Toolbox - Export entities to BigQuery

Export entities from a processed document (or document shards) to a BigQuery table.

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For detailed documentation that includes this code sample, see the following:

Code sample

Python

For more information, see the Document AI Python API reference documentation .

To authenticate to Document AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  from 
  
 google.cloud.documentai_toolbox 
  
 import 
 document 
 # TODO(developer): Uncomment these variables before running the sample. 
 # Given a document.proto or sharded document.proto in path gs://bucket/path/to/folder 
 # gcs_bucket_name = "bucket" 
 # gcs_prefix = "path/to/folder" 
 # dataset_name = "test_dataset" 
 # table_name = "test_table" 
 # project_id = "YOUR_PROJECT_ID" 
 def 
  
 entities_to_bigquery_sample 
 ( 
 gcs_bucket_name 
 : 
 str 
 , 
 gcs_prefix 
 : 
 str 
 , 
 dataset_name 
 : 
 str 
 , 
 table_name 
 : 
 str 
 , 
 project_id 
 : 
 str 
 , 
 ) 
 - 
> None 
 : 
 wrapped_document 
 = 
 document 
 . 
 Document 
 . 
 from_gcs 
 ( 
 gcs_bucket_name 
 = 
 gcs_bucket_name 
 , 
 gcs_prefix 
 = 
 gcs_prefix 
 ) 
 job 
 = 
 wrapped_document 
 . 
 entities_to_bigquery 
 ( 
 dataset_name 
 = 
 dataset_name 
 , 
 table_name 
 = 
 table_name 
 , 
 project_id 
 = 
 project_id 
 ) 
 # Also supported: 
 # job = wrapped_document.form_fields_to_bigquery( 
 #     dataset_name=dataset_name, table_name=table_name, project_id=project_id 
 # ) 
 print 
 ( 
 "Document entities loaded into BigQuery" 
 ) 
 print 
 ( 
 f 
 "Job ID: 
 { 
 job 
 . 
 job_id 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Table: 
 { 
 job 
 . 
 destination 
 . 
 path 
 } 
 " 
 ) 
 

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