Fields 

What is a field? 

A field refers to a specific attribute or variable that is part of a model's structure. It is a characteristic or property that describes an aspect of the model's subject matter. Fields are used to define the structure and content of the model, and they can represent different types of information.

For example, take a model for a customer entity in an e-commerce system. The customer model represents the information related to a customer, such as their name and date of birth. In this case, each of these attributes represents a field in the customer model.

Here's an example representation of a customer model with its fields:

Field 1: name (field type: string ) - stores the customer's full name.

Field 2: dateOfBirth (field type: date / time ) - stores the customer's birth date.

Field defaults 

In Gadget, you can set a default value for most field types in the schema editor. This default value will be used when creating a record if no specific value is provided. You can modify the default value anytime, but the change will only affect new records created afterward.

Types of fields 

Working with a record state field 

The shopifyShop model includes a record state field that stores a specific status for each record. While using record state for implementing business logic is optional, it can be a useful way to determine permissions and actions.

Rather than relying on generic operations like create, update, and delete, Gadget allows you to define specific and meaningful actions such as publish, fulfill, or complete. Each action can transition a record from one state to another. For example, publishing a record may move it from the Unpublished state to the Published state, while completing a task can move it from Not Started or Doing to Done.

The record state field holds the current state of each record. The field configuration panel defines the available states for this field.

Default system fields 

Each model in Gadget has three fields managed by default. These fields are:

• id: This field captures a unique ID for each of your records within a table

• createdAt: This field captures the timestamp at record creation
• updatedAt: This field captures the timestamp of the last event which changed the record

System fields cannot be given a different name / API identifier.

Computed fields 

Produces a value according to a Gelly code snippet using other field values.

For more information, see our computed fields guide

Extending fields with validations 

In Gadget, validation is an extension of the field component of a model that helps prevent the entry of malformed or inconsistent data into your system. When modifying records, Gadget verifies that any new data satisfies the validations defined for each field. If an action attempts to write invalid data, it will be unsuccessful, and the invalid data will not be saved.

When making API calls to write data, Gadget provides structured error messages that indicate what data is invalid. These error messages can be presented directly to users, helping guide them in correcting the problematic data.

Validations play a crucial role in maintaining data integrity and ensuring that only valid and coherent data is stored in your system. They serve as a safeguard against incorrect or incompatible data and facilitate a smooth user experience by providing clear feedback on data entry errors.

Applicable validations to field types 

Gadget offers a selection of common validations for each field type. These vary from one field type to another:

Required validation 

A required validation refers to the process of ensuring that a particular input or data field is not empty or null when it is required to have a value. It is a form of data validation that checks whether a user has provided the necessary information before proceeding with a certain operation or action.

Uniqueness validation 

The Uniqueness validation in Gadget ensures that each value for a field occurs only once in the database. It is commonly used for fields like email or username to guarantee that each value is unique within the system.

Underlying database constraints are leveraged to enforce the uniqueness validation reliably, even in transactional contexts and under load.

If a Uniqueness validation is added to a model that already contains data, the setup may fail if there are duplicate values for the field. In such cases, the uniqueness constraint is not enforced until the duplicate data is corrected by either deleting records or modifying the field values to ensure uniqueness. Once the data is made unique, the validation can be re-added and verified to succeed.

The Uniqueness validation can be configured as case-sensitive or case-insensitive by toggling the Case Sensitive option. When the option is disabled, values are considered duplicates regardless of letter casing. This is useful for scenarios like URL slugs or emails, where users may enter values with different casing but uniqueness should be maintained regardless of casing.

Number Min/Max range validation 

Number min/max range validation ensures whether a numeric value falls within a specified range of minimum and maximum values. It is commonly used to ensure that numeric input or data meets certain constraints or requirements.

String length range validation 

String length range validation is a type of data validation that ensures whether a string has a specific length or falls within a certain range of lengths. It is commonly used to enforce length restrictions or requirements on user input or data fields

Image validation 

The Image File validation ensures that uploaded files meet three criteria:

1. They have an image based MIME type or subtype — see MDN's reference.
2. They are in one of the following image file formats: gif, jpg, png, svg, or webp (common web formats); apng, bmp, bpg, cr2, cur, dcm, flif, heic, ico, jp2, jpm, jpx, jxr, psd, or tif (additional formats).
3. They do not contain an animation if the Allow animated images option is disabled.

File size range validation 

File size range validation ensures the size of a file falls within a specified range of acceptable sizes. It is commonly used when handling file uploads or processing files in applications. By validating the file size, you can control resource consumption, prevent server overload, and maintain data integrity.

Color Validation 

Color validation ensures whether a given value represents a valid color. It is typically used to ensure that color values provided by users or within a system adhere to a specific format or range of valid colors.

Vector dimension validation 

The Vector dimensions validation in Gadget ensures that all vectors stored in a field have the same count of dimensions.

It's important to note that Gadget restricts the sorting or filtering of vectors unless all the stored vectors and input vectors have the same dimension count. This is because many vector operations used in Gadget are not defined for vectors with different dimensions.

To enforce the consistency of vector dimensions, you can add a Vector dimensions validation to a field. This validation ensures that all vectors stored in the field have the same number of dimensions.

For more details about this validation and any related errors, you can refer to the GGT_DIFFERENT_VECTOR_DIMENSIONS error in the Gadget documentation.

RegEx pattern validation 

RegExp also known as regular expression pattern validation, is used to validate strings or data against a specific pattern or format using regular expressions. Regular expressions (RegEx) are sequences of characters that define a search pattern, allowing for powerful and flexible pattern matching and validation.

Gadget uses the RegExp engine built into node.js to run RegExp Pattern validations. For information on how to write JavaScript regular expressions, please refer to MDN's reference.

Adding custom code validation 

In Gadget, you can add your custom validations written in JavaScript. The custom validation runs a JS function each time a record is created or updated to check if that change should succeed. If the function reports no errors, then the save will be complete, and if the data is somehow invalid, the validation can add structured error messages to the different fields of the record being changed.

Each custom validation file must export a function as the default export function from the module. The function can be marked async or return a Promise. The function shouldn't return anything and, instead, should add errors to any fields determined to be invalid using the passed-in errors object, which holds a structured set of errors keyed by a field.

Here's a custom validation that tests if a record's full name is not null and its last name is also not null:

JavaScript
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export default async ({ api, record, errors, logger, field }) => {
  if (record.firstName && !record.lastName) {
    errors.add("lastName", "must be set if the first name is set");
  }
};

Here's a validation that tests if a record's phone number is valid:

JavaScript
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1export default async ({ api, record, errors, logger, field }) => {
2  const PhoneNumber = require("awesome-phonenumber");
3  const number = new PhoneNumber(record["customerPhoneNumber"]);
4  if (!number.isValid()) {
5    errors.add("customerPhoneNumber", "is not a valid phone number");
6  }
7};

If a validation function throws an error while executing, the action validating the current record will fail, and if the action is transactional, any operations performed in the run function will be rolled back.