriptionInstall the packagepipinstallazure-mgmt-webpubsub
pipinstallazure-identityAuthenticationBy default,Azure Active Directorytoken authentication depends on correct configure of following environment variables.AZURE_CLIENT_IDfor Azure client ID.AZURE_TENANT_IDfor Azure tenant ID.AZURE_CLIENT_SECRETfor Azure client secret.In addition, Azure subscription ID can be configured via environment variableAZURE_SUBSCRIPTION_ID.With above configuration, client can be authenticated by following code:fromazure.identityimportDefaultAzureCredentialfromazure.mgmt.webpubsubimportWebPubSubManagementClientimportossub_id=os.getenv("AZURE_SUBSCRIPTION_ID")client=WebPubSubManagementClient(credential=DefaultAzureCredential(),subscription_id=sub_id)ExamplesCode samples for this package can be found atWebPubSub Managementon docs.microsoft.com andSamples RepoTroubleshootingNext stepsProvide FeedbackIf you encounter any bugs or have suggestions, please file an issue in theIssuessection of the project.Release History1.1.0 (2023-03-20)Features AddedAdded operation group WebPubSubCustomCertificatesOperationsAdded operation group WebPubSubCustomDomainsOperationsModel WebPubSubHubProperties has a new parameter event_listeners1.1.0b1 (2022-11-02)Features AddedAdded operation group WebPubSubCustomCertificatesOperationsAdded operation group WebPubSubCustomDomainsOperationsModel WebPubSubHubProperties has a new parameter event_listeners1.0.0 (2021-10-11)FeaturesModel PrivateEndpointConnection has a new parameter group_idsModel WebPubSubResource has a new parameter host_name_prefixModel WebPubSubResource has a new parameter disable_local_authModel WebPubSubResource has a new parameter resource_log_configurationModel WebPubSubResource has a new parameter live_trace_configurationModel WebPubSubResource has a new parameter disable_aad_authAdded operation WebPubSubOperations.list_skusAdded operation group WebPubSubHubsOperationsBreaking changesModel WebPubSubResource no longer has parameter featuresModel WebPubSubResource no longer has parameter event_handler1.0.0b1 (2021-04-16)Initial Release
Package: azure-mgmt-workloadmonitor
The package has been deprecated. For more info, please seehttps://github.com/azure-deprecation/dashboard/issues/239Release History1.0.0b4 (2022-11-29)Other ChangesDeprecated this package. For more info, please seehttps://github.com/azure-deprecation/dashboard/issues/2391.0.0b3 (2022-10-27)Other ChangesAdded generated samples in github repoDrop support for python<3.7.01.0.0b2 (2020-11-09)FeaturesAdded operation group HealthMonitorsOperationsBreaking changesRemoved operation group MonitorsOperations1.0.0b1 (2020-10-29)Initial Release
Package: azureml-accel-models
Easily create and train a model using various deep neural networks (DNNs) as a featurizer for deployment to Azure or a Data Box Edge device for ultra-low latency inference. These models are currently available:ResNet 50ResNet 152DenseNet-121VGG-16SSD-VGGSetupFollow theseinstructionsto install the Azure ML SDK on your local machine, create an Azure ML workspace, and set up your notebook environment, which is required for the next step.Once you have set up your environment, install the Azure ML Accel Models SDK:pipinstallazureml-accel-modelsNote:*This package requires you to install tensorflow >= 1.6. This can be done using:pipinstallazureml-accel-models[cpu]If your machine supports GPU, then you can leverage the tensorflow-gpu functionality using:pipinstallazureml-accel-models[gpu]AzureML-Accel-ModelsCreate a featurizer using the Accelerated ModelsConvert tensorflow model to ONNX format using AccelOnnxConverterCreate a container image with AccelContainerImage for deploying to either Azure or Data Box EdgeUse the sample PredictionClient for inference on a Accelerated Model Host or create your own GRPC clientResourcesRead more about FPGAs.
Package: azureml-contrib-notebook
This is a preview feature for AzureML Python SDK that allows you to submit jupyter notebook as a run.To get started with AzureML Python SDK follow theseinstructionsPlease install azureml-contrib-notebook to submit jupyter notebook as a run:pipinstallazureml-contrib-notebookFor local run please install papermill package, along with nbconvert:pipinstall"papermill<2""nbconvert<6"To enable metrics update from local run in user managed environment please install nteract-scrapbook package:pipinstallnteract-scrapbook
Package: azureml-contrib-opendatasets
This package provides a set of APIs to consume Azure Open Datasets.In general, it allows users to turn the open datasets into both SPARK and Pandas dataframe,
with filters that are commonly applied to each specific dataset.For some of the open datasets, it provides enricher capability to join with other data. For example,
you can join your data with weather data by lat/long/zipcode + time quite easily.This package also contains open datasets with the following third-party notices.[1]:ftp://ftp.ncdc.noaa.gov/pub/data/noaa/readme.txt[2]:https://www.ncei.noaa.gov/thredds/catalog/gfs-004-files/catalog.html?dataset=gfs-g4-files[3]:http://opendefinition.org/licenses/odc-pddl/[4]:https://data.seattle.gov/stories/s/Data-Policy/6ukr-wvup/[5]:https://datasf.org/opendata/terms-of-use/[6]:https://www.chicago.gov/city/en/narr/foia/data_disclaimer.html[7]:https://www1.nyc.gov/home/terms-of-use.page
Package: azureml-contrib-pipeline-steps
NoteThis package has been deprecated and moved toazureml-pipeline-steps. Please refer to thisdocumentationfor more information.Azure Machine Learning Batch InferenceAzure Machine Learning Batch Inference targets large inference jobs that are not time-sensitive. Batch Inference provides cost-effective inference compute scaling, with unparalleled throughput for asynchronous applications. It is optimized for high-throughput, fire-and-forget inference over large collections of data.Getting Started with Batch Inference Public PreviewBatch inference public preview offers a platform in which to do large inference or generic parallel map-style operations. Please visitAzure Machine Learning Notebooksto find tutorials on how to leverage this service.
Package: azureml-contrib-server
The azureml-contrib-server is local HTTP service used to expose a subset of the functionality provided by the AzureML SDK to VS Tools for AI extensions (VSCode and Visual Studio) and includes the following:Utility methods that glues together the AML SDK and the REST API.HTTP server that offers part of AML SDK functionality.SetupInstall AzureML Contrib Server package:pipinstallazureml-contrib-server
Package: azureml-core
The azureml-core provides core packages, modules, and classes for Azure Machine Learning and includes the following:Creating/managing workspaces and experiments, and submitting/accessing model runs and run output/logging.Creating/managing Machine learning compute targets and resourcesModels, images and web services.Modules supporting data representation for Datastore and Dataset in Azure Machine Learning.Azure Machine Learning exception classes.Module used internally to prepare the Azure ML SDK for remote environments.SetupFollow theseinstructionsto install the Azure ML SDK on your local machine, create an Azure ML workspace, and set up your notebook environment, which is required for the next step.Once you have set up your environment, install the Azure ML core package:pipinstallazureml-core
Package: azureml-dataprep-rslex
Azure Machine Learning Data Prep RsLexAzure Machine Learning Data Prep RsLex is a Rust implementation of Data Prep's capabilities to load, transform, and write data for machine learning workflows.
You can interact with RsLex via the Data Prep SDK,azureml-dataprep, by callinguse_rust_execution(True)before using the SDK.Install the SDKTo install Azure Machine Learning Data Prep RsLex, use the following command:pipinstall--upgradeazureml-dataprep-rslexNOTE: This package is not intended for direct installation or usage.azureml-dataprepdepends on this package.
Package: azureml-featurestore
# Azure Machine Learning Feature Store Python SDKTheazureml-featurestorepackage is the core SDK interface for Azure ML Feature Store. This SDK works along theazure-ai-mlSDK to provide the managed feature store experience.## Main features in theazureml-featurestorepackage
- Develop feature set specification in Spark with the ability for feature transformation.
- List and get feature sets defined in Azure ML Feature Store.
- Generate and resolve feature retrieval specification.
- Run offline feature retrieval with point-in-time join.## Getting startedYou can install the package via ` pip install azureml-featurestore `To learn more about Azure ML managed feature store visithttps://aka.ms/featurestore-get-started# Change Log## 1.0.0 (2023.11.14)
- [GA] Custom feature source: Custom feature source supports customized source process code script with a user defined dictionary as input.
- [GA] International regions and sovereign cloud support.
- [GA] Offline backfill materialization now replaces all data within a feature window instead of doing upsert based on timestamp.
- [GA] Added bootstrap option for materialization, which enables materializing data from offline store into online store.
- Re-enabling materialization in a feature set now invalidates all previously materialized data.
- Feature set spec dump now accepts a file path or a folder path as dump target, and an overwrite option to control whether to override the target.
- Various bug fixes## 0.1.0b6 (2023.11.1)Various bug fixes## 0.1.0b5 (2023.10.4)Various bug fixes## 0.1.0b4 (2023.08.28)New Features:[Public preview] Added custom feature source. Custom feature source supports customized source process code script with a user defined dictionary as input.[Public preview] Added csv feature source, deltatable feature source, mltable feature source, parquet feature source as new feature source experience. Previous feature source usage compatibility will be deprecated in 6 months.Bug fixesBreaking changes:- Movedinit_online_lookup,shutdown_online_lookupandget_online_featuresout of FeatureStoreClient, and into the module as standalone functions.
-get_online_featurescontract changed from accepting (for theobservation_dataargument) and returningpandas.DataFrameto accepting (as theobservation_dataargument) and returningpyarrow.Table.Other changes:- Moved online feature store support into public preview.## 0.1.0b3 (2023.07.10)Various bug fixes## 0.1.0b2 (2023.06.13)New Features:[Private preview] Added online store support. Online store supports materialization and online feature values retrieval from Redis cache for batch scoring.Various bug fixes## 0.1.0b1 (2023.05.15)New Features:Initial release.