Streamlit Integration

Warning

This module is a Beta Feature and is subject to change. To enable this functionality for testing please follow the configuration instructions here setting PYKX_BETA_FEATURES='true'

This functionality is presently not supported on Windows, for full utilisation of this functionality PYKX_THREADING='true' nust be set in configuration.

Introduction

Streamlit provides an open source framework allowing users to turn Python scripts into sharable web applications. Functionally, Streamlit provides access to external data-sources using the concept of connections which allow users to develop conforming APIs which will integrate directly with streamlit applications as extension connection types.

The integration outlined below makes use of this by generating a new pykx.streamlit.PyKXConnection connection type which provides the ability to create synchronous connections to existing q/kdb+ sessions.

A full breakdown of the API documentation of this class can be found here.

Requirements and limitations

To run this functionality, users must have streamlit>=1.28 installed local to their Python session.

This can be installed using the following command:

pip install pykx[streamlit]

Functional walkthrough

This walkthrough will demonstrate the following steps:

1. Initialize a q/kdb+ server on a specified port and populating some data.
2. Generate a streamlit.py script which queries the q server and creates a basic streamlit application.
3. Run the streamlit application and view locally

Initializing a q/kdb+ server

This step ensures you have a q process running and a kdb+ table available to query. If you have this already, proceed to the next step.

Ensure that you have q installed. If you do not have this installed please follow the guide provided here, retrieving your license following the instructions provided here.

q -p 5050

Create a table which you will use within your Python analytics defined below.

q)N:1000
q)tab:([]sym:N?`AAPL`MSFT`GOOG`FDP;price:100+N?100f;size:10+N?100)

Set a requirement for users to provide a username/password if you wish to add security to your q process.

.z.pw:{[u;p]$[(u~`user)&p~`password;1b;0b]}

Generate a streamlit script/application

The following script generates a simple streamlit application which:

1. Set environment variables and import required libraries
2. Define a function to run for generation of the streamlit application
   1. Name the streamlit application.
   2. Create a connection to the q process initialized on port 5050 above.
   3. Query the q process retrieving a small tabular subset of data using a qsql statement.
   4. Generate a Matplotlib graph directly using the PyKX table.
   5. Display both the table and graph

This script can additionally be downloaded here.

# Set environment variables needed to run Steamlit integration
import os
os.environ['PYKX_BETA_FEATURES'] = 'true'

# This is optional but suggested as without it's usage caching
# is not supported within streamlit
os.environ['PYKX_THREADING'] = 'true'

import streamlit as st
import pykx as kx
import matplotlib.pyplot as plt

def main():
    st.header('PyKX Demonstration')
    connection = st.connection('pykx',
                               type=kx.streamlit.PyKXConnection,
                               port=5050,
                               username='user',
                               password='password')
    if connection.is_healthy():
        tab = connection.query('select from tab where size<11')
    else:
        raise kx.QError('Connection object was not deemed to be healthy')
    fig, x = plt.subplots()
    x.scatter(tab['size'], tab['price'])

    st.write('Queried kdb+ remote table')
    st.write(tab)

    st.write('Generated plot')
    st.pyplot(fig)

if __name__ == "__main__":
   try:
       main()
   finally:
       kx.shutdown_thread()