Release v0.12.0

CHANGELOG.md

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 # Version changelog
 
+## 0.12.0
+
+* Added method to detect rows are written to the `MockBackend` ([#292](https://github.com/databrickslabs/lsql/issues/292)). In this commit, the `MockBackend` class in the 'backends.py' file has been updated with a new method, 'has_rows_written_for', which allows for differentiation between a table that has never been written to and one with zero rows. This method checks if a specific table has been written to by iterating over the table stubs in the `_save_table` attribute and returning `True` if the given full name matches any of the stub full names. Additionally, the class has been supplemented with the `rows_written_for` method, which takes a table name and mode as input and returns a list of rows written to that table in the given mode. Furthermore, several new test cases have been added to test the functionality of the `MockBackend` class, including checking if the `has_rows_written_for` method correctly identifies when there are no rows written, when there are zero rows written, and when rows are written after the first and second write operations. These changes improve the overall testing coverage of the project and aid in testing the functionality of the `MockBackend` class. The new methods are accompanied by documentation strings that explain their purpose and functionality.
+
+
 ## 0.11.0
 
 * Added filter spec implementation ([#276](https://github.com/databrickslabs/lsql/issues/276)). In this commit, a new `FilterHandler` class has been introduced to handle filter files with the suffix `.filter.json`, which can parse filter specifications in the header of the filter file and validate the filter columns and types. The commit also adds support for three types of filters: `DATE_RANGE_PICKER`, `MULTI_SELECT`, and `DROPDOWN`, which can be linked with multiple visualization widgets. Additionally, a `FilterTile` class has been added to the `Tile` class, which represents a filter tile in the dashboard and includes methods to validate the tile, create widgets, and generate filter encodings and queries. The `DashboardMetadata` class has been updated to include a new method `get_datasets()` to retrieve the datasets for the dashboard. These changes enhance the functionality of the dashboard by adding support for filtering data using various filter types and linking them with multiple visualization widgets, improving the customization and interactivity of the dashboard, and making it more user-friendly and efficient.

src/databricks/labs/lsql/__about__.py

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-__version__ = "0.11.0"
+__version__ = "0.12.0"