Document(
shards: List[google.cloud.documentai_v1.types.document.Document],
gcs_bucket_name: Optional[str] = None,
gcs_prefix: Optional[str] = None,
)
Represents a wrapped Document.
This class hides away the complexities of using Document protobuf response outputted by BatchProcessDocuments or ProcessDocument methods and implements convenient methods for searching and extracting information within the Document.
Optional. The name of the gcs bucket.
Format: gs://bucket/optional_folder/target_folder/
where gcs_bucket_name=bucket
.
:type: Optional[str]
(List[Entity]): A list of Entities in the Document.
Attributes
Name | Description |
gcs_prefix |
Optional[str]
Optional. The prefix of the json files in the target_folder. Format: gs://bucket/optional_folder/target_folder/ where gcs_prefix=optional_folder/target_folder .
For more information please take a look at https://cloud.google.com/storage/docs/json_api/v1/objects/list .
|
pages |
Optional[str]
(List[Page]): A list of Pages in the Document. |
Methods
entities_to_bigquery
entities_to_bigquery(
dataset_name: str, table_name: str, project_id: Optional[str] = None
)
Adds extracted entities to a BigQuery table.
Name | Description |
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. |
Type | Description |
bigquery.job.LoadJob | The BigQuery LoadJob for adding the entities. |
entities_to_dict
entities_to_dict()
Returns Dictionary of entities in document.
Type | Description |
Dict | The Dict of the entities indexed by type. |
from_document_path
from_document_path(document_path: str)
Loads Document from local document_path.
Name | Description |
document_path |
str
Required. The path to the document.json file. |
Type | Description |
Document | A document from local document_path. |
from_documentai_document
from_documentai_document(
documentai_document: google.cloud.documentai_v1.types.document.Document,
)
Loads Document from local documentai_document.
Name | Description |
documentai_document |
documentai.Document
Optional. The Document.proto response. |
Type | Description |
Document | A document from local documentai_document. |
from_gcs
from_gcs(gcs_bucket_name: str, gcs_prefix: str)
Loads Document from Cloud Storage.
Name | Description |
gcs_bucket_name |
str
Required. The gcs bucket. Format: Given |
gcs_prefix |
str
Required. The prefix to the location of the target folder. Format: Given |
Type | Description |
Document | A document from gcs. |
get_entity_by_type
get_entity_by_type(target_type: str)
Returns the list of Entities of target_type.
Name | Description |
target_type |
str
Required. target_type. |
Type | Description |
List[Entity] | A list of Entity matching target_type. |
get_form_field_by_name
get_form_field_by_name(target_field: str)
Returns the list of FormFields named target_field.
Name | Description |
target_field |
str
Required. Target field name. |
Type | Description |
List[FormField] | A list of FormField matching target_field. |
search_pages
search_pages(target_string: Optional[str] = None, pattern: Optional[str] = None)
Returns the list of Pages containing target_string or text matching pattern.
Name | Description |
target_string |
Optional[str]
Optional. target str. |
pattern |
Optional[str]
Optional. regex str. |
Type | Description |
List[Page] | A list of Pages. |
split_pdf
split_pdf(pdf_path: str, output_path: str)
Splits local PDF file into multiple PDF files based on output from a Splitter/Classifier processor.
Name | Description |
pdf_path |
str
Required. The path to the PDF file. |
output_path |
str
Required. The path to the output directory. |
Type | Description |
List[str] | A list of output pdf files. |