2 Parsing payments

This chapter explains the fundamentals of files formatted by an Automated Clearing House (ACH). You will work on parsing an initial sample file to better understand some of the record layouts used, as well as the software development practice of unit testing. You will also expand your knowledge of generative AI and see how to apply it to a real-world problem.

2.1 Modernizing our legacy software

Now that we have gone through PI planning and have been assigned our project, we will begin working on our first spike. In SAFe, spikes are a type of story, often referred to as an enabler story. A variety of enabler story categories may be used (e.g., exploration, architectural, infrastructure, and compliance). In our case, our story may be classified as an exploration type or a research spike. However, the details are not as important as our activities because the particulars may vary between Agile frameworks. Essentially, this story aims to provide the team with some experience working in Python and learning about the ACH file layout so that we can understand prospective solutions better.

2.2 Understanding the ACH

2.3 Parsing an ACH file

2.3.1 Asking ChatGPT to parse an ACH file

2.3.2 Parsing an ACH file with Copilot

2.3.3 Generative AI: Trust but verify

2.4 Automated testing

2.4.1 Testing the number of records read

2.4.2 Parsing the records

2.4.3 File header record (type 1)

2.4.4 Batch header record (type 5)

2.5 Entry detail record (type 6)

2.5.1 Addenda record (type 7)

2.5.2 Batch control record (type 8)

2.5.3 File trailer record (type 9)