v0.3.0

• Added automated upgrade framework (#50). This update introduces an automated upgrade framework for managing and applying upgrades to the product, with a new upgrades.py file that includes a ProductInfo class having methods for version handling, wheel building, and exception handling. The test code organization has been improved, and new test cases, functions, and a directory structure for fixtures and unit tests have been added for the upgrades functionality. The test_wheels.py file now checks the version of the Databricks SDK and handles cases where the version marker is missing or does not contain the __version__ variable. Additionally, a new Application State Migrations section has been added to the README, explaining the process of seamless upgrades from version X to version Z through version Y, addressing the need for configuration or database state migrations as the application evolves. Users can apply these upgrades by following an idiomatic usage pattern involving several classes and functions. Furthermore, improvements have been made to the _trim_leading_whitespace function in the commands.py file of the databricks.labs.blueprint module, ensuring accurate and consistent removal of leading whitespace for each line in the command string, leading to better overall functionality and maintainability.
• Added brute-forcing SerdeError with as_dict() and from_dict() (#58). This commit introduces a brute-forcing approach for handling SerdeError using as_dict() and from_dict() methods in an open-source library. The new SomePolicy class demonstrates the usage of these methods for manual serialization and deserialization of custom classes. The as_dict() method returns a dictionary representation of the class instance, and the from_dict() method, decorated with @classmethod, creates a new instance from the provided dictionary. Additionally, the GitHub Actions workflow for acceptance tests has been updated to include the ready_for_review event type, ensuring that tests run not only for opened and synchronized pull requests but also when marked as "ready for review." These changes provide developers with more control over the deserialization process and facilitate debugging in cases where default deserialization fails, but should be used judiciously to avoid brittle code.
• Fixed nightly integration tests run as service principals (#52). In this release, we have enhanced the compatibility of our codebase with service principals, particularly in the context of nightly integration tests. The Installation class in the databricks.labs.blueprint.installation module has been refactored, deprecating the current method and introducing two new methods: assume_global and assume_user_home. These methods enable users to install and manage blueprint as either a global or user-specific installation. Additionally, the existing method has been updated to work with the new Installation methods. In the test suite, the test_installation.py file has been updated to correctly detect global and user-specific installations when running as a service principal. These changes improve the testability and functionality of our software, ensuring seamless operation with service principals during nightly integration tests.
• Made test_existing_installations_are_detected more resilient (#51). In this release, we have added a new test function test_existing_installations_are_detected that checks if existing installations are correctly detected and retries the test for up to 15 seconds if they are not. This improves the reliability of the test by making it more resilient to potential intermittent failures. We have also added an import from databricks.sdk.retries named retried which is used to retry the test function in case of an AssertionError. Additionally, the test function test_existing has been renamed to test_existing_installations_are_detected and the xfail marker has been removed. We have also renamed the test function test_dataclass to test_loading_dataclass_from_installation for better clarity. This change will help ensure that the library is correctly detecting existing installations and improve the overall quality of the codebase.

Contributors: @nfx

v0.2.5

• Automatically enable workspace filesystem if the feature is disabled (#42).

Contributors: @pritishpai

v0.2.4

• Added more integration tests for Installation (#39).
• Fixed yaml optional import error (#38).

Contributors: @nfx

v0.2.3

• Added special handling for notebooks in Installation.upload(...) (#36).

Contributors: @nfx

v0.2.2

• Fixed issues with uploading wheels to DBFS and loading a non-existing install state (#34).

Contributors: @nfx

v0.2.1

• Aligned Installation framework with UCX project (#32).

Contributors: @nfx

v0.2.0

• Added common install state primitives with strong typing (#27).
• Added documentation for Invoking Databricks Connect (#28).
• Added more documentation for Databricks CLI command router (#30).
• Enforced pylint standards (#29).

Contributors: @nfx, @sundarshankar89

v0.1.0

• Changed python requirement from 3.10.6 to 3.10 (#25).

Contributors: @ggwiebe

v0.0.6

• Make find_project_root more deterministic (#23).

Contributors: @nfx

v0.0.5

• Make it work with ucx (#21).

Contributors: @nfx