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Use Dash to Build to Web Apps on Greenplum Data

The CData Python Connector for Greenplum enables you to create Python applications that use pandas and Dash to build Greenplum-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 Greenplum, the pandas module, and the Dash framework, you can build Greenplum-connected web applications for Greenplum data. This article shows how to connect to Greenplum with the CData Connector and use pandas and Dash to build a simple web app for visualizing Greenplum data.

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

Connecting to Greenplum Data

Connecting to Greenplum 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 Greenplum, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the default database for the authenticate user is used.

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

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

cnxn = mod.connect("User=user;Password=admin;Database=dbname;Server=127.0.0.1;Port=5432;")

Execute SQL to Greenplum

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 Freight, ShipName 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-greenplumedataplot'

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 Greenplum data and configure the app layout.

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

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='Greenplum 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 Greenplum data.

python greenplum-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Greenplum Python Connector to start building Python apps with connectivity to Greenplum 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.greenplum as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=user;Password=admin;Database=dbname;Server=127.0.0.1;Port=5432;")

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

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

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

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