Update RELEASE.md

kedro-datasets/RELEASE.md

@@ -1,9 +1,13 @@
 # Upcoming Release:
 
 ## Major features and improvements
-* Added automatic inference of file format for `pillow.ImageDataSet` to be passed to `save()`
+* Implemented lazy loading of dataset subpackages and classes.
+    * Suppose that SQLAlchemy, a Python SQL toolkit, is installed in your Python environment. With this change, the SQLAlchemy library will not be loaded (for `pandas.SQLQueryDataSet` or `pandas.SQLTableDataSet`) if you load a different pandas dataset (e.g. `pandas.CSVDataSet`).
+* Added automatic inference of file format for `pillow.ImageDataSet` to be passed to `save()`.
 
 ## Bug fixes and other changes
+* Improved error messages for missing dataset dependencies.
+    * Suppose that SQLAlchemy, a Python SQL toolkit, is not installed in your Python environment. Previously, `from kedro_datasets.pandas import SQLQueryDataSet` or `from kedro_datasets.pandas import SQLTableDataSet` would result in `ImportError: cannot import name 'SQLTableDataSet' from 'kedro_datasets.pandas'`. Now, the same imports raise the more helpful and intuitive `ModuleNotFoundError: No module named 'sqlalchemy'`.
 
 ## Community contributions
 Many thanks to the following Kedroids for contributing PRs to this release:
@@ -12,7 +16,7 @@ Many thanks to the following Kedroids for contributing PRs to this release:
 
 # Release 1.4.2
 ## Bug fixes and other changes
-* Fixed documentations of `GeoJSONDataSet` and `SparkStreamingDataSet`
+* Fixed documentations of `GeoJSONDataSet` and `SparkStreamingDataSet`.
 * Fixed problematic docstrings causing Read the Docs builds on Kedro to fail.
 
 # Release 1.4.1:
@@ -32,16 +36,16 @@ Many thanks to the following Kedroids for contributing PRs to this release:
 ## Major features and improvements
 * Added pandas 2.0 support.
 * Added SQLAlchemy 2.0 support (and dropped support for versions below 1.4).
-* Added a save method to the APIDataSet
+* Added a save method to `APIDataSet`.
 * Reduced constructor arguments for `APIDataSet` by replacing most arguments with a single constructor argument `load_args`. This makes it more consistent with other Kedro DataSets and the underlying `requests` API, and automatically enables the full configuration domain: stream, certificates, proxies, and more.
-* Relaxed Kedro version pin to `>=0.16`
+* Relaxed Kedro version pin to `>=0.16`.
 * Added `metadata` attribute to all existing datasets. This is ignored by Kedro, but may be consumed by users or external plugins.
 * Added `ManagedTableDataSet` for managed delta tables on Databricks.
 
 ## Bug fixes and other changes
 * Relaxed `delta-spark` upper bound to allow compatibility with Spark 3.1.x and 3.2.x.
 * Upgraded required `polars` version to 0.17.
-* Renamed `TensorFlowModelDataset` to `TensorFlowModelDataSet` to be consistent with all other plugins in kedro-datasets.
+* Renamed `TensorFlowModelDataset` to `TensorFlowModelDataSet` to be consistent with all other plugins in Kedro-Datasets.
 
 ## Community contributions
 Many thanks to the following Kedroids for contributing PRs to this release:
@@ -102,11 +106,11 @@ Datasets are Kedro’s way of dealing with input and output in a data and machin
 The datasets have always been part of the core Kedro Framework project inside `kedro.extras`. In Kedro `0.19.0`, we will remove datasets from Kedro to reduce breaking changes associated with dataset dependencies. Instead, users will need to use the datasets from the `kedro-datasets` repository instead.
 
 ## Major features and improvements
-* Changed `pandas.ParquetDataSet` to load data using pandas instead of parquet
+* Changed `pandas.ParquetDataSet` to load data using pandas instead of parquet.
 
 # Release 0.1.0:
 
-The initial release of `kedro-datasets`.
+The initial release of Kedro-Datasets.
 
 ## Thanks to our main contributors