# File Structure of JSON Format Decision Tables exported or imported in JSON format require certain mandatory attributes to maintain a consistent structure. Below are the required and optional components of a decision table JSON file. ### Mandatory Elements * `name`**:** name of the decision table; * `type`**:** always `"decision-table"` for decision tables; * `status`**:** the current[ state of the decision table](https://docs.decisionrules.io/doc/v1/other/rule-state) ("`published`" or "`pending`"); * `inputSchema`**:** describes the [input variables](https://docs.decisionrules.io/doc/v1/decision-tables/input-and-output) of the decision table. Each variable should be defined as an object, which can hold different attributes or substructures; * `outputSchema`**:** describes the expected [output variables](https://docs.decisionrules.io/doc/v1/decision-tables/input-and-output) from the decision table * `decisionTable`**:** contains the rule itself: * `columns`: defines the [different types of columns](https://docs.decisionrules.io/doc/v1/decision-table-designer#column-types-and-table-structure) in the table, such as input (conditions), calculation, and result columns; * `condition`: condition columns specify the criteria that inputs need to meet; * `calculation`: columns that calculate values based on the input or other conditions; * `columnOutput`: defines the result of the decision table based on the calculations or conditions; * `rows`:[ rows](https://docs.decisionrules.io/doc/v1/decision-table-designer#row) of the decision table; * `cells`: each row contains cells, which correspond to the column definitions, and they hold specific values or functions applied to the data; * `active:` a boolean attribute that defines if a [row is active](https://docs.decisionrules.io/doc/v1/decision-table-designer#deactivate-and-activate-row) (true) or not; ### Optional Elements * `description`: a textual description of the decision table; * `ruleAlias`: an [alias for the rule](https://docs.decisionrules.io/doc/v1/other/rule-alias). If this is left as an empty string, the system will generate one automatically upon import; * `createdIn`: the date and time of the rule's creation, following the ISO 8601 format. If left empty, this will be generated automatically upon import; * `lastUpdate`: the date and time of the last update, also in ISO 8601 format. If empty, it will be automatically generated upon import; * `tags`**:** an array containing[ tags](https://docs.decisionrules.io/doc/v1/other/tagging) for categorizing the rule. It may be an empty array; * `visualData`: contains information about the visual presentation of the columns, including: * `columns`: an array where each object contains: * `columnId`: the unique identifier for the column (string); * `width`: the width of the column in the UI (number); * `auditLog`: specifies the [audit logging](https://docs.decisionrules.io/doc/v1/business-intelligence/audit-logs) configuration; * `active`: defines whether audit logging is active; * `debug`: contains a nested attribute `active`, which controls whether debug logging is enabled; * `ttl`: time to live (in days) for the audit logs (optional, with a default of 14 days). ### Examples #### Minimal File Structure Example: ```json { "name": "", "description": "", "type": "decision-table", "status": "", "inputSchema": {}, "outputSchema": {}, "decisionTable": { "columns": [], "rows": [] } } ``` #### File Structure Example: {% code lineNumbers="true" %} ```json { "name": "Example table", "description": "", "inputSchema": { "input": {} }, "outputSchema": { "output": {} }, "decisionTable": { "columns": [ { "condition": { "type": "simple", "name": "Condition", "definition": { "content": "input", "type": "INPUT_VARIABLE", "valid": false } }, "columnId": "ec57bb7c-8e90-4aee-da49-17b607a6b09a", "type": "input", "alias": "col-green-elephant" }, { "calculation": { "variable": "calcVar", "name": "Calculation" }, "columnId": "a93899f3-d75b-8f64-3b05-781bc42e836a", "type": "calc", "alias": "col-turquoise-eagle" }, { "columnOutput": { "type": "simple", "outputVariable": "output", "name": "Result" }, "columnId": "2e46eb73-de05-51bc-5913-4b261bbe2069", "type": "output", "alias": "col-violet-lion" } ], "rows": [ { "active": true, "cells": [ { "column": "ec57bb7c-8e90-4aee-da49-17b607a6b09a", "scalarCondition": { "operator": "function", "value": { "functionName": "EQUAL", "parameters": [ 1, "1" ] }, "type": "function", "stringValue": "EQ(1, \"1\")" }, "type": "input" }, { "column": "a93899f3-d75b-8f64-3b05-781bc42e836a", "outputScalarValue": { "value": { "functionName": "ABS", "parameters": [ { "functionName": "MINUS_CHAR", "parameters": [ 2 ] } ] }, "type": "function", "stringValue": "ABS(-2)" }, "type": "calc" }, { "column": "2e46eb73-de05-51bc-5913-4b261bbe2069", "outputScalarValue": { "type": "function", "value": "\"1 equals '1', and absolute value of -2 is {calcVar}\"", "stringValue": "\"1 equals '1', and absolute value of -2 is {calcVar}\"" }, "type": "output" } ] }, { "active": true, "cells": [ { "column": "ec57bb7c-8e90-4aee-da49-17b607a6b09a", "scalarCondition": { "operator": "function", "value": { "functionName": "LESS", "parameters": [ 2, 6 ] }, "type": "function", "stringValue": "LT(2, 6)" }, "type": "input" }, { "column": "a93899f3-d75b-8f64-3b05-781bc42e836a", "outputScalarValue": { "value": { "functionName": "AVG", "parameters": [ 10, 16, 80, 5 ] }, "type": "function", "stringValue": "AVG(10, 16, 80, 5)" }, "type": "calc" }, { "column": "2e46eb73-de05-51bc-5913-4b261bbe2069", "outputScalarValue": { "value": "\"2 is less than 6, and average of 10, 16, 80 and 5 is {calcVar}\"", "type": "function", "stringValue": "\"2 is less than 6, and average of 10, 16, 80 and 5 is {calcVar}\"" }, "type": "output" } ] } ] }, "type": "decision-table", "status": "published", "auditLog": { "active": false, "debug": { "active": false }, "ttl": 14 }, "visualData": { "columns": [ { "columnId": "2e46eb73-de05-51bc-5913-4b261bbe2069", "width": 708 }, { "columnId": "ec57bb7c-8e90-4aee-da49-17b607a6b09a", "width": 297 }, { "columnId": "a93899f3-d75b-8f64-3b05-781bc42e836a", "width": 466 } ] }, "ruleAlias": "comprehensive-vole", "createdIn": "2024-09-25T10:01:54.140Z", "lastUpdate": "2024-09-25T11:10:12.365Z", "tags": [] } ``` {% endcode %} ### Conclusion When working with Decision Tables in JSON format, it's crucial to adhere to the structure, ensuring that mandatory elements like `name`, `type`, `status`, and schemas are defined. Optional elements such as descriptions, audit logs, and visual data offer flexibility and can improve clarity and management. By following these guidelines, users can maintain a consistent and reliable Decision Table structure that ensures smooth data handling and integration.