Dimension Mapping Config

Registered Dimension Mappings

pydantic model dsgrid.config.mapping_tables.MappingTableModel

Attributes for a dimension mapping table

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• file_hash (str | None)

• filename (str | None)

• records (List)

Validators:

• add_records » records

• check_filename » filename

• compute_file_hash » file_hash

field file_hash: str | None = None

Hash of the contents of the file, computed by dsgrid.

Validated by:

• compute_file_hash

field filename: str | None = None (alias 'file')

Filename containing association table records. Only assigned for user input and output purposes. The registry database stores records in the mapping JSON document.

Validated by:

• check_filename

field records: List = []

dimension mapping records in filename that get loaded at runtime

Validated by:

• add_records

validator add_records  »  records

Add records from the file.

validator check_filename  »  filename

Validate record file

validator compute_file_hash  »  file_hash

Compute file hash.

classmethod from_pre_registered_model(model: DimensionMappingPreRegisteredBaseModel, from_dimension, to_dimension)

serialize_cls(val, _)

pydantic model dsgrid.config.mapping_tables.MappingTableRecordModel

Represents one record in dimension mapping record files. Maps one dimension to another.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• from_fraction (float)

• from_id (str)

• to_id (str | None)

Validators:

• check_to_id » from_id

• check_to_id » to_id

field from_fraction: float = 1.0

Fraction of from_id to map to to_id

field from_id: str [Required]

Source mapping

Validated by:

• check_to_id

field to_id: str | None = None

Destination mapping

Validated by:

• check_to_id

validator check_to_id  »  from_id, to_id

pydantic model dsgrid.config.dimension_mapping_base.DimensionMappingBaseModel

Base class for mapping dimensions

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• archetype (dsgrid.config.dimension_mapping_base.DimensionMappingArchetype | None)

• description (str)

• from_dimension (dsgrid.config.dimensions.DimensionReferenceModel)

• from_fraction_tolerance (float)

• id (str | None)

• key (str | None)

• mapping_id (str | None)

• mapping_type (dsgrid.config.dimension_mapping_base.DimensionMappingType)

• rev (str | None)

• to_dimension (dsgrid.config.dimensions.DimensionReferenceModel)

• to_fraction_tolerance (float)

• version (str | None)

Validators:

• check_archetype » archetype

field archetype: DimensionMappingArchetype | None = None

Dimension mapping archetype, determined based on mapping_type

Validated by:

• check_archetype

field description: str [Required]

Description of dimension mapping

field from_dimension: DimensionReferenceModel [Required]

From dimension

field from_fraction_tolerance: float = 1e-09

Tolerance to apply when checking from_fraction column sums

field id: str | None = None (alias '_id')

Registry database ID

field key: str | None = None (alias '_key')

Registry database key

field mapping_id: str | None = None

Unique dimension mapping identifier, generated by dsgrid

field mapping_type: DimensionMappingType = 'many_to_one_aggregation'

Type/purpose of the dimension mapping

field rev: str | None = None (alias '_rev')

Registry database revision

field to_dimension: DimensionReferenceModel [Required]

To dimension

field to_fraction_tolerance: float = 1e-09

Tolerance to apply when checking to_fraction column sums

field version: str | None = None

Version, generated by dsgrid

validator check_archetype  »  archetype

Dimension Mapping Reference

pydantic model dsgrid.config.dimension_mapping_base.DimensionMappingReferenceModel

Reference to a dimension mapping stored in the registry.

The DimensionMappingReferenceModel is utilized by the project configuration (project.json5) as well as by the dimension mapping reference configuration (dimension_mapping_references.json5) that may be required when submitting a dataset to a project.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• from_dimension_type (dsgrid.dimension.base_models.DimensionType)

• mapping_id (str)

• required_for_validation (bool | None)

• to_dimension_type (dsgrid.dimension.base_models.DimensionType)

• version (str)

field from_dimension_type: DimensionType [Required]

Dimension Type

field mapping_id: str [Required]

Unique ID of the dimension mapping

field required_for_validation: bool | None = True

Set to False if a given dimension association is NOT required for input dataset validation; default is True

field to_dimension_type: DimensionType [Required]

Dimension Type

field version: str [Required]

Version of the dimension

pydantic model dsgrid.config.dimension_mapping_base.DimensionMappingReferenceListModel

List of dimension mapping references used by the dimensions_mappings.json5 config

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• references (list[dsgrid.config.dimension_mapping_base.DimensionMappingReferenceModel])

field references: list[DimensionMappingReferenceModel] [Required]

List of dimension mapping references

pydantic model dsgrid.config.dimension_mappings_config.DimensionMappingsConfigModel

Represents dimension mapping model configurations

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• mappings (List[dsgrid.config.mapping_tables.MappingTableModel])

field mappings: List[MappingTableModel] [Required]

dimension mappings between and within projects and datasets

pydantic model dsgrid.config.mapping_tables.DatasetBaseToProjectMappingTableModel

Attributes for a dimension mapping table to map soon-to-be-registered dataset base dimensions to a project’s dimensions. This will be converted to a MappingTableModel as soon as the dimensions are registered.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• filename (str)

field filename: str [Required] (alias 'file')

Filename containing association table records.

pydantic model dsgrid.config.mapping_tables.DatasetBaseToProjectMappingTableListModel

Represents the config file passed to register-and-submit-dataset command.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• mappings (List[dsgrid.config.mapping_tables.DatasetBaseToProjectMappingTableModel])

field mappings: List[DatasetBaseToProjectMappingTableModel] [Required]

pydantic model dsgrid.config.dimension_mapping_base.DimensionMappingDatasetToProjectBaseModel

Base class for mapping soon-to-be registered dimensions for a dataset. Used when automatically registering mappings while submitting a dataset to a project.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• dimension_type (dsgrid.dimension.base_models.DimensionType)

field dimension_type: DimensionType [Required]

Dimension types that will be mapped

Unregistered Dimension Mappings

pydantic model dsgrid.config.mapping_tables.MappingTableByNameModel

Attributes for a dimension mapping table for soon-to-be registered dimensions by name. This will be converted to a MappingTableModel as soon as the dimensions are registered.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• filename (str)

field filename: str [Required] (alias 'file')

Filename containing association table records.

pydantic model dsgrid.config.dimension_mapping_base.DimensionMappingPreRegisteredBaseModel

Base class for mapping soon-to-be registered dimensions. As soon as the dimensions are registered this will be converted to a DimensionMappingBaseModel and then registered.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• archetype (dsgrid.config.dimension_mapping_base.DimensionMappingArchetype | None)

• description (str)

• from_fraction_tolerance (float | None)

• mapping_type (dsgrid.config.dimension_mapping_base.DimensionMappingType)

• to_fraction_tolerance (float | None)

field archetype: DimensionMappingArchetype | None = None

Dimension mapping archetype, determined based on mapping_type

field description: str [Required]

Description of dimension mapping

field from_fraction_tolerance: float | None = 1e-09

Tolerance value to apply to the from_fraction column

field mapping_type: DimensionMappingType = 'many_to_one_aggregation'

Type/purpose of the dimension mapping

field to_fraction_tolerance: float | None = 1e-09

Tolerance value to apply to the to_fraction column

pydantic model dsgrid.config.dimensions.DimensionReferenceByNameModel

Reference to a dimension that has yet to be registered.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Fields:

• dimension_type (dsgrid.dimension.base_models.DimensionType)

• name (str)

field dimension_type: DimensionType [Required] (alias 'type')

Type of the dimension

field name: str [Required]

Dimension name