evidi-fabric 0.1.11

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Introduction

This repo tracks the evidi_fabric package which is intended to collect useful helper when working with fabric

Build and Test

poetry build
poetry config repositories.evidi_fabric https://pkgs.dev.azure.com/cloud-agility/5a74dae0-b39a-4e4d-85cf-bf150f827302/_packaging/evidi_fabric/pypi/upload/

Generate a Personal Access Token in Azure DevOps and use it here

poetry config http-basic.evidi_fabric INITIALS PAT

where INITIALS can be anything and PAT is your new token. You need to have Contributor access to the python_packages feed.

poetry publish --repository evidi_fabric

Make sure to bump the version number for each publish. Consider using release candidates when testing stuff e.g.

0.0.3
0.1.0-alpha.0
0.1.0-alpha.1
...
0.1.0

This can be semi-automated with poetry by using these commands:

poetry version prerelease

and

poetry version patch

In this case the first command will create a new prerelease version for a patch update. You can run the first command several times while you iterate your fixes. Once you are satisfied you can run poetry version patch to make a new patch release. Then when you merge to master this release will be automatically published to inspari-ai pypi feed.

Note that you cannot upload the same package version twice. Thus you need to bump some part of the version everytime you want to publish. The suggested workflow is that prereleases are published manually while "production" releases are only done by the pipeline to make sure that master branch and latest published version tracks each other.

See the docs for details. See also the possible improvement.

For fast patch, build and publish, you can use the following command:

poetry version patch && poetry build && poetry publish --repository evidi_fabric

The same as the above, but publishing the packge directly to PyPi (hence open source!)

poetry version patch && poetry build && python3 -m twine upload dist/*

To upgrade your local repositories with the latest version of the package with pip, run:

pip install --upgrade evidi_fabric