Working with All Futures is very similar to working with a Rails model class. Depending on what you want to build, you will define the attributes, validations, callbacks and instance methods you need.

Creating a faceted search filter

Define a class that inherits from AllFutures, in a location that makes sense for your application. Many times, app/models is a suitable home but in the example, an app/filters folder was created.

Your first task is to define attributes representing the data structure you intend to persist. attribute supports all of the same data types you could use in a migration:

class CustomerFilter < AllFutures
# Facets
attribute :search, :string
attribute :threshold, :float, default: 0.1
attribute :status, :string
attribute :lawyers, :boolean, default: false
attribute :low, :integer, default: 21
attribute :high, :integer, default: 65
# Pagination
attribute :items, :integer, default: 10
attribute :page, :integer, default: 1
# Sorting
attribute :order, :string, default: "name"
attribute :direction, :string, default: "asc"

The above code is an example of using All Futures to implement an exclusion filter. It's taken from the Beast Mode repo, and is used to hold the values required to create a faceted search UI for a tabular dataset.

Facets, Pagination and Sorting

When working with tabular data, there are typically three concerns:

  1. Facets: attributes used to exclude and filter data from the total pool of possible values

  2. Pagination: attributes used to track the current page and number of items per page

  3. Sorting: attributes used to sort the filtered results in a specific direction (ASC vs DESC)

The CustomerFilter doesn't describe the data - that's the model's job. Instead, facets describe the ways a user might exclude rows. Facets are composable, meaning that you can add them together to remove more data. Ultimately, the filter that is applied is the sum total of all active facets.

Hole In The Wall

For example, the lawyers attribute is used to reduce the results to only rows where the name of the employer has the string and in it. threshold is used to alternate between loose and strict text matching.

You can see this for yourself if you search for "ste". Initially, you'll see 7 matches. If you turn on Uptight mode, it reduces the results to 3 matches.

When designing faceted search UIs, it's important that you handle impossible states so that there are no combinations of filters which could produce invalid combinations or even errors.

For example, it's recommended that you configure Pagy so that a user viewing page 10 is automatically taken to page 5 if the user adjust the number of records per-page from 10 to 20. Set Pagy::VARS[:overflow] = :last_page in your pagy.rb initializer.

Providing a scope

Since this example doesn't require any attribute validation, we complete the Filter by defining a scope method to return an ActiveRecord::Relation object. You can pass this relation directly into Pagy to perform the search, or additional scope clauses can be added to suit the needs of your application.

class CustomerFilter < AllFutures
# Attribute definitions cut for brevity
def scope
.between(low, high)
.order(order => direction)
.search_for(search, threshold)

The business logic required to filter the data is fully contained in the model as a set of scopes. This CustomerFilter#scope method simply connects the dots to provide access to a relation for this filter instance.

Draw the rest of the owl

Going through building the rest of a faceted search is beyond the scope of this document, but you are encouraged to clone and explore the Beast Mode codebase and/or follow along with the tutorial blog post.

There will soon be further guides suggesting strategies for real-time field validation and UI state persistence.

What other scenarios would you like to see documented? Let me know on Discord.