What is Swift and what are its top alternatives?
Swift is a powerful and intuitive programming language developed by Apple for iOS, macOS, watchOS, and tvOS app development. It combines modern language features with a simple and concise syntax, making it easier to write and maintain code. Key features of Swift include type inference, optionals, generics, closures, and protocols. However, Swift is limited by its compatibility with Apple platforms only, which restricts its usage for cross-platform development and limits its reach to a broader audience.
- Kotlin: Kotlin is a modern, expressive, and statically typed programming language developed by JetBrains. It is fully interoperable with Java, making it a popular choice for Android app development. Key features of Kotlin include null safety, extension functions, coroutines, and data classes. Pros of Kotlin compared to Swift include its interoperability with Java, strong support for functional programming, and wide adoption in the Android community. However, Kotlin is not natively supported by Apple platforms like Swift.
- React Native: React Native is a JavaScript framework developed by Facebook for building cross-platform mobile apps. It allows developers to write code in JavaScript and compile it into native code for iOS and Android. Key features of React Native include hot reloading, a large and active community, and support for third-party plugins. Pros of React Native compared to Swift include faster development cycles, code reusability between platforms, and a lower learning curve for JavaScript developers. However, React Native may not offer the same performance as native app development with Swift.
- Flutter: Flutter is an open-source UI toolkit developed by Google for building natively compiled applications for mobile, web, and desktop from a single codebase. It uses the Dart programming language and provides a rich set of pre-built widgets for designing user interfaces. Key features of Flutter include hot reload, customizable widgets, and high performance. Pros of Flutter compared to Swift include rapid development, support for multiple platforms, and a reactive programming model. However, Flutter may require developers to learn Dart, which could be a barrier for those familiar with Swift.
- Java: Java is a popular, high-level programming language known for its portability and performance. It is widely used for developing enterprise applications, web applications, and Android apps. Key features of Java include platform independence, automatic memory management, multi-threading support, and a large standard library. Pros of Java compared to Swift include a vast ecosystem of libraries and tools, strong community support, and cross-platform compatibility. However, Java may have a steeper learning curve for beginners coming from Swift.
- C#: C# is a versatile and object-oriented programming language developed by Microsoft for building Windows applications, web services, and mobile apps with Xamarin. It offers features such as type safety, automatic garbage collection, LINQ (Language Integrated Query), and async/await for asynchronous programming. Pros of C# compared to Swift include seamless integration with the .NET framework, strong tooling support in Visual Studio, and cross-platform development with Xamarin. However, C# is primarily targeted towards Windows development and may have less community support for mobile app development than Swift.
- Python: Python is a high-level, interpreted programming language known for its simplicity and readability. It is widely used for web development, data analysis, machine learning, and automation tasks. Key features of Python include dynamic typing, extensive standard library, easy syntax, and support for multiple programming paradigms. Pros of Python compared to Swift include its versatility for a wide range of applications, strong community support, and extensive third-party libraries. However, Python may not offer the same performance as Swift for mobile app development.
- Rust: Rust is a systems programming language developed by Mozilla, known for its focus on safety, speed, and concurrency. It is designed to prevent memory errors and ensure thread safety through a strict ownership system and borrow checker. Key features of Rust include zero-cost abstractions, pattern matching, fearless concurrency, and extensive compiler checks. Pros of Rust compared to Swift include its emphasis on performance and safety, support for low-level programming, and strong community backing. However, Rust may have a steeper learning curve for developers transitioning from Swift.
- Go: Go, also known as Golang, is a statically typed programming language developed by Google, designed for concurrency and scalability in modern applications. It offers features such as goroutines for lightweight threading, a garbage collector, strong standard library, and efficient compilation speed. Pros of Go compared to Swift include its simplicity, fast compilation times, built-in support for concurrency, and easy deployment. However, Go may not offer the same level of support for mobile app development as Swift.
- JavaScript: JavaScript is a widely used scripting language for web development, supported by all modern web browsers. It is known for its dynamic typing, prototypal inheritance, asynchronous programming model, and high flexibility. Pros of JavaScript compared to Swift include its ubiquity on the web, extensive libraries and frameworks such as React and Angular, and cross-platform compatibility. However, JavaScript may have performance limitations compared to Swift for high-performance mobile applications.
- Ruby: Ruby is a dynamic, object-oriented programming language known for its simplicity and productivity. It is commonly used for web development, automation, and scripting tasks. Key features of Ruby include its elegant syntax, metaprogramming capabilities, rich ecosystem of gems, and focus on developer happiness. Pros of Ruby compared to Swift include rapid prototyping, expressiveness, strong community support, and a focus on developer joy. However, Ruby may not offer the same level of performance optimization as Swift for complex mobile applications.
Top Alternatives to Swift
- Objective-C
Objective-C is a superset of the C programming language and provides object-oriented capabilities and a dynamic runtime. Objective-C inherits the syntax, primitive types, and flow control statements of C and adds syntax for defining classes and methods. It also adds language-level support for object graph management and object literals while providing dynamic typing and binding, deferring many responsibilities until runtime. ...
- React Native
React Native enables you to build world-class application experiences on native platforms using a consistent developer experience based on JavaScript and React. The focus of React Native is on developer efficiency across all the platforms you care about - learn once, write anywhere. Facebook uses React Native in multiple production apps and will continue investing in React Native. ...
- Kotlin
Kotlin is a statically typed programming language for the JVM, Android and the browser, 100% interoperable with Java ...
- Golang
Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language. ...
- Java
Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere! ...
- Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...
- Rust
Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory. ...
- Xcode
The Xcode IDE is at the center of the Apple development experience. Tightly integrated with the Cocoa and Cocoa Touch frameworks, Xcode is an incredibly productive environment for building amazing apps for Mac, iPhone, and iPad. ...
Swift alternatives & related posts
Objective-C
- Ios212
- Xcode115
- Backed by apple62
- Osx47
- Interface builder40
- Good old fashioned ooe with a modern twist10
- Goober, please2
- Object-oriented1
- Handles well null values (no NullPointerExceptions)1
- UNREADABLE1
related Objective-C posts
Excerpts from how we developed (and subsequently open sourced) Uber's cross-platform mobile architecture framework, RIBs , going from Objective-C to Swift in the process for iOS: https://github.com/uber/RIBs
Uber’s new application architecture (RIBs) extensively uses protocols to keep its various components decoupled and testable. We used this architecture for the first time in our new rider application and moved our primary language from Objective-C to Swift. Since Swift is a very static language, unit testing became problematic. Dynamic languages have good frameworks to build test mocks, stubs, or stand-ins by dynamically creating or modifying existing concrete classes.
Needless to say, we were not very excited about the additional complexity of manually writing and maintaining mock implementations for each of our thousands of protocols.
The information required to generate mock classes already exists in the Swift protocol. For Uber’s use case, we set out to create tooling that would let engineers automatically generate test mocks for any protocol they wanted by simply annotating them.
The iOS codebase for our rider application alone incorporates around 1,500 of these generated mocks. Without our code generation tool, all of these would have to be written and maintained by hand, which would have made testing much more time-intensive. Auto-generated mocks have contributed a lot to the unit test coverage that we have today.
We built these code generation tools ourselves for a number of reasons, including that there weren’t many open source tools available at the time we started our effort. Today, there are some great open source tools to generate resource accessors, like SwiftGen. And Sourcery can help you with generic code generation needs:
https://eng.uber.com/code-generation/ https://eng.uber.com/driver-app-ribs-architecture/
(GitHub : https://github.com/uber/RIBs )
We are using React Native in #SmartHome to share the business logic between Android and iOS team and approach users with a unique brand experience. The drawback is that we require lots of native Android SDK and Objective-C modules, so a good part of the invested time is there. The gain for a app that relies less on native communication, sensors and OS tools should be even higher.
Also it helps us set different testing stages: we use Travis CI for the javascript (business logic), Bitrise to run build tests and @Detox for #end2end automated user tests.
We use a microservices structure on top of Zeit's @now that read from firebase. We use JWT auth to authenticate requests among services and from users, following GitHub philosophy of using the same infrastructure than its API consumers. Firebase is used mainly as a key-value store between services and as a backup database for users. We also use its authentication mechanisms.
You can be super locked-in if you also rely on it's analytics, but we use Amplitude for that, which offers us great insights. Intercom for communications with end-user and Mailjet for marketing.
- Learn once write everywhere214
- Cross platform173
- Javascript168
- Native ios components122
- Built by facebook69
- Easy to learn65
- Bridges me into ios development45
- No compile39
- It's just react39
- Declarative36
- Fast22
- Virtual Dom13
- Insanely fast develop / test cycle12
- Livereload12
- Great community11
- It is free and open source9
- Native android components9
- Easy setup9
- Backed by Facebook9
- Highly customizable7
- Scalable7
- Awesome6
- Everything component6
- Great errors6
- Win win solution of hybrid app6
- Not dependent on anything such as Angular5
- Simple5
- Awesome, easy starting from scratch4
- OTA update4
- As good as Native without any performance concerns3
- Easy to use3
- Many salary2
- Can be incrementally added to existing native apps2
- Hot reload2
- Over the air update (Flutter lacks)2
- 'It's just react'2
- Web development meets Mobile development2
- Ngon1
- Javascript23
- Built by facebook19
- Cant use CSS12
- 30 FPS Limit4
- Slow2
- Generate large apk even for a simple app2
- Some compenents not truly native2
related React Native posts
Your tech stack is solid for building a real-time messaging project.
React and React Native are excellent choices for the frontend, especially if you want to have both web and mobile versions of your application share code.
ExpressJS is an unopinionated framework that affords you the flexibility to use it's features at your term, which is a good start. However, I would recommend you explore Sails.js as well. Sails.js is built on top of Express.js and it provides additional features out of the box, especially the Websocket integration that your project requires.
Don't forget to set up Graphql codegen, this would improve your dev experience (Add Typescript, if you can too).
I don't know much about databases but you might want to consider using NO-SQL. I used Firebase real-time db and aws dynamo db on a few of my personal projects and I love they're easy to work with and offer more flexibility for a chat application.
I am starting to become a full-stack developer, by choosing and learning .NET Core for API Development, Angular CLI / React for UI Development, MongoDB for database, as it a NoSQL DB and Flutter / React Native for Mobile App Development. Using Postman, Markdown and Visual Studio Code for development.
Kotlin
- Interoperable with Java73
- Functional Programming support55
- Null Safety50
- Official Android support46
- Backed by JetBrains44
- Concise37
- Modern Multiplatform Applications36
- Expressive Syntax28
- Target to JVM27
- Coroutines26
- Open Source24
- Statically Typed19
- Practical elegance19
- Android support17
- Type Inference17
- Readable code14
- Powerful as Scala, simple as Python, plus coroutines <313
- Better Java12
- Pragmatic10
- Lambda9
- Better language for android8
- Expressive DSLs8
- Target to JavaScript8
- Used for Android6
- Less boilerplate code6
- Fast Programming language5
- Less code5
- Native4
- Less boiler plate code4
- Friendly community4
- Functional Programming Language4
- Spring3
- Official Google Support3
- Latest version of Java2
- Well-compromised featured Java alternative1
- Java interop makes users write Java in Kotlin7
- Frequent use of {} keys4
- Hard to make teams adopt the Kotlin style2
- Nonullpointer Exception2
- Friendly community1
- Slow compiler1
- No boiler plate code1
related Kotlin posts
Hi Community! Trust everyone is keeping safe. I am exploring the idea of building a #Neobank (App) with end-to-end banking capabilities. In the process of exploring this space, I have come across multiple Apps (N26, Revolut, Monese, etc) and explored their stacks in detail. The confusion remains to be the Backend Tech to be used?
What would you go with considering all of the languages such as Node.js Java Rails Python are suggested by some person or the other. As a general trend, I have noticed the usage of Node with React on the front or Node with a combination of Kotlin and Swift. Please suggest what would be the right approach!
In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.
Golang
- High-performance549
- Simple, minimal syntax395
- Fun to write363
- Easy concurrency support via goroutines302
- Fast compilation times273
- Goroutines194
- Statically linked binaries that are simple to deploy181
- Simple compile build/run procedures151
- Great community137
- Backed by google136
- Garbage collection built-in53
- Built-in Testing46
- Excellent tools - gofmt, godoc etc44
- Elegant and concise like Python, fast like C39
- Awesome to Develop37
- Used for Docker26
- Flexible interface system26
- Great concurrency pattern25
- Deploy as executable24
- Open-source Integration21
- Easy to read19
- Fun to write and so many feature out of the box17
- Go is God16
- Its Simple and Heavy duty14
- Concurrency14
- Powerful and simple14
- Easy to deploy14
- Best language for concurrency13
- Rich standard library11
- Safe GOTOs11
- Easy setup10
- Clean code, high performance10
- High performance10
- Simplicity, Concurrency, Performance9
- Cross compiling8
- Hassle free deployment8
- Single binary avoids library dependency issues8
- Gofmt7
- Simple, powerful, and great performance7
- Used by Giants of the industry7
- Garbage Collection6
- WYSIWYG5
- Very sophisticated syntax5
- Excellent tooling5
- Kubernetes written on Go4
- Keep it simple and stupid4
- Widely used4
- No generics2
- Looks not fancy, but promoting pragmatic idioms1
- Operator goto1
- You waste time in plumbing code catching errors42
- Verbose25
- Packages and their path dependencies are braindead23
- Google's documentations aren't beginer friendly16
- Dependency management when working on multiple projects15
- Automatic garbage collection overheads10
- Uncommon syntax8
- Type system is lacking (no generics, etc)7
- Collection framework is lacking (list, set, map)5
- Best programming language3
- A failed experiment to combine c and python1
related Golang posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)
We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.
Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.
#FrameworksFullStack #Languages
Java
- Great libraries601
- Widely used445
- Excellent tooling400
- Huge amount of documentation available395
- Large pool of developers available334
- Open source208
- Excellent performance203
- Great development158
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language60
- Used for Web52
- High Performance46
- Managed memory46
- Native threads44
- Statically typed43
- Easy to read35
- Great Community33
- Reliable platform29
- Sturdy garbage collection24
- JVM compatibility24
- Cross Platform Enterprise Integration22
- Universal platform20
- Good amount of APIs20
- Great Support18
- Great ecosystem14
- Lots of boilerplate11
- Backward compatible11
- Everywhere10
- Excellent SDK - JDK9
- Static typing7
- Cross-platform7
- It's Java7
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Portability6
- Clojure5
- Used for Android development5
- Vast Collections Library5
- Best martial for design4
- Most developers favorite4
- Old tech4
- Javadoc3
- History3
- Testable3
- Great Structure3
- Stable platform, which many new languages depend on3
- Type Safe2
- Faster than python2
- Job0
- Verbosity33
- NullpointerException27
- Nightmare to Write17
- Overcomplexity is praised in community culture16
- Boiler plate code12
- Classpath hell prior to Java 98
- No REPL6
- No property4
- Code are too long3
- Non-intuitive generic implementation2
- There is not optional parameter2
- Floating-point errors2
- Java's too statically, stronglly, and strictly typed1
- Returning Wildcard Types1
- Terrbible compared to Python/Batch Perormence1
related Java posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.
Python
- Great libraries1.2K
- Readable code961
- Beautiful code847
- Rapid development787
- Large community689
- Open source437
- Elegant393
- Great community282
- Object oriented272
- Dynamic typing220
- Great standard library77
- Very fast60
- Functional programming55
- Easy to learn49
- Scientific computing45
- Great documentation35
- Productivity29
- Easy to read28
- Matlab alternative28
- Simple is better than complex24
- It's the way I think20
- Imperative19
- Free18
- Very programmer and non-programmer friendly18
- Powerfull language17
- Machine learning support17
- Fast and simple16
- Scripting14
- Explicit is better than implicit12
- Ease of development11
- Clear and easy and powerfull10
- Unlimited power9
- It's lean and fun to code8
- Import antigravity8
- Print "life is short, use python"7
- Python has great libraries for data processing7
- Although practicality beats purity6
- Now is better than never6
- Great for tooling6
- Readability counts6
- Rapid Prototyping6
- I love snakes6
- Flat is better than nested6
- Fast coding and good for competitions6
- There should be one-- and preferably only one --obvious6
- High Documented language6
- Great for analytics5
- Lists, tuples, dictionaries5
- Easy to learn and use4
- Simple and easy to learn4
- Easy to setup and run smooth4
- Web scraping4
- CG industry needs4
- Socially engaged community4
- Complex is better than complicated4
- Multiple Inheritence4
- Beautiful is better than ugly4
- Plotting4
- Many types of collections3
- Flexible and easy3
- It is Very easy , simple and will you be love programmi3
- If the implementation is hard to explain, it's a bad id3
- Special cases aren't special enough to break the rules3
- Pip install everything3
- List comprehensions3
- No cruft3
- Generators3
- Import this3
- If the implementation is easy to explain, it may be a g3
- Can understand easily who are new to programming2
- Batteries included2
- Securit2
- Good for hacking2
- Better outcome2
- Only one way to do it2
- Because of Netflix2
- A-to-Z2
- Should START with this but not STICK with This2
- Powerful language for AI2
- Automation friendly1
- Sexy af1
- Slow1
- Procedural programming1
- Ni0
- Powerful0
- Keep it simple0
- Still divided between python 2 and python 353
- Performance impact28
- Poor syntax for anonymous functions26
- GIL22
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow12
- Indentations matter a lot8
- Not everything is expression8
- Incredibly slow7
- Explicit self parameter in methods7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Fake object-oriented programming5
- Threading5
- The "lisp style" whitespaces5
- Official documentation is unclear.5
- Hard to obfuscate5
- Circular import5
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- The benevolent-dictator-for-life quit4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
related Python posts
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)
We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.
Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.
#FrameworksFullStack #Languages
- Guaranteed memory safety145
- Fast132
- Open source88
- Minimal runtime75
- Pattern matching71
- Type inference63
- Concurrent57
- Algebraic data types56
- Efficient C bindings47
- Practical43
- Best advances in languages in 20 years37
- Safe, fast, easy + friendly community32
- Fix for C/C++30
- Stablity25
- Zero-cost abstractions24
- Closures23
- Extensive compiler checks20
- Great community20
- Async/await18
- No NULL type18
- Completely cross platform: Windows, Linux, Android15
- No Garbage Collection15
- High-performance14
- Great documentations14
- Super fast12
- High performance12
- Generics12
- Guaranteed thread data race safety11
- Safety no runtime crashes11
- Macros11
- Fearless concurrency11
- Compiler can generate Webassembly10
- Helpful compiler10
- RLS provides great IDE support9
- Prevents data races9
- Easy Deployment9
- Painless dependency management8
- Real multithreading8
- Good package management7
- Support on Other Languages5
- Hard to learn27
- Ownership learning curve24
- Unfriendly, verbose syntax12
- High size of builded executable4
- Many type operations make it difficult to follow4
- No jobs4
- Variable shadowing4
- Use it only for timeoass not in production1
related Rust posts
Hello!
I'm a developer for over 9 years, and most of this time I've been working with C# and it is paying my bills until nowadays. But I'm seeking to learn other languages and expand the possibilities for the next years.
Now the question... I know Ruby is far from dead but is it still worth investing time in learning it? Or would be better to take Python, Golang, or even Rust? Or maybe another language.
Thanks in advance.
Sentry's event processing pipeline, which is responsible for handling all of the ingested event data that makes it through to our offline task processing, is written primarily in Python.
For particularly intense code paths, like our source map processing pipeline, we have begun re-writing those bits in Rust. Rust’s lack of garbage collection makes it a particularly convenient language for embedding in Python. It allows us to easily build a Python extension where all memory is managed from the Python side (if the Python wrapper gets collected by the Python GC we clean up the Rust object as well).
- IOS Development130
- Personal assistant on steroids33
- Easy setup29
- Excellent integration with Clang17
- Beautiful3
- Built-in everything1
- Massively bloated and complicated for smaller projects6
- Horrible auto completiting and text editing3
- Slow startup1
- Very slow emulator1
related Xcode posts
As a Engineering Manager & Director at SmartZip, I had a mix of front-end, back-end, #mobile engineers reporting to me.
Sprints after sprints, I noticed some inefficiencies on the MobileDev side. People working multiple sprints in a row on their Xcode / Objective-C codebase while some others were working on Android Studio. After which, QA & Product ensured both applications were in sync, on a UI/UX standpoint, creating addional work, which also happened to be extremely costly.
Our resources being so limited, my role was to stop this bleeding and keep my team productive and their time, valuable.
After some analysis, discussions, proof of concepts... etc. We decided to move to a single codebase using React Native so our velocity would increase.
After some initial investment, our initial assumptions were confirmed and we indeed started to ship features a lot faster than ever before. Also, our engineers found a way to perform this upgrade incrementally, so the initial platform-specific codebase wouldn't have to entirely be rewritten at once but only gradually and at will.
Feedback around React Native was very positive. And I doubt - for the kind of application we had - no one would want to go back to two or more code bases. Our application was still as Native as it gets. And no feature or device capability was compromised.
I've recently switched to using Expo for initializing and developing my React Native apps. Compared to React Native CLI, it's so much easier to get set up and going. Setting up and maintaining Android Studio, Android SDK, and virtual devices used to be such a headache. Thanks to Expo, I can now test my apps directly on my Android phone, just by installing the Expo app. I still use Xcode Simulator for iOS testing, since I don't have an iPhone, but that's easy anyway. The big win for me with Expo is ease of Android testing.
The Expo SDK also provides convenient features like Facebook login, MapView
, push notifications, and many others. https://docs.expo.io/versions/v31.0.0/sdk/