Alternatives to Elixir logo

Alternatives to Elixir

Go, Erlang, Clojure, Ruby, and Rust are the most popular alternatives and competitors to Elixir.
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What is Elixir and what are its top alternatives?

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.
Elixir is a tool in the Languages category of a tech stack.
Elixir is an open source tool with 18.2K GitHub stars and 2.6K GitHub forks. Here’s a link to Elixir's open source repository on GitHub

Top Alternatives to Elixir

  • Go

    Go

    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. ...

  • Erlang

    Erlang

    Some of Erlang's uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems. ...

  • Clojure

    Clojure

    Clojure is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system. ...

  • Ruby

    Ruby

    Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming. ...

  • Rust

    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. ...

  • Haskell

    Haskell

    It is a general purpose language that can be used in any domain and use case, it is ideally suited for proprietary business logic and data analysis, fast prototyping and enhancing existing software environments with correct code, performance and scalability. ...

  • Python

    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. ...

  • Scala

    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. ...

Elixir alternatives & related posts

Go logo

Go

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9.6K
3K
An open source programming language that makes it easy to build simple, reliable, and efficient software
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+ 1
3K
PROS OF GO
  • 511
    High-performance
  • 375
    Simple, minimal syntax
  • 343
    Fun to write
  • 289
    Easy concurrency support via goroutines
  • 261
    Fast compilation times
  • 183
    Goroutines
  • 173
    Statically linked binaries that are simple to deploy
  • 144
    Simple compile build/run procedures
  • 129
    Backed by google
  • 125
    Great community
  • 46
    Garbage collection built-in
  • 40
    Built-in Testing
  • 36
    Excellent tools - gofmt, godoc etc
  • 33
    Elegant and concise like Python, fast like C
  • 28
    Awesome to Develop
  • 22
    Flexible interface system
  • 21
    Used for Docker
  • 21
    Great concurrency pattern
  • 18
    Deploy as executable
  • 17
    Open-source Integration
  • 14
    Fun to write and so many feature out of the box
  • 11
    Its Simple and Heavy duty
  • 11
    Easy to read
  • 10
    Powerful and simple
  • 9
    Go is God
  • 9
    Safe GOTOs
  • 9
    Easy to deploy
  • 7
    Hassle free deployment
  • 7
    Rich standard library
  • 7
    Concurrency
  • 7
    Best language for concurrency
  • 7
    Easy setup
  • 6
    Used by Giants of the industry
  • 6
    Simplicity, Concurrency, Performance
  • 6
    Clean code, high performance
  • 6
    High performance
  • 6
    Single binary avoids library dependency issues
  • 5
    Simple, powerful, and great performance
  • 5
    Cross compiling
  • 4
    Garbage Collection
  • 4
    Excellent tooling
  • 4
    Very sophisticated syntax
  • 4
    Gofmt
  • 4
    WYSIWYG
  • 3
    Kubernetes written on Go
  • 2
    Keep it simple and stupid
  • 1
    Widely used
  • 0
    No generics
  • 0
    Operator goto
CONS OF GO
  • 38
    You waste time in plumbing code catching errors
  • 23
    Verbose
  • 22
    Packages and their path dependencies are braindead
  • 15
    Dependency management when working on multiple projects
  • 12
    Google's documentations aren't beginer friendly
  • 10
    Automatic garbage collection overheads
  • 7
    Uncommon syntax
  • 6
    Type system is lacking (no generics, etc)
  • 2
    Collection framework is lacking (list, set, map)

related Go posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 37 upvotes · 3.4M views

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

See more
Nick Parsons
Director of Developer Marketing at Stream · | 35 upvotes · 1.2M views

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

See more
Erlang logo

Erlang

578
577
294
A programming language used to build massively scalable soft real-time systems with requirements on high availability
578
577
+ 1
294
PROS OF ERLANG
  • 57
    Concurrency Support
  • 57
    Real time, distributed applications
  • 53
    Fault tolerance
  • 32
    Soft real-time
  • 28
    Open source
  • 19
    Functional programming
  • 17
    Message passing
  • 12
    Immutable data
  • 10
    Works as expected
  • 4
    Facebook chat uses it at backend
  • 2
    Knowledgeable community
  • 2
    Practical
  • 1
    Bullets included
CONS OF ERLANG
    Be the first to leave a con

    related Erlang posts

    Sebastian Gębski

    Another major decision was to adopt Elixir and Phoenix Framework - the DX (Developer eXperience) is pretty similar to what we know from RoR, but this tech is running on the top of rock-solid Erlang platform which is powering planet-scale telecom solutions for 20+ years. So we're getting pretty much the best from both worlds: minimum friction & smart conventions that eliminate the excessive boilerplate AND highly concurrent EVM (Erlang's Virtual Machine) that makes all the scalability problems vanish. The transition was very smooth - none of Ruby developers we had decided to leave because of Elixir. What is more, we kept recruiting Ruby developers w/o any requirement regarding Elixir proficiency & we still were able to educate them internally in almost no time. Obviously Elixir comes with some more tools in the stack: Credo , Hex , AppSignal (required to properly monitor BEAM apps).

    See more
    Shared insights
    on
    ConsulConsulElixirElixirErlangErlang
    at

    Postmates built a tool called Bazaar that helps onboard new partners and handles several routine tasks, like nightly emails to merchants alerting them about items that are out of stock.

    Since they ran Bazaar across multiple instances, the team needed to avoid sending multiple emails to their partners by obtaining lock across multiple hosts. To solve their challenge, they created and open sourced ConsulMutEx, and an Elixir module for acquiring and releasing locks with Consul and other backends.

    It works with Consul’s KV store, as well as other backends, including ets, Erlang’s in-memory database.

    See more
    Clojure logo

    Clojure

    1.2K
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    A dynamic programming language that targets the Java Virtual Machine
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    PROS OF CLOJURE
    • 111
      It is a lisp
    • 97
      Persistent data structures
    • 96
      Concise syntax
    • 85
      jvm-based language
    • 85
      Concurrency
    • 78
      Interactive repl
    • 74
      Code is data
    • 60
      Open source
    • 56
      Lazy data structures
    • 54
      Macros
    • 45
      Functional
    • 21
      Simplistic
    • 19
      Immutable by default
    • 18
      Excellent collections
    • 17
      Fast-growing community
    • 14
      Multiple host languages
    • 12
      Simple (not easy!)
    • 12
      Practical Lisp
    • 9
      Addictive
    • 9
      Community
    • 8
      It creates Reusable code
    • 8
      Because it's really fun to use
    • 7
      Web friendly
    • 7
      Minimalist
    • 7
      Rapid development
    • 5
      Java interop
    • 5
      Programmable programming language
    • 4
      Regained interest in programming
    • 3
      Compiles to JavaScript
    • 2
      Share a lot of code with clojurescript/use on frontend
    • 2
      EDN
    CONS OF CLOJURE
    • 9
      Cryptic stacktraces
    • 4
      Need to wrap basically every java lib
    • 3
      Toxic community
    • 3
      Good code heavily relies on local conventions
    • 2
      Tonns of abandonware
    • 2
      Slow application startup
    • 1
      Tricky profiling
    • 1
      Macros are overused by devs
    • 1
      Have no good and fast fmt
    • 1
      Bad documented libs
    • 1
      Usable only with REPL
    • 1
      LISP!!!!!!!!!!
    • 1
      Configuration bolierplate
    • 1
      Conservative community
    • 1
      IDE with high learning curve

    related Clojure posts

    Stitch is run entirely on AWS. All of our transactional databases are run with Amazon RDS, and we rely on Amazon S3 for data persistence in various stages of our pipeline. Our product integrates with Amazon Redshift as a data destination, and we also use Redshift as an internal data warehouse (powered by Stitch, of course).

    The majority of our services run on stateless Amazon EC2 instances that are managed by AWS OpsWorks. We recently introduced Kubernetes into our infrastructure to run the scheduled jobs that execute Singer code to extract data from various sources. Although we tend to be wary of shiny new toys, Kubernetes has proven to be a good fit for this problem, and its stability, strong community and helpful tooling have made it easy for us to incorporate into our operations.

    While we continue to be happy with Clojure for our internal services, we felt that its relatively narrow adoption could impede Singer's growth. We chose Python both because it is well suited to the task, and it seems to have reached critical mass among data engineers. All that being said, the Singer spec is language agnostic, and integrations and libraries have been developed in JavaScript, Go, and Clojure.

    See more

    I adopted Clojure and ClojureScript because:

    • it's 1 language, multiple platforms.
    • Simple syntax.
    • Designed to avoid unwanted side effects and bugs.
    • Immutable data-structures.
    • Compact code, very expressive.
    • Source code is data.
    • It has super-flexible macro.
    • Has metadata.
    • Interoperability with JavaScript, Java and C#.
    See more
    Ruby logo

    Ruby

    22K
    13.8K
    3.9K
    A dynamic, interpreted, open source programming language with a focus on simplicity and productivity
    22K
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    + 1
    3.9K
    PROS OF RUBY
    • 598
      Programme friendly
    • 532
      Quick to develop
    • 488
      Great community
    • 466
      Productivity
    • 430
      Simplicity
    • 272
      Open source
    • 234
      Meta-programming
    • 203
      Powerful
    • 157
      Blocks
    • 138
      Powerful one-liners
    • 65
      Flexible
    • 56
      Easy to learn
    • 48
      Easy to start
    • 40
      Maintainability
    • 36
      Lambdas
    • 30
      Procs
    • 19
      Fun to write
    • 19
      Diverse web frameworks
    • 11
      Reads like English
    • 8
      Rails
    • 8
      Makes me smarter and happier
    • 7
      Elegant syntax
    • 6
      Very Dynamic
    • 5
      Programmer happiness
    • 5
      Matz
    • 4
      Generally fun but makes you wanna cry sometimes
    • 4
      Fun and useful
    • 3
      Friendly
    • 3
      Object Oriented
    • 3
      There are so many ways to make it do what you want
    • 2
      Easy packaging and modules
    • 2
      Primitive types can be tampered with
    • 2
      Elegant code
    CONS OF RUBY
    • 7
      Memory hog
    • 7
      Really slow if you're not really careful
    • 3
      Nested Blocks can make code unreadable
    • 2
      Encouraging imperative programming
    • 1
      Ambiguous Syntax, such as function parentheses

    related Ruby posts

    Kamil Kowalski
    Lead Architect at Fresha · | 27 upvotes · 808.5K views

    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.

    See more
    Jonathan Pugh
    Software Engineer / Project Manager / Technical Architect · | 25 upvotes · 1.3M views

    I needed to choose a full stack of tools for cross platform mobile application design & development. After much research and trying different tools, these are what I came up with that work for me today:

    For the client coding I chose Framework7 because of its performance, easy learning curve, and very well designed, beautiful UI widgets. I think it's perfect for solo development or small teams. I didn't like React Native. It felt heavy to me and rigid. Framework7 allows the use of #CSS3, which I think is the best technology to come out of the #WWW movement. No other tech has been able to allow designers and developers to develop such flexible, high performance, customisable user interface elements that are highly responsive and hardware accelerated before. Now #CSS3 includes variables and flexboxes it is truly a powerful language and there is no longer a need for preprocessors such as #SCSS / #Sass / #less. React Native contains a very limited interpretation of #CSS3 which I found very frustrating after using #CSS3 for some years already and knowing its powerful features. The other very nice feature of Framework7 is that you can even build for the browser if you want your app to be available for desktop web browsers. The latest release also includes the ability to build for #Electron so you can have MacOS, Windows and Linux desktop apps. This is not possible with React Native yet.

    Framework7 runs on top of Apache Cordova. Cordova and webviews have been slated as being slow in the past. Having a game developer background I found the tweeks to make it run as smooth as silk. One of those tweeks is to use WKWebView. Another important one was using srcset on images.

    I use #Template7 for the for the templating system which is a no-nonsense mobile-centric #HandleBars style extensible templating system. It's easy to write custom helpers for, is fast and has a small footprint. I'm not forced into a new paradigm or learning some new syntax. It operates with standard JavaScript, HTML5 and CSS 3. It's written by the developer of Framework7 and so dovetails with it as expected.

    I configured TypeScript to work with the latest version of Framework7. I consider TypeScript to be one of the best creations to come out of Microsoft in some time. They must have an amazing team working on it. It's very powerful and flexible. It helps you catch a lot of bugs and also provides code completion in supporting IDEs. So for my IDE I use Visual Studio Code which is a blazingly fast and silky smooth editor that integrates seamlessly with TypeScript for the ultimate type checking setup (both products are produced by Microsoft).

    I use Webpack and Babel to compile the JavaScript. TypeScript can compile to JavaScript directly but Babel offers a few more options and polyfills so you can use the latest (and even prerelease) JavaScript features today and compile to be backwards compatible with virtually any browser. My favorite recent addition is "optional chaining" which greatly simplifies and increases readability of a number of sections of my code dealing with getting and setting data in nested objects.

    I use some Ruby scripts to process images with ImageMagick and pngquant to optimise for size and even auto insert responsive image code into the HTML5. Ruby is the ultimate cross platform scripting language. Even as your scripts become large, Ruby allows you to refactor your code easily and make it Object Oriented if necessary. I find it the quickest and easiest way to maintain certain aspects of my build process.

    For the user interface design and prototyping I use Figma. Figma has an almost identical user interface to #Sketch but has the added advantage of being cross platform (MacOS and Windows). Its real-time collaboration features are outstanding and I use them a often as I work mostly on remote projects. Clients can collaborate in real-time and see changes I make as I make them. The clickable prototyping features in Figma are also very well designed and mean I can send clickable prototypes to clients to try user interface updates as they are made and get immediate feedback. I'm currently also evaluating the latest version of #AdobeXD as an alternative to Figma as it has the very cool auto-animate feature. It doesn't have real-time collaboration yet, but I heard it is proposed for 2019.

    For the UI icons I use Font Awesome Pro. They have the largest selection and best looking icons you can find on the internet with several variations in styles so you can find most of the icons you want for standard projects.

    For the backend I was using the #GraphCool Framework. As I later found out, #GraphQL still has some way to go in order to provide the full power of a mature graph query language so later in my project I ripped out #GraphCool and replaced it with CouchDB and Pouchdb. Primarily so I could provide good offline app support. CouchDB with Pouchdb is very flexible and efficient combination and overcomes some of the restrictions I found in #GraphQL and hence #GraphCool also. The most impressive and important feature of CouchDB is its replication. You can configure it in various ways for backups, fault tolerance, caching or conditional merging of databases. CouchDB and Pouchdb even supports storing, retrieving and serving binary or image data or other mime types. This removes a level of complexity usually present in database implementations where binary or image data is usually referenced through an #HTML5 link. With CouchDB and Pouchdb apps can operate offline and sync later, very efficiently, when the network connection is good.

    I use PhoneGap when testing the app. It auto-reloads your app when its code is changed and you can also install it on Android phones to preview your app instantly. iOS is a bit more tricky cause of Apple's policies so it's not available on the App Store, but you can build it and install it yourself to your device.

    So that's my latest mobile stack. What tools do you use? Have you tried these ones?

    See more
    Rust logo

    Rust

    2.2K
    2.6K
    893
    A safe, concurrent, practical language
    2.2K
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    + 1
    893
    PROS OF RUST
    • 121
      Guaranteed memory safety
    • 108
      Fast
    • 71
      Open source
    • 65
      Minimal runtime
    • 56
      Pattern matching
    • 52
      Type inference
    • 50
      Algebraic data types
    • 45
      Concurrent
    • 42
      Efficient C bindings
    • 37
      Practical
    • 29
      Best advances in languages in 20 years
    • 21
      Safe, fast, easy + friendly community
    • 21
      Fix for C/C++
    • 17
      Closures
    • 16
      Stablity
    • 15
      Zero-cost abstractions
    • 13
      Extensive compiler checks
    • 11
      Great community
    • 8
      No Garbage Collection
    • 8
      No NULL type
    • 7
      Completely cross platform: Windows, Linux, Android
    • 7
      Super fast
    • 7
      Async/await
    • 6
      Safety no runtime crashes
    • 6
      Great documentations
    • 5
      High performance
    • 5
      High-performance
    • 5
      Fearless concurrency
    • 5
      Guaranteed thread data race safety
    • 5
      RLS provides great IDE support
    • 5
      Generics
    • 4
      Painless dependency management
    • 4
      Prevents data races
    • 4
      Macros
    • 4
      Compiler can generate Webassembly
    • 4
      Easy Deployment
    • 3
      Helpful compiler
    • 1
      Support on Other Languages
    CONS OF RUST
    • 21
      Hard to learn
    • 20
      Ownership learning curve
    • 7
      Unfriendly, verbose syntax
    • 3
      Variable shadowing
    • 2
      Many type operations make it difficult to follow
    • 2
      High size of builded executable
    • 2
      No jobs

    related Rust posts

    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 98.6K views
    Shared insights
    on
    PythonPythonRustRust
    at

    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).

    See more
    Jakub Olan
    Node.js Software Engineer · | 17 upvotes · 167.3K views

    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.

    See more
    Haskell logo

    Haskell

    847
    873
    471
    An advanced purely-functional programming language
    847
    873
    + 1
    471
    PROS OF HASKELL
    • 82
      Purely-functional programming
    • 63
      Statically typed
    • 56
      Type-safe
    • 38
      Open source
    • 37
      Great community
    • 29
      Composable
    • 28
      Built-in concurrency
    • 27
      Built-in parallelism
    • 21
      Referentially transparent
    • 18
      Generics
    • 13
      Intellectual satisfaction
    • 13
      Type inference
    • 10
      If it compiles, it's correct
    • 7
      Flexible
    • 6
      Monads
    • 4
      Great type system
    • 3
      Proposition testing with QuickCheck
    • 2
      Best in class thinking tool
    • 2
      Great maintainability of the code
    • 2
      Fun
    • 2
      One of the most powerful languages *(see blub paradox)*
    • 2
      Highly expressive, type-safe, fast development time
    • 1
      Type classes
    • 1
      Better type-safe than sorry
    • 1
      Pattern matching and completeness checking
    • 1
      Kind system
    • 1
      Purely-functional Programming
    • 1
      Reliable
    • 0
      Orthogonality
    • 0
      Predictable
    CONS OF HASKELL
    • 6
      Too much distraction in language extensions
    • 5
      Error messages can be very confusing
    • 3
      No best practices
    • 3
      No good ABI
    • 3
      Libraries have poor documentation
    • 2
      Sometimes performance is unpredictable
    • 2
      Poor packaging for apps written in it for Linux distros
    • 1
      Slow compilation

    related Haskell posts

    Vadim Bakaev
    Shared insights
    on
    HaskellHaskellScalaScala

    Why I am using Haskell in my free time?

    I have 3 reasons for it. I am looking for:

    Fun.

    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.

    See more
    Python logo

    Python

    116.4K
    90.6K
    6.4K
    A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
    116.4K
    90.6K
    + 1
    6.4K
    PROS OF PYTHON
    • 1.1K
      Great libraries
    • 921
      Readable code
    • 815
      Beautiful code
    • 764
      Rapid development
    • 669
      Large community
    • 414
      Open source
    • 375
      Elegant
    • 264
      Great community
    • 257
      Object oriented
    • 206
      Dynamic typing
    • 68
      Great standard library
    • 51
      Very fast
    • 47
      Functional programming
    • 33
      Scientific computing
    • 31
      Easy to learn
    • 29
      Great documentation
    • 25
      Matlab alternative
    • 22
      Productivity
    • 21
      Easy to read
    • 19
      Simple is better than complex
    • 17
      It's the way I think
    • 17
      Imperative
    • 15
      Very programmer and non-programmer friendly
    • 14
      Powerful
    • 14
      Free
    • 13
      Fast and simple
    • 13
      Powerfull language
    • 12
      Scripting
    • 9
      Explicit is better than implicit
    • 9
      Machine learning support
    • 8
      Unlimited power
    • 8
      Ease of development
    • 7
      Import antigravity
    • 7
      Clear and easy and powerfull
    • 6
      It's lean and fun to code
    • 6
      Print "life is short, use python"
    • 5
      Great for tooling
    • 5
      Fast coding and good for competitions
    • 5
      There should be one-- and preferably only one --obvious
    • 5
      Python has great libraries for data processing
    • 5
      High Documented language
    • 5
      I love snakes
    • 5
      Although practicality beats purity
    • 5
      Flat is better than nested
    • 4
      Readability counts
    • 3
      Multiple Inheritence
    • 3
      Complex is better than complicated
    • 3
      Lists, tuples, dictionaries
    • 3
      Rapid Prototyping
    • 3
      Plotting
    • 3
      Socially engaged community
    • 3
      Great for analytics
    • 3
      Beautiful is better than ugly
    • 3
      CG industry needs
    • 2
      No cruft
    • 2
      Easy to learn and use
    • 2
      List comprehensions
    • 2
      Generators
    • 2
      Special cases aren't special enough to break the rules
    • 2
      Now is better than never
    • 2
      If the implementation is hard to explain, it's a bad id
    • 2
      If the implementation is easy to explain, it may be a g
    • 2
      Simple and easy to learn
    • 2
      Import this
    • 1
      It is Very easy , simple and will you be love programmi
    • 1
      Because of Netflix
    • 1
      Web scraping
    • 1
      Better outcome
    • 1
      Batteries included
    • 1
      Powerful language for AI
    • 1
      Easy to setup and run smooth
    • 1
      Pip install everything
    • 1
      Only one way to do it
    • 1
      A-to-Z
    • 1
      Many types of collections
    • 1
      Flexible and easy
    • 0
      Pro
    • 0
      Powerful
    CONS OF PYTHON
    • 48
      Still divided between python 2 and python 3
    • 26
      Performance impact
    • 26
      Poor syntax for anonymous functions
    • 18
      Package management is a mess
    • 18
      GIL
    • 13
      Too imperative-oriented
    • 12
      Hard to understand
    • 10
      Dynamic typing
    • 8
      Very slow
    • 8
      Not everything is expression
    • 7
      Indentations matter a lot
    • 7
      Explicit self parameter in methods
    • 6
      Poor DSL capabilities
    • 6
      No anonymous functions
    • 6
      Requires C functions for dynamic modules
    • 5
      The "lisp style" whitespaces
    • 5
      Hard to obfuscate
    • 4
      The benevolent-dictator-for-life quit
    • 4
      Lack of Syntax Sugar leads to "the pyramid of doom"
    • 4
      Threading
    • 4
      Fake object-oriented programming
    • 4
      Incredibly slow
    • 3
      Not suitable for autocomplete
    • 3
      Official documentation is unclear.
    • 2
      Circular import
    • 1
      Training wheels (forced indentation)
    • 1
      Meta classes

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    Conor Myhrvold
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    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:

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    Nick Parsons
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    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.

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    Scala

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    PROS OF SCALA
    • 186
      Static typing
    • 177
      Jvm
    • 176
      Pattern-matching
    • 169
      Scala is fun
    • 137
      Types
    • 93
      Concurrency
    • 88
      Actor library
    • 83
      Solve functional problems
    • 83
      Open source
    • 80
      Solve concurrency in a safer way
    • 42
      Functional
    • 22
      Fast
    • 22
      Generics
    • 17
      It makes me a better engineer
    • 15
      Syntactic sugar
    • 12
      Scalable
    • 10
      First-class functions
    • 10
      Type safety
    • 9
      Interactive REPL
    • 8
      Expressive
    • 7
      SBT
    • 6
      Case classes
    • 6
      Implicit parameters
    • 4
      Rapid and Safe Development using Functional Programming
    • 4
      Object-oriented
    • 4
      JVM, OOP and Functional programming, and static typing
    • 4
      Used by Twitter
    • 3
      Functional Proframming
    • 2
      Beautiful Code
    • 2
      Safety
    • 2
      Spark
    • 2
      Growing Community
    • 1
      DSL
    • 1
      Rich Static Types System and great Concurrency support
    • 1
      Naturally enforce high code quality
    • 1
      Mill build tool
    • 1
      Akka Streams
    • 1
      Akka
    • 1
      Reactive Streams
    • 1
      Easy embedded DSLs
    • 0
      Freedom to choose the right tools for a job
    CONS OF SCALA
    • 9
      Slow compilation time
    • 5
      Multiple ropes and styles to hang your self
    • 3
      Too few developers available
    • 3
      Complicated subtyping
    • 1
      My coworkers using scala are racist against other stuff

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    Marc Bollinger
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    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.

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