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Use Dash to Build to Web Apps on eBay Data

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

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

Connecting to eBay Data

Connecting to eBay 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.

If you will be accessing your own account, you can generate an OAuthAccessToken from your developer account dashboard. You can also allow other users to securely access their own accounts.

Both of these methods require you to create an application key set to obtain values for the following connection properties: AppId, CertId, DevId, and SiteId.

The user consent flow additionally requires the RuName and CallbackURL.

See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

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

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

cnxn = mod.connect("AppId=MyAppId;CertId=MyCertId;DevId=MyDevId;SiteId=MySiteId;RuName=MyRuName;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to eBay

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 Title, HitCount FROM ItemListing WHERE ListingStatus = 'active'", 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-ebayedataplot'

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 data and configure the app layout.

trace = go.Bar(x=df.Title, y=df.HitCount, name='Title')

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 ItemListing 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 data.

python ebay-dash.py

Free Trial & More Information

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

cnxn = mod.connect("AppId=MyAppId;CertId=MyCertId;DevId=MyDevId;SiteId=MySiteId;RuName=MyRuName;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Title, HitCount FROM ItemListing WHERE ListingStatus = 'active'", cnxn)
app_name = 'dash-ebaydataplot'

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.Title, y=df.HitCount, name='Title')

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

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