How to Build an ETL App for Authorize.Net Data in Python with CData

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

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

Connecting to Authorize.Net Data

Connecting to Authorize.Net 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 obtain the necessary connection properties on the Security Settings -> General Settings page after logging into your Merchant Account.

• UseSandbox: The Authorize.Net API to be used to process transactions. If you are using a production account, this property can be left blank. If you are using a developer test account, set this to 'TRUE'.
• LoginID: The API login Id associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions. Note that this value is not the same as the login Id that you use to log in to the Merchant Interface.
• TransactionKey: The transaction key associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions.

After installing the CData Authorize.Net Connector, follow the procedure below to install the other required modules and start accessing Authorize.Net 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 Authorize.Net 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.authorizenet as mod

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

cnxn = mod.connect("LoginId=MyLoginId;TransactionKey=MyTransactionKey;")

Create a SQL Statement to Query Authorize.Net

Use SQL to create a statement for querying Authorize.Net. In this article, we read data from the SettledBatchList entity.

sql = "SELECT MarketType, TotalCharge FROM SettledBatchList WHERE IncludeStatistics = 'True'"

Extract, Transform, and Load the Authorize.Net Data

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

Loading Authorize.Net Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'settledbatchlist_data.csv')

With the CData Python Connector for Authorize.Net, you can work with Authorize.Net 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 CData Python Connector for Authorize.Net to start building Python apps and scripts with connectivity to Authorize.Net 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.authorizenet as mod

cnxn = mod.connect("LoginId=MyLoginId;TransactionKey=MyTransactionKey;")

sql = "SELECT MarketType, TotalCharge FROM SettledBatchList WHERE IncludeStatistics = 'True'"

table1 = etl.fromdb(cnxn,sql)

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

etl.tocsv(table2,'settledbatchlist_data.csv')