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

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

Connecting to Sybase Data

Connecting to Sybase 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 Sybase, specify the following connection properties:

• Server: Set this to the name or network address of the Sybase database instance.
• Database: Set this to the name of the Sybase database running on the specified Server.

Optionally, you can also secure your connections with TLS/SSL by setting UseSSL to true.

Sybase supports several methods for authentication including Password and Kerberos.

Connect Using Password Authentication

Set the AuthScheme to Password and set the following connection properties to use Sybase authentication.

• User: Set this to the username of the authenticating Sybase user.
• Password: Set this to the username of the authenticating Sybase user.

Connect using LDAP Authentication

To connect with LDAP authentication, configure Sybase server-side to use the LDAP authentication mechanism.

After configuring Sybase for LDAP, you can connect using the same credentials as Password authentication.

Connect Using Kerberos Authentication

To leverage Kerberos authentication, begin by enabling it setting AuthScheme to Kerberos. See the Using Kerberos section in the Help documentation for more information on using Kerberos authentication.

You can find an example connection string below:

Server=MyServer;Port=MyPort;User=SampleUser;Password=SamplePassword;Database=MyDB;Kerberos=true;KerberosKDC=MyKDC;KerberosRealm=MYREALM.COM;KerberosSPN=server-name

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;Charset=iso_1;")

Execute SQL to Sybase

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 Id, ProductName FROM Products WHERE ProductName = 'Konbu'", 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-sybaseedataplot'

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 Sybase data and configure the app layout.

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

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='Sybase Products 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 Sybase data.

python sybase-dash.py

👁 Sybase 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 Sybase to start building Python apps with connectivity to Sybase 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.sybase as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;Charset=iso_1;")

df = pd.read_sql("SELECT Id, ProductName FROM Products WHERE ProductName = 'Konbu'", cnxn)
app_name = 'dash-sybasedataplot'

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

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='Sybase Products Data', barmode='stack')
		})
], className="container")

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