Add fields

This is the official documentation of the agent_ruby Ruby agent.

Forest Admin allows creating new Fields on any Collection, either computationally, by fetching data on an external API or based on other data that is available on the connected data sources.

By default, the fields that you create will be read-only, but you can make them filterable, sortable, and writable by using the relevant methods.

How does it work?

When creating a new field you will need to provide:

Field	Description
column_type	Type of the new field which can be any primitive or composite type
dependencies	List of fields that you need from the source records and linked records in order to run the handler
values	Handler which computes the new value for a batch of records
enum_values (optional)	When columnType is Enum, you must specify the values that the field will support

Examples

Adding a field by concatenating other fields

This example adds a user.displayName field, which is computed by concatenating the first and last names.

include ForestAdminDatasourceCustomizer::Decorators::Computed

# User Collection has the following structure: { id, firstName, lastName }
@create_agent.customize_collection('user') do |collection|
  collection.add_field(
    'displayName',
    ComputedDefinition.new(
      # Type of the new field
      column_type: 'String',
      # Dependencies which are needed to compute the new field (must not be empty)
      dependencies: %w[firstName lastName],
      # Compute function for the new field
      # Note that the function computes the new values in batches: the return value must be
      # an array which contains the new values in the same order than the provided records.
      values: proc { |records| records.map { |record| "#{record["firstName"]} #{record["lastName"]}" } }
    )
  )
end

Adding a field that depends on another computed field

This example adds a user.displayName field, which is computed by concatenating the first and last names, and then another which capitalize it.

include ForestAdminDatasourceCustomizer::Decorators::Computed

# User Collection has the following structure: { id, firstName, lastName }
@create_agent.customize_collection('user') do |collection|
  collection
    # Create a first field which is computed by concatenating the first and last names
    .add_field(
      'displayName',
      ComputedDefinition.new(
        column_type: 'String',
        dependencies: %w[firstName lastName],
        values: proc { |records| records.map { |record| "#{record['firstName']} #{record['lastName']}" } }
      )
    )
    # Create a second field which is computed by uppercasing the first field
    .add_field(
      'displayNameCaps',
      ComputedDefinition.new(
        column_type: 'String',
        dependencies: ['displayName'], # It is legal to depend on another computed field
        values: proc { |records| records.map { |record| record['displayName'].upcase } }
      )
    )
end

Adding a field that depends on a many-to-one relationship

We can improve the previous example by adding the city of the user to the display name.

include ForestAdminDatasourceCustomizer::Decorators::Computed

# Structure:
# User    { id, addressId, firstName, lastName }
# Address { id, city }
@create_agent.customize_collection('user') do |collection|
  collection.add_field(
    'displayName',
    ComputedDefinition.new(
      column_type: 'String',

      # We added 'address:city' in the list of dependencies,
      # which tells forest to fetch the related record
      dependencies: %w[firstName lastName address:city],
      values: proc { |records| records.map { |record| "#{record['firstName']} #{record['lastName']} (from #{record['address']['city']})" } }
    )
  )
end

Adding a field that depends on a one-to-many relationship

Let's now add a user.totalSpending field by summing the amount of all orders.

include ForestAdminDatasourceCustomizer::Decorators::Computed
include ForestAdminDatasourceToolkit::Components::Query
include ForestAdminDatasourceToolkit::Components::Query::ConditionTree

# Structure:
# User  { id }
# Order { id, customer_id, amount }
@create_agent.customize_collection('user') do |collection|
  collection.add_field(
    'totalSpending',
    ComputedDefinition.new(
      column_type: 'Number',
      dependencies: ['id'],
      values: proc do |records, context|
        record_ids = records.map { |record| record['id'] }

        # We're using Forest Admin's query interface
        filter = Filter.new(condition_tree: Nodes::ConditionTreeLeaf.new('customer_id', Operators::IN, record_ids))
        aggregation = Aggregation.new(operation: 'Sum', field: 'amount', groups: [ { field: 'customer_id' } ])
        rows = context.datasource.get_collection('order').aggregate(filter, aggregation)

        records.map do |record|
          filtered = rows.select { |row| row['group']['customer_id'] == record['id'] }
          filtered.empty? ? 0 : filtered[0]['value']
        end
      end
    )
  )
end

Adding a field fetching data from an API

Let's imagine that we want to check if the email address of our users is deliverable. We can use a verification API to perform that work.

The API we're using is fictional, and the structure of the response is:

{
  "[e-mail]": {
    "usernameChecked": false,
    "usernameValid": null,
    "domainValid": true
  },
  "[e-mail]": {
    "usernameChecked": false,
    "usernameValid": null,
    "domainValid": true
  }
}

include ForestAdminDatasourceCustomizer::Decorators::Computed
include ForestAdminDatasourceToolkit::Components::Query
include ForestAdminDatasourceToolkit::Components::Query::ConditionTree

# Fictional verification API.
include Fake::EmailVerificationClient

client = EmailVerificationClient.new
client.api_key = 'MY_FAKE_API_KEY'

# "User" Collection has the following structure: { id, email }
@create_agent.customize_collection('user') do |collection|
  collection.add_field(
    'emailDeliverable',
    ComputedDefinition.new(
      column_type: 'Boolean',
      dependencies: ['email'],
      values: proc do |records|
        response = client.verify_emails(records.map { |record| record['email'] })

        records.map do |record|
          check = response[record['email']]
          check['domainValid'] && (!check['usernameChecked'] || check['usernameValid'])
        end
      end
    )
  )
end

Performance

When adding many fields, keep in mind that:

• You should refrain from making queries to external services

  • Use relationships in the dependencies array when that is possible

  • Use batch APIs calls instead of performing requests one by one inside of the records.map handler.

• Only add fields you need in the dependencies list

  • This will reduce the pressure on your data sources (fewer columns to fetch)

  • And increase the probability of reducing the number of records that will be passed to your handler (records are deduplicated).

• Do not duplicate code between handlers of different fields: fields can depend on each other (no cycles allowed).