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It's time for the awesome Matz to give us the keynote, so let's get started and welcome him.
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Welcome to the stage!
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Giving a keynote in English makes me nervous every time, but I believe I can manage.
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In recent years, we have been working on something called Ruby 3.
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Ruby 3 represents the future of Ruby. However, you will not see Ruby 3 this year or next year; it's a vision for the distant future.
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In that sense, Ruby 3 is currently more of a concept than a reality.
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Since it is just a vague notion, we must acknowledge that these ideas are fragile, but we need some goals to aim towards in order to advance the Ruby community.
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Especially for the Ruby community, setting clear goals is essential for progress.
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A very important aspect of the future Ruby is that it should remain compatible with current Ruby versions.
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We experienced a huge gap when we transitioned from Ruby 1.8 to 1.9, which was very challenging.
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We needed to support multiple encodings and better Unicode support during that transition.
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We want to avoid such pain in the foreseeable future.
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So, despite the fact that we are trying to introduce many dramatic features in Ruby 3, we will strive to maintain compatibility with the existing versions.
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The key features of Ruby 3 will focus on performance, concurrency, and typing.
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For performance, we have a slogan: "Ruby 3 x 3," meaning that Ruby 3 will be three times faster than Ruby 2.
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That sounds great, right? We are working on optimizing the garbage collection (GC), improving the virtual machine (VM), and other optimizations.
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We are also investigating the introduction of Just-In-Time (JIT) compilation to the Ruby virtual machine.
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However, making Ruby three times faster is not an easy task.
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We've been developing Ruby and its interpreters for more than 20 years, and we have already optimized many easy targets.
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Because of that, achieving a threefold increase in speed will be quite a challenge.
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We compare Ruby 3 to Ruby 2.0, which is a version that's about three years old, and we've improved Ruby consistently.
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For instance, each year since Ruby 2.0, we've introduced improvements at a rate of 5 to 10%.
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Each version is designed to be faster than the previous one.
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Hence, we aim to include all of those efforts in Ruby 3, even though not everything can be three times faster.
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We will choose specific benchmarks where Ruby 3 will run faster than Ruby 2.
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These benchmarks will be small; we don't want to install large frameworks or huge applications for testing.
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However, they should not be overly simplistic, like calculating factorials.
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We want realistic benchmarks that reflect actual performance improvements.
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Now, let's discuss concurrency. I started designing Ruby in 1993, and back then, computers only had one CPU.
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That meant we didn’t have to worry about threading or parallelism since there was only one execution thread at a time.
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Because of that, I only considered concurrency and added threading to the language.
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But I didn't give much thought to parallelism.
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Today, however, we are living in a multi-core age with dual-core, quad-core, and octa-core CPUs in laptops and smartphones.
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Everyone wants to leverage concurrency and parallelism.
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People want to utilize concurrency and parallelism through threading.
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But we face challenges with threading, especially in Ruby, due to the Global Interpreter Lock (GIL).
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Due to the GIL, only one thread can run at a time in the Ruby virtual machine.
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So, there is no true parallelism, even on multi-core machines.
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This creates a trade-off between performance and safety. Multicore machines can perform better, but threading introduces complexity.
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Managing threads independently while ensuring synchronization is quite challenging.
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By changing a few lines of code, it's possible to remove the GIL from the Ruby virtual machine.
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However, your threaded program will likely crash if you try that.
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We prioritize safety in the Ruby virtual machine.
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Threading can be considerably complex without the right language features, unlike languages like Elixir.
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For this reason, we concluded we need better abstractions for concurrency.
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We investigated various models: the actor model, streaming model, and ownership model.
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Last year, I discussed the concurrency topic in my keynote, particularly focusing on the streaming model.
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However, we decided to abandon the streaming model and have opted for a form of the ownership model with slight modifications.
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This model needs a name, so we are looking for a suitable term.
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Kichi, who is in charge of the virtual machine, has been searching for this concept for years.
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Finally, we came up with a name for this idea: ‘Guild.’
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A guild represents a community of craftsmanship, reminiscent of role-playing games.
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In this guild model, each object is a member of a guild, and you can transfer the membership of an object to another guild.
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However, objects must be moved instead of copied, and such transfers can occur via channels.
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Think of it like goroutines, with some abstractions layered on top of the current Ruby model.
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It resembles the actor model and shares minimal mutable state.
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While classes and modules can be shared, we will still have the GIL.
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Each guild is isolated, allowing multiple guilds to run in parallel.
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Within a guild, you can still have threads, but only one thread can run at a time.
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This concurrency model ensures that different guilds can execute in parallel, enhancing performance.
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We provide a better abstraction for concurrency while maintaining compatibility.
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This approach should reduce bugs in the system.
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We've moved away from the streaming model and instead experimented with that model in another language I created called Stream.
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This is my personal toy language featuring the streaming model available on GitHub.
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Now, let’s move on to the final and biggest topic of this keynote: typing.
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In this decade, we have seen the rise of many new programming languages, most of which are statically typed.
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Examples include TypeScript, Flow, Go, and Swift. Statically typed languages have gained a lot of popularity.
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I often hear hostile claims that Ruby is dead because it lacks static typing.
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Who really cares? We should not be swayed by technological trends that come and go.
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For example, during the 1980s, dynamically typed programming languages like Lisp and Smalltalk were very popular.
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Eventually, many developers shifted towards statically typed object-oriented languages like Java.
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Yet, some developers from the Java world later transitioned to Ruby and JavaScript.
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And now we see some of those developers moving toward statically typed languages like Swift and Go.
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This cycle of migration happens roughly every decade.
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What does the future hold? It's possible that we will see a shift towards statically typed languages again.
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As front-liners, we must think about the future of dynamic typing.
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So, what does typing mean in dynamically typed programming languages like Ruby?
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In statically typed languages, a class is a type, but in Ruby, the class is not necessarily a type.
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We have a principle called duck typing.
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Duck typing suggests that if something behaves like a duck, it is treated as a duck.
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In other words, we ignore inheritance or internal structure and focus on behavior.
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In Ruby, we care about how things behave rather than the details of how they are implemented.
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Thus, duck typing is the Ruby way, where simplicity and ease of use are prioritized.
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Dynamic typing allows us to ignore unnecessary formalities and reduces cognitive load.
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Our mental resources are limited, so we should conserve them.
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For example, when we need a logging function, we might use a string to log messages.
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In a statically typed version, we might need to provide type annotations.
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But in Ruby, we can create a StringIO to log messages and retrieve them easily.
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However, in the static typed world, that would fail because StringIO and other types do not share a common ancestor.
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This is where duck typing shines: it allows flexibility and reduces mental costs when developing programs.
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Furthermore, duck typing leaves room for ambiguity, making it easier to represent behaviors without strict rules.
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In Ruby, a type is not nominal; instead, it's defined by the expected behavior.
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We don't need exact names or strict inheritance hierarchies.
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Although we can call for more expressive interfaces, that often causes unnecessary limitations.
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In Ruby, we prioritize 'Don't Repeat Yourself' (DRY), which means avoiding redundancy.
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If you can execute a program without some factors, you should remove them.
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Currently, dynamic typing implies that we don’t need to repeat type annotations.
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While dynamic typing has its downsides, such as discovering errors only at runtime, this can promote better development practices.
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Nonetheless, dynamically typed languages often produce less clear error messages.
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For example, receiving an error message like ‘undefined method for a new class' can be frustrating.
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With class annotations, documentation suffers as well, as we often only provide type information in comments.
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While static typing can be productive, it contradicts the essence of Ruby.
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While it would look like we are incorporating static typing without truly enforcing it, the essence of Ruby lies in its flexibility.
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As engineers, our goal is to find solutions without unnecessary complications.
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One solution is type inference, seen in languages such as Scala or OCaml.
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Type inference allows the compiler to determine variable types without explicit annotations.
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This strikes a balance between flexibility and type safety.
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The compiler can catch more errors during compile time, combining the benefits of dynamic and static typing.
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For instance, we can simplify the Go interface example with inferred types, which closely resembles Ruby's dynamic typing.
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This gives us a sense of dynamic inference, defined by behavior instead of strict naming.
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In Ruby, inferred types are not necessarily linked to class names; they represent expected behavior.
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However, inference isn't perfect. For example, we may encounter situations where one object conforms to a type but lacks others.
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Duck typing doesn't guarantee full coverage like suggestive static typing can in other languages.
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Still, we achieve more reliable typing in Ruby through inference, reducing the chances of error at runtime.
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We can incorporate ad-hoc type information for error detection, allowing runtime analysis.
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By combining known type behaviors from specific objects, we can check type compatibility.
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For example, if a method requires a particular type of argument, the system should recognize this and provide feedback.
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Also, runtime type information allows for more profound insights, improving the developer experience.
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By collecting data on argument types, we can create a type database for our applications.
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This knowledge can enhance our coding experience, enabling better productivity tools in the future.
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This is still in the conceptual phase, but we're actively researching these improvements.
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It's crucial for Ruby to keep evolving. Many older languages have stagnated, leading to diminishing communities.
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I don't want that for the Ruby community; I want it to flourish. Ruby needs to progress to avoid stagnation.
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We need motivation and a driving force to continue moving forward.
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The primary motivation behind Ruby 3 is to enhance productivity and enjoyment in programming.
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We care about programmers and their experiences while using Ruby.
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The question on your minds might be: when will all of this be available?
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The short answer is: I don't know.
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The longer answer suggests that it will take years.
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We have a lot of work ahead with duck typing, Ruby 3 x 3, guilds, and other features.
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You may need to wait a couple of years, unfortunately, but we welcome your feedback and contributions.
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We want your input to help us continue moving forward in the Ruby community.
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Each Ruby user and developer can contribute to Ruby’s growth.
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This is perhaps the most important message and motivation behind the Ruby 3 project.
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Let’s embrace programming in Ruby, enjoy it, and focus on improving our ecosystems.
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Together, we can strive to become better programmers.
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This concludes my keynote. Thank you, and happy hacking!
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Thank you, Matz.
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[End of transcript]
