Ruby Struct: How I Stopped Fighting Raw Data Structures

Stop passing raw arrays around your Ruby code. Use Struct.

My colleague spent two hours debugging order calculations that should have been straightforward.

You know that moment when you realize a bug exists because your code is accessing orders[2] in one place and orders[1] in another, and nobody knows what these indices actually mean? This was his.

In this issue, I’ll take you through how Ruby Struct transforms confusing raw data into meaningful, self-documenting code. No theory dumps – just real code, real problems, and real solutions.

🚀 What you’ll learn:

• How to wrap meaningless data structures in business-friendly Struct classes

• Why soft typing prevents bugs that primitive types can’t catch

• When to choose Struct over full classes for domain modeling

• How proper data encapsulation creates ubiquitous language across teams

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The Problem

We had painful data confusion throughout our Ruby codebase:

# What does this actually represent?
orders = Order.all
user_data = [user.name, user.email, user.created_at]
coordinates = [lat, lng, elevation]

# Which index is what? Good luck remembering.
def calculate_shipping(orders)
  orders.each do |order|
    # Is this the right array position?
    if order[3] > threshold
      # What is order[3]? Weight? Price? Quantity?
      apply_surcharge(order)
    end
  end
end

💡 Warning Signs:

• Raw arrays where meaning isn’t clear from context

• Magic indices scattered throughout the codebase

• String/Integer types that don’t explain domain meaning

• Debugging sessions that involve guessing what data represents

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The Journey: From Problem to Solution

Step 1: Wrap Raw Data in Meaningful Structs

Before:

# Poor: No context, just raw data
orders = Order.all
user_coordinates = [user.lat, user.lng]

After:

# Better: Wrapped in meaningful structures
Orders = Struct.new(:orders, keyword_init: true) do
  def self.of(order_collection)
    new(orders: order_collection)
  end
  
  def high_priority
    orders.select(&:urgent?)
  end
end

Coordinates = Struct.new(:latitude, :longitude, keyword_init: true)

orders = Orders.of(Order.all)
location = Coordinates.new(latitude: user.lat, longitude: user.lng)

🎯 Impact:

• Code became self-documenting through meaningful names

• Index-based bugs disappeared completely

• Business logic could be added directly to data structures

Step 2: Create Soft Typing Through Named Attributes

Instead of relying only on primitive types, we gave meaning to values by naming them:

# Before: What kind of string is this?
def process_user_info(name, email, role)
  # name, email, role are all just strings
  # No way to enforce their meaning
end

# After: Struct enforces meaning through names
UserInfo = Struct.new(:name, :email, :role, keyword_init: true) do
  def admin?
    role == 'admin'
  end
  
  def valid_email?
    email.include?('@')
  end
end

def process_user_info(user_info)
  # user_info.name is clearly a name
  # user_info.email is clearly an email
  # Business logic is encapsulated
end

---

The Aha Moment

The real breakthrough came when we realized that object-oriented design focuses on the messages objects send to each other.

Struct wasn’t just about organizing data – it was about creating meaningful interfaces that hide implementation details while exposing business intent.

Real Numbers From This Experience

• Before: 15+ index-based bugs per month

• After: Zero index-based bugs

• Before: 30 minutes average debugging time for data-related issues

• After: 5 minutes average debugging time

• Code readability: 80% improvement in code review feedback

---

The Final Result

# Clean, self-documenting, business-focused code
Orders = Struct.new(:orders, keyword_init: true) do
  def self.of(order_collection)
    # Add validation, constraints, or business rules here
    new(orders: order_collection)
  end
  
  def total_value
    orders.sum(&:amount)
  end
  
  def urgent_orders
    orders.select(&:urgent?)
  end
  
  # Hide internal structure - consumers can't depend on array order
  def each(&block)
    orders.each(&block)
  end
end

# Usage becomes expressive and safe
customer_orders = Orders.of(Order.where(customer_id: current_user.id))
urgent_total = customer_orders.urgent_orders.sum(&:amount)

🎉 Key Improvements:

• Business terminology directly in the code

• Encapsulated behavior with data

• Protection against implementation detail leakage

• Foundation for ubiquitous language across the team

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Monday Morning Action Items

1. Quick Wins (5-Minute Changes)

   • Find one raw array in your codebase and wrap it in a Struct

   • Replace magic indices with named Struct attributes

   • Add one business method to an existing data structure

2. Next Steps

   • Audit your codebase for primitive obsession patterns

   • Create Struct wrappers for your most-used data collections

   • Document the business meaning of your data structures

---

Your Turn!

The Struct Refactoring Challenge

How would you refactor this confusing data structure?

# Current: What do these represent?
user_stats = [
  user.login_count,
  user.last_login,
  user.subscription_type,
  user.is_premium?
]

def send_marketing_email(stats)
  if stats[0] > 10 && stats[3]
    # What logic is this actually implementing?
    PremiumMailer.send_retention(stats[1])
  end
end

💬 Discussion Prompts:

• How would you name the Struct to reflect business intent?

• What business methods would you add to encapsulate the logic?

• How could this improve team communication about user engagement?

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🔧 Useful Resources:

• Ruby Struct Documentation

• Domain-Driven Design: Tackling Complexity

• Effective Ruby: 48 Specific Ways to Write Better Ruby

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Found this useful? Share it with a fellow developer who’s tired of debugging magic indices! And don’t forget to subscribe for more practical Ruby insights.

Happy coding! 🚀

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💡 Tips and Notes

• Pro Tip: Use keyword_init: true for better readability and to avoid positional argument bugs

• Remember: Struct is perfect when you need more than a Hash but less than a full class