Extract, Transform, and Load Avalara AvaTax Data in Python

Ready to get started?

Download a free trial of the Avalara Connector to get started:

 Download Now

Learn more:

Avalara AvaTax Icon Avalara Python Connector

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

The CData Python Connector for Avalara AvaTax enables you to create ETL applications and pipelines for Avalara AvaTax data in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Avalara AvaTax and the petl framework, you can build Avalara AvaTax-connected applications and pipelines for extracting, transforming, and loading Avalara AvaTax data. This article shows how to connect to Avalara AvaTax with the CData Python Connector and use petl and pandas to extract, transform, and load Avalara AvaTax data.

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

Connecting to Avalara AvaTax Data

Connecting to Avalara AvaTax 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.

The primary method for performing basic authentication is to provide your login credentials, as follows:

  • User: Set this to your username.
  • Password: Set this to your password.

Optionally, if you are making use of a sandbox environment, set the following:

  • UseSandbox: Set this to true if you are authenticating with a sandbox account.

Authenticating Using Account Number and License Key

Alternatively, you can authenticate using your account number and license key. Connect to data using the following:

  • AccountId: Set this to your Account Id. The Account Id is listed in the upper right hand corner of the admin console.
  • LicenseKey: Set this to your Avalara Avatax license key. You can generate a license key by logging into Avalara Avatax as an account administrator and navigating to Settings -> Reset License Key.

After installing the CData Avalara AvaTax Connector, follow the procedure below to install the other required modules and start accessing Avalara AvaTax through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Avalara AvaTax Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL 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 petl as etl
import pandas as pd
import cdata.avalaraavatax as mod

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

cnxn = mod.connect("User=MyUser;Password=MyPassword;")

Create a SQL Statement to Query Avalara AvaTax

Use SQL to create a statement for querying Avalara AvaTax. In this article, we read data from the Transactions entity.

sql = "SELECT Id, TotalTax FROM Transactions WHERE Code = '051349'"

Extract, Transform, and Load the Avalara AvaTax Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Avalara AvaTax data. In this example, we extract Avalara AvaTax data, sort the data by the TotalTax column, and load the data into a CSV file.

Loading Avalara AvaTax Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'TotalTax')


In the following example, we add new rows to the Transactions table.

Adding New Rows to Avalara AvaTax

table1 = [ ['Id','TotalTax'], ['NewId1','NewTotalTax1'], ['NewId2','NewTotalTax2'], ['NewId3','NewTotalTax3'] ]

etl.appenddb(table1, cnxn, 'Transactions')

With the CData Python Connector for Avalara AvaTax, you can work with Avalara AvaTax data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the Avalara AvaTax Python Connector to start building Python apps and scripts with connectivity to Avalara AvaTax data. Reach out to our Support Team if you have any questions.

Full Source Code

import petl as etl
import pandas as pd
import cdata.avalaraavatax as mod

cnxn = mod.connect("User=MyUser;Password=MyPassword;")

sql = "SELECT Id, TotalTax FROM Transactions WHERE Code = '051349'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'TotalTax')


table3 = [ ['Id','TotalTax'], ['NewId1','NewTotalTax1'], ['NewId2','NewTotalTax2'], ['NewId3','NewTotalTax3'] ]

etl.appenddb(table3, cnxn, 'Transactions')