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

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Extract and transform live Authorize.Net data in Python with petl and the CData Connect AI Python SDK.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK 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 Connect AI and use petl to extract, transform, and load Authorize.Net data.

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so petl can read directly from the SDK connection with etl.fromdb. There is no driver to install per source: connect with a Personal Access Token and build your pipeline.

Connect to Authorize.Net in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "Authorize.Net" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to Authorize.Net.

    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.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update the user-based permissions. Updating permissions

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

  1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. Creating a new PAT
  4. The PAT is only visible at creation, so copy it and store it securely.

Install Required Modules

Install the SDK and the petl framework using the pip utility:

pip install cdata-connect-ai
pip install petl

Build an ETL App for Authorize.Net Data in Python

Once the required modules are installed, you are ready to build the ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, import the modules and connect to Connect AI with your account email and PAT:

import petl as etl
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

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. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, AuthorizeNet1).

sql = (
    "SELECT MarketType, TotalCharge "
    "FROM [AuthorizeNet1].[AuthorizeNet].[SettledBatchList] "
    "WHERE IncludeStatistics = 'True'"
)

Extract, Transform, and Load the Authorize.Net Data

With a connection and query in hand, 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.

table1 = etl.fromdb(conn, sql)

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

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

Authorize.Net is a read-only source in Connect AI, so this pipeline can extract and transform Authorize.Net data but not load rows back. Close the connection when the extract is complete:

conn.close()

With the CData Connect AI Python SDK, you can work with Authorize.Net data just like you would with any database, including direct access to data in ETL packages like petl.

More Information and Free Trial

Now you can pipe live Authorize.Net data through petl using the CData Connect AI Python SDK. For more information on connecting to Authorize.Net (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building data pipelines for live Authorize.Net data in Python.



Full Source Code

import petl as etl
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

sql = (
    "SELECT MarketType, TotalCharge "
    "FROM [AuthorizeNet1].[AuthorizeNet].[SettledBatchList] "
    "WHERE IncludeStatistics = 'True'"
)

table1 = etl.fromdb(conn, sql)

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

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

Ready to get started?

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