Validify

Procedural macros that provide attributes for data validation and modification. Particularly useful in the context of web payloads.

Modifiers

Modifier	Type	Description
trim*	String	Removes surrounding whitespace
uppercase*	String	Calls `.to_uppercase()`
lowercase*	String	Calls `.to_lowercase()`
capitalize*	String	Makes the first char of the string uppercase
custom	Any	Takes a function whose argument is `&mut <Type>`
validify	impl Validify / impl Iterator<Item = impl Validify>	Can only be used on fields that are structs (or collections of) implementing the `Validify` trait. Runs all the nested struct's modifiers and validations.

*Also works for Vec<String> by running the modifier on each element.

Validators

All validators also take in a code and message as parameters, their values are must be string literals if specified.

Validator	Type	Params	Param type	Description
email	String	--	--	Checks emails based on this spec.
ip	String	format	Ident (v4/v6)	Checks if the string is an IP address.
url	String	--	--	Checks if the string is a URL.
length	Collection	min, max, equal	LitInt	Checks if the collection length is within the specified params. Works through the HasLen trait.
range	Int/Float	min, max	LitFloat	Checks if the value is in the specified range.
must_match	Any	value	Ident	Checks if the field matches another field of the struct. The value must be equal to a field identifier on the deriving struct.
contains	Collection	value	Lit/Path	Checks if the collection contains the specified value. If used on a K,V collection, it checks whether it has the provided key.
contains_not	Collection	value	Lit/Path	Checks if the collection doesn't contain the specified value. If used on a K,V collection, it checks whether it has the provided key.
non_control_char	String	--	--	Checks if the field contains control characters
custom	Function	function	Path	Executes custom validation on the field by calling the provided function
regex	String	path	Path	Matches the provided regex against the field. Intended to be used with lazy_static by providing a path to an initialised regex.
credit_card	String	--	--	Checks if the field's value is a valid credit card number
phone	String	--	--	Checks if the field's value is a valid phone number
required	Option<T>	--	--	Checks whether the field's value is Some
is_in	impl PartialEq	collection	Path	Checks whether the field's value is in the specified collection
not_in	impl PartialEq	collection	Path	Checks whether the field's value is not in the specified collection
validate	impl Validate	--	--	Calls the underlying struct's `validate` implementation
iter	impl Iterator	List of validators	Validator	Runs the provided validators on each element of the iterable
time	NaiveDate[Time]	See below	See below	Performs a check based on the specified op

Time operators

All time operators may take in inclusive = bool. All time operator must take in time = bool when validating datetimes, by default time validators will attempt to validate dates.

in_period and the *_from_now operators are inclusive by default.

The target param must be a string literal date or a path to an argless function that returns a date[time].

If the target is a string literal, it must contain a format param, as per this.

Accepted interval parameters are seconds, minutes, hours, days, weeks.

The _from_now operators should not use negative duration due to how they validate the inputs, negative duration for in_period works fine.

Op	Params	Description
before	target	Check whether a date[time] is before the target one
after	target	Check whether a date[time] is after the target one
before_now	--	Check whether a date[time] is before today[now]
after_now	--	Check whether a date[time] is after today[now]
before_from_now	interval	Check whether a date[time] is before the specified interval from today[now]
after_from_now	interval	Check whether a date[time] is after the specified interval from the today[now]
in_period	target, interval	Check whether a date[time] falls within a certain period

Annotate the struct you want to modify and validate with the Validify attribute (if you do not need the payload or modification, derive validify::Validate):

use validify::Validify;

#[derive(Debug, Clone, serde::Deserialize, Validify)]
struct Testor {
    #[modify(lowercase, trim)]
    #[validate(length(equal = 8))]
    pub a: String,
    #[modify(trim, uppercase)]
    pub b: Option<String>,
    #[modify(custom(do_something))]
    pub c: String,
    #[modify(custom(do_something))]
    pub d: Option<String>,
    #[validify]
    pub nested: Nestor,
}

#[derive(Debug, Clone, serde::Deserialize, Validify)]
struct Nestor {
    #[modify(trim, uppercase)]
    #[validate(length(equal = 12))]
    a: String,
    #[modify(capitalize)]
    #[validate(length(equal = 14))]
    b: String,
}

fn do_something(input: &mut String) {
    *input = String::from("modified");
}

let mut test = Testor {
  a: "   LOWER ME     ".to_string(),
  b: Some("  makemeshout   ".to_string()),
  c: "I'll never be the same".to_string(),
  d: Some("Me neither".to_string()),
  nested: Nestor {
    a: "   notsotinynow   ".to_string(),
      b: "capitalize me.".to_string(),
  },
};

// The magic line
let res = test.validify();

assert!(matches!(res, Ok(_)));

// Parent
assert_eq!(test.a, "lower me");
assert_eq!(test.b, Some("MAKEMESHOUT".to_string()));
assert_eq!(test.c, "modified");
assert_eq!(test.d, Some("modified".to_string()));
// Nested
assert_eq!(test.nested.a, "NOTSOTINYNOW");
assert_eq!(test.nested.b, "Capitalize me.");

Notice how even though field d is an option, the function used to modify the field still takes in &mut String. This is because modifiers and validations are only executed when the field isn't None.

Traits

Validify is built around 3 simple traits:

Validate
Modify
Validify

These traits should theoretically never have to be implemented manually.

As their names suggest, the first two traits perform validation and modification, while the third combines those 2 actions into a single one - validify.

The traits contain a single function which is constructed based on struct annotations when deriving them.

Payload

Structs annotated with #[derive(Payload)] get an associated payload struct, e.g.

#[derive(validify::Validify, validify::Payload)]
struct Something {
  a: usize,
  b: String,
  c: Option<bool>
}

behind the scenes will generate an intermediary

#[derive(Debug, Clone, serde::Deserialize, validify::Validate)]
struct SomethingPayload {
  #[validate(required)]
  a: Option<usize>,
  #[validate(required)]
  b: Option<String>,
  c: Option<bool>,

  /* From and Into impls */
}

The motivation for this is to aid in deserializing potentially missing fields. Even though the payload struct cannot help with deserializing wrong types, it can still prove useful and provide a bit more meaningful error messages when fields are missing.

The original struct gets a ValidifyPayload implementation with 2 associated fns: validate_from and validify_from whose whose respective arguments are the generated payload.

The ValidifyPayload implementations first validate the required fields of the payload. Then, if any required fields are missing, no further modification/validation is done and the errors are returned. Next, the payload is transformed to the original struct and modifications and/or validations are run on it.

When a struct contains nested validifies (child structs annotated with #[validify]), all the children in the payload will also be transformed and validated as payloads first. This means that any nested structs must also derive Payload.

The payload and serde

Struct level attributes, such as rename_all are propagated to the payload. When attributes that modify field names are present, any field names in returned errors will be represented as the original (i.e. client payload).

There are a few special serde attributes that validify treats differently; rename, with and deserialize_with. It is highly advised these attributes are kept in a separate annotation from any other serde attributes, due to the way they are parsed for the payload.

The rename attribute is used by validify to set the field name in any errors during validation. The with and deserialize_with will be transfered to the payload field and will create a special deserialization function that will call the original and wrap the result in an option. If the custom deserializer already returns an option, it will do nothing.

Schema validation

Schema level validation can be performed using the following:

use validify::{Validify, ValidationErrors, schema_validation, schema_err};
#[derive(validify::Validify)]
#[validate(validate_testor)]
struct Testor {
    a: String,
    b: usize,
}

#[schema_validation]
fn validate_testor(t: &Testor) -> Result<(), ValidationErrors> {
  if t.a.as_str() == "yolo" && t.b < 2 {
    schema_err!("Invalid Yolo", "Cannot yolo with b < 2");
  }
}

The #[schema_validation] proc macro expands the function to:

fn validate_testor(t: &Testor) -> Result<(), ValidationErrors> {
    let mut errors = ValidationErrors::new();
    if t.a == "yolo" && t.b < 2 {
        errors.add(ValidationError::new_schema("Invalid Yolo").with_message("Cannot yolo with b < 2".to_string()));
    }
    if errors.is_empty() { Ok(()) } else { Err(errors) }
}

This makes schema validations a bit more ergonomic and concise. Like field level validation, schema level validation is performed after modification.

Errors

The main ValidationError is an enum with 2 variants, Field and Schema. Field errors are, as the name suggests, created when fields fail validation and are usually automatically generated unless using custom handlers (custom field validation functions always must return a result whose Err variant is ValidationError).

If you want to provide a message along with the error, you can directly specify it in the attribute (the same goes for the code), for example:

#[validate(contains(value = "something", message = "Does not contain something", code = "MUST_CONTAIN"))]

Keep in mind, when specifying validations this way, all attribute parameters MUST be specified as NameValue pairs. This means that if you write

#[validate(contains("something", message = "Bla"))],

you will get an error because the parser expects either a single value or multiple name value pairs.

The field_err! macro provides a shorthand for creating field errors when using custom functions.

Location

Locations are tracked for each error in a similar manner to JSON pointers. When using custom validation, whatever field name you specify in the returned error will be used in the location for that field. Keep in mind locations are not reliable when dealing with hashed map/set collections as the item ordering for those is not guaranteed.

Error location display will depend on the original client payload, i.e. they will be displayed in the original case the payload was received (e.g. when using serde's rename_all). Any overriden field names will be displayed as such.

Schema

Schema errors are usually created by the user in schema validation. The schema_err! macro alongside #[schema_validation] provides an ergonomic way to create schema errors. All errors are composed to a ValidationErrors struct which contains a vec of all the validation errors.

Params

When sensible, validify automatically appends failing parameters and the target values they were validated against to the errors created to provide more clarity to the client and to save some manual work.

One parameter that is always appended is the actual field which represents the value of the violating field's target property during the validation. Some validators append additional data to the errors representing the expected values for the field.

Examples

Date[times]s

use chrono::{NaiveDate, NaiveDateTime};

#[derive(Debug, validify::Validate)]
struct DateTimeExamples {
    #[validate(time(op = before, target = "2500-04-20", format = "%Y-%m-%d", inclusive = true))]
    before: NaiveDate,
    #[validate(time(op = before, target = "2500-04-20T12:00:00.000", format = "%Y-%m-%-dT%H:%M:%S%.3f"))]
    before_dt: NaiveDateTime,
    #[validate(time(op = after, target = "2022-04-20", format = "%Y-%m-%d"))]
    after: NaiveDate,
    #[validate(time(op = after, target = "2022-04-20T12:00:00.000", format = "%Y-%m-%-dT%H:%M:%S%.3f"))]
    after_dt: NaiveDateTime,
    #[validate(time(op = in_period, target = "2022-04-20", format = "%Y-%m-%d", weeks = -2))]
    period: NaiveDate,
}

With route handler

    use validify::{Validify, Payload, ValidifyPayload};

    #[derive(Debug, Validify, Payload)]
    struct JsonTest {
        #[modify(lowercase)]
        a: String,
        #[modify(trim, uppercase)]
        #[validate(length(equal = 11))]
        b: String,
    }

    // This would normally come from a framework
    struct Json<T>(T);

    fn test() {
      let jt = JsonTest {
          a: "MODIFIED".to_string(),
          b: "    makemeshout    ".to_string(),
      };
      let json = Json(JsonTestPayload::from(jt));
      mock_handler(json)
    }

    fn mock_handler(data: Json<JsonTestPayload>) {
      let data = data.0;
      let data = JsonTest::validify_from(data.into()).unwrap();
      mock_service(data);
    }

    fn mock_service(data: JsonTest) {
      assert_eq!(data.a, "modified".to_string());
      assert_eq!(data.b, "MAKEMESHOUT".to_string())
    }

See more examples in the test directory

Contributing

If you have any ideas on how to improve Validify, such as common validations you find useful or better error messages, do not hesitate to open an issue or PR. All ideas are welcome!