trailpack.packing.export_service
================================

.. py:module:: trailpack.packing.export_service

.. autoapi-nested-parse::

   Export service for converting UI data to Frictionless Data Package in Parquet.



Classes
-------

.. autoapisummary::

   trailpack.packing.export_service.DataPackageExporter


Module Contents
---------------

.. py:class:: DataPackageExporter(df: pandas.DataFrame, column_mappings: Dict[str, str], general_details: Dict[str, Any], sheet_name: str, file_name: str, suggestions_cache: Dict[str, List] = None, column_descriptions: Dict[str, str] = None, standard_version: str = '1.0.0')

   Service for exporting UI data to Frictionless Data Package in Parquet.

   Initialize with UI session state data.

   :param df: Pandas DataFrame with the actual data
   :param column_mappings: Mapping of column names to PyST concept IDs
   :param general_details: Metadata from the general details form
   :param sheet_name: Name of the Excel sheet
   :param file_name: Original file name
   :param suggestions_cache: Cache of PyST suggestions with id and label
   :param column_descriptions: User-provided descriptions/comments for columns
   :param standard_version: Trailpack standard version to validate against


   .. py:method:: _find_label_for_id(concept_id: str) -> Optional[str]

      Find label for a PyST concept ID from suggestions cache.



   .. py:method:: _format_validation_errors(validation_result) -> str

      Format validation errors for better readability.



   .. py:method:: _infer_field_type(series: pandas.Series) -> str

      Infer Frictionless field type from pandas Series.



   .. py:method:: _sanitize_resource_name(name: str) -> str

      Sanitize resource name to match the pattern ^[a-z0-9\-_\.]+$.

      The resource name must only contain:
      - Lowercase letters (a-z)
      - Numbers (0-9)
      - Hyphens (-)
      - Underscores (_)
      - Dots (.)

      :param name: Raw name string to sanitize

      :returns: Sanitized name matching the required pattern



   .. py:method:: _validate_dataframe_for_parquet(df: pandas.DataFrame) -> None

      Validate DataFrame is compatible with Arrow/Parquet format.

      :raises ValueError: If data quality issues are found (e.g., mixed types in columns)



   .. py:method:: build_fields() -> List[trailpack.packing.datapackage_schema.Field]

      Convert column mappings to Field definitions.



   .. py:method:: build_metadata(resource: trailpack.packing.datapackage_schema.Resource) -> Dict[str, Any]

      Build complete metadata using MetaDataBuilder.



   .. py:method:: build_resource(fields: List[trailpack.packing.datapackage_schema.Field]) -> trailpack.packing.datapackage_schema.Resource

      Create Resource definition with fields.



   .. py:method:: export(output_path: str, validate_standard: bool = True) -> Tuple[str, Optional[str], Optional[Any]]

      Execute full export workflow and write Parquet.

      :param output_path: Path where Parquet file will be written
      :param validate_standard: Whether to validate against Trailpack standard (default: True)

      :returns: Tuple of (output_path, quality_level, validation_result)
                - output_path: Path to exported Parquet file
                - quality_level: Validation level ("STRICT", "STANDARD", "BASIC", "INVALID") or None if validation skipped
                - validation_result: Full ValidationResult object for report generation, or None if validation skipped

      :raises ValueError: If validation fails or data quality issues found



   .. py:method:: generate_validation_report(validation_result) -> str

      Generate a complete validation report for download.

      Includes errors, warnings, and info (data quality metrics).

      :param validation_result: ValidationResult object from validation

      :returns: Formatted report as string



   .. py:method:: validate() -> Tuple[bool, List[str]]

      Validate all inputs before processing.



   .. py:attribute:: column_descriptions


   .. py:attribute:: column_mappings


   .. py:attribute:: df


   .. py:attribute:: file_name


   .. py:attribute:: general_details


   .. py:attribute:: schema


   .. py:attribute:: sheet_name


   .. py:attribute:: suggestions_cache


   .. py:attribute:: validator