Scala vs Swift: What are the differences?
Developers describe Scala as "A pure-bred object-oriented language that runs on the JVM". 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. On the other hand, Swift is detailed as "An innovative new programming language for Cocoa and Cocoa Touch". 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.
Scala and Swift belong to "Languages" category of the tech stack.
"Static typing", "Jvm" and "Pattern-matching" are the key factors why developers consider Scala; whereas "Ios", "Elegant" and "Not Objective-C" are the primary reasons why Swift is favored.
Scala and Swift are both open source tools. Swift with 48.2K GitHub stars and 7.71K forks on GitHub appears to be more popular than Scala with 11.8K GitHub stars and 2.73K GitHub forks.
Slack, Lyft, and Zillow are some of the popular companies that use Swift, whereas Scala is used by Keen, Lookout, and Tumblr. Swift has a broader approval, being mentioned in 979 company stacks & 526 developers stacks; compared to Scala, which is listed in 436 company stacks and 315 developer stacks.
What is Scala?
What is Swift?
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By mid-2015, around the time of the Series E, the Digital department at WeWork had grown to more than 40 people to support the company’s growing product needs.
By then, they’d migrated the main website off of WordPress to Ruby on Rails, and a combination React, Angular, and jQuery, though there were efforts to move entirely to React for the front-end.
The backend was structured around a microservices architecture built partially in Node.js, along with a combination of Ruby, Python, Bash, and Go. Swift/Objective-C and Java powered the mobile apps.
These technologies power the listings on the website, as well as various internal tools, like community manager dashboards as well as RFID hardware for access management.
At the heart of Uber’s mobile app development are four primary apps: Android rider, Android driver, iOS rider, and iOS driver. Android developers build in Java, iOS in Objective C and Swift. Engineers across both platforms land code into a monolithic code base that ships each week.
They use some third-party libraries, but often build their own, since “Many open source libraries available are general-purpose, which can create binary bloat. For mobile engineering, every kilobyte matters.”
On Android, the build system is Gradle. For the UI, Butter Knife binds views and callbacks to fields and methods via annotation processing, and Picasso provides image loading.
As for iOS, all of the code lives in a monorepo built with Buck. For crash detection, KSCrash reports crashes to the internal reporting framework.
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!
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:
(GitHub : https://github.com/uber/RIBs )
Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.Apps
- Desktop: And Electron to ship it as a desktop application.
- Android: a mix of Java and Kotlin.
- iOS: written in a mix of Objective C and Swift.
- The core application and the API written in PHP/Hack that runs on HHVM.
- The data is stored in MySQL using Vitess.
- Caching is done using Memcached and MCRouter.
- The search service takes help from SolrCloud, with various Java services.
- The messaging system uses WebSockets with many services in Java and Go.
- Load balancing is done using HAproxy with Consul for configuration.
- Most services talk to each other over gRPC,
- Some Thrift and JSON-over-HTTP
- Voice and video calling service was built in Elixir.
- Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
I use Visual Studio Code because at this time is a mature software and I can do practically everything using it.
It's free and open source: The project is hosted on GitHub and it’s free to download, fork, modify and contribute to the project.
Multi-platform: You can download binaries for different platforms, included Windows (x64), MacOS and Linux (
LightWeight: It runs smoothly in different devices. It has an average memory and CPU usage. Starts almost immediately and it’s very stable.
.properties, XML and JSON files.
Integrated tools: Includes an integrated terminal, debugger, problem list and console output inspector. The project navigator sidebar is simple and powerful: you can manage your files and folders with ease. The command palette helps you find commands by text. The search widget has a powerful auto-complete feature to search and find your files.
Extensible and configurable: There are many extensions available for every language supported, including syntax highlighters, IntelliSense and code completion, and debuggers. There are also extension to manage application configuration and architecture like Docker and Jenkins.
Integrated with Git: You can visually manage your project repositories, pull, commit and push your changes, and easy conflict resolution.( there is support for SVN (Subversion) users by plugin)
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?
Why I am using Haskell in my free time?
I have 3 reasons for it. I am looking for:
Improve functional programming skill.
Improve problem-solving skill.
Laziness and mathematical abstractions behind Haskell makes it a wonderful language.
It is Pure functional, it helps me to write better Scala code.
Highly expressive language gives elegant ways to solve coding puzzle.
Back in the days, we started looking for a date on different matrimonial websites as there were no Dating Applications. We used to create different profiles. It all changed in 2012 when Tinder, an Online Dating application came into India Market.
Tinder allowed us to communicate with our potential soul mates. That too without paying any extra money. I too got 4-6 matches in 6 years. It changed the life of many Millennials. Tinder created a revolution of its own. P.S. - I still don't have a date :(
Posting my first article. Please have a look and do give feedback.
Communication InAppChat Dating Matrimonial #messaging
Swift Java PHP Magneto WordPress #Webhooks Added as the newest feature in #Channelize.io. It was initially hard for me to understand what Webhooks meant. But I got the gist of it. Simple example:
Webhooks are pretty much like our brains. for every task, our brains keep sending signals continuously. notifying us for eating, for moving, for removing our hand from Gas Stove or steam.
Imagine asking your brain if you're hungry, tired or hurt. That would be disastrous! Right?
Webhooks are pretty much the same thing, complete automation for your web development projects triggered by some Events just like our Brain. Take a look at the article below to learn more about webhooks and how it works with Channelize.io. Do give your Suggestions also here.
The performance of Swift is almost the same as that of C++, which is considered the fastest in algorithm calculation arithmetics. Apple had this idea in mind and worked to improve the speed of Swift. For example, Swift 2.0 has beaten C++ in several computation algorithms, such as Mandelbrot algorithm. Objective-C is slower because it contains C API legacy.
Swift is faster than Objective-C, because it removed the limitations of C language and has been improved with the help of advanced technologies that were unavailable when C was developed. As mentioned by Apple, Swift was originally designed to operate faster.
Despite the fact that languages are different, they both integrate, and work with Cocoa and Cocoa Touch APIs, for all Apple platforms. Therefore, a regular app-user would not recognize the difference in operating speed between Objective-C vs Swift. Speed also depends on a programmer’s level and capabilities, since a slow app can be written in Swift as well.
Its performance approaches the one of C++ which is considered the fastest algorithm calculation arithmetics. And Apple strives to improve the speed of Swift. Learn more here https://mlsdev.com/blog/51-7-advantages-of-using-swift-over-objective-c
Scala is the God of languages. A legend. The Mount Rushmore of hybrid OO/functional languages is Scala's face four times over.
Ok, honestly, we love Scala. We love(d) Java (and it's parents C and C++), and we love(d) all the languages that borrowed cough stole cough from Java over the years such as Groovy, Clojure, and C#.
It may not be perfect (it totally is, but since programming languages don't have egos of their own, we don't want to paint it too bright), but it is awesome. It runs on the JVM, you can utilize Spring, it works great for data processing (which is sorta kinda the thing we do here, folks), and it just makes sense at all levels.
iPhone app, a new born language, it may good but the IDE, xcode is bad compare with Visual Studio. It just like a baby. playground can only use without connect to other library...you can not do a simply refactor of renaming a variable. You can go to definition and find reference, but you can not go to implementation....I should write them on xcode not here basically it is not the fault of swift, but it tightly to it, unless you want to use a notepad to write it.
Nearly our entire server codebase is written in Scala (if you haven't heard of it, it's a programming language that is basically what you would get if Java + ML had a baby). This has worked out super well. It enables us to write concise easy to deal with code that is typechecked at compile time. It's also been a big help with recruiting.
worked with scala for around 2 years. really enjoyed the language and getting back into the world of functional. unfortunately the community is heavily fragmented and the language itself broken and inconsistent. that with the various factions involved made it a put of for long term investment.
Scala, Akka and Spray (which became Akka-Http) provided the building blocks for the menu service.
Akka's actors and finite-state machine were a natural way to model a USSD menu (a series of stateful interactions between a subscriber and the USSD gateway).
Replaces entirely the Java Language to build a much more expressive and powerful code on the backend, while leveraging at the same time the Java Platform Tools and Frameworks, is a mixture of old and mature with new and sexy.
Most of our newer apps are written completely in swift, with our older ones and some special cases using a mix of Swift and Objective-C, but with Swift 2, the language is pretty much a must-use. "guard" is <3.
Flutter is coded with Swift v.2.3 and can be run with Xcode v.8.2.1. To launch in Xcode 9.3, the code needs to be migrated to Swift 4.1
Most of the app code was gradually rewritten in Swift for better performance and code maintenance.