Use Dash to Build to Web Apps on eBay Analytics Data

Ready to get started?

Download for a free trial:

Download Now

Learn more:

eBay Analytics Python Connector

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



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

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

Connecting to eBay Analytics Data

Connecting to eBay Analytics 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.

You can authenticate to eBay Analytics only via the OAuth 2 authentication method. The eBay Analytics API requires an access token created with the authorization code grant flow to authorize the requests.

You can follow the guide in the Help documentation for a step by step guide on how to authenticate using the OAuth 2 protocol.

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

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

cnxn = mod.connect("OAuthClientId=MyAppID;OAuthClientSecret=MyCertID;RuName=MyRuName;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to eBay Analytics

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 ListingName, ClickThroughRate FROM TrafficReportByListing WHERE ListingId = '201284405428'", 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-ebayanalyticsedataplot'

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 eBay Analytics data and configure the app layout.

trace = go.Bar(x=df.ListingName, y=df.ClickThroughRate, name='ListingName')

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='eBay Analytics TrafficReportByListing 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 eBay Analytics data.

python ebayanalytics-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=MyAppID;OAuthClientSecret=MyCertID;RuName=MyRuName;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT ListingName, ClickThroughRate FROM TrafficReportByListing WHERE ListingId = '201284405428'", cnxn)
app_name = 'dash-ebayanalyticsdataplot'

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.ListingName, y=df.ClickThroughRate, name='ListingName')

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='eBay Analytics TrafficReportByListing Data', barmode='stack')
		})
], className="container")

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