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Hello, everyone! Welcome to my talk.
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Today, I will be discussing functional programming (FP) for fun and profit.
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The title might be misleading because, as I rehearsed this morning, I realized it's not as fun as I thought it would be.
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But since you’re already here, you might as well stay till the end!
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I want to open up with a GitHub article titled "Functional Programming is Finally Going Mainstream." This article discusses the increasing adoption of functional programming over the years.
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You might have seen discussions, tutorials, or explanations about functional programming concepts here and there, as well as memes and parodies related to some of its concepts.
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You might be wondering what functional programming really is and whether you should care about it if you just want to write your Ruby code.
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After all, Ruby is known for being object-oriented, where everything is an object.
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Today, I want to convince you that functional programming can help us write better Ruby code.
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Before we dive into that, let me share a bit about myself. My name is Jenny—it's easier for everyone to call me that—and two big events happened in my life two months ago: I started working at Shopify and moved from Taiwan to Toronto, Canada.
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I primarily program with Ruby, but there was a time when I almost transitioned to Elixir, which is one of the main reasons I am giving this talk.
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You’ll soon find out that I drew a lot of inspiration from Elixir for this presentation.
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Also, if you visit my personal website, you will see a string of chicks that follow the cursor wherever it goes, which is kind of therapeutic.
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Okay, with that introduction out of the way, let's talk about the functional programming paradigms.
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According to Wikipedia, functional programming is a way to classify programming languages based on their features.
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There are many programming paradigms out there, such as object-oriented programming, characterized by message-passing between objects and encapsulating state and behavior.
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Functional programming, which is the focus of today's discussion, has its own unique set of features, which I will talk about shortly.
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To help us understand these concepts better, let’s first look at a mental model.
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Consider three elements: value, behavior, and time.
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To illustrate this, let’s look at an example: a function 'puts' that prints out the string "Hello, World!" and returns nil.
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In this case, we see two components: behavior—what the function does, and value—what it holds.
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In another example, if we assign 'rubyconf mini' to a variable 'curve' and later change it by uppercasing it, we are illustrating the element of time.
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Between lines of code, the bytes in the machine change, resulting in the value of the variable 'curve' being updated.
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To understand what time represents, we can think of it as the value of an identity we hold on to during a specific period.
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This is my mental model of what object-oriented programming looks like: an object encapsulates value and behavior, while time is implicitly involved because values can change over time.
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In functional programming, each element has a distinct concept associated with it, and the goal today is to explore each of these elements.
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Let's begin with the first element: value.
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When discussing value in functional programming, we need to address immutability.
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Immutability means that once you initialize a value, you do not change it.
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In Ruby, this is achieved by freezing objects, such as an array.
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When defining objects using the class keyword, you should avoid using attribute writers and accessors, which allow other objects to mutate its attributes.
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This goes against the definition of immutability, and thus, we must understand why immutability is important.
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With immutable objects, we eliminate shared state complexities. We don’t need to care about when and where objects change because they never do.
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Consider this example: I have a flight scheduled for November 14th, and if my friend copies my flight and changes the date to November 13th, it reflects on my flight as well.
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This occurs due to shared state: by mutating state, we can run into unexpected bugs.
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In programming, immutability helps us avoid these pitfalls.
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Now, how can we implement immutability in Ruby? The first piece of advice is to think twice about every state limitation you introduce.
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Ruby, at a language level, doesn’t support immutability natively like some other programming languages, so it's up to us to avoid writing mutable code.
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This good habit will reduce the likelihood of producing bugs.
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For instance, there’s a gem called 'dry-struct' that is part of the dry-ruby collection.
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This gem offers powerful and useful tools supporting functional programming ideas, including immutable data structures.
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In Ruby 3.2, there’s also a new feature called data defined, which provides simple immutable value objects. You can play with this in the latest version and find excellent documentation.
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So, although we have tools to aid us, it’s equally important to be mindful of state mutations and their consequences.
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We have now covered the value aspect of functional programming. By enforcing immutability as a constraint, we create programs that are easier to debug and reason about.
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Next, let's examine behavior in functional programming.
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The core concept is the use of pure functions.
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A pure function meets two conditions: it depends only on its input arguments and does not depend on any external values.
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For example, if we create a function that uses the Time class, it’s not pure because it depends on the module, resulting in different outputs even with the same input.
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In contrast, if we pass the timestamp itself as an input, we create a pure function, as its output can now be predicted based on the input.
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The second condition for a pure function is not mutating the state, which implies having no side effects.
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If a function alters the string value passed to it, it cannot be considered pure, as doing so mutates its state.
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To make this function pure, we must create a new string without altering the original.
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Why do we want to restrict ourselves in this way? Joe Armstrong, the creator of Erlang, points out that all languages come with an implicit environment.
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This implicitness can lead to unexpected consequences and confusion.
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Avoiding implicit environments allows us to focus on smaller, manageable parts of a problem.
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This approach leads to improved efficiency and bug prevention, as we can concentrate on details.
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To summarize, by striving for pure functions, we minimize the complexities that arise in programming.
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The next element we’ll discuss is time, particularly in relation to processes and concurrency.
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In object-oriented programming, concurrency can be challenging due to time being an implicit factor.
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This leads to potential issues, such as race conditions and deadlocks when multiple processes run simultaneously.
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The infamous Global Interpreter Lock (GIL) in Ruby restricts it such that only one thread may execute at any time, improving safety but reducing concurrent capabilities.
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On the other hand, functional programming tackles this issue by explicitly treating time as a separate element, which can simplify concurrency.
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In an example from Elixir, a functional programming language, concurrency is inherently implemented through its actor model.
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In this model, each process acts as an individual unit that can only communicate with others through message passing, ensuring no shared state.
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Elixir processes are lightweight, allowing millions to run simultaneously, thereby enhancing concurrency.
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Ruby has introduced a similar concept called 'Ractor' starting from version 3.0, which aims to improve concurrency.
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In a Ractor model, every Ractor can run in parallel without sharing state, making computation safer and more efficient.
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If we attempt to send objects between Ractors, they must be immutable to maintain the simplicity of state.
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I’m looking forward to future developments in Ractor and the potential it offers for Ruby programming.
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In conclusion, functional programming promotes the use of immutable data and pure functions.
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Together, these concepts not only enhance code reliability and maintainability but also provide an excellent foundation for concurrent programming.
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The best part is, you can apply these principles in Ruby!
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I hope you found value in this talk and encourage you to explore further into functional programming.
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Remember, adopting a new paradigm requires practice and adaptation.
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These are the resources that I found useful, and I will upload my slides later.
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Thank you for your time!
