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

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

Connecting to Teradata Data

Connecting to Teradata 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.

To connect to Teradata, provide authentication information and specify the database server name.

• User: Set this to the username of a Teradata user.
• Password: Set this to the password of the Teradata user.
• DataSource: Specify the Teradata server name, DBC Name, or TDPID.
• Port: Specify the port the server is running on.
• Database: Specify the database name. If not specified, the default database is used.

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;")

Execute SQL to Teradata

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 ProductId, ProductName FROM NorthwindProducts WHERE CategoryId = '5'", 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-teradataedataplot'

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 Teradata data and configure the app layout.

trace = go.Bar(x=df.ProductId, y=df.ProductName, name='ProductId')

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='Teradata 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 Teradata data.

python teradata-dash.py

👁 Teradata 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 Teradata to start building Python apps with connectivity to Teradata 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.teradata as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;")

df = pd.read_sql("SELECT ProductId, ProductName FROM NorthwindProducts WHERE CategoryId = '5'", cnxn)
app_name = 'dash-teradatadataplot'

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.ProductId, y=df.ProductName, name='ProductId')

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

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