2020 年编程语言盘点展望：Java 老兵不死，Kotlin 蓄势待发

在进入新的十年之际，各行各业都在进行盘点与展望。SegmentFault 作为开发者社区与科技行业的垂直媒体，一直关注行业的发展与相关动态，近期已陆续为大家整理了各大平台、社区针对技术领域作出的预测与盘点。

今天，继续为大家粗译（文末有原文地址，粗译仅供大家前期了解，建议阅读英文原文）O'Reilly 发布的编程语言发展展望 —— 《Where programming languages are headed in 2020》。

该盘点及分析由数位编程专家整理得出，包含了大量他们对于某些经典编程语言以及新兴编程语言的思考以及基于行业的分析。

Python

今年 Python 的最大新闻是，Python 之父吉多·范·罗苏姆（Guido van Rossum）正式退休，并将 Python 交给了 Python 指导委员会。到目前为止，这次权力转移并没有出现“阵痛”，正如《Python Crash Course》的作者 Eric Matthes 所认为的那样，这是很正常的，因为“ Guido 在很长一段时间里仍将保持自己在社区中的角色。” 此外，2020 年还将终止对 Python 2.7 的支持，这很可能导致坚持使用 Python2.7 的人变得很难受。

但不管怎样，Python 仍然是数据科学的首选语言。

对于 Matthes 而言，Python 令人兴奋的一个方面是“来自一个社区的各种有趣且关键的项目已经诞生了，而社区已经如此有意识地建立了这么长时间。” Python 指导委员会成员和 CPython 的核心开发人员 Carol Willing 也庆祝了这些项目，例如 Binder 服务，该服务通过在 Jupyter Notebook 中创建可执行环境来促进可重复的研究，尤其是当它们超出其最初的目标时。

她指出，“活页夹去年在许多 Python 会议上被广泛用于教学讲习班和教程。” Willing 还向 CircuitPython 和 Mu 项目大声疾呼，问道：“谁会不喜欢硬件呢，闪烁的 LED、传感器，以及使用 Mu 的用户友好的编辑器，这对成年人和孩子来说不都是很棒的选择？”

Java

今年对 Java 来说，主要都是好消息。本·埃文斯（Ben Evans）解释说：“再一次，关于 Java 灭亡的传言再一次成为了平台批评者的一厢情愿。”

但这并不是一帆风顺的。正如我们去年指出的那样，Java 11 于 2018 年 9 月发布并带来了许多新功能，包括许多在使用容器方面具有明显优势的重要功能。但是，根据 JetBrains 的调查，这次新版本的推出并没有带来广泛的采用，超过 80％ 的开发人员仍在使用 Java 8。

Evans想知道：“这是否意味着人们没有像我们所知道的那样在容器中运行Java？还是人们只是不知道在容器中使用 Java 11 的好处？”

尽管采用速度缓慢，但 Java 的六个月发布节奏一直在不断发展-Java 12于2019年3月下降，Java 13于9月问世。根据 Trisha Gee 的说法，它确实开始显示其价值：

每个版本很小，但是可以预见。尽管它们并不都具有令人兴奋的新语言更改，但是您可以看到该语言正在稳步向前发展。

此外，它支持预览功能的这种想法，我认为我们切换表达式的工作效果非常好 —— 开发人员必须尝试使用该功能并根据使用感觉来提供真实的反馈，而不是抽象的，概念性的反馈想法。在 Java 13 中，开关表达式的语法进行了少量更改，这是有可能的，因为它是预览功能，并且没有固定设置。

每个版本很小，但是可以预见。尽管它们并不都具有令人兴奋的新语言更改，但是您可以看到该语言正在稳步向前发展。

此外，它支持预览功能的这种想法，我认为我们切换表达式的工作效果非常好 —— 开发人员必须尝试使用该功能并根据使用感觉来提供真实的反馈，而不是抽象的，概念性的反馈想法。在 Java 13 中，开关表达式的语法进行了少量更改，这是有可能的，因为它是预览功能，并且没有固定设置。

至于刚刚到来的 2020 年，埃文斯（Evans）建议 2020 年可以持续关注 2019 年的发展趋势：

我们将如何接近 Valhalla 项目的生产版本？提供模式匹配和代数数据类型（Project Amber）的增量策略是否会奏效？Quarkus 会履行其承诺和早期粉丝的信念吗？2020 年将成为 Kotlin 会在 Android 领域迈出跨跃性的重要一步吗？

这是激动人心的时刻，我们正在过渡到新的事物，并且正在发生很多事情。

我们将如何接近 Valhalla 项目的生产版本？提供模式匹配和代数数据类型（Project Amber）的增量策略是否会奏效？Quarkus 会履行其承诺和早期粉丝的信念吗？2020 年将成为 Kotlin 会在 Android 领域迈出跨跃性的重要一步吗？

这是激动人心的时刻，我们正在过渡到新的事物，并且正在发生很多事情。

Kotlin

谷歌在 2019 年 5 月宣布 Kotlin 现在是 Android 应用开发人员的首选语言，这表明了该语言已经被广泛采用。

尽管许多 Android 开发人员尚未完全迁移到 Kotlin，但已经迁移的人都知道它提供的好处。《Head First Kotlin》的作者 Dawn 和 David Griffiths 分享了 Kotlin崛起背后的一些原因：

对于由 IDE 公司创建的语言，Kotlin 拥有良好的工具支持水平也就不足为奇了。用于代码合同的实验性 DSL 使开发人员能够提供有关代码行为方式的保证。您的功能有副作用吗？是否可以保证返回非空值？代码合同允许您做出这些承诺，并且编译器可以使用它们来放松编译时检查。

现在，不同的 Kotlin 平台之间的障碍也正在被打破。“expect”/”actual”限定符使开发人员可以更轻松地编写跨 Java / Native / JS 环境兼容的代码。序列化支持意味着将 JSON 数据转换为 Kotlin 对象更加容易，反之亦然。

对于由 IDE 公司创建的语言，Kotlin 拥有良好的工具支持水平也就不足为奇了。用于代码合同的实验性 DSL 使开发人员能够提供有关代码行为方式的保证。您的功能有副作用吗？是否可以保证返回非空值？代码合同允许您做出这些承诺，并且编译器可以使用它们来放松编译时检查。

现在，不同的 Kotlin 平台之间的障碍也正在被打破。“expect”/”actual”限定符使开发人员可以更轻松地编写跨 Java / Native / JS 环境兼容的代码。序列化支持意味着将 JSON 数据转换为 Kotlin 对象更加容易，反之亦然。

希望看到 Kotlin 继续保持惊人的增长 —— 并且不仅仅是在 Android 中。JetBrains 开发人员倡导团队负责人 Hadi Hariri 指出 Kotlin / Everywhere 的成功，使得人们可以在 Android，Google Cloud Platform 和多平台开发中学习 Kotlin 的基本知识和最佳实践，并用数据举例证明：

“从 5 月到 11 月，我们已经成功地覆盖了 86 个国家/地区的 30,000人。KotlinConf 在 2019 年连续三年销售一空，有 1,700 多名与会者。这尤其表明，开发者对该语言的兴趣和采用正在增长。”

Go

当 Gophers 回顾 2019 年时，他们可能会记得尝试提案的传奇故事。Go 开发人员兼作家 Jon Bodner 解释说：

关于 Go 的最常见的抱怨之一是错误处理太冗长。因此，在 6 月初，Go 核心开发人员建议添加一个名为 try 的新内置函数。GitHub 的 issue 现在已打开，以讨论此新功能。一个月之内，有将近 800 条评论，其中大多数是负面的。反对这项新功能的人们感到，这种改变使代码过于“不可思议”，并掩盖了逻辑流程。审查反馈后，Go 小组将提案标记为已完成，并于 7 月 16 日关闭。

关于 Go 的最常见的抱怨之一是错误处理太冗长。因此，在 6 月初，Go 核心开发人员建议添加一个名为 try 的新内置函数。GitHub 的 issue 现在已打开，以讨论此新功能。一个月之内，有将近 800 条评论，其中大多数是负面的。反对这项新功能的人们感到，这种改变使代码过于“不可思议”，并掩盖了逻辑流程。审查反馈后，Go 小组将提案标记为已完成，并于 7 月 16 日关闭。

这个过程值得注意的不是功能的失败，而是，正如 Bodner 所描述的那样，“过程发生的方式：提出了一个功能，讨论受到尊重，但许多人认为更改与 Go 的风格不一致。最后，管理语言的人决定尊重多数意见。这就是开发人员谈论社区时的意思。”

2020 年应该使 Go 的 Contracts 规范更加清晰，这就是众所周知的 Generics 提案。

根据 Bodner 的说法，“ Go 似乎将使用一种与其他语言略有不同的方法来实现泛型，但它很适合 Go 的习惯用法。” 希望它将使 Go 保持其惯用的风格，同时添加开发人员发现在其他语言中有用的功能。

Rust

我们与《Programming Rust》的合著者 Jim Blandy 进行了沟通，以了解他对 Rust 在 2019 年的进步的看法如何变化。

去年，他指出，“ Rust 长期以来一直以一种形式或另一种形式支持异步编程，但是异步函数为这种代码提供了语法与 Rust 以前的产品相比，这是一个重大改进。”

他对 Rust 语法进行改进的希望是否实现了？是的，最终：布兰迪解释说，异步/等待语法直到 2019 年 11 月 7 日发布的 1.39 版才变得稳定。

“最初，我们希望异步/等待语法可以成为 Rust 2018 版的一部分，但它花了更长的时间才把事情做好。” 不过，他对 2020 年 Rust 对 Rust 的意义寄予了很高的期望：“将异步集成到语言中可以使借阅检查器了解您的操作，因此异步代码看起来像惯用的 Rust。

Rust 社区也对 WebAssembly 感到兴奋，今年 WebAssembly 成为了 C / FFI 的理论替代品，用于需要便携式，高性能模块的生态系统。正如 Rust 专家 Nathan Stocks 指出的那样：“您也可以使用轻型沙箱！” 令 Stocks 印象最深的是“有多少理论已经成功原型化并得到了证明。”

以前，我曾把WebAssembly纯粹视为一个编译目标，以便在浏览器中运行非JS语言的代码。能够从浏览器之外的任何语言使用Web程序集的功能令人不寒而栗。

以前，我曾把WebAssembly纯粹视为一个编译目标，以便在浏览器中运行非JS语言的代码。能够从浏览器之外的任何语言使用Web程序集的功能令人不寒而栗。

Swift

去年 Swift 发生的最大的故事是苹果公司用于在所有苹果设备上设计用户界面的最新框架 SwiftUI 的发布，以及 TensorFlow 的 Swift 版本。

正如 Timirah James 解释的那样，SwiftUI 的声明性已经赢得了开发人员的广泛关注，并且已经被视为 UIKit 的未来继任者。

至于 TensorFlow 的 Swift，Buttfield-Addison 称之为“ Swift 的根本新用途”。他解释说：“ Swift 一直是一种出色的应用程序开发和系统编程语言，并且是一种新兴的 Web 和后端开发语言，但是现在，借助 Swift for TensorFlow，它也是一个强大的 ML 框架。” 原因如下：

Swift for TensorFlow 由一个团队开发，该团队包括 Swift 的原始创建者 Chris Lattner，并提供（或将在完成后提供）机器学习和数值计算所需的一切。最令人惊讶的是，Swift 的基础编译器框架和设计使对具有可自动区分功能的可区分编程的完全一流支持成为可能。

完整的语言可区分编程将使以前不可能的事情成为可能：最好的例子是在构建神经网络时能够使用标准编程调试器逐步进行反向传播并调试派生类。

Swift for TensorFlow 还为 Swift 提供了完整的 Python 支持，使数据科学家可以使用清晰的 Swift 代码将所需的有用和熟悉的 Python 框架进行混合和匹配。

Swift for TensorFlow 由一个团队开发，该团队包括 Swift 的原始创建者 Chris Lattner，并提供（或将在完成后提供）机器学习和数值计算所需的一切。最令人惊讶的是，Swift 的基础编译器框架和设计使对具有可自动区分功能的可区分编程的完全一流支持成为可能。

完整的语言可区分编程将使以前不可能的事情成为可能：最好的例子是在构建神经网络时能够使用标准编程调试器逐步进行反向传播并调试派生类。

Swift for TensorFlow 还为 Swift 提供了完整的 Python 支持，使数据科学家可以使用清晰的 Swift 代码将所需的有用和熟悉的 Python 框架进行混合和匹配。

展望未来，James 和 Buttfield-Addison 都很高兴看到 Swift 所采取的新方向，James 指出“ Swift 在移动社区以外的不同社区和堆栈中迅速采用，特别是在无服务器领域，” Buttfield-Addison 呼吁“令人惊叹的网络开发框架（如 Kitura）以及各种针对特殊领域的令人惊叹的框架……例如 SwiftPlot，它是 Python 中无处不在的 Matplotlib 的 Swift 本机版本。”

未来是什么样的？

变化是不可避免的，并且随着编程语言继续倾向于针对云，微服务，大数据和机器学习中的新趋势进行优化，每种语言及其生态系统将继续以自己独特的方式进行适应。

某些语言可能会在 2020 年发布大版本，比如 C ++ 20 将于今年夏天发布，Scala 3.0 有望在 2020 年末发布。但很明显，即使是最小的更改也可能在程序员的日常生活中引起巨大的波澜。

原文链接：

https://www.oreilly.com/radar/where-programming-languages-are-headed-in-2020/

Where programming languages are headed in 2020

Experts discuss what's in store for popular and growing programming languages.

Zan McQuade & Amanda Quinn

As we enter a new decade, we asked programming experts⁠—including several of our own O’Reilly authors and instructors⁠—for their thoughts on what’s in store for some established players and fast-growing languages.

Python

The biggest news this year in Python is that creator and “benevolent dictator for life” Guido van Rossum retired, leaving Python in the hands of the Python Steering Council. So far, it’s been a painless shift in power, which as Eric Matthes, author of Python Crash Course, argues, should come as no surprise, since “Guido has carried himself, and his role in the community, with such poise for so long.” 2020 will also see the end of support for Python 2.7, which will likely cause its share of headaches among holdouts. Meanwhile, Python continues to be the language of choice for data science.

For Matthes, one exciting aspect of Python has been “the variety of interesting and critical projects that have come out of a community where diversity has so intentionally been built for so long.” Carol Willing, a member of the Python Steering Council and a core developer of CPython, also celebrates these projects—like the Binder service, which promotes reproducible research by creating an executable environment from your Jupyter Notebooks—particularly as they expand beyond their initial aims. Binder, she notes, “was widely used last year for teaching workshops and tutorials at many Python conferences.” Willing also offered a shout-out to the CircuitPython and Mu projects, asking, “Who doesn’t love hardware, blinking LEDs, sensors, and using Mu, a user-friendly editor that is fantastic for adults and kids?”

Java

It’s mostly good news on the Java front. Java Champion Ben Evans explains, “Once again, rumours of Java’s demise have proved to be little more than wishful thinking on the part of the platform’s detractors.” But it hasn’t all been smooth sailing. As we noted last year, the release of Java 11 in September 2018 brought a raft of new features, including many that give the release a significant, clear advantage for using containers. However, wide adoption of this latest release hasn’t followed suit, with more than 80% of developers still on Java 8, according to this JetBrains survey. Evans wonders, “Does this mean that people aren’t running Java in containers as much as we’re told they are? Or do people just not know about the benefits of 11 in containers?”

Despite the slow rate of adoption, Java’s six-month release cadence has been trucking along—Java 12 dropped in March 2019, with Java 13 following in September. And according to Java Champion Trisha Gee, it’s really starting to show its value:

Each release is quite small but predictable. And although they don’t all have exciting new language changes, you can see the language moving forward steadily. In addition, it enables this idea of preview features, which I think we saw working really well for switch expressions—developers got to try out the feature and give real feedback based on how it feels to work with, instead of feedback on abstract, conceptual ideas. In response, there was a small change to the syntax of switch expressions, which was possible due to it being a preview feature and not set in stone, in Java 13. Now this updated syntax is scheduled to be part of JDK 14 as a production-ready feature.

2019 brought another surprise when Oracle moved Java SE to a subscription-based model. But as Marc Loy, coauthor of Learning Java, fifth edition (now in early release), points out, “The Java community at large has approached this unfortunate change with increased enthusiasm for the OpenJDK.”

As for the coming year, Evans suggests that 2020 will be about watching the 2019 trends play out:

How close to a production version of Project Valhalla will we be? Will the incremental strategy of delivering pattern matching and algebraic data types (Project Amber) pay off? Will Quarkus bear out its promise and the faith of its early fans? Will 2020 be the year that Kotlin makes a significant beachhead beyond Android? These are exciting times—we’re in transition toward something new, and there’s a lot going on.

Kotlin

Google announced in May 2019 that Kotlin is now its preferred language for Android app developers, boosting the language’s already strong adoption. Although many Android developers are still in the process of making the move to Kotlin, those who have already transitioned know the benefits it offers. Dawn and David Griffiths, authors of Head First Kotlin, share a few reasons behind Kotlin’s ascendance:

For a language created by an IDE company, it’s no surprise that Kotlin has a healthy level of tooling support. The experimental DSL for code contracts gives developers the ability to provide guarantees about the ways that code behaves. Does your function have side effects? Is it guaranteed to return a non-null value? Code contracts allow you to make these promises, and the compiler can use them to loosen compile-time checks.

The barriers between different Kotlin platforms are now also breaking down. The “expect”/”actual” qualifiers allow developers to more easily write code that is compatible across Java/Native/JS environments. And serialization support now means that it’s even easier to convert JSON data into Kotlin objects, and vice versa.

Expect to see Kotlin continue its impressive growth—and not just in Android. Hadi Hariri, leader of the developer advocacy team at JetBrains, points to the success of Kotlin/Everywhere—a series of community-led events where you can learn the essentials and best practices of Kotlin in Android, Google Cloud Platform, and multiplatform development—as proof: “From May to November, we’ve managed to reach close to 30,000 people in 86 countries. KotlinConf sold out three years in a row with more than 1,700 attendees in 2019. This really shows, amongst other things, that interest and adoption of the language is growing.”

Go

When Gophers think back on 2019, they’ll likely remember the saga of the try proposal. Go developer and writer Jon Bodner explains:

One of the most common complaints about Go is that error handling is too verbose. So in early June, the Go core developers proposed adding a new built-in function called try. A GitHub issue was opened to discuss this new feature. Within a month, there were nearly 800 comments, most of them negative. The people who were against the new feature felt that this change made code too “magical” and obscured the logic flow. After reviewing the feedback, the Go team marked the proposal as closed and rejected on July 16.

What’s notable about this process wasn’t the failure of the feature but rather, as Bodner describes it, “the way the process happened: a feature was proposed, the discussion was respectful, but many felt that the change was inconsistent with Go’s style. In the end, the people who steward the language decided to respect the majority opinion. That’s what developers mean when they talk about community.”

2020 should bring more clarity to Go’s Contracts specification, better known as the Generics proposal. According to Bodner, “It looks like Go is going to implement generics using an approach that is a bit different from other languages, but which fits nicely into the idioms of Go.” It will hopefully allow Go to keep its idiomatic style while adding a feature that developers have found useful in other languages.

Rust

We checked in with Jim Blandy, coauthor of Programming Rust, to see how his vision of Rust’s progress changed over the course of 2019. Last year, he noted that, “Rust has supported asynchronous programming in one form or another for a long time, but async functions provide a syntax for this sort of code that is a major improvement over what Rust has had before.” Did his hope for improvements to the Rust syntax come to fruition? Yes, eventually: Blandy explained that async/await syntax didn’t become stable until version 1.39, which was released November 7, 2019. “Originally, we were hoping async/await syntax could be part of the 2018 edition of Rust, but it took longer to get things right.” Still, he has high hopes for what async will mean for Rust in 2020: “Integrating async into the language lets the borrow checker understand what you’re doing, so asynchronous code can look like idiomatic Rust.” And as Blandy points out, the Rust ecosystem is acting quickly to take advantage of the language’s new expressiveness.

The Rust community is also excited about WebAssembly, which this year became a theoretical replacement to C/FFI for ecosystems that need portable, high-performance modules. And as Rust expert Nathan Stocks notes, “You get light sandboxing as well!” What impressed Stocks most was “how much of the theory had been prototyped and demonstrated successfully.”

I had previously thought of WebAssembly purely as a compilation target to run code from non-JS languages in the browser. The addition of the ability to consume web assembly from any language outside the browser was mind-bending.

Swift

The biggest stories in Swift last year were the releases of SwiftUI, Apple’s newest framework for designing user interfaces across all Apple devices, and Swift for TensorFlow, a platform for deep learning and differentiable programming integrating Google’s TensorFlow framework with Swift. SwiftUI, as Timirah James explains, “has already gained so much traction amongst developers (rightfully so) with its declarative nature and is already being seen as a possible future successor to UIKit.” As for Swift for TensorFlow, Paris Buttfield-Addison calls it “a radical new use for Swift.” He explains, “Swift has always been a great app development and systems programming language, and is a great up-and-coming web and back-end development language, but now, with Swift for TensorFlow, it’s a powerful ML framework, too.” Here’s why:

Swift for TensorFlow is developed by a team that includes the original creator of Swift, Chris Lattner, and provides (or will, when it’s done) everything you need for machine learning and numerical computing. Most surprisingly is the full first-class support for differentiable programming with automatic differentiation, which is made possible by Swift’s underlying compiler framework and design.

Full in-language differentiable programming will make a whole collection of previously impossible things possible: the best example is being able to use a standard programming debugger to step through backpropagation and debug derivatives when you’re building a neural network.

Swift for TensorFlow also brings full Python support to Swift, allowing data scientists to mix and match the useful and familiar Python frameworks they need, with clean expressive Swift code.

Looking ahead, both James and Buttfield-Addison are excited to see the new directions Swift takes, with James pointing to “Swift adoption across different communities and stacks beyond mobile, especially in the serverless realm,” and Buttfield-Addison calling out “amazing web development frameworks, like Kitura, and all sorts of amazing frameworks for niche areas…such as SwiftPlot, which is a Swift native version of the ubiquitous Matplotlib from Python.”

What lies ahead?

Change is inevitable, and as programming languages continue to lean in to optimization for new trends in the cloud, microservices, big data, and machine learning, each language and its ecosystem will continue to adapt in its own unique way. Big releases may be on the horizon in 2020 for certain languages—C++20 will be released this summer and Scala 3.0 is expected in late 2020—but what’s clear is even the smallest changes can cause huge waves in the daily lives of programmers.