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Python Connector Libraries for Amazon Marketplace Data Connectivity. Integrate Amazon Marketplace with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use Dash to Build to Web Apps on Amazon Marketplace Data



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

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

Connecting to Amazon Marketplace Data

Connecting to Amazon Marketplace 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 the Amazon Marketplace Webservice (MWS), AWSAccessKeyId, MWSAuthToken, AWSSecretKey and SellerId are required. You can optionally set the Marketplace property. For more information on obtaining values for these properties, refer to the Help documentation.

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

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

cnxn = mod.connect("AWS Access Key Id=myAWSAccessKeyId;AWS Secret Key=myAWSSecretKey;MWS Auth Token=myMWSAuthToken;Seller Id=mySellerId;Marketplace=United States;")

Execute SQL to Amazon Marketplace

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 AmazonOrderId, OrderStatus FROM Orders WHERE IsReplacementOrder = 'True'", 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-amazonmarketplaceedataplot'

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 Marketplace data and configure the app layout.

trace = go.Bar(x=df.AmazonOrderId, y=df.OrderStatus, name='AmazonOrderId')

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 Marketplace 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 Amazon Marketplace data.

python amazonmarketplace-dash.py

Free Trial & More Information

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

cnxn = mod.connect("AWS Access Key Id=myAWSAccessKeyId;AWS Secret Key=myAWSSecretKey;MWS Auth Token=myMWSAuthToken;Seller Id=mySellerId;Marketplace=United States;")

df = pd.read_sql("SELECT AmazonOrderId, OrderStatus FROM Orders WHERE IsReplacementOrder = 'True'", cnxn)
app_name = 'dash-amazonmarketplacedataplot'

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.AmazonOrderId, y=df.OrderStatus, name='AmazonOrderId')

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

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