Alternatives to Lua logo

Alternatives to Lua

Python, JavaScript, Arduino, Java, and Golang are the most popular alternatives and competitors to Lua.
2.3K
991
+ 1
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What is Lua and what are its top alternatives?

Lua combines simple procedural syntax with powerful data description constructs based on associative arrays and extensible semantics. Lua is dynamically typed, runs by interpreting bytecode for a register-based virtual machine, and has automatic memory management with incremental garbage collection, making it ideal for configuration, scripting, and rapid prototyping.
Lua is a tool in the Languages category of a tech stack.
Lua is an open source tool with 1.4K GitHub stars and 451 GitHub forks. Here’s a link to Lua's open source repository on GitHub

Top Alternatives to Lua

  • 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. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • Arduino
    Arduino

    Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software. ...

  • Java
    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! ...

  • Golang
    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. ...

  • 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. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

Lua alternatives & related posts

Python logo

Python

239.6K
195.5K
6.9K
A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
239.6K
195.5K
+ 1
6.9K
PROS OF PYTHON
  • 1.2K
    Great libraries
  • 961
    Readable code
  • 846
    Beautiful code
  • 787
    Rapid development
  • 689
    Large community
  • 435
    Open source
  • 393
    Elegant
  • 282
    Great community
  • 272
    Object oriented
  • 220
    Dynamic typing
  • 77
    Great standard library
  • 59
    Very fast
  • 55
    Functional programming
  • 49
    Easy to learn
  • 45
    Scientific computing
  • 35
    Great documentation
  • 29
    Productivity
  • 28
    Easy to read
  • 28
    Matlab alternative
  • 23
    Simple is better than complex
  • 20
    It's the way I think
  • 19
    Imperative
  • 18
    Free
  • 18
    Very programmer and non-programmer friendly
  • 17
    Powerfull language
  • 17
    Machine learning support
  • 16
    Fast and simple
  • 14
    Scripting
  • 12
    Explicit is better than implicit
  • 11
    Ease of development
  • 10
    Clear and easy and powerfull
  • 9
    Unlimited power
  • 8
    It's lean and fun to code
  • 8
    Import antigravity
  • 7
    Print "life is short, use python"
  • 7
    Python has great libraries for data processing
  • 6
    Although practicality beats purity
  • 6
    Flat is better than nested
  • 6
    Great for tooling
  • 6
    Rapid Prototyping
  • 6
    Readability counts
  • 6
    High Documented language
  • 6
    I love snakes
  • 6
    Fast coding and good for competitions
  • 6
    There should be one-- and preferably only one --obvious
  • 6
    Now is better than never
  • 5
    Great for analytics
  • 5
    Lists, tuples, dictionaries
  • 4
    Easy to learn and use
  • 4
    Simple and easy to learn
  • 4
    Easy to setup and run smooth
  • 4
    Web scraping
  • 4
    CG industry needs
  • 4
    Socially engaged community
  • 4
    Complex is better than complicated
  • 4
    Multiple Inheritence
  • 4
    Beautiful is better than ugly
  • 4
    Plotting
  • 3
    If the implementation is hard to explain, it's a bad id
  • 3
    Special cases aren't special enough to break the rules
  • 3
    Pip install everything
  • 3
    List comprehensions
  • 3
    No cruft
  • 3
    Generators
  • 3
    Import this
  • 3
    It is Very easy , simple and will you be love programmi
  • 3
    Many types of collections
  • 3
    If the implementation is easy to explain, it may be a g
  • 2
    Batteries included
  • 2
    Should START with this but not STICK with This
  • 2
    Powerful language for AI
  • 2
    Can understand easily who are new to programming
  • 2
    Flexible and easy
  • 2
    Good for hacking
  • 2
    A-to-Z
  • 2
    Because of Netflix
  • 2
    Only one way to do it
  • 2
    Better outcome
  • 1
    Sexy af
  • 1
    Slow
  • 1
    Securit
  • 0
    Ni
  • 0
    Powerful
CONS OF PYTHON
  • 53
    Still divided between python 2 and python 3
  • 28
    Performance impact
  • 26
    Poor syntax for anonymous functions
  • 22
    GIL
  • 19
    Package management is a mess
  • 14
    Too imperative-oriented
  • 12
    Hard to understand
  • 12
    Dynamic typing
  • 12
    Very slow
  • 8
    Indentations matter a lot
  • 8
    Not everything is expression
  • 7
    Incredibly slow
  • 7
    Explicit self parameter in methods
  • 6
    Requires C functions for dynamic modules
  • 6
    Poor DSL capabilities
  • 6
    No anonymous functions
  • 5
    Fake object-oriented programming
  • 5
    Threading
  • 5
    The "lisp style" whitespaces
  • 5
    Official documentation is unclear.
  • 5
    Hard to obfuscate
  • 5
    Circular import
  • 4
    Lack of Syntax Sugar leads to "the pyramid of doom"
  • 4
    The benevolent-dictator-for-life quit
  • 4
    Not suitable for autocomplete
  • 2
    Meta classes
  • 1
    Training wheels (forced indentation)

related Python posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M 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
Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 3.5M 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
JavaScript logo

JavaScript

350.9K
267.2K
8.1K
Lightweight, interpreted, object-oriented language with first-class functions
350.9K
267.2K
+ 1
8.1K
PROS OF JAVASCRIPT
  • 1.7K
    Can be used on frontend/backend
  • 1.5K
    It's everywhere
  • 1.2K
    Lots of great frameworks
  • 896
    Fast
  • 745
    Light weight
  • 425
    Flexible
  • 392
    You can't get a device today that doesn't run js
  • 286
    Non-blocking i/o
  • 236
    Ubiquitousness
  • 191
    Expressive
  • 55
    Extended functionality to web pages
  • 49
    Relatively easy language
  • 46
    Executed on the client side
  • 30
    Relatively fast to the end user
  • 25
    Pure Javascript
  • 21
    Functional programming
  • 15
    Async
  • 13
    Full-stack
  • 12
    Setup is easy
  • 12
    Its everywhere
  • 12
    Future Language of The Web
  • 11
    JavaScript is the New PHP
  • 11
    Because I love functions
  • 10
    Like it or not, JS is part of the web standard
  • 9
    Expansive community
  • 9
    Everyone use it
  • 9
    Can be used in backend, frontend and DB
  • 9
    Easy
  • 8
    Easy to hire developers
  • 8
    No need to use PHP
  • 8
    For the good parts
  • 8
    Can be used both as frontend and backend as well
  • 8
    Powerful
  • 8
    Most Popular Language in the World
  • 7
    Popularized Class-Less Architecture & Lambdas
  • 7
    It's fun
  • 7
    Nice
  • 7
    Versitile
  • 7
    Hard not to use
  • 7
    Its fun and fast
  • 7
    Agile, packages simple to use
  • 7
    Supports lambdas and closures
  • 7
    Love-hate relationship
  • 7
    Photoshop has 3 JS runtimes built in
  • 7
    Evolution of C
  • 6
    1.6K Can be used on frontend/backend
  • 6
    Client side JS uses the visitors CPU to save Server Res
  • 6
    It let's me use Babel & Typescript
  • 6
    Easy to make something
  • 6
    Can be used on frontend/backend/Mobile/create PRO Ui
  • 5
    Promise relationship
  • 5
    Stockholm Syndrome
  • 5
    Function expressions are useful for callbacks
  • 5
    Scope manipulation
  • 5
    Everywhere
  • 5
    Client processing
  • 5
    Clojurescript
  • 5
    What to add
  • 4
    Because it is so simple and lightweight
  • 4
    Only Programming language on browser
  • 1
    Test2
  • 1
    Easy to learn
  • 1
    Easy to understand
  • 1
    Not the best
  • 1
    Hard to learn
  • 1
    Subskill #4
  • 1
    Test
  • 0
    Hard 彤
CONS OF JAVASCRIPT
  • 22
    A constant moving target, too much churn
  • 20
    Horribly inconsistent
  • 15
    Javascript is the New PHP
  • 9
    No ability to monitor memory utilitization
  • 8
    Shows Zero output in case of ANY error
  • 7
    Thinks strange results are better than errors
  • 6
    Can be ugly
  • 3
    No GitHub
  • 2
    Slow

related JavaScript posts

Zach Holman

Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

See more
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M 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
Arduino logo

Arduino

1.2K
1K
7
An open-source electronics prototyping platform based on flexible, easy-to-use hardware and software.
1.2K
1K
+ 1
7
PROS OF ARDUINO
  • 5
    It's uncomplicated, reliable, easy to understand, easy
  • 2
    Barato
CONS OF ARDUINO
    Be the first to leave a con

    related Arduino posts

    Andrew Van Norman
    Escape Room Host at The Ruse Escape Rooms · | 9 upvotes · 10.9K views
    Shared insights
    on
    ArduinoArduinoRaspberry PiRaspberry Pi

    I'm just starting to learn coding with the specific purpose of maintaining the Raspberry Pi-controlled Arduino boards that control our puzzles. I'm learning basics with Scratch 3, and I'm learning how to create a custom block and control its function, shape, and category. I've mostly worked in the service industry and maintenance/Demo since I left the Army Infantry, so I'm definitely kinda dumb; But I've also been selected for some of the more technical jobs involved in those fields, so I'm not stupid... Thank you for your input on the pros/cons.

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    Java logo

    Java

    132.6K
    100.3K
    3.7K
    A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
    132.6K
    100.3K
    + 1
    3.7K
    PROS OF JAVA
    • 599
      Great libraries
    • 445
      Widely used
    • 400
      Excellent tooling
    • 395
      Huge amount of documentation available
    • 334
      Large pool of developers available
    • 208
      Open source
    • 202
      Excellent performance
    • 157
      Great development
    • 150
      Used for android
    • 148
      Vast array of 3rd party libraries
    • 60
      Compiled Language
    • 52
      Used for Web
    • 46
      High Performance
    • 46
      Managed memory
    • 44
      Native threads
    • 43
      Statically typed
    • 35
      Easy to read
    • 33
      Great Community
    • 29
      Reliable platform
    • 24
      Sturdy garbage collection
    • 24
      JVM compatibility
    • 22
      Cross Platform Enterprise Integration
    • 20
      Universal platform
    • 20
      Good amount of APIs
    • 18
      Great Support
    • 14
      Great ecosystem
    • 11
      Backward compatible
    • 11
      Lots of boilerplate
    • 10
      Everywhere
    • 9
      Excellent SDK - JDK
    • 7
      It's Java
    • 7
      Cross-platform
    • 7
      Static typing
    • 6
      Mature language thus stable systems
    • 6
      Better than Ruby
    • 6
      Long term language
    • 6
      Portability
    • 5
      Clojure
    • 5
      Vast Collections Library
    • 5
      Used for Android development
    • 4
      Most developers favorite
    • 4
      Old tech
    • 3
      History
    • 3
      Great Structure
    • 3
      Stable platform, which many new languages depend on
    • 3
      Javadoc
    • 3
      Testable
    • 3
      Best martial for design
    • 2
      Type Safe
    • 2
      Faster than python
    • 0
      Job
    CONS OF JAVA
    • 33
      Verbosity
    • 27
      NullpointerException
    • 17
      Nightmare to Write
    • 16
      Overcomplexity is praised in community culture
    • 12
      Boiler plate code
    • 8
      Classpath hell prior to Java 9
    • 6
      No REPL
    • 4
      No property
    • 3
      Code are too long
    • 2
      Non-intuitive generic implementation
    • 2
      There is not optional parameter
    • 2
      Floating-point errors
    • 1
      Java's too statically, stronglly, and strictly typed
    • 1
      Returning Wildcard Types
    • 1
      Terrbible compared to Python/Batch Perormence

    related Java posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M 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
    Kamil Kowalski
    Lead Architect at Fresha · | 28 upvotes · 3.9M 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
    Golang logo

    Golang

    22.1K
    13.7K
    3.3K
    An open source programming language that makes it easy to build simple, reliable, and efficient software
    22.1K
    13.7K
    + 1
    3.3K
    PROS OF GOLANG
    • 548
      High-performance
    • 395
      Simple, minimal syntax
    • 363
      Fun to write
    • 301
      Easy concurrency support via goroutines
    • 273
      Fast compilation times
    • 193
      Goroutines
    • 180
      Statically linked binaries that are simple to deploy
    • 150
      Simple compile build/run procedures
    • 136
      Backed by google
    • 136
      Great community
    • 53
      Garbage collection built-in
    • 45
      Built-in Testing
    • 44
      Excellent tools - gofmt, godoc etc
    • 39
      Elegant and concise like Python, fast like C
    • 37
      Awesome to Develop
    • 26
      Used for Docker
    • 25
      Flexible interface system
    • 24
      Deploy as executable
    • 24
      Great concurrency pattern
    • 20
      Open-source Integration
    • 18
      Easy to read
    • 17
      Fun to write and so many feature out of the box
    • 16
      Go is God
    • 14
      Easy to deploy
    • 14
      Powerful and simple
    • 14
      Its Simple and Heavy duty
    • 13
      Best language for concurrency
    • 13
      Concurrency
    • 11
      Rich standard library
    • 11
      Safe GOTOs
    • 10
      Clean code, high performance
    • 10
      Easy setup
    • 9
      High performance
    • 9
      Simplicity, Concurrency, Performance
    • 8
      Hassle free deployment
    • 8
      Single binary avoids library dependency issues
    • 7
      Gofmt
    • 7
      Cross compiling
    • 7
      Simple, powerful, and great performance
    • 7
      Used by Giants of the industry
    • 6
      Garbage Collection
    • 5
      Very sophisticated syntax
    • 5
      Excellent tooling
    • 5
      WYSIWYG
    • 4
      Keep it simple and stupid
    • 4
      Widely used
    • 4
      Kubernetes written on Go
    • 2
      No generics
    • 1
      Operator goto
    • 1
      Looks not fancy, but promoting pragmatic idioms
    CONS OF GOLANG
    • 42
      You waste time in plumbing code catching errors
    • 25
      Verbose
    • 23
      Packages and their path dependencies are braindead
    • 16
      Google's documentations aren't beginer friendly
    • 15
      Dependency management when working on multiple projects
    • 10
      Automatic garbage collection overheads
    • 8
      Uncommon syntax
    • 7
      Type system is lacking (no generics, etc)
    • 5
      Collection framework is lacking (list, set, map)
    • 3
      Best programming language
    • 1
      A failed experiment to combine c and python

    related Golang posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 10.1M 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
    Building cool things on the internet 🛠️ at Stream · | 35 upvotes · 3.5M 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
    Ruby logo

    Ruby

    41.2K
    21.3K
    4K
    A dynamic, interpreted, open source programming language with a focus on simplicity and productivity
    41.2K
    21.3K
    + 1
    4K
    PROS OF RUBY
    • 605
      Programme friendly
    • 536
      Quick to develop
    • 490
      Great community
    • 468
      Productivity
    • 432
      Simplicity
    • 273
      Open source
    • 234
      Meta-programming
    • 207
      Powerful
    • 156
      Blocks
    • 139
      Powerful one-liners
    • 69
      Flexible
    • 58
      Easy to learn
    • 51
      Easy to start
    • 42
      Maintainability
    • 37
      Lambdas
    • 30
      Procs
    • 21
      Fun to write
    • 19
      Diverse web frameworks
    • 13
      Reads like English
    • 10
      Makes me smarter and happier
    • 9
      Rails
    • 8
      Very Dynamic
    • 8
      Elegant syntax
    • 6
      Matz
    • 5
      Object Oriented
    • 5
      Programmer happiness
    • 4
      Elegant code
    • 4
      Generally fun but makes you wanna cry sometimes
    • 4
      Friendly
    • 4
      Fun and useful
    • 3
      Easy packaging and modules
    • 3
      There are so many ways to make it do what you want
    • 2
      Primitive types can be tampered with
    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 · | 28 upvotes · 3.9M 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 · 2.9M 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?

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    Simon Reymann
    Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.2M views

    Our whole DevOps stack consists of the following tools:

    • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
    • Respectively Git as revision control system
    • SourceTree as Git GUI
    • Visual Studio Code as IDE
    • CircleCI for continuous integration (automatize development process)
    • Prettier / TSLint / ESLint as code linter
    • SonarQube as quality gate
    • Docker as container management (incl. Docker Compose for multi-container application management)
    • VirtualBox for operating system simulation tests
    • Kubernetes as cluster management for docker containers
    • Heroku for deploying in test environments
    • nginx as web server (preferably used as facade server in production environment)
    • SSLMate (using OpenSSL) for certificate management
    • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
    • PostgreSQL as preferred database system
    • Redis as preferred in-memory database/store (great for caching)

    The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

    • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
    • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
    • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
    • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
    • Scalability: All-in-one framework for distributed systems.
    • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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    Tymoteusz Paul
    Devops guy at X20X Development LTD · | 23 upvotes · 8.3M views

    Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

    It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

    I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

    We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

    If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

    The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

    Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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    Johnny Bell

    I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

    I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

    I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

    Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

    Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

    With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

    If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

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    Russel Werner
    Lead Engineer at StackShare · | 32 upvotes · 2.2M views

    StackShare Feed is built entirely with React, Glamorous, and Apollo. One of our objectives with the public launch of the Feed was to enable a Server-side rendered (SSR) experience for our organic search traffic. When you visit the StackShare Feed, and you aren't logged in, you are delivered the Trending feed experience. We use an in-house Node.js rendering microservice to generate this HTML. This microservice needs to run and serve requests independent of our Rails web app. Up until recently, we had a mono-repo with our Rails and React code living happily together and all served from the same web process. In order to deploy our SSR app into a Heroku environment, we needed to split out our front-end application into a separate repo in GitHub. The driving factor in this decision was mostly due to limitations imposed by Heroku specifically with how processes can't communicate with each other. A new SSR app was created in Heroku and linked directly to the frontend repo so it stays in-sync with changes.

    Related to this, we need a way to "deploy" our frontend changes to various server environments without building & releasing the entire Ruby application. We built a hybrid Amazon S3 Amazon CloudFront solution to host our Webpack bundles. A new CircleCI script builds the bundles and uploads them to S3. The final step in our rollout is to update some keys in Redis so our Rails app knows which bundles to serve. The result of these efforts were significant. Our frontend team now moves independently of our backend team, our build & release process takes only a few minutes, we are now using an edge CDN to serve JS assets, and we have pre-rendered React pages!

    #StackDecisionsLaunch #SSR #Microservices #FrontEndRepoSplit

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