Implement Azure ML Service tasks #1590
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Here I am, brain the size of a planet and they ask me to welcome you to Prefect. So, welcome to the community @frsann! 🎉 🎉 |
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| - datastore_name (str, optional): The name of the datastore. If not defined, the container name will be used. | ||
| - create_container_if_not_exists (bool, optional): Create a container, if one does not exist with the given name. | ||
| - overwrite_existing_datastore (bool, optional): Overwrite an existing datastore. If the datastore does not exist, it will be created. | ||
| - azure_credentials_secret (str, optinonal): The name of the Prefect Secret that stores your Azure credentials; this Secret must be a JSON string with two keys: `ACCOUNT_NAME` and `ACCOUNT_KEY` |
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What's the background behind this being the only task that requires azure credentials?
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The authentication to the Azure ML service is done through the Workspace-object.
In the case you point out, we are registering/linking a Blob Container to the Workspace, and the we're authenticating to the Blob storage, not the Workspace.
The authentication in Blob storage is different from Azure ML service (and managing resources in Azure more generally). See this Jupypter notebook for an example.
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Okay that makes a lot more sense, thanks for explaining and linking the notebook!
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@frsann It seems like your commits aren't linked to you as a user (https://help.github.com/en/articles/why-are-my-commits-linked-to-the-wrong-user#commits-are-not-linked-to-any-user) and show up as the grey Octocat. Would you like to adjust that and reopen this PR? |
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I'm going to merge this now so that it goes out in the next release! |
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@joshmeek Thanks for the heads up! I definitely want my GitHub points! 😄 Fixed the problem by linking my other email to my Github account. |
UI: Use a button to add filters rather than automatically adding new rows
Thanks for contributing to Prefect!
Please describe your work and make sure your PR:
CHANGELOG.md(if appropriate)docs/outline.tomlfor API reference docs (if appropriate)Note that your PR will not be reviewed unless all three boxes are checked.
What does this PR change?
It adds tasks to work with Azure Machine Learning Service, and more specifically Datasets and Datastores.
Why is this PR important?
Helps Azure ML service users to register and update datastore and datasets from Prefect.