Python Program Structure for OpenAPI Integration

docs/api/datahub-apis.md

@@ -38,6 +38,77 @@ Learn more about the GraphQL API:
 
 - **[GraphQL API →](docs/api/graphql/getting-started.md)**
 
+## Python Program Structure for OpenAPI Integration
+
+This section provides a detailed guide on structuring a Python program for creating a `schemaField` for a BigQuery column using DataHub's OpenAPI. This guide is intended for developers looking to programmatically interact with DataHub using Python.
+
+### Prerequisites
+- Install the `requests` library: `pip install requests`
+- Set up any necessary authentication for interacting with DataHub's API.
+
+### Schema Field Definition
+Define a schema field in Python, including necessary attributes and types. Example:
+```python
+schema_field = {
+    "fieldPath": "column_name",
+    "type": {
+        "type": {
+            "__type": "StringType"
+        }
+    },
+    "nativeDataType": "STRING"
+}
+```
+
+### API Request Construction
+Construct the API request by setting up headers, defining the payload, and handling the response. Example:
+```python
+import requests
+import json
+
+# Define the DataHub server URL
+datahub_url = "http://localhost:8080"
+
+# Define the dataset URN
+dataset_urn = "urn:li:dataset:(urn:li:dataPlatform:bigquery,project.dataset.table,PROD)"
+
+# Define the SchemaMetadata aspect
+schema_metadata = {
+    "__type": "SchemaMetadata",
+    "schemaName": "SampleSchema",
+    "platform": "urn:li:dataPlatform:bigquery",
+    "fields": [schema_field]
+}
+
+# Define the request payload
+payload = {
+    "aspect": schema_metadata,
+    "entityType": "dataset",
+    "entityUrn": dataset_urn
+}
+
+# Set up headers, including authentication if needed
+headers = {
+    "Content-Type": "application/json",
+    # "Authorization": "Bearer YOUR_ACCESS_TOKEN"  # Uncomment if authentication is required
+}
+
+# Make the POST request to the DataHub OpenAPI endpoint
+response = requests.post(f"{datahub_url}/entities", headers=headers, data=json.dumps(payload))
+
+# Check the response
+if response.status_code == 200:
+    print("Schema field created successfully!")
+else:
+    print(f"Failed to create schema field: {response.status_code} - {response.text}")
+```
+
+### Error Handling
+Implement best practices for error handling when making API requests.
+
+### Authentication
+Detailed steps on how to authenticate requests, especially if DataHub requires specific authentication methods.
+
 ## DataHub API Comparison
 
 DataHub supports several APIs, each with its own unique usage and format.

docs/api/openapi/openapi-usage-guide.md

@@ -26,6 +26,26 @@ in the OpenAPI UI are all autogenerated at build time from the PDL models to JSO
 
 While the full OpenAPI spec is always available at [**GMS_SERVER_HOST:GMS_PORT/openapi/swagger-ui/index.html**](http://localhost:8080/openapi/swagger-ui/index.html), here's a quick overview of the main OpenAPI endpoints and their purpose.
 
+### Python Program Structure for OpenAPI Integration
+
+This section provides a detailed guide on structuring a Python program for creating a `schemaField` for a BigQuery column using DataHub's OpenAPI. This guide is intended for developers looking to programmatically interact with DataHub using Python.
+
+#### Prerequisites
+- Install the `requests` library using `pip install requests`.
+- Set up any necessary authentication for interacting with DataHub's API.
+
+#### Schema Field Definition
+- Define a schema field in Python, specifying necessary attributes and types.
+
+#### API Request Construction
+- Construct the API request by setting up headers, defining the payload, and handling the response.
+
+#### Error Handling
+- Implement best practices for error handling when making API requests.
+
+#### Authentication
+- Follow detailed steps to authenticate requests, especially if DataHub requires specific authentication methods.
+
 
 ### Entities (/entities)