So, let’s talk about Ruby’s Enumerator class. It’s super handy, especially when you’re looking to manage data without either bogging down your memory or sacrificing performance. If you’ve ever needed to process big data sets or deal with heavy APIs, you’ll find Enumerator to be quite the lifesaver. We will delve into customizing these enumerators and also leverage lazy evaluation. Sounds complex? Don’t worry, we’re breaking it down.

To kick things off, what exactly is an enumerator? It boils down to an object that allows stepping through a bunch of elements. Think of it as a guided tour through your data collection. It’s not just about going through the elements but doing so efficiently. This is particularly crucial when you’re eyeballing vast datasets and don’t want to slam everything into your app’s memory at once. Ruby’s Enumerator class arms you with a suite of methods for traversing collections in various cool ways.

Creating custom enumerators in Ruby is kind of like crafting a tailored solution for your data-iterative needs. The magic happens in defining a block that yields values on demand. This means you only load into memory what’s necessary — no hoarding here. This makes it fantastic for large datasets where every megabyte counts.

Here’s a simple way to get your feet wet with custom enumerators:

enum = Enumerator.new do |yielder|
  puts "Starting the custom enumerator..."
  [1, 2].each do |n|
    puts "Giving #{n} to the yielder"
    yielder << n
  end
  puts "each_slice is still asking for more values..."
  [3, 4].each do |n|
    puts "Giving #{n} to the yielder"
    yielder << n
  end
end

enum.each_slice(3) do |slice|
  puts "We have enough, let's take a slice: #{slice}"
end

Here, the enumerator feeds values to the block in manageable slices. This means you’re only working with chunks of data at a time, helping you avoid that dreaded memory bloat.

Next, we dive into one of the coolest tricks in Ruby’s toolbox: lazy evaluation. It’s essentially procrastination for the win! Computations are delayed until they’re absolutely necessary. Ruby’s Enumerator::Lazy class is designed to effortlessly incorporate this lazy approach.

Imagine working on a FizzBuzz sequence but avoiding the whole load-everything-along-the-way routine:

def divisible_by?(num)
  ->(input) { (input % num).zero? }
end

def fizzbuzz_from(value)
  Enumerator::Lazy.new(value..Float::INFINITY) do |yielder, val|
    yielder << case val
               when divisible_by?(15)
                 "FizzBuzz"
               when divisible_by?(3)
                 "Fizz"
               when divisible_by?(5)
                 "Buzz"
               else
                 val
               end
  end
end

x = fizzbuzz_from(7)
9.times { puts x.next }

The Enumerator::Lazy class churns out FizzBuzz results starting from any given number, and it does so only when requested. Efficiency at its finest!

Enumerators are not just limited to basic collections. You can get fancy and use them with any iterable resource. An interesting use-case is paginating through an API data fetch, like Stripe’s API:

class StripeListEnumerator
  def initialize(resource, params: {}, options: {}, cursor: nil)
    pagination_params = {}
    pagination_params[:starting_after] = cursor unless cursor.nil?
    @list = resource.public_send(:list, params.merge(pagination_params), options)
  end

  def to_enumerator
    to_enum(:each).lazy
  end

  private

  def each
    loop do
      @list.each do |item, _index|
        yield item, item.id
      end
      @list = @list.next_page
      break if @list.empty?
    end
  end
end

In the snippet above, the enumerator interacts with the Stripe API, fetching data in pages as needed — a smart way of preventing your app from drowning in too much data at once.

So why bother with custom enumerators? This approach offers various perks:

Memory Efficiency: Yielding values as needed means no unnecessary data clogging up memory.

Flexibility: You get to customize iteration logic to fit your exact needs.

Performance: Lazy evaluation ensures computations happen only when necessary, speeding things up.

Scalability: Custom enumerators make it easier to handle large datasets and help scale your applications more effectively.

Picture this real-world scenario: say you’re working with a database and a particular SQL query is returning boatloads of IDs, more than your memory can handle comfortably. Custom enumerators come to the rescue:

def customer_property_ids(batch_size = 1000)
  sql = "SELECT DISTINCT PropertyId FROM AddressMatch"
  enum = Enumerator.new do |yielder|
    client.execute(sql).each_slice(batch_size) do |batch_ids|
      yielder << batch_ids
    end
  end
  enum
end

customer_property_ids.each do |batch_ids|
  # Process batch_ids here
end

In this setup, IDs are processed in neat batches, sidestepping the memory exhaustion hassle altogether.

Wrapping it up, Ruby’s Enumerator class lets you take precise control over how you traverse and handle data collections — all while keeping memory footprint slender and performance peppy. Whether dealing with hefty data sets from databases, APIs, or specific in-app data processing needs, custom enumerators prove to be a remarkably robust ally. With these insights and examples, you’re ready to start leveraging the power of custom enumerators in your Ruby adventures. Happy coding!