Below are all the currently supported constraints. If you need more you can create your own Custom validators as well.
propertyName = { // The field under validation must be yes, on, 1, or true. This is useful for validating "Terms of Service" acceptance.
accepted : any value// The field under validation must be a date after the set targetDate after : targetDate// The field under validation must be a date after or equal the set targetDate afterOrEqual : targetDate// The field must be alpha ONLY alpha : any value// The field under validation is an array and all items must pass this validation as well arrayItem : {// All the constraints to validate the items with }// The field under validation must be a date before the set targetDate before : targetDate// The field under validation must be a date before or equal the set targetDate beforeOrEqual : targetDate// The field under validation is a struct and all nested validation rules must pass constraints: {// All the constraints for the nested struct }// The field under validation must be a date that is equal the set targetDate dateEquals : targetDate// discrete math modifiers discrete : (gt,gte,lt,lte,eq,neq):value// the field must or must not be an empty value// needed because `required` counts empty strings as valid// and `type` ignores empty strings as "not required" empty : boolean [false]// value in list inList : list// An alias for arrayItem items : {// All the constraints to validate the items with }// max value max : value // Validation method to use in the target object must return boolean accept the incoming value and target object
method : methodName// min value min : value// An alias for constraints nestedConstraints: {// All the constraints for the nested struct }// range is a range of values the property value should exist in range : eg: 1..10 or 5..-5// regex validation regex : valid no case regex// required field or not, includes null values required : boolean [false] // The field under validation must be present and not empty if the `anotherfield` field is equal to the passed `value`.
requiredIf : { anotherfield:value, anotherfield:value } // The field under validation must be present and not empty unless the `anotherfield` field is equal to the passed
requiredUnless : { anotherfield:value, anotherfield:value }// same as but with no case sameAsNoCase : propertyName// same as another property sameAs : propertyName// size or length of the value which can be a (struct,string,array,query) size : numeric or range, eg:10 or 6..8// specific type constraint, one in the list. type : (alpha,array,binary,boolean,component,creditcard,date,email,eurodate,float,GUID,integer,ipaddress,json,numeric,query,ssn,string,struct,telephone,url,usdate,UUID,xml,zipcode),
// UDF to use for validation, must return boolean accept the incoming value and target object, validate(value,target,metadata):boolean
udf =variables.UDF or this.UDF or a closure.// Check if a column is unique in the database unique = { table : The table name, column : The column to check, defaults to the property field in check }// Custom validator, must implement coldbox.system.validation.validators.IValidator validator : path or wirebox id, example:'mypath.MyValidator' or 'id:MyValidator'}
accepted
The field must be yes, on, 1, or true. This is useful for validating "Terms of Service" acceptance.
terms = { accepted =true }
after
The field under validation must be a value after a given date. The dates will be passed into the dateCompare() function in order to be converted and tested.
The field under validation must be a value after or equal a given date. The dates will be passed into the dateCompare() function in order to be converted and tested.
This validator is used to validate an array's items. It will iterate through each of the array's items and validate each item against the validationData constraints you pass in.
luckyNumbers = {
required : true,
type : "array",
arrayItem : {
required : true,
type : "numeric"
}
}
You may also specify items as an alias to arrayItem.
luckyNumbers = {
required : true,
type : "array",
items : {
required : true,
type : "numeric"
}
}
Any validation errors found will be named using the parent field name and array index.
var validationResult = validate(
target = {
"luckyNumbers": [ 7, 11, "not a number", 21 ]
},
constraints = {
required : true,
type : "array",
items : {
required : true,
type : "numeric"
}
}
);
// validationResult.getAllErrorsAsJson(){"luckyNumbers[3]": ["The 'item' has an invalid type, expected type is numeric"]}
You can validate nested structs by nesting a constraints validator.
invoiceItems = { required :true, type :"array", arrayItem : { type :"struct", constraints : { logDate : { required :true, type :"date" }, isBilled : { required:true, type :"boolean" }, notes : { required:true } } }}
There is a shortcut notation available for arrayItem that uses a specialized field name to skip nesting the constraints.
before
The field under validation must be a value before a given date. The dates will be passed into the dateCompare() function in order to be converted and tested.
The field under validation must be a value before or equal a given date. The dates will be passed into the dateCompare() function in order to be converted and tested.
There is a shortcut notation available for constraints that uses a specialized field name to skip nesting the constraints.
dateEquals
The field under validation must be a value that is the same as the given date. The dates will be passed into the dateCompare() function in order to be converted and tested.
The field is not required but if it exists it cannot be empty.
myField = { empty =false }
This is needed since required validators allow empty strings when false while type validators ignore empty values as valid. This means we can have a situation as follows:
{"startDate": {"required":false,"type":"date" }}
With these validation rules passing in startDate = "" would pass the validation! The empty validator helps us ensure that the value passed in is not empty (and, in this case, a date).
The field must be less than or equal to the defined value
myField = { max =25 }
method
The methodName will be called on the target object and it will pass in validationData, targetValue, and metadata. It must return a boolean response: true = pass, false = fail.
Any data you place in the metadata structure will be set in the validation result object for later retrieval.
myField = { method ="methodName" }functionmethodName( validationData, targetValue, metadata ){ metadata[ "customMessage" ] ="I am a custom message set via metadata.";returnfalse;}
min
The field must be greater than or equal to the defined value
The field under validation must be present and not empty if the anotherfield field is equal to the passed value. The validation data can be a struct or a string representing the field to check.
// Struct basedmyField = { // myField is required if field2 = test and field3 = hello requiredIf = { field2 ="test", field3 ="hello" }}// String BasedmyField = {// myField is required if field3 exists and has a value. requiredIf ="field3"}
requiredUnless
The field under validation must be present and not empty unless the anotherfield field is equal to the passed value. The validation data can be a struct or a string representing the field to check.
myField = { // myField is required unless field2 = test and field3 = hello requiredUnless = { field2 ="test", field3 ="hello" }}// String BasedmyField = {// myField is required unless field3 exists and has a value. requiredUnless ="field3"}
sameAsNoCase
The field must be the same as another field with no case sensitivity
myField = { sameAs ="otherField" }
sameAs
The field must be the same as another field with case sensitivity
myField = { sameAs ="otherField" }
size
The field value size must be within the range values and the validation data must follow the range pattern: min..max. Value can be a (struct,string,array,query)
myField = { size :10 }myFiedl = { size :"8..20" }
type
One of the most versatile validators. It can test if the value is of the following specific types:
alpha
array
binary
boolean
component
creditcard
date
email
eurodate
float
GUID
integer
ipaddress
json
numeric
query
ssn
string
struct
telephone
url
usdate
UUID
xml
zipcode
myField = { type :"float" }myField = { type :"json" }myField = { type :"xml" }
udf
The field value, the target object, and an empty metadata structure will be passed to the declared closure/lambda to use for validation. The UDF must return boolean, validate( value, target, metadata ):boolean. NOTE: The target object passed in is actually an instance of "GenericObject", not a struct. To access the underlying struct, use the getMemento() function and perfom any comparisons on that. See the example below.
Any data you place in the metadata structure will be set in the validation result object for later retrieval.
myField = { udf=function( value, target, metadata ) { returntrue; } }myField = { udf= (value ,target, metadata ) =>true }myField = { udf=function( value, target, metadata ) { metadata[ "customMessage" ] ="This is a custom error message from within the udf";returnfalse; }myField = { udf=function( value, target, metadata ) {var myData =target.getMemento();return myData["blah"] == something && value > someNumber;}
unique
The field must be a unique value in a specific database table. The validation data is a struct with the following keys:
table : The name of the table to check
column : The column to check, defaults to the property field in check