Use Dash to Build to Web Apps on Amazon S3 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 Amazon S3, the pandas module, and the Dash framework, you can build Amazon S3-connected web applications for Amazon S3 data. This article shows how to connect to Amazon S3 with the CData Connector and use pandas and Dash to build a simple web app for visualizing Amazon S3 data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Amazon S3 data in Python. When you issue complex SQL queries from Amazon S3, the driver pushes supported SQL operations, like filters and aggregations, directly to Amazon S3 and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Amazon S3 Data

Connecting to Amazon S3 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 authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

Note: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

After installing the CData Amazon S3 Connector, follow the procedure below to install the other required modules and start accessing Amazon S3 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 Amazon S3 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.amazons3 as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Amazon S3 Connector to create a connection for working with Amazon S3 data.

cnxn = mod.connect("AccessKey=a123;SecretKey=s123;")

Execute SQL to Amazon S3

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 Name, OwnerId FROM ObjectsACL WHERE Name = 'TestBucket'", 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-amazons3edataplot'

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 Amazon S3 data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.OwnerId, name='Name')

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='Amazon S3 ObjectsACL 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 Amazon S3 data.

python amazons3-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Amazon S3 to start building Python apps with connectivity to Amazon S3 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.amazons3 as mod
import plotly.graph_objs as go

cnxn = mod.connect("AccessKey=a123;SecretKey=s123;")

df = pd.read_sql("SELECT Name, OwnerId FROM ObjectsACL WHERE Name = 'TestBucket'", cnxn)
app_name = 'dash-amazons3dataplot'

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.Name, y=df.OwnerId, name='Name')

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='Amazon S3 ObjectsACL Data', barmode='stack')
		})
], className="container")

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