Metadata-Version: 2.1
Name: projetaai-azure
Version: 0.1.0b0
Summary: Enables Azure services integration with ProjetaAi/Kedro
License: Apache
Author: Ipiranga
Requires-Python: >=3.9,<3.10
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: Jinja2 (>=3.1.2,<4.0.0)
Requires-Dist: PyYAML (>=6.0,<7.0)
Requires-Dist: adlfs (>=2022.9.1,<2023.0.0)
Requires-Dist: azure-ai-ml (==0.1.0b4)
Requires-Dist: azure-cli (==2.36.0)
Requires-Dist: azureml-core (==1.45.0)
Requires-Dist: azureml-pipeline-core (==1.45.0)
Requires-Dist: click (>=8.1.3,<9.0.0)
Requires-Dist: kedro (>=0.18.2,<0.19.0)
Requires-Dist: kedro-projetaai (==0.1.0b1)
Requires-Dist: pandas (>=1.3,<2.0)
Requires-Dist: pyarrow (>=9.0.0,<10.0.0)
Requires-Dist: pywin32 (>=304,<305); platform_system == "Windows"
Requires-Dist: requirements-parser (>=0.5.0,<0.6.0)
Requires-Dist: tomli (>=2.0.1,<3.0.0)
Requires-Dist: typing-extensions (>=4.3.0,<5.0.0)
Requires-Dist: universal-pathlib (>=0.0.20,<0.0.21)
Description-Content-Type: text/markdown

# ProjetaAi Azure
ProjetaAi plugin to enable Kedro integration with Azure services.

## Wip

- Credential assignment
- Batch endpoint
- Realtime endpoint

## Usable

- Blob Gen2 credential registration: `kedro credential create azure`
    - Datastore credential retrivial when running a pipeline in AzureML
- Pipeline conversion: `kedro pipeline create azure`
    - Environment creation (gets updated automatically)
    - Drafts gets updated too
- Scheduling (weekly): `kedro pipeline azure schedule`
    - Requires pipeline to be published
    - Updates current schedule if exists
- Draft publishing: `kedro pipeline azure publish`
    - Updates endpoint default pipeline after first call
    - Forwards schedules if current published exists

> Use `--help` with any of these commands in order to know what arguments are required

