Modified blob-triggered azure function

Author: hvalfangst

hvalfangst_function/function_app.py

@@ -13,57 +13,68 @@
 logger = logging.getLogger(__name__)
 
 
-@app.blob_trigger(arg_name="inbound", path="hvalfangstcontainer/in/input.csv", connection="")
-@app.blob_output(arg_name="outbound", path="hvalfangstcontainer/out/statistics.json", connection="")
+@app.blob_trigger(arg_name="inbound", path="hvalfangstcontainer/in/input.csv", connection="AzureWebJobsStorage")
+@app.blob_output(arg_name="outbound", path="hvalfangstcontainer/out/statistics.json", connection="AzureWebJobsStorage")
 def blob_trigger(inbound: func.InputStream, outbound: func.Out[str]):
     try:
+        logging.info("Triggered blob function with blob: %s", inbound.name)
+
         # Read CSV content from the blob
         csv_content = inbound.read().decode("utf-8")
+        logging.info("Read CSV content from blob successfully")
 
         # Convert CSV content to a pandas DataFrame
         df = pd.read_csv(StringIO(csv_content))
+        logging.info("Converted CSV content to DataFrame")
 
         # Label encode 'Gender' and 'State' columns
         label_encoder = LabelEncoder()
         df['Gender'] = label_encoder.fit_transform(df['Gender'])
         df['State'] = label_encoder.fit_transform(df['State'])
+        logging.info("Label encoded 'Gender' and 'State' columns")
 
         # Calculate correlations
         gender_to_income_corr = df[['Gender', 'Income']].corr().iloc[0, 1]
         experience_to_income_corr = df[['Experience', 'Income']].corr().iloc[0, 1]
         state_to_income_corr = df[['State', 'Income']].corr().iloc[0, 1]
+        logging.info("Calculated correlations")
 
         # Create statistics dictionary
         statistics = {
             "gender_to_income_corr": gender_to_income_corr,
             "experience_to_income_corr": experience_to_income_corr,
             "state_to_income_corr": state_to_income_corr
         }
+        logging.info("Created statistics dictionary: %s", statistics)
 
         # Convert statistics to JSON format
         statistics_json = json.dumps(statistics, indent=2)
+        logging.info("Converted statistics to JSON format")
 
         # Upload statistics JSON file to storage account container blob
         outbound.set(statistics_json)
-        logging.info("- - - - - |File 'statistics.json' was uploaded| - - - - - ")
+        logging.info("File 'statistics.json' was uploaded")
 
     except Exception as e:
-        logging.error(f"An error occurred: {str(e)}")
+        logging.error("An error occurred: %s", str(e))
         return f"Error: {str(e)}"
 
 
 @app.route(route="upload_csv", auth_level=func.AuthLevel.ANONYMOUS)
 @app.blob_output(arg_name="outbound", path="hvalfangstcontainer/in/input.csv", connection="")
 def upload_csv(req: func.HttpRequest, outbound: func.Out[str]) -> str:
     try:
+        logging.info("Received HTTP request to upload CSV")
+
         # Parse raw bytes derived from request body to string
         string_body = req.get_body().decode("utf-8")
+        logging.info("Parsed request body to string")
 
         # Upload parsed string body, which conforms to CSV format
         outbound.set(string_body)
-        logging.info("- - - - -  |Successfully uploaded CSV content| - - - - - ")
+        logging.info("Successfully uploaded CSV content")
         return "Successfully uploaded CSV content"
 
     except Exception as e:
-        logging.error(f"An error occurred: {str(e)}")
+        logging.error("An error occurred: %s", str(e))
         return f"Error: {str(e)}"