Use Dash to Build to Web Apps on TaxJar Data

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TaxJar Python Connector

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



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

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

Connecting to TaxJar Data

Connecting to TaxJar 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 authenticate to the TaxJar API, you will need to first obtain the API Key from the TaxJar UI.

NOTE: the API is available only for Professional and Premium TaxJar plans.

If you already have a Professional or Premium plan you can find the API Key by logging in the TaxJar UI and navigating to Account -> TaxJar API. After obtaining the API Key, you can set it in the APIKey connection property.

Additional Notes

  • By default, the CData connector will retrieve data of the last 3 months in cases where the entity support date range filtering. You can set StartDate to specify the minimum creation date of the data retrieved.
  • If the API Key has been created for a sandbox API account please set UseSandbox to true, but not all endpoints will work as expected. For more information, refer to the TaxJar developer documentation.

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

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

cnxn = mod.connect("APIKey=3bb04218ef8t80efdf1739abf7257144;")

Execute SQL to TaxJar

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 TransactionID, UserID FROM Orders WHERE TransactionID = '123'", 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-taxjaredataplot'

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 TaxJar data and configure the app layout.

trace = go.Bar(x=df.TransactionID, y=df.UserID, name='TransactionID')

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='TaxJar 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 TaxJar data.

python taxjar-dash.py

Free Trial & More Information

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

cnxn = mod.connect("APIKey=3bb04218ef8t80efdf1739abf7257144;")

df = pd.read_sql("SELECT TransactionID, UserID FROM Orders WHERE TransactionID = '123'", cnxn)
app_name = 'dash-taxjardataplot'

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.TransactionID, y=df.UserID, name='TransactionID')

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

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