Ready to get started?

Learn more about the CData Python Connector for DigitalOcean or download a free trial:

Download Now

Use Dash to Build to Web Apps on DigitalOcean Data

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

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

Connecting to DigitalOcean Data

Connecting to DigitalOcean 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.

DigitalOcean uses OAuth 2.0 authentication. To authenticate using OAuth, you can use the embedded credentials or register an app with DigitalOcean.

See the Getting Started guide in the CData driver documentation for more information.

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

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

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to DigitalOcean

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, Name FROM Droplets WHERE Id = '1'", 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-digitaloceanedataplot'

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 DigitalOcean data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.Name, 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='DigitalOcean Droplets 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 DigitalOcean data.

python digitalocean-dash.py

Free Trial & More Information

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

cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, Name FROM Droplets WHERE Id = '1'", cnxn)
app_name = 'dash-digitaloceandataplot'

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.Name, 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='DigitalOcean Droplets Data', barmode='stack')
		})
], className="container")

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