Connect a Python Application (SQL Alchemy) to Streambased

The Python programming language has a number of powerful libraries like Pandas for data manipulation and analytics workloads. Let's add some real-time data.

Prerequisites:

• A running Streambased instance, for instructions see here

• A Python installation with the following extra packages:

  • sqlalchemy-trino

Step 1: Create a python application

The following sample code show how to integrate python with Streambased cloud:

import sqlalchemy

from sqlalchemy as db
server_host='[server host]'
server_port='[server port]'
engine = sqlalchemy.create_engine(f"trino://{server_host}:{server_port}/kafka",
                       connect_args ={"schema":"streambased"})

conn = engine.connect() 
query = "select * from purchases limit 100"
exe = conn.execute(query) 
result = exe.fetchmany(5) 
print(result)

By default server port is 8080 and server host is the name of the host on which the docker instance has been launched.

Step 2: Experiment

Change the query variable to execute different statement in your python environment