Good Morning All -
This didn't seem like such a daunting task until I tried it. Of course, it's my very first function in Unity Catalog.
Attached are images of both the UDF and example usage I created to send messages via the Python requests library within the UDF. I'll see if I can paste in the code below.
The UDF is supplied with a URL and payload (JSON - Adaptative card for MS Teams). It should send the payload as a Teams message and works as intended when defined internally within a Python notebook. But when defined within UC and executed from a notebook, it sends no message and returns no errors.
I would appreciate it if one of you experts would eyeball this thing and pull me out of the weeds. I can't believe I'm the first one to try this although hours spent researching it has only resulted in references to defining the processing internally within the notebook.
==================== UDF ===========================
CREATE OR REPLACE FUNCTION mycatalog.myschema.udf_send_post_request(
url STRING,
payload STRING
)
RETURNS STRING
LANGUAGE PYTHON
AS
$$
import requests
import json
def udf_send_post_request(url, payload):
try:
# Convert payload from string to JSON
payload_json = json.loads(payload)
response = requests.post(url, json=payload_json)
response.raise_for_status() # Raise an error for bad status codes
return response.text
except requests.exceptions.RequestException as e:
return f"Error: {e}"
$$;
==================== USAGE ===========================
# Set the catalog and schema
spark.sql("USE CATALOG mycatalog")
spark.sql("USE SCHEMA myschema")
# Example usage
url = "myURL"
payload = {
"type": "AdaptiveCard",
"attachments": [
{
"contentType": "application/vnd.microsoft.card.adaptive",
"content": {
"$schema": "http://adaptivecards.io/schemas/adaptive-card.json",
"type": "AdaptiveCard",
"version": "1.2",
"body": [
{
"type": "TextBlock",
"text": "**TEST EXTERNAL FUNCTION**",
}
]
}
}
]
}
payload_str = json.dumps(payload)
# Create a DataFrame with the URL and payload
df = spark.createDataFrame([(url, payload_str)], ["url", "payload"])
# Use the function in a SQL query
df.createOrReplaceTempView("temp_table")
result = spark.sql(f"""SELECT udf_send_post_request(url, payload) AS response FROM temp_table""")
result.show()
Thank You for Any & All Input,
Bob
