What is Kotlin and what are its top alternatives?
Top Alternatives to Kotlin
- Scala
Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them. ...
- Swift
Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C. ...
- 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! ...
- Groovy
It is a powerful multi-faceted programming language for the JVM platform. It supports a spectrum of programming styles incorporating features from dynamic languages such as optional and duck typing, but also static compilation and static type checking at levels similar to or greater than Java through its extensible static type checker. It aims to greatly increase developer productivity with many powerful features but also a concise, familiar and easy to learn syntax. ...
- 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. ...
- 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. ...
- 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. ...
- Flutter
Flutter is a mobile app SDK to help developers and designers build modern mobile apps for iOS and Android. ...
Kotlin alternatives & related posts
- Static typing187
- Pattern-matching178
- Jvm177
- Scala is fun172
- Types138
- Concurrency95
- Actor library88
- Solve functional problems86
- Open source81
- Solve concurrency in a safer way80
- Functional44
- Fast24
- Generics23
- It makes me a better engineer18
- Syntactic sugar17
- Scalable13
- First-class functions10
- Type safety10
- Interactive REPL9
- Expressive8
- SBT7
- Case classes6
- Implicit parameters6
- Rapid and Safe Development using Functional Programming4
- JVM, OOP and Functional programming, and static typing4
- Object-oriented4
- Used by Twitter4
- Functional Proframming3
- Spark2
- Beautiful Code2
- Safety2
- Growing Community2
- DSL1
- Rich Static Types System and great Concurrency support1
- Naturally enforce high code quality1
- Akka Streams1
- Akka1
- Reactive Streams1
- Easy embedded DSLs1
- Mill build tool1
- Freedom to choose the right tools for a job0
- Slow compilation time11
- Multiple ropes and styles to hang your self7
- Too few developers available6
- Complicated subtyping4
- My coworkers using scala are racist against other stuff2
related Scala posts
I am new to Apache Spark and Scala both. I am basically a Java developer and have around 10 years of experience in Java.
I wish to work on some Machine learning or AI tech stacks. Please assist me in the tech stack and help make a clear Road Map. Any feedback is welcome.
Technologies apart from Scala and Spark are also welcome. Please note that the tools should be relevant to Machine Learning or Artificial Intelligence.
Lumosity is home to the world's largest cognitive training database, a responsibility we take seriously. For most of the company's history, our analysis of user behavior and training data has been powered by an event stream--first a simple Node.js pub/sub app, then a heavyweight Ruby app with stronger durability. Both supported decent throughput and latency, but they lacked some major features supported by existing open-source alternatives: replaying existing messages (also lacking in most message queue-based solutions), scaling out many different readers for the same stream, the ability to leverage existing solutions for reading and writing, and possibly most importantly: the ability to hire someone externally who already had expertise.
We ultimately migrated to Kafka in early- to mid-2016, citing both industry trends in companies we'd talked to with similar durability and throughput needs, the extremely strong documentation and community. We pored over Kyle Kingsbury's Jepsen post (https://aphyr.com/posts/293-jepsen-Kafka), as well as Jay Kreps' follow-up (http://blog.empathybox.com/post/62279088548/a-few-notes-on-kafka-and-jepsen), talked at length with Confluent folks and community members, and still wound up running parallel systems for quite a long time, but ultimately, we've been very, very happy. Understanding the internals and proper levers takes some commitment, but it's taken very little maintenance once configured. Since then, the Confluent Platform community has grown and grown; we've gone from doing most development using custom Scala consumers and producers to being 60/40 Kafka Streams/Connects.
We originally looked into Storm / Heron , and we'd moved on from Redis pub/sub. Heron looks great, but we already had a programming model across services that was more akin to consuming a message consumers than required a topology of bolts, etc. Heron also had just come out while we were starting to migrate things, and the community momentum and direction of Kafka felt more substantial than the older Storm. If we were to start the process over again today, we might check out Pulsar , although the ecosystem is much younger.
To find out more, read our 2017 engineering blog post about the migration!
Swift
- Ios259
- Elegant180
- Not Objective-C126
- Backed by apple107
- Type inference93
- Generics61
- Playgrounds54
- Semicolon free49
- OSX38
- Tuples offer compound variables36
- Clean Syntax24
- Easy to learn24
- Open Source22
- Beautiful Code21
- Functional20
- Dynamic12
- Linux12
- Protocol-oriented programming11
- Promotes safe, readable code10
- No S-l-o-w JVM9
- Explicit optionals8
- Storyboard designer7
- Optionals6
- Type safety6
- Super addicting language, great people, open, elegant5
- Best UI concept5
- Its friendly4
- Highly Readable codes4
- Fail-safe4
- Powerful4
- Faster and looks better4
- Swift is faster than Objective-C4
- Feels like a better C++4
- Easy to learn and work3
- Much more fun3
- Protocol extensions3
- Native3
- Its fun and damn fast3
- Strong Type safety3
- Easy to Maintain3
- Protocol as type2
- All Cons C# and Java Swift Already has2
- Esay2
- MacOS2
- Type Safe2
- Protocol oriented programming2
- Can interface with C easily1
- Actually don't have to own a mac1
- Free from Memory Leak1
- Swift is easier to understand for non-iOS developers.1
- Numbers with underbar1
- Optional chain1
- Great for Multi-Threaded Programming1
- Runs Python 8 times faster1
- Objec1
- Must own a mac6
- Memory leaks are not uncommon2
- Very irritatingly picky about things that’s1
- Complicated process for exporting modules1
- Its classes compile to roughly 300 lines of assembly1
- Is a lot more effort than lua to make simple functions1
- Overly complex options makes it easy to create bad code0
related Swift 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!
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 )
Java
- Great libraries602
- 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.
- Java platform44
- Much more productive than java33
- Concise and readable29
- Very little code needed for complex tasks28
- Dynamic language22
- Nice dynamic syntax for the jvm13
- Very fast9
- Can work with JSON as an object7
- Easy to setup7
- Supports closures (lambdas)6
- Literal Collections6
- Syntactic sugar3
- Optional static typing3
- Developer Friendly2
- Groovy Code can be slower than Java Code3
- Absurd syntax1
- Objects cause stateful/heap mess1
related Groovy posts
Some may wonder why did we choose Grails ? Really good question :) We spent quite some time to evaluate what framework to go with and the battle was between Play Scala and Grails ( Groovy ). We have enough experience with both and, to be honest, I absolutely in love with Scala; however, the tipping point for us was the potential speed of development. Grails allows much faster development pace than Play , and as of right now this is the most important parameter. We might convert later though. Also, worth mentioning, by default Grails comes with Gradle as a build tool, so why change?
Presently, a web-based ERP is developed in Groovy on Grails. Now the ERP is getting revamped with more functionalities. Is it advisable to continue with the same software and framework or try something new especially Node.js over ExpressJS?
Python
- Great libraries1.2K
- Readable code962
- Beautiful code847
- Rapid development788
- Large community690
- Open source438
- 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
Golang
- High-performance551
- Simple, minimal syntax395
- Fun to write363
- Easy concurrency support via goroutines303
- Fast compilation times273
- Goroutines195
- Statically linked binaries that are simple to deploy181
- Simple compile build/run procedures151
- Great community137
- Backed by google137
- Garbage collection built-in53
- Built-in Testing47
- Excellent tools - gofmt, godoc etc44
- Elegant and concise like Python, fast like C40
- 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 God17
- Powerful and simple14
- Easy to deploy14
- Its Simple and Heavy duty14
- Concurrency14
- Best language for concurrency13
- Safe GOTOs11
- Rich standard library11
- Clean code, high performance10
- Easy setup10
- High performance10
- Simplicity, Concurrency, Performance9
- Cross compiling8
- Single binary avoids library dependency issues8
- Hassle free deployment8
- Used by Giants of the industry7
- Simple, powerful, and great performance7
- Gofmt7
- Garbage Collection6
- WYSIWYG5
- Very sophisticated syntax5
- Excellent tooling5
- Keep it simple and stupid4
- Widely used4
- Kubernetes written on Go4
- 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
- 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.
- Hot Reload142
- Cross platform122
- Performance104
- Backed by Google89
- Compiled into Native Code73
- Fast Development60
- Open Source58
- Fast Prototyping53
- Single Codebase49
- Expressive and Flexible UI48
- Reactive Programming36
- Material Design34
- Dart30
- Widget-based29
- Target to Fuchsia26
- IOS + Android20
- Easy to learn17
- Great CLI Support16
- You can use it as mobile, web, Server development14
- Tooling14
- Debugging quickly13
- Have built-in Material theme13
- Community12
- Good docs & sample code12
- Target to Android12
- Support by multiple IDE: Android Studio, VS Code, XCode11
- Written by Dart, which is easy to read code10
- Easy Testing Support10
- Target to iOS9
- Real platform free framework of the future9
- Have built-in Cupertino theme9
- Easy to Unit Test8
- Easy to Widget Test8
- Large Community1
- Need to learn Dart29
- Lack of community support10
- No 3D Graphics Engine Support10
- Graphics programming8
- Lack of friendly documentation6
- Lack of promotion2
- Https://iphtechnologies.com/difference-between-flutter1
related Flutter posts
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.
The only two programming languages I know are Python and Dart, I fall in love with Dart when I learned about the type safeness, ease of refactoring, and the help of the IDE. I have an idea for an app, a simple app, but I need SEO and server rendering, and I also want it to be available on all platforms. I can't use Flutter or Dart anymore because of that. I have been searching and looks like there is no way to avoid learning HTML and CSS for this. I want to use Supabase as BASS, at the moment I think that I have two options if I want to learn the least amount of things because of my lack of time available:
Quasar Framework: They claim that I can do all the things I need, but I have to use JavaScript, and I am going to have all those bugs with a type-safe programming language avoidable. I guess I can use TypeScript?, but that means learning both, and I am not sure if I will be able to use 100% Typescript. Besides Vue.js, Node.js, etc.
Blazor and .NET: There is MAUI with razor bindings in .Net now, and also a Blazor server. And as far as I can see, the transition from Dart to C# will be easy. I guess that I have to learn some Javascript here and there, but I have to less things I guess, am I wrong? But Blazor is a new technology, Vue is widely used.