I have just created a simple bundle with databricks, and is using Databricks connect to debug locally. This is my script:

from pyspark.sql import SparkSession, DataFrame

def get_taxis(spark: SparkSession) -> DataFrame:
  return spark.read.table("samples.nyctaxi.trips")


# Create a new Databricks Connect session. If this fails,
# check that you have configured Databricks Connect correctly.
# See https://docs.databricks.com/dev-tools/databricks-connect.html.
def get_spark() -> SparkSession:
  try:
    from databricks.connect import DatabricksSession
    return DatabricksSession.builder.getOrCreate()
  except ImportError:
    return SparkSession.builder.getOrCreate()

def test_connection():
    try:
        print("Attempting to create Spark session...")
        spark = get_spark()
        print("Successfully created Spark session")
        
        # Test with a simple query first
        print("Testing with a simple query...")
        test_query = "SELECT 1 as test"
        test_df = spark.sql(test_query)
        print("Simple query successful")
        
        # If simple query works, try listing tables
        print("Attempting to list tables...")
        spark.sql("SHOW DATABASES").show()
        
        return spark
        
    except Exception as e:
        print(f"Error type: {type(e).__name__}")
        print(f"Error message: {str(e)}")
        print(f"Error location: {e.__traceback__.tb_frame.f_code.co_filename}:{e.__traceback__.tb_lineno}")
        raise

def main():
    try:
        # First test the connection
        spark = test_connection()
        print("Connection test completed successfully")
        
        # If connection works, proceed with the original code
        print("Proceeding with main query...")
        
        # Define your SQL query
        sql_query = """
        select * from supermarket_dev.streaming_bronze.source_setting where source_application = 'iban'
        """
        
        print(f"Executing query: {sql_query}")
        # Execute the SQL query and convert the results into a DataFrame
        df = spark.sql(sql_query)
        
        print("Query executed successfully")
        print(f"DataFrame is empty: {df.isEmpty()}")
        print(f"DataFrame schema: {df.schema}")
        
        # Show the DataFrame contents
        first = df.first()
        print(f"First row: {first}")

    except Exception as e:
        print(f"Error type: {type(e).__name__}")
        print(f"Error message: {str(e)}")
        print(f"Error location: {e.__traceback__.tb_frame.f_code.co_filename}:{e.__traceback__.tb_lineno}")
        raise

if __name__ == '__main__':
  main()

Every time i call spark.sql then the debugger freezes following and VS code just stands like this:

If I deploy it then I can see it runs through successfully:

Any pointers what to do or what can cause this?