feat: Add entities_to_dict() and entities_to_bigquery() to Document wrapper (#50)

* feat: Add `entities_to_dict()` and `entities_to_bigquery()` to Document wrapper

- Uploads entities to an existing dataset, creates new table if it doesn't already exist.

## Example Output Table

| supplier_iban | purchase_order | supplier_email      | freight_amount | supplier_address             | receiver_address             | total_amount | supplier_name | total_tax_amount | payment_terms    | line_item                                                                     | receiver_name | receiver_email    | due_date   | invoice_date | invoice_id | currency | receiver_tax_id | net_amount | vat |
|---------------|----------------|---------------------|----------------|------------------------------|------------------------------|--------------|---------------|------------------|------------------|-------------------------------------------------------------------------------|---------------|-------------------|------------|--------------|------------|----------|-----------------|------------|-----|
|            50 |              1 | user@companyabc.com |            600 | 111 Main Street Anytown, USA | 222 Main Street Anytown, USA |         2140 | Company ABC   |              140 | 6 month contract | [Tool A 500 1.00 500.00,Service B 1 900.00 900.00,Resource C 50 12.00 600.00] | John Doe      | johndoe@email.com | 2025-01-01 |   1970-01-01 | NO. 001    | $        |               1 |       2000 | 140 |

* Removed unneeded test code

* Added bigquery library to setup.py

* Updated Docstrings

* Fixed Test import linter error

* Added bigQuery Library to Testing Constraints

* Added handling of Nested Entities (properties)

* Dependency Update for Tests

* Update Dependencies

* Fixed Test Output

* Updated DatasetReference based on Deprecation Warning

* samples: Added Entities to BigQuery Sample Code

* Added Required tag to `entities_to_bigquery()` arguments

* Fixed Issues from merge conflict

* Fixed numpy import

---------

Co-authored-by: Gal Zahavi <38544478+galz10@users.noreply.github.com>

Author: holtskinner

packages/google-cloud-documentai-toolbox/google/cloud/documentai_toolbox/wrappers/document.py

@@ -21,6 +21,7 @@
 from typing import Dict, List, Optional
 
 from google.api_core import client_info
+from google.cloud import bigquery
 from google.cloud import documentai
 from google.cloud import storage
 from google.cloud import documentai_toolbox
@@ -50,6 +51,8 @@ def _entities_from_shards(
     for shard in shards:
         for entity in shard.entities:
             result.append(Entity(documentai_entity=entity))
+            for prop in entity.properties:
+                result.append(Entity(documentai_entity=prop))
     return result
 
 
@@ -368,6 +371,69 @@ def get_entity_by_type(self, target_type: str) -> List[Entity]:
         """
         return [entity for entity in self.entities if entity.type_ == target_type]
 
+    def entities_to_dict(self) -> Dict:
+        r"""Returns Dictionary of entities in document.
+
+        Returns:
+            Dict:
+                The Dict of the entities indexed by type.
+
+        """
+        entities_dict: Dict = {}
+        for entity in self.entities:
+            entity_type = entity.type_.replace("/", "_")
+
+            existing_entity = entities_dict.get(entity_type)
+            if not existing_entity:
+                entities_dict[entity_type] = entity.mention_text
+                continue
+
+            # For entities that can have multiple (e.g. line_item)
+            # Change Entity Type to a List
+            if not isinstance(existing_entity, list):
+                existing_entity = [existing_entity]
+
+            existing_entity.append(entity.mention_text)
+            entities_dict[entity_type] = existing_entity
+
+        return entities_dict
+
+    def entities_to_bigquery(
+        self, dataset_name: str, table_name: str, project_id: Optional[str] = None
+    ) -> bigquery.job.LoadJob:
+        r"""Adds extracted entities to a BigQuery table.
+
+        Args:
+            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:
+            bigquery.job.LoadJob:
+                The BigQuery LoadJob for adding the entities.
+
+        """
+        bq_client = bigquery.Client(project=project_id)
+        table_ref = bigquery.DatasetReference(
+            project=project_id, dataset_id=dataset_name
+        ).table(table_name)
+
+        job_config = bigquery.LoadJobConfig(
+            schema_update_options=[
+                bigquery.SchemaUpdateOption.ALLOW_FIELD_ADDITION,
+                bigquery.SchemaUpdateOption.ALLOW_FIELD_RELAXATION,
+            ],
+            source_format=bigquery.SourceFormat.NEWLINE_DELIMITED_JSON,
+        )
+
+        return bq_client.load_table_from_json(
+            json_rows=[self.entities_to_dict()],
+            destination=table_ref,
+            job_config=job_config,
+        )
+
     def split_pdf(self, pdf_path: str, output_path: str) -> List[str]:
         r"""Splits local PDF file into multiple PDF files based on output from a Splitter/Classifier processor.
 

packages/google-cloud-documentai-toolbox/google/cloud/documentai_toolbox/wrappers/entity.py

@@ -37,13 +37,20 @@ class Entity:
     documentai_entity: documentai.Document.Entity = dataclasses.field(repr=False)
     type_: str = dataclasses.field(init=False)
     mention_text: str = dataclasses.field(init=False, default="")
+    normalized_text: str = dataclasses.field(init=False, default="")
     # Only Populated for Splitter/Classifier Output
     start_page: int = dataclasses.field(init=False)
     end_page: int = dataclasses.field(init=False)
 
     def __post_init__(self):
         self.type_ = self.documentai_entity.type_
         self.mention_text = self.documentai_entity.mention_text
+        if (
+            self.documentai_entity.normalized_value
+            and self.documentai_entity.normalized_value.text
+        ):
+            self.normalized_text = self.documentai_entity.normalized_value.text
+
         if self.documentai_entity.page_anchor.page_refs:
             self.start_page = int(self.documentai_entity.page_anchor.page_refs[0].page)
             self.end_page = int(self.documentai_entity.page_anchor.page_refs[-1].page)

packages/google-cloud-documentai-toolbox/samples/snippets/entities_to_bigquery_sample.py

@@ -0,0 +1,50 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+
+# [START documentai_toolbox_entities_to_bigquery]
+
+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
+    )
+
+    print("Document entities loaded into BigQuery")
+    print(f"Job ID: {job.job_id}")
+    print(f"Table: {job.destination.path}")
+
+
+# [END documentai_toolbox_entities_to_bigquery]

packages/google-cloud-documentai-toolbox/samples/snippets/requirements-test.txt

@@ -1,2 +1,3 @@
 pytest==7.2.1
-mock==5.0.1
+mock==5.0.1
+google-cloud-bigquery==3.5.0

packages/google-cloud-documentai-toolbox/samples/snippets/requirements.txt

@@ -1,3 +1,4 @@
+google-cloud-bigquery==3.5.0
 google-cloud-documentai==2.12.0
 google-cloud-storage==2.7.0
 google-cloud-documentai-toolbox==0.1.1a0

packages/google-cloud-documentai-toolbox/samples/snippets/test_entities_to_bigquery_sample.py

@@ -0,0 +1,54 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import os
+import uuid
+
+import pytest
+from samples.snippets import entities_to_bigquery_sample
+
+from google.cloud import bigquery
+
+location = "us"
+project_id = os.environ["GOOGLE_CLOUD_PROJECT"]
+gcs_bucket_name = "documentai_toolbox_samples"
+gcs_input_uri = "output/123456789/0"
+dataset_name = f"document_ai_toolbox_test_{uuid.uuid4().hex}"
+table_name = f"test_table_{uuid.uuid4().hex}"
+
+
+def test_entities_to_bigquery_sample(capsys: pytest.CaptureFixture) -> None:
+    client = bigquery.Client(project=project_id)
+    dataset = bigquery.Dataset(f"{project_id}.{dataset_name}")
+    dataset.location = "US"
+    dataset = client.create_dataset(dataset, timeout=30, exists_ok=True)
+
+    entities_to_bigquery_sample.entities_to_bigquery_sample(
+        gcs_bucket_name=gcs_bucket_name,
+        gcs_prefix=gcs_input_uri,
+        dataset_name=dataset_name,
+        table_name=table_name,
+        project_id=project_id,
+    )
+    out, _ = capsys.readouterr()
+
+    assert "Document entities loaded into BigQuery" in out
+    assert "Job ID:" in out
+    assert (
+        f"Table: /projects/{project_id}/datasets/{dataset_name}/tables/{table_name}"
+        in out
+    )
+
+    client.delete_dataset(dataset)

packages/google-cloud-documentai-toolbox/samples/snippets/test_quickstart_sample.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -31,4 +31,4 @@ def test_quickstart_sample(capsys: pytest.CaptureFixture) -> None:
     out, _ = capsys.readouterr()
 
     assert "Number of Pages: 1" in out
-    assert "Number of Entities: 22" in out
+    assert "Number of Entities: 35" in out

packages/google-cloud-documentai-toolbox/setup.py

@@ -49,6 +49,7 @@
         "proto-plus >= 1.22.0, <2.0.0dev",
         "proto-plus >= 1.22.2, <2.0.0dev; python_version>='3.11'",
         "grpc-google-iam-v1 >= 0.12.4, < 0.13dev",
+        "google-cloud-bigquery >= 3.5.0, < 4.0.0dev",
         "google-cloud-documentai >= 1.2.1, < 3.0.0dev",
         "google-cloud-storage >= 1.31.0, < 3.0.0dev",
         "numpy >= 1.18.1",

packages/google-cloud-documentai-toolbox/testing/constraints-3.10.txt

@@ -6,6 +6,8 @@ libcst
 pandas
 proto-plus
 grpc-google-iam-v1
+google-cloud-bigquery
 google-cloud-documentai
 google-cloud-storage
+numpy
 pikepdf

packages/google-cloud-documentai-toolbox/testing/constraints-3.11.txt

@@ -6,6 +6,8 @@ libcst
 pandas
 proto-plus
 grpc-google-iam-v1
+google-cloud-bigquery
 google-cloud-documentai
 google-cloud-storage
+numpy
 pikepdf