Introduced an `all_nullable` boolean option in both `load_folder.py` and `load_sas.py`, allowing users to specify whether all columns should be treated as nullable during schema inference. This feature addresses scenarios where the data sampling may incorrectly suggest that columns are non-nullable, preventing potential errors during data loading. Updated YAML configuration files to include examples of this new option, enhancing usability and providing clearer documentation for users.
Implemented a new feature allowing users to specify explicit column type mappings via a `column_types` configuration in both `load_folder.py` and `load_sas.py`. This addition enables users to bypass automatic type inference for specific columns, ensuring correct data types are used when loading datasets. Updated the YAML configuration files to include examples of the new `column_types` option, enhancing usability and flexibility in handling varying data formats across files.
Introduce generate_sample_folder.py to create a test folder with clustered SAS XPORT files, including configurations for schema compatibility checks. Implement load_folder.py to facilitate loading entire directories of SAS files into Postgres, supporting explicit and auto-detect clustering. Update sample_folder_config.yaml for usage examples and configuration structure. Enhance load_sas.py with a public schema compatibility check function for orchestrators.
