When is an input field in Lightning is invalid?
A lightning:input field that expects a certain data type is invalid if an incorrect data format is entered. For example, the email type on lightning:input expects an email address and the number type expects a number.
What are some examples of validating fields in Lightning?
For example, the email type on lightning:input expects an email address and the number type expects a number. A lightning:input field that specifies a certain criteria or attribute, max , min, pattern, and so on, is invalid if the criteria isn’t met.
How to validate fields in Lightning aura components?
Client-side field validation provides an initial check for user data before submitting it to the server. Implement your own server-side validation to ensure that user data is saved in the expected format. Consider the following guidelines.
How to implement custom validation in Salesforce Lightning input?
The error message are defined based on the pattern mismatch, required, max length, min length, etc. attributes. The custom error message for the mentioned attributes can be defined in the corresponding messageWhenPatternMismatch, messageWhenTypeMismatch, messageWhenValueMissing, etc error message attributes.
How does the reduce function work in Lightning?
Here, In the onClick handler method, the reduce function iterates over components which is having id value as field. The initial value of the function is set as true and the callback accumulate all components validity into a single boolean output. More details on reduce function is provided on the last.
How to validate data in Lightning aura component?
Implement your own server-side validation to ensure that user data is saved in the expected format. Consider the following guidelines. When working with Salesforce data, we recommend that you use the lightning:recordForm, lightning:recordEditForm, lightning:recordViewForm, or force:recordData base components.
How is lightning data service used in Salesforce?
They are built on Lightning Data Service, which ensures data consistency, while handling sharing rules and field-level security for you. The components also provide field validation and error handling.