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Use Dash to Build to Web Apps on WooCommerce Data

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

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

Connecting to WooCommerce Data

Connecting to WooCommerce 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.

WooCommerce supports the following authentication methods: one-legged OAuth1.0 Authentication and standard OAuth2.0 Authentication.

Connecting using one-legged OAuth 1.0 Authentication

Specify the following properties (NOTE: the below credentials are generated from WooCommerce settings page and should not be confused with the credentials generated by using WordPress OAuth2.0 plugin):

  • ConsumerKey
  • ConsumerSecret

Connecting using WordPress OAuth 2.0 Authentication

After having configured the plugin, you may connect to WooCommerce by providing the following connection properties:

  • OAuthClientId
  • OAuthClientSecret
  • CallbackURL
  • InitiateOAuth - Set this to either GETANDREFRESH or REFRESH

In either case, you will need to set the Url property to the URL of the WooCommerce instance.

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

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

cnxn = mod.connect("Url=https://example.com/; ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad; ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5; InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to WooCommerce

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 ParentId, Total FROM Orders WHERE ParentId = '3'", 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-woocommerceedataplot'

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 WooCommerce data and configure the app layout.

trace = go.Bar(x=df.ParentId, y=df.Total, name='ParentId')

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='WooCommerce 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 WooCommerce data.

python woocommerce-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Url=https://example.com/; ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad; ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5; InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT ParentId, Total FROM Orders WHERE ParentId = '3'", cnxn)
app_name = 'dash-woocommercedataplot'

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.ParentId, y=df.Total, name='ParentId')

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

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