Release 0.18.2

Major features and improvements

Added abfss to list of cloud protocols, enabling abfss paths.
Kedro now uses the Rich library to format terminal logs and tracebacks.
The file conf/base/logging.yml is now optional. See our documentation for details.
Introduced a kedro.starters entry point. This enables plugins to create custom starter aliases used by kedro starter list and kedro new.
Reduced the kedro new prompts to just one question asking for the project name.

Bumped pyyaml upper bound to make Kedro compatible with the pyodide stack.
Updated project template's Sphinx configuration to use myst_parser instead of recommonmark.
Reduced number of log lines by changing the logging level from INFO to DEBUG for low priority messages.
Kedro's framework-side logging configuration no longer performs file-based logging. Hence superfluous info.log/errors.log files are no longer created in your project root, and running Kedro on read-only file systems such as Databricks Repos is now possible.
The root logger is now set to the Python default level of WARNING rather than INFO. Kedro's logger is still set to emit INFO level messages.
SequentialRunner now has consistent execution order across multiple runs with sorted nodes.
Bumped the upper bound for the Flake8 dependency to <5.0.
kedro jupyter notebook/lab no longer reuses a Jupyter kernel.
Required cookiecutter>=2.1.1 to address a known command injection vulnerability.
The session store no longer fails if a username cannot be found with getpass.getuser.
Added generic typing for AbstractDataSet and AbstractVersionedDataSet as well as typing to all datasets.
Rendered the deployment guide flowchart as a Mermaid diagram, and added Dask.

The module kedro.config.default_logger no longer exists; default logging configuration is now set automatically through kedro.framework.project.LOGGING. Unless you explicitly import kedro.config.default_logger you do not need to make any changes.