Saravanan666/pypi-org huggingface dataset:
Package: azure-core-experimental
Azure Core Experimental client library for PythonAzure Core Experimental client library provides experimental features that are not ready for stable release. The main reason might be because the feature depends on some other packages that there is no stable version available yet. If its dependant package introduces breaking changes, the features maybe break. It is not recommended to use azure core experimental library in production environment.Getting startedInstall the azure core experimental package withpip:pipinstallazure-core-experimentalFeatures listpyodide transporthttpx transportContributingThis project welcomes contributions and suggestions.  Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visithttps://cla.microsoft.com.When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct. For more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.Release History1.0.0b4 (2023-08-03)Bugs FixedCreate new httpx client when used without "with" (#31362)Fix httpx sample with right API name1.0.0b3 (2023-07-06)Bug FixesUpdate httpx transport to handle timeout and connection verify kwargs fromazure.core.pipeline.transport.HttpRequest.Add a read override forreadfor clients usingazure.core.rest.HttpResponseto get the response body.1.0.0b2 (2023-04-06)Features Addedhttpx implementation of azure-core transport protocol1.0.0b1 (2022-10-06)Initial releaseFeatures Addedpyodide implementation of azure-core transport protocol
Package: azure-core-tracing-opencensus
Azure Core Tracing OpenCensus client library for PythonGetting startedInstall the opencensus python for Python withpip:pipinstallazure-core-tracing-opencensus--preNow you can use opencensus for Python as usual with any SDKs that is compatible
with azure-core tracing. This includes (not exhaustive list), azure-storage-blob, azure-keyvault-secrets, azure-eventhub, etc.Key conceptsYou don't need to pass any context, SDK will get it for youThe opencensus threading plugin is installed with this packageExamplesThere is no explicit context to pass, you just create your usual opencensus and tracer and
call any SDK code that is compatible with azure-core tracing. This is an example
using Azure Monitor exporter, but you can use any exporter (Zipkin, etc.).fromopencensus.ext.azure.trace_exporterimportAzureExporterfromopencensus.trace.tracerimportTracerfromopencensus.trace.samplersimportAlwaysOnSamplerfromazure.storage.blobimportBlobServiceClientexporter=AzureExporter(instrumentation_key="uuid of the instrumentation key (see your Azure Monitor account)")tracer=Tracer(exporter=exporter,sampler=AlwaysOnSampler())withtracer.span(name="MyApplication")asspan:client=BlobServiceClient.from_connection_string('connectionstring')client.delete_container('my_container')# Call will be tracedTroubleshootingThis client raises exceptions defined inAzure Core.Next stepsMore documentation on OpenCensus configuration can be found on theOpenCensus websiteContributingThis project welcomes contributions and suggestions.  Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visithttps://cla.microsoft.com.When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct. For more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.Release History1.0.0b9 (2023-05-09)Bugs FixedFixed a bug where starting a span would fail if an unexpected keyword argument was passed in toOpenCensusSpan.Other ChangesPython 2.7 is no longer supported. Please use Python version 3.7 or later.1.0.0b8 (2021-07-01)Fix for supportingkindkeyword while instantiating the span.1.0.0b7 (2021-04-08)LinkandSpanKindcan now be added while creating the span instance.1.0.0b6 (2020-05-04)linkandlink_from_headersnow accept attributes.1.0.0b5 (2020-01-14)BugfixFix context passing for multi-threadingDon't fail on unknown span type, but maps to PRODUCER or UNSPECIFIEDFeaturesImplement new "change_context" API1.0.0b4 (2019-10-07)FeaturesOpencensus implementation of azure-core tracing protocol
Package: azure-cosmosdb-table
Microsoft Azure CosmosDB Table SDK for PythonThis project provides a client library in Python that makes it easy to
consume Microsoft Azure CosmosDB Table services. For documentation please see
the Microsoft AzurePython Developer Centerand ourAPI ReferencePage.If you are looking for the Service Bus or Azure Management
libraries, please visithttps://github.com/Azure/azure-sdk-for-python.CompatibilityIMPORTANT: If you have an earlier version of the azure package
(version < 1.0), you should uninstall it before installing this package.You can check the version using pip:pipfreezeIf you see azure==0.11.0 (or any version below 1.0), uninstall it first then install it again:pipuninstallazurepipinstallazureFeaturesTableCreate/Read/Update/Delete TablesCreate/Read/Update/Delete EntitiesBatch operationsAdvanced Table OperationsGetting StartedDownloadOption 1: Via PyPiTo install via the Python Package Index (PyPI), type:pip install azure-cosmosdb-tableOption 2: Source Via GitTo get the source code of the SDK via git just type:git clone git://github.com/Azure/azure-cosmosdb-python.git
cd ./azure-cosmosdb-table
python setup.py installOption 3: Source ZipDownload a zip of the code via GitHub or PyPi. Then, type:cd ./azure-cosmosdb-table
python setup.py installMinimum RequirementsPython 2.7, 3.3, 3.4, 3.5, or 3.6.See setup.py for dependenciesUsageTo use this SDK to call Microsoft Azure storage services, you need to
firstcreate an account.Code SampleSee the samples directory for table usage samples.Need Help?Be sure to check out the Microsoft AzureDeveloper Forums on MSDNor
theDeveloper Forums on Stack Overflowif you have trouble with the
provided code.Contribute Code or Provide FeedbackIf you would like to become an active contributor to this project, please
follow the instructions provided inAzure Projects Contribution
Guidelines. You can find more details for contributing in theCONTRIBUTING.md doc.If you encounter any bugs with the library, please file an issue in theIssuessection of the project.Learn MorePython Developer CenterAzure Storage ServiceAzure Storage Team BlogAPI Reference
Package: azurecost
azurecostSimple and easy command line to view azure costs.Support python3 only.SettingsazloginExamplesshow cost monthly$azurecost-smy-subscription
key2023-082023-09
------------------------------------
total492.7780.28
CognitiveServices492.7780.28
Bandwidth00Storage00You can omit the -s by specifying the environment variable AZURE_SUBSCRIPTION_ID.$exportAZURE_SUBSCRIPTION_ID=xxxxxxxxxxxxxxxxxxxxxxxxxxxxx
$exportAZURE_RESOURCE_GROUP=xxxxxxxxxxxxxxxxxxxxxxxxxxxxx
$azurecost
key2023-082023-09
------------------------------------
total492.7780.28
CognitiveServices492.7780.28
Bandwidth00Storage00show cost (Multiple Dimensions)$ azurecost -s my-subscription -d ResourceGroup -d ServiceName
key                                     2023-08    2023-09
------------------------------------  ---------  ---------
total                                    492.77     426.97
RG-1, Cognitive Services                 281        366
RG-2, Cognitive Services                 211.77      60.97
RG-3, Storage                              0          0
RG-4, Storage                              0          0
RG-5, Storage                              0          0
RG-6, Storage                              0          0
RG-7, Bandwidth                            0          0
RG-7, Storage                              0          0Python APIsubscription="my-subscription"core=Azurecost(False,"MONTHLY",["ServiceName"],subscription_name=subscription,# resource_group="my-rg")total_results,results=core.get_usage(ago=2,)text=core.convert_tabulate(total_results,results)print(text)InstallationpipinstallazurecostCIinstall test package$ ./scripts/ci.sh installtest$ ./scripts/ci.sh run-testflake8 and black and pytest.release pypi$ ./scripts/ci.sh releasegit tag and pypi release.
Package: azure-databricks-api
Azure Databricks API WrapperA Python, object-oriented wrapper for theAzure Databricks REST API 2.0InstallationThis package is pip installable.pipinstallazure-databricks-apiImplemented APIsAs of June 25th, 2020 there are 12 different services available in the Azure Databricks API. Currently, the following services are supported by the Azure Databricks API Wrapper.ClustersCluster Policies(Preview)DBFSGroups(Must be Databricks admin)Instance PoolsJobsLibrariesMLflowSCIM(Preview)SecretsTokenWorkspaceClient InstantiationTo create the client object, you pass the Azure region your workspace is located in and thegenerated Personal Access Tokenfromazure_databricks_apiimportAzureDatabricksRESTClientazure_region='[INSERT YOUR AZURE REGION HERE]'token='[INSERT YOUR PERSONAL ACCESS TOKEN]'client=AzureDatabricksRESTClient(region=azure_region,token=token)Clusters Client UsageThe services above are implemented as children objects of the client. For example, to pin a cluster, you can either pass thecluster_nameorcluster_idto thepin()method:client.clusters.pin(cluster_name='test_cluster_name')The other services are implemented similarly. (e.g.client.tokensorclient.groups)
Package: azure-databricks-sdk-python
Azure Databricks SDK PythonWarningThis project has been archived and is no longer actively maintained or supported. We highly recommend migrating to the official Databricks SDK for Python available athttps://github.com/databricks/databricks-sdk-py.azure-databricks-sdk-pythonis a Python SDK for theAzure Databricks REST API 2.0.Easily, perform all the operations as if on the Databricks UI:fromazure_databricks_sdk_pythonimportClientfromazure_databricks_sdk_python.types.clustersimportAutoScale,ClusterAttributesclient=Client(databricks_instance="<instance>",personal_access_token="<token>")spark_conf={'spark.speculation':True}autoscale=AutoScale(min_workers=0,max_workers=1)attributes=ClusterAttributes(cluster_name="my-cluster",spark_version="7.2.x-scala2.12",node_type_id="Standard_D3_v2",spark_conf=spark_conf,autoscale=autoscale)created=client.clusters.create(attributes)print(created.cluster_id)Beloved Featuresazure-databricks-sdk-pythonis ready for your use-case:Clear standard to access to APIs.Contains custom types for the API results and requests.Support for Personal Access token authentification.Support for Azure AD authentification.Support for the use of Azure AD service principals.Allows free-style API calls with a force mode -(bypass types validation).Error handeling and proxy support.Officially supports 3.6+, and runs great on PyPy.Implementation ProgressPlease refer to the progress below:FeatureProgressAuthentification100% ✔Custom types25%API Wrappers25%Error handling80%Proxy support0%Documentation20%As for specific API wrappers:APIProgressClusters API100% ✔Secrets API100% ✔Token API100% ✔Jobs API0%DBFS API0%Groups API0%Libraries API0%Workspace API0%Clusters Policies API0%Instance Pools API0%MLflow API0%Permissions API0%SCIM API0%Token Management API0%DocumentationCheck the documentation onreadthedocs.org.
Package: azure-data-collector
azure-data-collectorWhat is it?azure-data-collector is a Python client package for uploading events to Azure Monitor/Log Analytics workspace using the data collector api.How do I use it?fromazuredatacollector.datacollectorimportDataCollectorClient# Setup clientclient=DataCollectorClient(WORKSPACE_ID,SHARED_KEY)# Upload data without proxytest_data=[{"col":"row1"},{"col":"row2"},{"col":"row3"}]client.post_data(test_data,"TestLATable")# Upload data with proxyclient.proxies={"http":"http://127.0.0.1:8080"}metric=client.post_data(test_data,"TestLATable")Referencehttps://learn.microsoft.com/en-us/azure/azure-monitor/logs/data-collector-api
Package: azure-data-factory-generator
Ingenii Azure Data Factory GeneratorPython based generator to create Azure Data Factory pipelines from configurations.This package integrates easily with theIngenii Azure Data Platform, but this package can be used independently as long as some required linked services and data sets are created ahead of time. These are detailed in the sections below.Current Version: 0.1.4Package installationInstall the packageusing pipwithpip install azure_data_factory_generatoror, for a particular versionpip install azure_data_factory_generator==0.1.4Alternatively, add it to yourrequirements.txtfile.Use the package by calling it directly with the locations of your config files and the folder that the generated objects should be placed within:python -m azure_data_factory_generator path/to/config/files/folder path/to/generated/files/folderUsing the packageFor details on using the package please refer to theAzure Data Factory Usage documentation.Version History0.1.4: Add object annotations to track what is managed by this package0.1.3: Extend schedule to handle when only the hours of the dayt are specified0.1.2: Change the name of the secret name for the SAS URI to access the config tables0.1.1: Add schedule generation from configuration, many more tests0.1.0: Initial package, FTP/SFTP connections with basic authentication
Package: azure-datalake-utils
Azure Datalake UtilsUtilidades para interactuar con Azure Datalake.El objetivo es evitar que personas denominadas cientificos ciudadanos tengan que interactuar con librerias, que no son, totalmente relacionadas con el analisis de datos.La hipotesis detras de este pensamiento es que se puede lograr incrementar la adopción de estas herramientas si se facilitan y simplifica la interacción de pandas con la lectura del datalake.Documentation:https://centraal-api.github.io/azure-datalake-utilsGitHub:https://github.com/centraal-api/azure-datalake-utilsPyPI:https://pypi.org/project/azure-datalake-utils/Free software: Apache-2.0FeaturesControl de autenticación directamente con el Directorio activo de Azure.Lectura de archivos csv, excel, json y parquet de una forma más concisa.Creación de token SAS para generar URL a un path especifico.Publicar nueva versionSeguirchecklist del template orginal.CreditsLa librería es creada y mantenida porCentraal Studio.Centraal Studio Agredece la alianza conHaceb, cuyos retos internos  de democratizar el acceso a información han motivado la creación de esta librería.//This package is created and mantained byCentraal Studio.Centraal Studio appreciate the alliance withHaceb, which internal efforts to democratize the access of company information has motivated the creation of the library.This package was created withCookiecutterand thewaynerv/cookiecutter-pypackageproject template.
Package: azure-ddns
Azure Dynamic DNSInstallationpip install azure-ddnsRunYou can run the cli tool with all the parameters like thisazure-ddns --subscription-id your_ubscription_id --tenant-id your_tenant_id --client-id your_client_id --client-secret your_client_secret --resource-group your_ressource_group_name --zone your_zone_name --record your_record-nameYou can also use a json fileazure-ddns --config path/to/your/config.jsonThe json should be formated like this:{"subscriptionId":"","resourceGroup":"","zoneName":"","recordName":"","clientId":"","clientSecret":"","tenantId":""}
Package: azure-devops-automation
ADO AutomationIntroductionA collection of automation tools to use in ADO pipelines and webhooksInstallationpip install azure-devops-automationPull Request functionsA sampleyamlfile is included which runschangelogand thencheckinfor the current PR if included in the PR Build validation policieschangelogUpdates (and creates if required) a CHANGELOG markdown file using data from a given Pull Requestpython-mado_automation.PRchangelog--help
usage:ado_automations.PRchangelog[-h]--pathPATH--collectionuriCOLLECTIONURI--projectPROJECT--prPR

options:-h,--helpshowthishelpmessageandexit--pathPATHrelativepathtochangelogfile,includingfilename--collectionuriCOLLECTIONURIbaseuritoADOorganisation--projectPROJECTADOprojectname--prPRpullrequestIDcheckinCommits and pushes any changes made in the detached head state after a PR merge into the PR source branch. Commits with the name and email address of the PR author, pushes as BuildService.python-mado_automation.PRcheckin--help
usage:ado_automations.PRcheckin[-h]--collectionuriCOLLECTIONURI--projectPROJECT--prPR[-v]options:-h,--helpshowthishelpmessageandexit--collectionuriCOLLECTIONURIbaseuritoADOorganisation--projectPROJECTADOprojectname--prPRpullrequestID-v,--verbosityincreaseoutputverbosityBuild and TestTests are written for pytest in/tests/test_*.pyContributeCode repository (ADO)HomepageWhat's New?See CHANGELOGComing NextValidate against complex and edge cases (eg main updated by other working branches since creating source branch)Create setup script to generate yaml templatesadd section markers to CHANGELOG to allow import into READMEAzure-Function to call via Webhook to update parent/children items when changing a work item on ADO Boards
Package: azure-devops-keyring
Note:this package is deprecated in favor ofartifacts-keyring.azure-devops-keyringProvides authentication forAzure DevOpsvia thekeyringlibraryThis is an extension tokeyring, and will automatically be loaded.
Bothpipandtwinewill usekeyringto
find credentials.To install this package:pip install azure-devops-keyringTo use this package throughpiportwine, just provide your repository URL when installing or
uploading to your Azure Artifacts feed.To use this package directly, usetwine.get_credentialand provide your feed URL as the system
requiring credentials. The username is optional, and the name that should be used will be returned.
Package: azure-devops-pyspark
Azure Devops PySpark:  A productive library to extract data from Azure Devops and apply agile metrics.What is it?Azure Devops PySpark is a Python package that provides the most productive way to extract data from Azure Devops and build agile metrics.
It runs on PySpark, enabling all the features the technology makes available.Main FeaturesGet authenticated quickly and simply.All columns of the project are automatically mapped, use the filter_columns method to filter only those you want to form your dataframes with.SparkSession already created in spark variable.Get all your organization's backlogs with the methodbacklog.Get all your organization's items with the methoditems.Get all your organization's iterations with the methoditerations.Get all your organization's members with the methodmembers.Get all your organization's tags with the methodtags.Get all your organization's teams with the methodteams.Explore the simplicity of Agile class to build powerful metrics for your organization.Quick examplefromAzureDevopsPySparkimportAzure,Agilefrompyspark.sql.functionsimportdatediff#use in agile metricsdevops=Azure('ORGANIZATION','PROJECT','PERSONAL ACCESS TOKENS')## Filter columnsdevops.filter_columns(['IterationPath','Id','State','WorkItemType','CreatedDate','ClosedDate','Iteration_Start_Date','Iteration_End_Date'])## Pyspark Dataframedf_backlog=devops.backlog()df_items=devops.items()df_iterations=devops.iterations()df_members=devops.members()df_tags=devops.tags()df_teams=devops.teams()## Agile Metricsagile=Agile()## A new dataframedf_agil=df.items.join(df_iterations,'IterationPath')## Metrics## Average time between CreatedDate and ClosedDate of items in the last 90 days.lead_time=agile.avg(df=df_agil,ref=[datediff,'ClosedDate','CreatedDate'],# The day difference between the CreatedDate and ClosedDate of each item.iteration_path='IterationPath',# GroupBy.new='LeadTimeDays',# New column name.literal_filter=['ClosedDate >= 90'],# Filtering items from the last 90 days.filters={'WorkItemType':'Task','State':'Closed'}# Custom filters for metric.).dfAuthorThe Azure-Devops-PySpark library was written by Guilherme Silva <https://www.linkedin.com/in/gusantosdev/> in 2022.https://github.com/gusantos1/Azure-Devops-SparkLicenseGNU General Public License v3.0.
Package: azuredevopsX
DevopsXGeneral InformationSoftware:DevopsXAuthor:Paulo Sérgio dos Santos JúniorAuthor's e-mail:paulossjunior@gmail.comSource Repository:https://gitlab.com/immigrant-data-driven-development/libs/application/azuredevopsGoalDevOps é um produto da Microsoft que fornece controle de versão, relatórios, gerenciamento de requisitos, gerenciamento de projetos, compilações automatizadas, gerenciamento de laboratório, recursos de gerenciamento de testes e versões.DocumentationThe Documentation can be found in thislinkGenerate documentationTo create the code documentation:pdoc--html--forceazuredevopsX/--outputdocsAcess code documentationTo accesss the documenation, go to folder docs/devopsX and open index.htmlInstalationTo install devopsX, run this command in your terminal:pipinstallazuredevopsXUsagefromazuredevopsXimportfactoriesfrompprintimportpprintorganization_url="<DEVOPS URL>"personal_access_token="<personal code access>"project_service=factories.ProjectFactory(personal_access_token=personal_access_token,organization_url=organization_url)projects=project_service.get_projects()forprojectinprojects:pprint(project.__dict__)
Package: azure-devtools
Development tools for Python-based Azure toolsThis package contains tools to aid in developing Python-based Azure code.This includes the following components:scenario_testsA testing framework to handle much of the busywork
associated with testing code that interacts with Azure.ci_toolsSome tooling to help developing CI tools. This includes some Git helpers,
Github RestAPI wrapper and a Bot framework for Github issues.ContributingThis project has adopted theMicrosoft Open Source Code of Conduct.
For more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.
Package: azure-digitaltwins-nspkg
# Microsoft Azure SDK for PythonThis is the Microsoft Azure Digitaltwins namespace package. It isn’t intended to
be installed directly. Digitaltwins client libraries are located elsewhere:
- [azure-digitaltwins-core](https://pypi.org/project/azure-digitaltwins-core)This package is for Python 2 only. It provides the necessary files for other
packages to extend theazurenamespace. Python 3.x libraries use
[PEP420](https://www.python.org/dev/peps/pep-0420/) instead.
Package: azuredlock
# azuredlockazure + redlock onboarding script.This is mainly just a wrapper around theaz cliwhich is a dependency.The quickest path is to do apip install azuredlockand then
runazuredlock onboardfrom the Azure Cloud Shell which is in the
Azure Portal since it already has the cli and uses a form of
Managed Identities so you don’t even have to login for it to work.## Install in Azure Cloud ShellUse thebashshellRunpip install –user azuredlockPut the newly installed command in your path:export PATH=$PATH:~/.local/binRunazuredlockto see help commands orazuredlock onboard –help