Module document (0.13.3a0)

Wrappers for Document AI Document type.

Classes

Document

Document(
    shards: typing.List[google.cloud.documentai_v1.types.document.Document],
    gcs_bucket_name: typing.Optional[str] = None,
    gcs_prefix: typing.Optional[str] = None,
    gcs_uri: typing.Optional[str] = None,
    gcs_input_uri: typing.Optional[str] = None,
)

Represents a wrapped Document.

This class hides away the complexities of using the Document protobuf response outputted by BatchProcessDocuments or ProcessDocument methods and implements convenient methods for searching and extracting information within the Document.

Modules Functions

_apply_text_offset

_apply_text_offset(
    documentai_object: typing.Union[typing.Dict[str, typing.Dict], typing.List],
    text_offset: int,
) -> None

Applies a text offset to all text_segments in documentai_object.

Parameters
Name	Description
`documentai_object`	`object` Required. Document AI object to apply `text_offset` to.
`text_offset`	`int` Required. Text offset to apply. From `Document.shard_info.text_offset`.

_bigquery_column_name

_bigquery_column_name(input_string: str) -> str

Converts a string into a BigQuery column name. https://cloud.google.com/bigquery/docs/schemas#column_names

Parameter
Name	Description
`input_string`	`str` Required: The string to convert.

_dict_to_bigquery

_dict_to_bigquery(
    dic: typing.Dict[str, typing.Union[str, typing.List[str]]],
    dataset_name: str,
    table_name: str,
    project_id: typing.Optional[str],
) -> google.cloud.bigquery.job.load.LoadJob

Loads dictionary to a BigQuery table.

Parameters
Name	Description
`dic`	`Dict[str, Union[str, List[str]]]` Required: The dictionary to insert.
`dataset_name`	`str` Required. Name of the BigQuery dataset.
`table_name`	`str` Required. Name of the BigQuery table.
`project_id`	`Optional[str]` Optional. Project ID containing the BigQuery table. If not passed, falls back to the default inferred from the environment.

Returns
Type	Description
`bigquery.job.LoadJob`	The BigQuery LoadJob for adding the dictionary.

_entities_from_shards

_entities_from_shards(
    shards: typing.List[google.cloud.documentai_v1.types.document.Document],
) -> typing.List[google.cloud.documentai_toolbox.wrappers.entity.Entity]

Returns a list of Entities and Properties from a list of documentai.Document shards.

Parameter
Name	Description
`shards`	`List[google.cloud.documentai.Document]` Required. List of document shards.

Returns
Type	Description
`List[Entity]`	a list of Entities.

_get_batch_process_metadata

_get_batch_process_metadata(
    operation_name: str,
    location: typing.Optional[str] = None,
    timeout: typing.Optional[float] = None,
) -> google.cloud.documentai_v1.types.document_processor_service.BatchProcessMetadata

Get BatchProcessMetadata from a batch_process_documents() long-running operation.

Parameters
Name	Description
`operation_name`	`str` Required. The fully qualified operation name for a `batch_process_documents()` operation.
`location`	`str` Optional. The location of the processor used for `batch_process_documents()`. Deprecated. Maintained for backwards compatibility.
`timeout`	`float` Optional. Default None. Time in seconds to wait for operation to complete. If None, will wait indefinitely.

Returns
Type	Description
`documentai.BatchProcessMetadata`	Metadata from batch process.

_get_shards

_get_shards(
    gcs_bucket_name: str, gcs_prefix: str
) -> typing.List[google.cloud.documentai_v1.types.document.Document]

Returns a list of documentai.Document shards from a Cloud Storage folder.

Parameters
Name	Description
`gcs_bucket_name`	`str` Required. The name of the gcs bucket. Format: `gs://{bucket_name}/{optional_folder}/{target_folder}/` where gcs_bucket_name=`bucket`.
`gcs_prefix`	`str` Required. The prefix of the json files in the target_folder. Format: `gs://{bucket_name}/{optional_folder}/{target_folder}/` where gcs_prefix=`{optional_folder}/{target_folder}`.

Returns
Type	Description
`List[google.cloud.documentai.Document]`	A list of documentai.Documents.

_insert_into_dictionary_with_list

_insert_into_dictionary_with_list(
    dic: typing.Dict[str, typing.Union[str, typing.List[str]]], key: str, value: str
) -> typing.Dict[str, typing.Union[str, typing.List[str]]]

Inserts value into a dictionary that can contain lists.

Parameters
Name	Description
`dic`	`Dict[str, Union[str, List[str]]]` Required. The dictionary to insert into.
`key`	`str` Required. The key to be created or inserted into.
`value`	`str` Required. The value to be inserted.

Returns
Type	Description
`Dict[str, Union[str, List[str]]]`	The dictionary after adding the key-value pair.

_pages_from_shards

_pages_from_shards(
    shards: typing.List[google.cloud.documentai_v1.types.document.Document],
) -> typing.List[google.cloud.documentai_toolbox.wrappers.page.Page]

Returns a list of Pages from a list of documentai.Document shards.

Parameter
Name	Description
`shards`	`List[google.cloud.documentai.Document]` Required. List of document shards.

Returns
Type	Description
`List[Page]`	A list of Pages.