Use Dash to Build to Web Apps on Azure Table 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 Azure, the pandas module, and the Dash framework, you can build Azure Table-connected web applications for Azure Table data. This article shows how to connect to Azure Table with the CData Connector and use pandas and Dash to build a simple web app for visualizing Azure Table data.

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

Connecting to Azure Table Data

Connecting to Azure Table 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.

Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

After installing the CData Azure Table Connector, follow the procedure below to install the other required modules and start accessing Azure Table 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 Azure Table 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.azuretables as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("AccessKey=myAccessKey;Account=myAccountName;")

Execute SQL to Azure Table

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 Name, Price FROM NorthwindProducts WHERE ShipCity = 'New York'", 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-azuretablesedataplot'

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 Azure Table data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.Price, name='Name')

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='Azure Table NorthwindProducts 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 Azure Table data.

python azuretables-dash.py

Free Trial & More Information

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

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.azuretables as mod
import plotly.graph_objs as go

cnxn = mod.connect("AccessKey=myAccessKey;Account=myAccountName;")

df = pd.read_sql("SELECT Name, Price FROM NorthwindProducts WHERE ShipCity = 'New York'", cnxn)
app_name = 'dash-azuretablesdataplot'

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.Name, y=df.Price, name='Name')

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='Azure Table NorthwindProducts Data', barmode='stack')
		})
], className="container")

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