Spooq

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* [ADD] Annotator: New transformer to load and apply comments to dataframes
* [MOD] Mapper: Change mode and missing_column_handling from strings to Enums
* [MOD] Mapper: Add support for column comments (via annotator)

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* [MOD] Mapper: Add validation mode

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* [MOD] Mapper: Custom transformations can now also be used with ``select``, ``withColumn`` or ``where`` clauses
* [MOD] Mapper: Custom transformations can now be passed as python objects with or without parameters
* [MOD] Mapper: Spark's built-in data types can now be passed as simple strings (f.e. "string")
* [MOD] Mapper: Renaming (shortening) of most custom Mapper transformations (https://spooq.rtfd.io/en/latest/transformer/mapper_transformations.html)
* [ADD] Mapper: ``str_to_array`` transformation
* [ADD] Mapper: ``map_values`` transformation
* [ADD] Mapper: ``apply`` transformation
* [MOD] Tests use now Python 3.8
* [MOD] Spark 3.3.0 compatibility (Tested for all Spark version from 3.0 to 3.3)
* [MOD] Clean up documentation
* [FIX] Tests with github actions

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* [MOD] Mapper: Replace missing column parameters (`nullify_missing_columns`, `skip_missing_columns`, `ignore_missing_columns`) with one single parameter: `missing_column_handling`.

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* [MOD] Mapper: Add additional parameter allowing skipping of transformations in case the source column is missing:

- `nullify_missing_columns`: set source column to null in case it does not exist
- `skip_missing_columns`: skip transformation in case the source column does not exist
- `ignore_missing_columns`: DEPRECATED -> use `nullify_missing_columns` instead

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* [FIX] Fix long overflow in extended_string_to_timestamp