Maps a source value to a bucket schema field. Used for mapping metadata, tags, columns, or extracted values to regular fields in the bucket schema (strings, numbers, arrays, etc.). Does NOT handle file content - use BlobMappingEntry for that. Example: Map S3 tag "category" to bucket field "content_category" { "target_type": "field", "source": {"type": "tag", "key": "category"} } Example: Map folder name to "department" with lowercase transform { "target_type": "field", "source": {"type": "folder_path", "segment": 0}, "transform": "lowercase" } Example: Map filename regex capture to "date" field { "target_type": "field", "source": {"type": "filename_regex", "pattern": "^(\d{4}-\d{2}-\d{2})"}, "required": true } Attributes: target_type: Must be "field" for schema field mappings source: The source extractor defining where to get the value transform: Optional transformation to apply (lowercase, uppercase, trim) required: Whether missing values should fail the sync
| Name | Type | Description | Notes |
|---|---|---|---|
| target_type | str | Target type. Must be 'field' for regular schema fields. | [optional] [default to 'field'] |
| source | Source1 | ||
| transform | str | Optional transformation to apply to the extracted value. Supported transforms: 'lowercase' - convert to lowercase, 'uppercase' - convert to uppercase, 'trim' - remove leading/trailing whitespace, 'json_parse' - parse JSON string to object/array. Transforms are applied after extraction, before storage. | [optional] |
| required | bool | If True, the sync will fail if this field cannot be extracted. If False (default), missing values result in the field being omitted. Use required=True for critical fields that must be present. | [optional] [default to False] |
from mixpeek.models.field_mapping_entry import FieldMappingEntry
# TODO update the JSON string below
json = "{}"
# create an instance of FieldMappingEntry from a JSON string
field_mapping_entry_instance = FieldMappingEntry.from_json(json)
# print the JSON string representation of the object
print(FieldMappingEntry.to_json())
# convert the object into a dict
field_mapping_entry_dict = field_mapping_entry_instance.to_dict()
# create an instance of FieldMappingEntry from a dict
field_mapping_entry_from_dict = FieldMappingEntry.from_dict(field_mapping_entry_dict)