This lesson focuses on the IBM i side: creating Physical Files (PFs) for data storage and structures, then building a robust RPGLE program for CRUD basics. By the end, you'll have a callable module ready to power API endpoints. No prior web service experience required, just solid RPGLE fundamentals.
Why Use RPGLE for Web Services?
IBM i handles high-volume transactions well, such as in banking or inventory. Expose that with RESTful APIs. Keep data logic in RPGLE for rules, validation, and I/O. Use JavaScript for HTTP. You gain these.
Enough burble... we now what we want to do "learn how to create a simple webservice using iTOOLKIT and RPGLE" so let's dive in let's build the database foundation and an RPGLE program to read and serve that as a webservice. Then we will cover the JS wrapper and go through some testing with a free tool like SOAPUI or Postman.
Step 1: Set Up Test Data with Physical Files
Define our database first, we will create a very simple physical file for food ingredients - this is how you guess I am feeling hungry!
First let's create a sample library (aka schema) for this example:
TYPE(*TEST)
TEXT('Sample Library for WEBSERVICE Lesson')
CRTAUT(*USE)
Here’s a classic DDS layout for FOODFILE, because this webservice will track basic ingredient info:
A INGID 10S 0 TEXT('Ingredient ID')
A INGNAME 30A TEXT('Ingredient Name')
A CATEGORY 20A TEXT('Ingredient Category')
A MEASURE 10A TEXT('Measurement Unit')
A QUANTITY 7S 2 TEXT('Quantity Available')
A EXPDATE L TEXT('Expiration Date')
A ORGANIC 1A TEXT('Organic? Y/N')
A K INGID
Let's assume each of these fields (aka Columns) means this:
INGID: Primary key, numeric ID.
INGNAME: Ingredient name (e.g., "Tomato").
CATEGORY: Type (e.g., "Vegetable", "Spice").
MEASURE : Measurement unit (e.g., "grams", "ml").
QUANTITY: Decimal quantity.
EXPDATE: Expiration date.
ORGANIC: Flag for organic status.
Create this DDS in an IBM i Source File, or from your VSCode development environment. Once created you need to populate it with some sample data. You can use DFU to manually enter the data.
Alternately - let's give old fashioned DDS the boot and do this simply, quickly and easily with SQL:
SQL DDL Equivalent
If you're modernizing with SQL, here’s the equivalent CREATE TABLE statement:
INGID DECIMAL(10,0) NOT NULL PRIMARY KEY,
INGNAME VARCHAR(30) NOT NULL,
CATEGORY VARCHAR(20),
MEASURE VARCHAR(10),
QUANTITY DECIMAL(7,2),
EXPDATE DATE,
ORGANIC CHAR(1) CHECK (ORGANIC IN ('Y', 'N'))
);
SQL Enhancements:
VARCHAR allows flexible text storage.
CHECK constraint ensures valid organic flag.
DATE type for expiration is more precise than L in DDS.
Bonus: Sample Insert
Now lets throw in some sample data for using in our code examples
(1001, 'Tomato', 'Vegetable', 'grams', 250.00, '2025-11-01', 'Y'),
(1002, 'Basil', 'Herb', 'grams', 50.00, '2026-06-15', 'Y'),
(1003, 'Olive Oil', 'Pantry', 'ml', 500.00, '2027-03-01', 'N'),
(1004, 'Parmesan', 'Dairy', 'grams', 200.00, '2025-12-10', 'N'),
(1005, 'Black Pepper','Spice', 'grams', 30.00, '2028-01-01', 'N');
We now have a sample file, ready to be served up to the internet, or any external system.
But first, let's consider some important security considerations.