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Table of contents
  1. VoK-Util Module
    1. When to use this module
    2. Support for Grid Filter Bar
      1. Filter Binder
      2. How this works: Wiring Filters To Custom Database Backend
      3. DataLoaders
    3. Support for Session
    4. Cookies

VoK-Util Module

Repository: vok-util-vaadin10

Provides utilities for creating UIs with Vaadin 14, but does not introduce support for any particular database type. Includes the Karibu-DSL library, depends on the vok-framework core and provides additional Vaadin 14 Kotlin wrappers.

Just add the following to your Gradle script, to depend on this module:

dependencies {

Note: to obtain the newest version see above for the most recent tag

When to use this module

Use this module when you want to use Vaadin 14+ and you need to have additional support for Session and Vaadin Grid (namely for filter components). Since VoK includes built-in support for SQL databases you may also want to include additional modules - read below.

When you want to also use the SQL database with the recommended approach (vok-db):

  • Depend on the vok-framework-v10-vokdb module instead - it will include this module, the vok-db module which sports VoK-ORM, and will implement proper filters which work with SQL databases.

VoK currently does not support usage of Vaadin 14 with JPA.

When you want to also use the SQL database plus some other ORM library, or the JDBC directly:

  • Depend on this module and implement the proper FilterFactory implementation yourself, in order to have support for Grid filter components. Read below on how to do that.

When you want to use the NoSQL database:

  • Depend on this module and implement the proper FilterFactory implementation yourself, in order to have support for Grid filter components.

Support for Grid Filter Bar

Hooking a Grid to a data loader is easy:

grid.setDataLoader(Person.dataLoader)  // uses vok-orm's DataLoader

To create a filtering field, monitor its value and update the DataLoader filter accordingly, you need to do something along these lines:

personGrid = grid<Person> {
  flexGrow = 1.0
  appendHeaderRow() // workaround for
  val filterBar: VokFilterBar<Person> = appendHeaderRow().asFilterBar(this)

  addColumnFor(Person::name) {
    filterBar.forField(TextField(), this).istartsWith()

This module provides a default set of filter components intended to be used with Vaadin Grid, to perform filtering of the data shown in the Grid:

  • A NumberFilterPopup which allows the user to specify a numeric range of accepted values, which may be potentially open.
  • A DateRangePopup which allows the user to specify a date range of accepted values.
  • A BooleanComboBox which is betterly suited for filtering than a Checkbox since it has three states: true: filters beans having the true value in given property; false: filters beans having the false value in given property; null which disables the filter.
  • An enumComboBox() function which allows the user to filter for a particular enum constant.

In addition, you can use any Vaadin field component:

  • A TextField for starts-with or full-text filtering.
  • A ComboBox with pre-populated values, to mimic enumComboBox() when there’s a limited set of values present in the column.
  • Possibly others.

FilterBar.configure() configures all filter fields by default as follows:

  • the width is set to 100%
  • the clear button is made visible for TextField and ComboBox.
  • HasValueChangeMode.setValueChangeMode is set to ValueChangeMode.LAZY: not to bombard the database with EAGER, but also not to wait until the focus is lost from the filter - not a good UX since the user types in something and waits and waits and waits with nothing going on.

You can override the configure() function to modify this behaviour.

Note that the filter components need an implementation of the FilterFactory to properly generate filter objects for a particular database backend. By default the [DataLoaderFilterFactory] is used: it produces vok-dataloader-compatible Filter instances which are accepted by vok-framework-v10-vokdb module. This detail is hidden within the asFilterBar() function.

There is no support for JPA.

Filter Binder

In order to produce a Filter from a filter component, a technique similar to Vaadin Binder is used. In general you first create filter component, then gradually convert its value to a Filter using helper methods and custom converters, then you call bind() to register the binding into the FilterBar. The FilterBar then attaches value change listener into the filter component, computes the global filter on every filter component change, then sets it to the VokDataLoader.

There are the following binding methods:

eq() tests for value equality. Usually used with EnumComboBox, allowing you to for example only show married people:

addColumnFor(Person::maritalStatus) {
    filterBar.forField(enumComboBox<MaritalStatus>(), this).eq()

Alternative usage: BooleanComboBox:

addColumnFor(Person::alive) {
    filterBar.forField(BooleanComboBox(), this).eq()

le() tests that the value is less-or-equal to the one in the filter component; ge() tests that the value is greater-or-equal to the one in the filter component; not really that useful.

inRange() is only applicable to filter values of type NumberInterval<Double> (for example produced by NumberRangePopup), allows you to filter numeric values of any type:

addColumnFor(Person::age) {
    filterBar.forField(NumberRangePopup(), this).inRange()

inRange() is also applicable to date-, and timestamp- based columns and filter values of type DateInterval. The browserTimeZone (comes from Karibu-DSL, please read Karibu-DSL TimeZone for more details) is used to match Instant, Date and Calendar-typed values with LocalDates.

addColumnFor(Person::dateOfBirth, converter = { it?.toString() }) {
    filterBar.forField(DateRangePopup(), this).inRange(Person::dateOfBirth)

istartsWith() is applicable to String-typed filters and is most commonly used with plain Vaadin TextField:

addColumnFor(Person::name) {
    filterBar.forField(TextField(), this).istartsWith()

fullText() is a more powerful version of istartsWith() but it requires proper full-text support to be configured on your database column. See vok-orm full-text filters for exact SQL commands. Applicable to String-typed filters and is most commonly used with plain Vaadin TextField:

addColumnFor(Person::name) {
    filterBar.forField(TextField(), this).fullText()

onDay() matches date/datetime-based values to be on given day. Applicable to LocalDate-typed filters, simply use Vaadin’s built-in DatePicker. Don’t forget to set the time zone properly.

addColumnFor(Person::dateTimeOfBirth) {
    filterBar.forField(DatePicker(), this).onDay(LocalDateTime::class)

How this works: Wiring Filters To Custom Database Backend

In order for the Grid to offer filtering components to the user, the programmer needs to create the filter components first. The filter components are then usually placed into a dedicated Grid header row.

The filter component creation flow is as follows:

  • You create the Grid header row, by calling Grid.appendHeaderRow().
  • You create the filter components by hand and attach them to the header row cells; you then need to intercept the value changes, recreate the filters and pass them to the data provider.

This manual process is a lot of work. Luckily, this process can be vastly automatized by a proper set of utility classes provided by VoK.

  • You wrap the Grid header row with a FilterBar class. FilterBar helps you register filter components, tracks changes made in them, constructs appropriate filters and sets them to Grid’s DataProvider. ‘bind’ them to the FilterRow.
  • In order for the FilterRow to do that, it needs an implementation of FilterFactory for your particular database backend. You usually use DataLoaderFilterFactory which produces VoK Filters.

The filter component call flow is as follows:

  • The user changes the value in the filter component; say, a String-based TextField which we need to perform ILIKE filtering.
  • The FilterRow intercepts the change and polls all filter components for the current values. In this example there will be just a single value of type String.
  • Since these values can’t be passed directly into the DataProvider, the values are converted to Filters via the FilterRow binding mechanism.
  • Those filter objects are then passed into the VokDataProvider.setFilter() method which will then notify the Grid that the data set may have been changed.
  • The Grid component will then refresh the data by calling DataProvider.fetch(); the VokDataProvider implementation will make sure to include the filters configured in the above step.

With this automatized approach, all you need to provide is:

  • A DataProvider which is able to fetch data from your backend
  • You can either make your DataProvider use vok-dataloader filters, or you will need to define a set of filter objects (say, LessThanFilter(25) and others) which your data provider will then accept and will be able to filter upon.
  • A FilterFactory implementation which will then produce your custom filter objects. For vok-dataloader filters you simply use the DataLoaderFilterFactory class.

With this machinery in place, you only need to create filter components and bind them to the FilterRow: basically create a converter pipeline which converts filter field value into an instance of Filter.

For more details please see the FilterBar.kt file.

For more information about using filters with DataProviders please see the Databases Guide.


Even easier way is to use vok-dataloader which provides a rich hierarchy of filters out-of-the-box, and the DataLoader interface is way simpler to implement than DataProvider. The FilterBar class already reuses vok-dataloader filter hierarchy, so all we need is to convert a data loader to a data provider. Luckily, that’s very easy:

val dataLoader: DataLoader<Person> = Person.dataLoader // to load stuff from a SQL database via vok-orm
val dataLoader: DataLoader<Person> = CrudClient("http://localhost:8080/rest/person/", // to load stuff from a REST endpoint via vok-rest-client
    // or you can implement your own DataLoader
val dataProvider: VokDataProvider<Person> = dataLoader.asDataProvider {!!}
grid.dataProvider = dataProvider
val filterBar: VokFilterBar<Person> = grid.appendHeaderRow().asFilterBar(this)
grid.addColumnFor(Person::name) {
  filterBar.forField(TextField(), this).ilike()

Or even shorter, by using VoK-provided extension methods to set the data loader to a Grid directly:

val dataLoader = // as above
grid.setDataLoader(dataLoader) {!! }
val filterBar: VokFilterBar<Person> = grid.appendHeaderRow().asFilterBar(this)
grid.addColumnFor(Person::name) {
  filterBar.forField(TextField(), this).ilike()

See vok-rest-client for how to use the REST client DataLoader.

Support for Session

Provides a Session object which gives handy access to the VaadinSession:

  • Session.current returns the current VaadinSession.
  • Session["key"] = value allows you to retrieve and/or store values into the session
  • Session[MySessionScopedService::class] = MySessionScopedService() allows you to store session-scoped services into the session. However, read below on how to do this properly.

Another important role of the Session object is that it provides a default point to which you can attach your session-scoped services. For example, the user login module of your app can attach the LoggedInUser service which contains both the currently logged in user, and the means to log in and log out:

class LoggedInUser : Serializable {
  val user: User? = null
    private set
  val isLoggedIn: Boolean
    get() = user != null

  fun login(username: String, password: String) {
    val user = User.findByUsername(username) ?: throw LoginException("No such user $username")
    if (!user.validatePassword(password)) throw LoginException("$username: invalid password")
    this.user = user
  fun logout() {
    user = null
val Session.loggedInUser: LoggedInUser get() = getOrPut { LoggedInUser() }

By using the above code, you will now be able to access the LoggedInUser from anywhere, simply by calling Session.loggedInUser.login(). No DI necessary!

Note: the session is accessible only from the code being run by Vaadin, with Vaadin UI lock properly held. It will not be accessible for example from background threads - you will need to store the UI reference and call ui.access() from your background thread.


There is a Cookies singleton which provides access to cookies attached to the current request:

  • Use Cookies += Cookie("autologin", "secret") to add a cookie;
  • Use Cookies.delete("autologin") to remove a cookie.
  • Use Cookies["autologin"] to access a cookie for the current request.