ABAP String to JSON: Conversion Techniques and Examples

Converting String to JSON in SAP ABAP

In SAP ABAP, converting a string into a JSON object typically involves using /UI2/CL_JSON or CALL TRANSFORMATION methods. Below are different approaches.

1. Using `/UI2/CL_JSON` (Recommended for Standard Cases)

The class /UI2/CL_JSON helps convert a JSON string into an ABAP structure or internal table.

Example: Convert JSON String to ABAP Structure

DATA: lv_json  TYPE string,
      ls_data  TYPE ty_json_data.  " Define your structure

lv_json = '{ "name": "SAP", "year": 2025 }'.

TRY.
    /ui2/cl_json=>deserialize(
      EXPORTING json = lv_json
      CHANGING  data = ls_data
    ).
    WRITE: 'Name:', ls_data-name, 'Year:', ls_data-year.
  CATCH cx_root INTO DATA(lx_error).
    WRITE: 'JSON Parsing Error:', lx_error->get_text( ).
ENDTRY.

✅ Converts JSON to an ABAP structure ❌ Requires structure definition before parsing

2. Using `CALL TRANSFORMATION` (For XML-like JSON Parsing)

You can also use CALL TRANSFORMATION to parse JSON into ABAP.

Example: Convert JSON to ABAP Structure

DATA: lv_json  TYPE string VALUE '{ "product": "ABAP", "version": "7.5" }',
      ls_data  TYPE ty_json_data.

CALL TRANSFORMATION id
  SOURCE XML lv_json
  RESULT ls_data.

WRITE: ls_data-product, ls_data-version.

✅ Works well for simple JSON ❌ Limited when dealing with nested structures

3. Converting JSON String to Internal Table

If your JSON contains multiple entries, convert it into an internal table.

Example: Convert JSON Array to Internal Table

DATA: lv_json TYPE string,
      lt_table TYPE TABLE OF ty_json_table.

lv_json = '[{ "id": 1, "name": "Alice" }, { "id": 2, "name": "Bob" }]'.

/ui2/cl_json=>deserialize(
  EXPORTING json = lv_json
  CHANGING  data = lt_table
).

LOOP AT lt_table INTO DATA(ls_row).
  WRITE: / ls_row-id, ls_row-name.
ENDLOOP.

✅ Parses JSON arrays into an internal table ❌ Requires correct field structure

4. Handling Nested JSON Objects

For deeply nested JSON, define nested structures.

Example: Handling Nested JSON

TYPES: BEGIN OF ty_address,
         city  TYPE string,
         zip   TYPE string,
       END OF ty_address.

TYPES: BEGIN OF ty_person,
         name     TYPE string,
         age      TYPE i,
         address  TYPE ty_address,
       END OF ty_person.

DATA: lv_json TYPE string VALUE '{ "name": "John", "age": 30, "address": { "city": "Berlin", "zip": "10117" } }',
      ls_person TYPE ty_person.

 /ui2/cl_json=>deserialize(
  EXPORTING json = lv_json
  CHANGING  data = ls_person
).

WRITE: ls_person-name, ls_person-age, ls_person-address-city, ls_person-address-zip.

✅ Works for nested JSON structures ❌ Needs manual structure definition

5. Handling Errors in JSON Parsing

Use exception handling to catch JSON errors.

TRY.
    /ui2/cl_json=>deserialize(
      EXPORTING json = lv_json
      CHANGING  data = ls_data
    ).
  CATCH cx_root INTO DATA(lx_error).
    WRITE: 'JSON Parsing Error:', lx_error->get_text( ).
ENDTRY.

✅ Ensures error handling during JSON conversion

🚀 Summary: Best Methods for Converting String to JSON

Method	Use Case
`/UI2/CL_JSON=>deserialize`	Best for simple & nested JSON
`CALL TRANSFORMATION id`	Works for basic JSON
`TABLE OF ty_json_table`	Converts JSON arrays
Nested Structures	Parses complex JSON objects
`TRY...CATCH`	Handles errors in JSON parsing

1. Using /UI2/CL_JSON (Recommended for Standard Cases)