Added documentation on how to enable specific checkers and how to silence specific warnings (#37). The latest release introduces new documentation in the README file for enabling specific checkers and disabling specific warnings for the pylint plugin for Databricks. The plugin offers checkers such as databricks-airflow, databricks-dbutils, databricks-legacy, databricks-notebooks, spark, and mocking, each with unique checks and codes. Users can use these checkers by adding the corresponding module name to the load-plugins configuration in their pylintrc or pyproject.toml file. The release also explains how to disable certain checks on specific lines using a comment with the disable directive followed by the corresponding symbol. Additionally, it includes information on how to use the Databricks SDK instead of internal APIs, legacy CLI, and dbutils. The docs.py script has also been updated with the new instructions on how to enable or disable specific checkers and warnings.
databricks-airflow,databricks-dbutils,databricks-legacy,databricks-notebooks,spark, andmocking, each with unique checks and codes. Users can use these checkers by adding the corresponding module name to theload-pluginsconfiguration in theirpylintrcorpyproject.tomlfile. The release also explains how to disable certain checks on specific lines using a comment with thedisabledirective followed by the corresponding symbol. Additionally, it includes information on how to use the Databricks SDK instead of internal APIs, legacy CLI, and dbutils. Thedocs.pyscript has also been updated with the new instructions on how to enable or disable specific checkers and warnings.