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All right, so welcome to "Steal This Talk". Today, I hope to give you some of my thoughts about how we can make Ruby more fun by learning from other languages.
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These languages have also tried to make fun a priority. A couple of notes before you begin.
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It is impossible for me to stand up here under the same lighting conditions that make me look really well-lit and naturally glowing.
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Additionally, this lighting makes it hard for me to see anyone in the audience.
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So if you have your hand raised or anything like that, I'm absolutely not going to be able to see you.
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Please feel free, however, to use my Twitter handle to tweet me questions.
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I will get a buzz on my phone when that happens, and I will respond to the questions that way.
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Hopefully, this will make for an engaging session as people have questions, and if I don’t get to your questions during the talk,
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I promise I’ll respond to you on Twitter afterwards.
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If you hate Twitter or just don't want to use it or don't have a Twitter account, that's 100% fine too.
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Please feel free to email me, and I'll also respond to your questions in the same way.
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All right, so just really briefly about me. I work for a wonderful company called Pivotal.
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Some of my fellow employees are up here in the front two rows.
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What I do there is work with enterprise companies who face a lot of challenges with how they build, deliver, develop, and design software.
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Writing software is difficult, and through that process, we get exposed to many different ways that people write software,
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different languages, and various assumptions about what is and isn't okay to put into software.
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I think that experience has formed the basis for this talk and exposed me to a lot of different ways of thinking about software and the tools that we use.
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I'd like to cover basically four themes.
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One is where do we come from as Rubyists? What are the ancestors of Ruby, and how have those languages influenced not only Ruby but also the broader programming community?
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Second, given that background, where might we be going in the future? What aspects of Ruby are probably going to be around long-term, and what might we see change?
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This is all speculation, of course; I know I'm not a dictator regarding the direction of the Ruby programming language.
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But what could we speculate on, and what are some things we're seeing in other programming languages that might be applicable to Ruby?
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Also, in the spirit of Ruby's current feature set and goals, what are some ways we could get there?
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I will show you some reference implementations of these ideas that are certainly not production-ready.
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There's a GitHub repo for it where I basically modified parts of the Ruby source code to produce these effects or some facsimile of them, at least.
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Then I'll close with a discussion about how we can do it to hopefully motivate you to try out these kinds of experiments on your own.
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Let’s start with where we are right now. The best way to understand where Ruby might be in the future is to look at how it got to where it is now.
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So let’s go back a bit into the history books.
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There’s a famous quote from George Santayana: "He who does not learn from history is doomed to repeat it." So let’s ensure we learn our history concerning Ruby.
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We use programming languages for all kinds of reasons.
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Some people just want to do work, while others are using it for fun or to do science.
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Some people use Ruby simply because it's enjoyable.
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Programming languages don’t exist in isolation; they are as much cultural artifacts as they are technological ones.
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They are products of the time and the assumptions made when they were designed and the challenges their designers faced.
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Of course, the people who contributed to the language in the first place need to be considered too.
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The chief advantage of programming languages over other kinds of tools is that they are malleable and mutable—they can change over time.
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If you mass-produce millions of screwdrivers and then discover they were supposed to be hammers, that's a big problem.
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In programming, however, if there's a problem, we can change it; we have that power.
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So the question is: Can we make those properties better for the tools that we have?
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If so, how? To explore that, I want to look at another programming language that is much older than Ruby but is still around.
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This language is the Massachusetts General Hospital Utility Multi-Programming System, or MUMPS for short.
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MUMPS is almost the opposite of Ruby in the sense that Ruby is considered a general-purpose programming language.
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MUMPS, however, is general-purpose with respect to its Turing completeness but very specific about the kinds of business problems it addresses.
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It turns out nobody likes saying the entire acronym, so it is commonly referred to simply as M.
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It’s worth noting that naming it after a deadly disease was perhaps not the brightest decision.
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MUMPS looks archaic by today's standards; however, if you rewind the clock to 1966 when it was created, it was comparatively modern.
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Despite its archaic appearance now, MUMPS has some of the most intriguing and, I would dare say, novel features.
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It's difficult to find some of these features anywhere else, showcasing how it addressed business issues at the time.
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I want to take you back about fifty years to 1966.
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In 1966, NASA had just finished the first-ever space docking.
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The U.S. Supreme Court had just decided on the Miranda case, establishing the Miranda warning.
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And the Batman series starring Adam West had just debuted on television.
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In the same year, the New Orleans Saints were created as an NFL franchise.
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The NFL needed an antitrust exception to merge with the AFL, and the two senators blocking it were from Louisiana.
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They agreed to create the New Orleans Saints in exchange for votes to pass the deal.
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However, you probably don’t care about any of that because as a technology director for the Massachusetts General Hospital system, something much more important happened in 1966.
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Transistors, which had been around for a while, started becoming miniaturized and cheaper.
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They began finding their way into sensors in small devices capable of taking readings from patients.
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Doctors loved these sensors because they eliminated the need for a team of nurses to gather routine patient data.
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What used to take an hour could now be done by a set of wires and recording instruments.
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This means each doctor could handle more patients than before and provide better care.
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However, the challenge was how to implement this in a hospital of that size.
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How would you manage the multitude of data points being collected every second?
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How could you report this data in a way that would be human-readable and accessible to practitioners?
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In 1966, MUMPS was trying to solve a problem akin to today's IoT challenges.
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At that time, the sensors were distributed all over the place and really basic—they could only write data.
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If you missed just one or two data points or recorded the wrong value, it could lead to a false diagnosis or incorrect treatment.
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In the worst-case scenario, it could mean not noticing a patient had a serious health issue.
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So how could you get that wide stream of data into a system that would reliably record it? That's what MUMPS was designed to tackle.
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MUMPS has a built-in database.
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When I say "built-in database," you might think of a standard library function for talking to databases or some communications protocol.
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But that's not what I mean. The memory model for MUMPS programs is not like the linear memory of most modern environments.
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Instead, it's a key-value store, which means that you read and write variables in memory by addressing and querying them inside this database.
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Essentially, all MUMPS programs had a tiny version of MongoDB inside them long before it was cool.
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That was MUMPS, but let’s consider what that might look like in a pseudo version of Ruby attempting to achieve similar functionality.
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A standard assignment in other programming languages might look like the following, where you assign the right-hand side of an operation to the left.
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In MUMPS, the operations are very different—it's a matter of setting keys and then querying those keys in the database.
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Instead of straightforward assignment, you can perform operations that yield new keys or sets of values.
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While it might visually seem similar to assignment, what's unique about MUMPS is that you can, for instance, ask to show all variables that start with a particular letter.
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This functionality would be more challenging to replicate in modern programming languages.
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When we talk about dynamic capabilities of MUMPS, we are considering features akin to metaprogramming.
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Remember, we are looking back to the year 1966, when metaprogramming was not yet a widely recognized concept.
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The ability to introspect your program dynamically was an innovative solution to the challenges they faced.
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They essentially took all of this data and dumped it directly into this database—there was no intermediate remote connection.
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The database was the program.
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This is a revolutionary way of solving problems: integrating a database directly into the execution process.
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This raises the question of whether we can apply what we've learned from Ruby's predecessors in similar ways.
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Languages are designed based on the best solutions available given the constraints of their time.
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Thus, Ruby also reflects the influences and ideas from those that came before it.
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Just look at Ruby's ancestors or its historical influences. When we consider the evolution of programming languages, it's essential to acknowledge what contributed to Ruby's shape.
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For instance, Lisp, a historical predecessor, is one of the oldest high-level languages, while Smalltalk introduced an idea of dynamic objects.
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Ada and other languages continued to develop structural elements that Ruby later benefited from.
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What about languages that are roughly contemporary with Ruby? Consider JVM-based languages such as Java.
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More recent languages like Scala and Clojure have also drawn inspiration from Ruby.
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On the other hand, newer languages like Elixir and Swift have taken cues from Ruby or featured developers who were originally Rubyists.
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So today, I want to discuss the aspects of those languages that might be interesting to bring back to Ruby.
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I'll divide this into a landscape of possible choices, representing things that could lead to improvement for Ruby.
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On the left axis, we'll look at things that yield more payoff for Ruby.
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The bottom axis, from left to right, comprises things that require more work.
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For instance, implementing gradual typing might require more effort compared to something like altering a few error messages.
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On the line, we will identify a fair trade-off: effort and payoff.
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Things above the line have more payoff for less work, and those below require more work for less payoff.
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We'll start off with relatively easy implementations based on my simplistic approach and a Ruby GitHub repository.
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Let’s take a look at error messages.
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When starting in any programming language, the first thing you encounter is probably the REPL or a simple 'Hello, world!' program.
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However, the second thing you see is when you mess up, and you receive an error message.
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Your first negative experience will be defined by how helpful that error message is in guiding you to fix the issue.
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Let’s start with a simple but incorrect C++ program.
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It’s not syntactically valid because it needs a type for the variable and lacks a main declaration.
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Imagine counting the number of error lines generated by trying to compile this program. How many errors do you think there would be?
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This is, of course, a trick question! So let’s hop over to the demo.
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Here’s that same file we saw before; let’s try to compile it.
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After compiling, we generate about twenty thousand error lines.
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And the result states that the type needs to be defined and becomes convoluted.
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This experience, while extreme, is not user-friendly.
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So let's look at Ruby. When you write a simple program to add two arguments, and you provide different types, Ruby will return a type error.
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However, in addition to showing a problem, Ruby also indicates the source of that issue.
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In comparison, Elm shows an error with contextual information, highlighting the line and explaining why the mismatch occurred.
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This clear communication indicates both what the expected type was and what was actually passed.
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Returning to Ruby, when we experience actual errors, we're often just presented with a stack trace.
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Ruby tells you the line where the issue is but lacks precise contextual definitions for that error.
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It’d be much better if Ruby could indicate which value contributed to the error and why.
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Adding context to these error messages, clearly identifying salient values involved and defining the differences between expectations and reality, would be extremely beneficial.
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Let’s move on to exception handling.
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Ruby primarily follows a bipartite strategy: one part of the code handles when things succeed, while another addresses failures.
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In contrast, Lisp and some functional programming languages utilize tripartite handling.
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In this approach, you set an invariant.
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When that invariant is violated, the code will branch into a section designed to handle that specific issue.
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This way, you can create a repair mechanism directly in your error handling.
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Another area worth discussing is pattern matching.
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In Ruby, we have case statements for branching based on object states.
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However, pattern matching requires you to enumerate every possibility for the object, ensuring no stones are left unturned.
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Essentially, it guarantees that any possible outcome is handled in your code.
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This is kind of like static type checking without a full static type system.
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Next is the topic of explicit module shadowing.
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In Ruby, when you mix in modules, you might want to override a method that is already defined in one of those modules.
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However, without a clear note indicating that you are overriding a method, it can be confusing for future readers of your code.
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We could benefit from a solution that explicitly marks when methods are being overridden.
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This way, anyone reviewing the code can understand the intention behind the method definition.
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Another topic is type inference; while not new, implementations are cropping up more in different languages.
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Type inference allows the programming environment to deduce the type of a variable.
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Imagine a future version of Ruby that utilizes gradual typing; type inference could make transitions smoother.
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This way, the user won't need to redefine types for everything they’ve created.
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Instead, the Ruby interpreter would automatically fill in the necessary metadata.
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The incorporation of all these ideas and a healthy appreciation for learning from both predecessors and contemporaries can empower Ruby.
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Ruby has thrived before and can continue to do so with these insights, ensuring it remains exciting and enjoyable to use.
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This concludes my talk; thank you for listening!
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Let me see if there are any more Twitter questions. Is the mic on? Yes? Okay.
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Keith Walsh asked regarding type inference, have you checked out Crystal?
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Crystal looks almost exactly like Ruby but with strong typing and interesting features.
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It’s appealing to those who enjoy the aesthetic of Ruby but prefer static typing.
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However, none of the libraries from Ruby work in Crystal as they are not binary compatible.
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In contrast, languages like Elixir share some similarities with Ruby thanks to their Rubyist roots.
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The beauty of Ruby is evident, inspiring many to modify and enrich the core concepts further.
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Yes, Keith, I have heard of Crystal; it’s cool, but I’m still learning more about its traits.
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Are there any other questions?
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I think there's another question about the font.
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The font is fast! Size VIII is my favorite.
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Thank you! I hope you enjoyed the talk.
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I didn’t see any other significant questions, but I will follow up with everyone afterwards.
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Thank you again for sitting through the technical difficulties, and have a wonderful rest of RubyConf!
