Use Dash to Build to Web Apps on Redis Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Redis, the pandas module, and the Dash framework, you can build Redis-connected web applications for Redis data. This article shows how to connect to Redis with the CData Connector and use pandas and Dash to build a simple web app for visualizing Redis data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Redis data in Python. When you issue complex SQL queries from Redis, the driver pushes supported SQL operations, like filters and aggregations, directly to Redis and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Redis Data

Connecting to Redis data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Set the following connection properties to connect to a Redis instance:

• : Set this to the name or address of the server your Redis instance is running on. You can specify the port in .
• : Set this to the password used to authenticate with a password-protected Redis instance , using the Redis AUTH command.

Set to negotiate SSL/TLS encryption when you connect.

After installing the CData Redis Connector, follow the procedure below to install the other required modules and start accessing Redis through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Redis Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.redis as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Redis Connector to create a connection for working with Redis data.

cnxn = mod.connect("Server=127.0.0.1;Port=6379;Password=myPassword;")

Execute SQL to Redis

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT City, CompanyName FROM Customers WHERE Country = 'US'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-redisedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Redis data and configure the app layout.

trace = go.Bar(x=df.City, y=df.CompanyName, name='City')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Redis Customers Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
 app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Redis data.

python redis-dash.py

👁 Redis data in a Dash web app (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Redis to start building Python apps with connectivity to Redis data. Reach out to our Support Team if you have any questions.

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Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.redis as mod
import plotly.graph_objs as go

cnxn = mod.connect("Server=127.0.0.1;Port=6379;Password=myPassword;")

df = pd.read_sql("SELECT City, CompanyName FROM Customers WHERE Country = 'US'", cnxn)
app_name = 'dash-redisdataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.City, y=df.CompanyName, name='City')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Redis Customers Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
 app.run_server(debug=True)