isvalid
v4.1.20
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Async JSON validation library for node.js.
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isvalid
isvalid is an asynchronous node.js library for validating and error correcting JavaScript data - which also includes JSON. It uses a very simple schema model - inspired by Mongoose.
Table of Content
- How to Use
- How it Works
- As Connect or Express Middleware
- Contributing
- License
How to Use
isvalid uses a simple schema modal to specify how the data should be formatted. It supports generic validators for all types and type specific validators.
Usage:
await isvalid(dataToValidate, validationSchema, callback)
Example
Here's a simple example on how to use the validator.
const isvalid = require('isvalid');
isvalid(inputData, {
'user': { type: String, required: true },
'pass': { type: String, required: true }
}).then((data) => {
// Data was validated and valid data is available.
}).catch((err) => {
// A validation error occurred.
});
– or using await
/async
.
const isvalid = require('isvalid');
let data = /* some data */
try {
data = await isvalid(data, {
'user': { type: String, required: true },
'pass': { type: String, required: true }
});
} catch(err) {
// A validation error occurred.
}
// data is validated.
There is also build-in support for usage as an express or connect middleware – see the As Connect or Express Middleware section below for more information.
How it Works
A Note on the Examples in this Document
In order to be a complete schema, schemas must have at least the type
, post
/pre
or equal
validator. But, as you will notice throughout this document, many of the examples have none of them. Instead they just use type shortcuts.
This is because isvalid supports type shortcuts for all its supported types, and you are - if you want to help yourself - going to use them a lot. You can read more about type shortcuts in the designated section at the near-bottom of this document.
Errors
All errors are thrown (in promises).
- Wrong parameters throw the
Error
type. - Schema errors throw the
SchemaError
type. - Validation errors throw the
ValidationError
type.
SchemaError
The SchemaError
contains a schema
property which is the actual schema in which there is an error. It also has a message
property with the description of the error that occurred.
ValidationError
The ValidationError
contains three properties besides the message
.
keyPath
is an array indicating the key path in the data where the error occurred.schema
is the schema that failed to validate.validator
is the name of the validator that failed.
Supported Types
These types are supported by the validator:
Object
Array
String
Number
Boolean
Date
- Custom types
There are some validators that are common to all types, and some types have specific validators.
You specify the type like this:
{ type: String }
or if type
is your only validator, you can just do this:
String
In the above example the input must be of type String
.
All schemas must have at least a type
, post
/pre
or equal
validator.
There is more information about shortcuts in the Type Shortcuts section below.
Validators Available to All Types
These validators are supported by all types.
default
Defaults data to a specific value if data is not present in the input. It takes a specific value or it can call a function to retrieve the value.
Type: Any value or a function.
Static Values
Example:
{
"email": { type: String, default: "[email protected]" }
}
This tells the validator, that an email
key is expected, and if it is not found, it should just assign it with (in this case) [email protected]
.
This works with all supported types - below with a boolean type:
{
"receive-newsletter": { type: Boolean, default: false }
}
Now if the receive-newsletter
key is absent in the data the validator will default it to false
.
Asynchronous Functions
An asynchronous default function works using promises.
{
"created": {
type: Date,
default: async function() {
return new Date();
}
}
}
Synchronous Functions
A synchronous default function works the same way.
{
"created": {
type: Date,
default: function() {
return new Date();
}
}
}
required
Values: true
, false
or 'implicit'
.
required
works a little like default. Except if the value is absent a ValidationError
is thrown.
{ type: String, required: true }
The above specifies that the data must be present and be of type String
.
Implicitly Required
Example:
{
type: Object,
required: 'implicit',
schema: {
'user': { type: String, required: true }
'email': String
}
}
The above example is to illustrate what 'implicit'
does. Because the key user
in the sub-schema is required, the parent object inherently also becomes required. If none of the sub-schemas are required, the parent object is also not required.
This enables you to specify that some portion of the data is optional, but if it is present - it's content should have some required keys.
See the example below.
{
type: Object,
required: false,
schema: {
'user': { type: String, required: true }
'email': String
}
}
In the above example the data will validate if the object is not present in the input, even though user
is required - because the parent object is explicitly not required. If the object - on the other hand - is present, it must have the user
key and it must be of type String
.
If
required
is not specified, thenObject
andArray
types are by default'implicit'
. All other types are by default non-required. Alsorequired
is ignored ifdefault
is specified.
equal
Type: Any
This validator allows for a static value. If this is provided the data must match the value of this validator.
This works with any type (also Object
and Array
) and a deep comparison is performed.
The
type
validator becomes optional when usingequal
.
errors
(Custom Error Messages)
Type: Object
errors
are really not a validator - it allows you to customize the errors emitted by the validators. All validators have default error messages, but these can be customized in order to make them more user and context friendly.
An example below.
{
'username': {
type: String,
required: true,
match: /^[^\s]+$/,
errors: {
type: 'Username must be a string.',
required: 'Username is required.',
match: 'Username cannot contain any white spaces.'
}
}
}
Now in case any of the validators fail, they will emit the error message specified - instead of the default built-in error message. The message
property of ValidationError
will contain the message on validation failure.
Error Shortcuts
There is also a shortcut version for the errors
validator. The above example can also be expressed like below.
{
'username': {
type: [String, 'Username must be a string.'],
required: [true, 'Username is required.'],
match: [/^[^\s]+$/, 'Username cannot contain any white spaces.']
}
}
It might be a more convenient way, and it maps the errors to the same line as the validator, so it is more easy to read.
Type Specific Validators
Validators Common to Object
and Array
schema
The schema
validator of Object
and Array
types specifies the schema of their children. Objects have keys and schemas - arrays only have a single schema.
An example below of an object schema with a user
key.
{
type: Object,
schema: {
'username': String
}
}
And an example below of an array of strings.
{
type: Array,
schema: String
}
There is also a shortcut version of describing objects and arrays. You can read more about that below in the Type Shortcuts section.
Object
Validators
The Object
type has only one specific validator - besides the common validators.
unknownKeys
Type String
of value: 'allow'
, 'deny'
or 'remove'
This validator is used to control how unknown keys in objects are handled.
The validator has three options:
allow
Pass any unknown key onto the validated object.deny
Throw aValidationError
if object has unknown key.remove
Remove the unknown key from the validated object.
Default is
deny
.
Array
Validators
The Array
type has three specific validator - besides the common validators.
len
Type: Number
or String
This ensures that an array has a specific length. This can be either a number or a range. The validator throws an error if the array length is outside the bounds of the specified range(s).
Examples:
{
type: Array,
len: 2,
schema: { … }
}
An array that should have exactly 2 items.
{
type: Array,
len: '2-',
schema: { … }
}
An array that should have at least 2 items.
{
type: Array,
len: '-2',
schema: { … }
}
An array that should have a maximum of 2 items.
{
type: Array,
len: '2-5',
schema: { … }
}
An array that should have at least 2 items and a maximum of 5 items.
{
type: Array,
len: '-2,5,8-',
schema: { … }
}
Negative values can be wrapped in parentheses.
{
type: Array,
len: '(-2)-2',
schema: { … }
}
It also supports non-integer values.
{
type: Array,
len: '(-2.2)-2.2',
schema: { … }
}
An array that should have at least 2 items, exactly 5 items or 8 or more items.
unique
Type: Boolean
This ensures that all elements in the array are unique - basically ensuring the array is a set. If two or more elements are the same, the validator throws an error.
Example:
{
type: Array,
unique: true,
schema: { … }
}
The
unique
validator does a deep comparison on objects and arrays.
autoWrap
Type: Boolean
If the provided data is not an array - but it matches the sub-schema - this will wrap the data in an array before actual validation.
Example:
{
type: Array,
autoWrap: true,
schema: { … }
}
If autoWrap
is set to true
and auto-wrap fails (the sub-schema cannot validate the data), then the type
validator will emit a 'Must be of type Array.'
error.
Default is
false
.
String
Validators
The String
type has four specific validator - besides the common validators.
trim
Type: Boolean
This does not do any actual validation. Instead it trims the input in both ends - before any other validators are checked. Use this if you want to remove any unforeseen white spaces added at the beginning or end of the string by the user.
len
Type: String
or Number
This ensures that the string's length is within a specified range. You can use the same formatting as Array
's len
validator described above (except it does not support ranges with negative values or non-integers).
match
Type: RegExp
This ensures that a string can be matched against a regular expression. The validator throws an error if the string does not match the pattern.
This example shows a string that must contain a string of at least one character of ASCII letters or decimal numbers:
{ type: String, match: /^[a-zA-Z0-9]+$/ }
enum
Type: Array
This is complimentary to match
- as this could also easily be achieved with match
- but it's simpler and easier to read. The validator ensures that the string can be matched against a set of values. If it does not, it throws a throws a ValidationError
.
{ type: String, enum: ['none','some','all'] }
In the above example the string can only have the values of none
, some
or all
.
Remark that
enum
is case sensitive.
Number
Validators
The Number
type has only one specific validator - besides the common validators.
Number
also does automatic type conversion fromString
toNumber
where possible. You can read more about that and other automatic type conversions in the Automatic Type Conversion section below
range
Type: Number
or String
This ensures that the number is within a certain range. If not the validator throws an error.
The range
validator uses the same formatting as the Array
's len
validator described above (except it does not support ranges with negative values or non-integers).
float
Type: String
of value: 'allow'
, 'deny'
, 'round'
, 'floor'
, 'ceil'
This tells the validator how to handle non-integers.
The validator has five options:
'allow'
Allow non-integer values.'deny'
Throw aValidationError
if the value is a non-integer.'round'
Round value to nearest integer.'floor'
Round to integer less than or equal to value.'ceil'
Round to integer bigger than or equal to value.
Default is
'allow'
.
Custom Types
Custom types are also supported, and all the generic validators work.
An example is below, where User
is a custom class.
{
'user': { type: User, required: true }
}
post
post
can be used when the possibilities of the validation schema falls short. post
basically outsources validation to a functions.
The
type
validator becomes optional when usingpost
. You can completely leave out any validation and just use apost
(orpre
) validator.
Example
{
type: Object,
schema: {
'password': { type: String, required: true },
'passwordRepeat': String
},
'post': async (data, schema) => {
if (data.password !== data.passwordRepeat) {
throw new Error('Passwords must match.');
}
}
}
In the above example we have specified an object with two keys - password
and passwordRepeat
. The validator first makes sure, that the object validates to the schema. If it does it will then call the post validator - which in this example throws an error if passwords do no match.
post
functions works both by returning promises (async functions) and returning a value.
- If no value is returned the data does not change.
- Thrown errors are caught and converted to a
ValidationError
internally.
Options with Post Validators
If you need to pass any options to your custom validator, you can do so by using a special options
property of the schema, that becomes available when you use post
(or pre
- see below).
An example below.
{
'myKey': {
options: {
myCustomOptions: 'here'
},
post: function(data, schema) {
// schema.options will now contain whatever options you supplied in the schema.
// In this example schema.options is { myCustomOptions: 'here'}.
}
}
}
Multiple Post Validators
The post
validator also support an array of functions. Instead of providing just one function, you can provide an array of functions. Synchronous and asynchronous functions can be mixed and matched as necessary.
An example.
{
post: [
function(data, schema) {
data(null, myValidatedData);
},
async function(data, schema) {
return mySecondValidatedData
}
]
}
If, though, any of the post validator functions throws an error, none of the rest of the post validators in the chain will get called, and isvalid will throw the error as a ValidationError
.
The
post
validator functions are called in order.
pre
pre
does the exact same thing as post
described above, except it is called before any other validators are validated. This gives you a chance to transform the data and return it before the actual validation.
Type Shortcuts
Some types can be specified using shortcuts. Instead of specifying the type, you simply just use the type. This works with Object
and Array
types.
In this document we've been using them extensively on Object
examples, and the first example of this document should have looked like this, if it hadn't been used.
isvalid(inputData, {
type: Object,
schema: {
'user': { type: String, required: true },
'pass': { type: String, required: true }
}
}, function(err, validData) {
/*
err: Error describing invalid data.
validData: The validated data.
*/
});
Object Shortcuts
Object shortcuts are used like this:
{
'user': String
}
and is the same as
{
type: Object,
schema: {
'user': { type: String }
}
}
Which means that data should be an object with a user
key of the type String
.
Internally the library tests for object shortcuts by examining the absent of the
type
,post
/pre
orequal
validators. So if you need objects schemas with validators for keys with those names, you must explicitly format the object usingtype
andschema
- hence the shortcut cannot be used.
Array Shortcuts
The same goes for arrays:
[String]
is the same as
{
type: Array,
schema: String
}
and is the same as
{
type: Array,
schema: { type: String }
}
Which means the data must be an array of strings.
Other Shortcuts
The others are a bit different. They are - in essence - a shortcut for the validator type
. Instead of writing type
you just specify the type directly. Available types are all the supported types of isvalid, namely Object
, Array
, String
, Number
, Boolean
, Date
and custom types.
An example below.
{
"favoriteNumber": Number
}
The above example is really an example of two shortcuts in one - the Object
and the Number
type shortcut. The above example would look like the one below, if shortcuts had not been used.
{
type: Object,
schema: {
"favoriteNumber": { type: Number }
}
}
Automatic Type Conversion
Numbers
If the schema has type Number
and the input holds a String
containing a number, the validator will automatically convert the string into a number.
Booleans
Likewise will schemas of type Boolean
will be automatically converted into a Boolean
if a String
with the value of true
or false
is in the data.
Dates
If the schema is of type Date
and the input is a String
containing an ISO-8601 formatted date, it will automatically be parsed and converted into a Date
.
ISO-8601 is the date format that JSON.stringify(...)
converts Date
instances into, so this allows you to just serialize to JSON on - as an example - the client side, and then isvalid will automatically convert that into a Date
instance when validating on the server side.
As Connect or Express Middleware
Connect and Express middleware is build in.
Usage:
isvalid.validate.body(schema)
validatesreq.body
.isvalid.validate.query(schema)
validatesreq.query
.isvalid.validate.param(schema)
validatesreq.param
.isvalid.validate.parameter(id, schema)
validatesreq.param
as a route.
Example
const { validate } = require('isvalid');
app.param('myparam', validate.param(Number)); // Validates parameter through param
app.post('/mypath/:myparam',
validate.parameter('myparam', Number), // Validates parameter through route.
validate.query({
'filter': String
}),
validate.body({
'mykey': { type: String, required: true }
}),
function(req, res) {
// req.param.myparam, req.body and req.query are now validated.
// - any default values - or type conversion - has been applied.
}
);
If validation fails,
isvalid
will unset the validated content (req.body
will becomeundefined
). This is to ensure that routes does not get called with invalid data, in case a validation error isn't correctly handled. On the opposite,req.body
will be set with the validated data (with transforms and automatic type conversion) if validation succeeds.
Contributing
Contributions are much welcomed, and some great contributions by others have been provided throughout the years.
If you feel like something is missing, please send me a pull request. It is, though, important, that you you follow any new features up with unit tests.
License
MIT