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Create Python applications that use pandas and Dash to build Sybase-connected web apps.
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, you will need to 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
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.
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)