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

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

Connecting to EnterpriseDB Data

Connecting to EnterpriseDB 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.

The following connection properties are required in order to connect to data.

• Server: The host name or IP of the server hosting the EnterpriseDB database.
• Port: The port of the server hosting the EnterpriseDB database.

You can also optionally set the following:

• Database: The default database to connect to when connecting to the EnterpriseDB Server. If this is not set, the user's default database will be used.

Connect Using Standard Authentication

To authenticate using standard authentication, set the following:

• User: The user which will be used to authenticate with the EnterpriseDB server.
• Password: The password which will be used to authenticate with the EnterpriseDB server.

Connect Using SSL Authentication

You can leverage SSL authentication to connect to EnterpriseDB data via a secure session. Configure the following connection properties to connect to data:

• SSLClientCert: Set this to the name of the certificate store for the client certificate. Used in the case of 2-way SSL, where truststore and keystore are kept on both the client and server machines.
• SSLClientCertPassword: If a client certificate store is password-protected, set this value to the store's password.
• SSLClientCertSubject: The subject of the TLS/SSL client certificate. Used to locate the certificate in the store.
• SSLClientCertType: The certificate type of the client store.
• SSLServerCert: The certificate to be accepted from the server.

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

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

cnxn = mod.connect("User=postgres;Password=admin;Database=postgres;Server=127.0.0.1;Port=5444")

Execute SQL to EnterpriseDB

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 ShipName, ShipCity FROM Orders WHERE ShipCountry = 'USA'", 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-enterprisedbedataplot'

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 EnterpriseDB data and configure the app layout.

trace = go.Bar(x=df.ShipName, y=df.ShipCity, name='ShipName')

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='EnterpriseDB Orders 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 EnterpriseDB data.

python enterprisedb-dash.py

👁 EnterpriseDB 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 EnterpriseDB to start building Python apps with connectivity to EnterpriseDB 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.enterprisedb as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=postgres;Password=admin;Database=postgres;Server=127.0.0.1;Port=5444")

df = pd.read_sql("SELECT ShipName, ShipCity FROM Orders WHERE ShipCountry = 'USA'", cnxn)
app_name = 'dash-enterprisedbdataplot'

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.ShipName, y=df.ShipCity, name='ShipName')

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='EnterpriseDB Orders Data', barmode='stack')
		})
], className="container")

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