Alternatives to IPython logo

Alternatives to IPython

Jupyter, Python, Anaconda, PyCharm, and Spyder are the most popular alternatives and competitors to IPython.
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What is IPython and what are its top alternatives?

IPython is a powerful interactive Python shell that provides features such as enhanced introspection, rich media output, and high-performance computing tools. It allows users to easily explore and analyze data, write and execute Python code, and visualize results. However, one limitation of IPython is that it is mainly focused on Python programming and may not be suitable for users looking for a more general-purpose interactive computing environment.

  1. Jupyter Notebook: Jupyter Notebook is an open-source web application that allows users to create and share documents that contain live code, equations, visualizations, and narrative text. It supports over 40 programming languages and provides a user-friendly interface for interactive computing.
  2. RStudio: RStudio is a popular integrated development environment for R that provides tools for data analysis, visualization, and modeling. It offers a wide range of features for R programming and helps users to efficiently work with data.
  3. Spyder: Spyder is an open-source IDE for Python with advanced editing, interactive testing, and debugging capabilities. It is designed for scientific computing and data analysis and provides a user-friendly interface for Python programming.
  4. Colab: Google Colab is a cloud-based Jupyter notebook environment that allows users to write and execute Python code in the browser. It provides free access to GPU and TPU for machine learning tasks.
  5. Atom: Atom is a customizable text editor that supports multiple programming languages and offers various packages for code editing and development. It can be extended with plugins and themes to customize the workflow.
  6. Zeppelin: Apache Zeppelin is a web-based notebook that enables data-driven and interactive data analytics. It supports multiple interpreters for different programming languages and data sources.
  7. Hydrogen: Hydrogen is an Atom package that brings the power of Jupyter kernels to Atom, allowing users to run code inline and visualize data while editing their code.
  8. Wing: Wing is a professional Python IDE that provides features such as code analysis, debugging, and project management tools. It offers an interactive Python shell and supports remote development.
  9. BeakerX: BeakerX is a collection of extensions for Jupyter Notebook that adds functionality for interactive data science and machine learning. It provides interactive widgets, time series plotting, and various data manipulation tools.
  10. Visual Studio Code: Visual Studio Code is a lightweight but powerful code editor that supports various programming languages and offers a wide range of extensions for customization and integration with different tools and services.

Top Alternatives to IPython

  • Jupyter
    Jupyter

    The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media. ...

  • 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. ...

  • Anaconda
    Anaconda

    A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda. ...

  • PyCharm
    PyCharm

    PyCharm’s smart code editor provides first-class support for Python, JavaScript, CoffeeScript, TypeScript, CSS, popular template languages and more. Take advantage of language-aware code completion, error detection, and on-the-fly code fixes! ...

  • Spyder
    Spyder

    It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. ...

  • 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. ...

  • Node.js
    Node.js

    Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices. ...

  • HTML5
    HTML5

    HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997. ...

IPython alternatives & related posts

Jupyter logo

Jupyter

2.6K
1.4K
57
Multi-language interactive computing environments.
2.6K
1.4K
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PROS OF JUPYTER
  • 19
    In-line code execution using blocks
  • 11
    In-line graphing support
  • 8
    Can be themed
  • 7
    Multiple kernel support
  • 3
    LaTex Support
  • 3
    Best web-browser IDE for Python
  • 3
    Export to python code
  • 2
    HTML export capability
  • 1
    Multi-user with Kubernetes
CONS OF JUPYTER
    Be the first to leave a con

    related Jupyter posts

    Jan Vlnas
    Senior Software Engineer at Mews · | 5 upvotes · 454.4K views

    From my point of view, both OpenRefine and Apache Hive serve completely different purposes. OpenRefine is intended for interactive cleaning of messy data locally. You could work with their libraries to use some of OpenRefine features as part of your data pipeline (there are pointers in FAQ), but OpenRefine in general is intended for a single-user local operation.

    I can't recommend a particular alternative without better understanding of your use case. But if you are looking for an interactive tool to work with big data at scale, take a look at notebook environments like Jupyter, Databricks, or Deepnote. If you are building a data processing pipeline, consider also Apache Spark.

    Edit: Fixed references from Hadoop to Hive, which is actually closer to Spark.

    See more
    Guillaume Simler

    Jupyter Anaconda Pandas IPython

    A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.

    The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead

    See more
    Python logo

    Python

    244.4K
    199.5K
    6.9K
    A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
    244.4K
    199.5K
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    6.9K
    PROS OF PYTHON
    • 1.2K
      Great libraries
    • 962
      Readable code
    • 847
      Beautiful code
    • 788
      Rapid development
    • 690
      Large community
    • 438
      Open source
    • 393
      Elegant
    • 282
      Great community
    • 272
      Object oriented
    • 220
      Dynamic typing
    • 77
      Great standard library
    • 60
      Very fast
    • 55
      Functional programming
    • 49
      Easy to learn
    • 45
      Scientific computing
    • 35
      Great documentation
    • 29
      Productivity
    • 28
      Easy to read
    • 28
      Matlab alternative
    • 24
      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
      Now is better than never
    • 6
      Great for tooling
    • 6
      Readability counts
    • 6
      Rapid Prototyping
    • 6
      I love snakes
    • 6
      Flat is better than nested
    • 6
      Fast coding and good for competitions
    • 6
      There should be one-- and preferably only one --obvious
    • 6
      High Documented language
    • 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
      Many types of collections
    • 3
      Flexible and easy
    • 3
      It is Very easy , simple and will you be love programmi
    • 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
      If the implementation is easy to explain, it may be a g
    • 2
      Can understand easily who are new to programming
    • 2
      Batteries included
    • 2
      Securit
    • 2
      Good for hacking
    • 2
      Better outcome
    • 2
      Only one way to do it
    • 2
      Because of Netflix
    • 2
      A-to-Z
    • 2
      Should START with this but not STICK with This
    • 2
      Powerful language for AI
    • 1
      Automation friendly
    • 1
      Sexy af
    • 1
      Slow
    • 1
      Procedural programming
    • 0
      Ni
    • 0
      Powerful
    • 0
      Keep it simple
    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 · 12.6M 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 · 4.3M 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
    Anaconda logo

    Anaconda

    431
    487
    0
    The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders
    431
    487
    + 1
    0
    PROS OF ANACONDA
      Be the first to leave a pro
      CONS OF ANACONDA
        Be the first to leave a con

        related Anaconda posts

        Which one of these should I install? I am a beginner and starting to learn to code. I have Anaconda, Visual Studio Code ( vscode recommended me to install Git) and I am learning Python, JavaScript, and MySQL for educational purposes. Also if you have any other pro-tips or advice for me please share.

        Yours thankfully, Darkhiem

        See more
        Shared insights
        on
        JavaJavaAnacondaAnacondaPythonPython

        I am going to learn machine learning and self host an online IDE, the tool that i may use is Python, Anaconda, various python library and etc. which tools should i go for? this may include Java development, web development. Now i have 1 more candidate which are visual studio code online (code server). i will host on google cloud

        See more
        PyCharm logo

        PyCharm

        27.8K
        23.6K
        451
        The Most Intelligent Python IDE
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        451
        PROS OF PYCHARM
        • 112
          Smart auto-completion
        • 93
          Intelligent code analysis
        • 77
          Powerful refactoring
        • 60
          Virtualenv integration
        • 54
          Git integration
        • 22
          Support for Django
        • 11
          Multi-database integration
        • 7
          VIM integration
        • 4
          Vagrant integration
        • 3
          In-tool Bash and Python shell
        • 2
          Plugin architecture
        • 2
          Docker
        • 1
          Django Implemented
        • 1
          Debug mode support docker
        • 1
          Emacs keybinds
        • 1
          Perforce integration
        CONS OF PYCHARM
        • 10
          Slow startup
        • 7
          Not very flexible
        • 6
          Resource hog
        • 3
          Periodic slow menu response
        • 1
          Pricey for full features

        related PyCharm posts

        christy craemer

        UPDATE: Thanks for the great response. I am going to start with VSCode based on the open source and free version that will allow me to grow into other languages, but not cost me a license ..yet.

        I have been working with software development for 12 years, but I am just beginning my journey to learn to code. I am starting with Python following the suggestion of some of my coworkers. They are split between Eclipse and IntelliJ IDEA for IDEs that they use and PyCharm is new to me. Which IDE would you suggest for a beginner that will allow expansion to Java, JavaScript, and eventually AngularJS and possibly mobile applications?

        See more

        I am a QA heading to a new company where they all generally use Visual Studio Code, my experience is with IntelliJ IDEA and PyCharm. The language they use is JavaScript and so I will be writing my test framework in javaScript so the devs can more easily write tests without context switching.

        My 2 questions: Does VS Code have Cucumber Plugins allowing me to write behave tests? And more importantly, does VS Code have the same refactoring tools that IntelliJ IDEA has? I love that I have easy access to a range of tools that allow me to refactor and simplify my code, making code writing really easy.

        See more
        Spyder logo

        Spyder

        120
        160
        11
        The Scientific Python Development Environment
        120
        160
        + 1
        11
        PROS OF SPYDER
        • 6
          Variable Explorer
        • 2
          More tools for Python
        • 2
          Free with anaconda
        • 1
          Intellisense
        CONS OF SPYDER
        • 1
          Slow to fire up

        related Spyder posts

        JavaScript logo

        JavaScript

        359.8K
        273.6K
        8.1K
        Lightweight, interpreted, object-oriented language with first-class functions
        359.8K
        273.6K
        + 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
        • 898
          Fast
        • 745
          Light weight
        • 425
          Flexible
        • 392
          You can't get a device today that doesn't run js
        • 286
          Non-blocking i/o
        • 237
          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
          Future Language of The Web
        • 12
          Its everywhere
        • 11
          Because I love functions
        • 11
          JavaScript is the New PHP
        • 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
          Most Popular Language in the World
        • 8
          Powerful
        • 8
          Can be used both as frontend and backend as well
        • 8
          For the good parts
        • 8
          No need to use PHP
        • 8
          Easy to hire developers
        • 7
          Agile, packages simple to use
        • 7
          Love-hate relationship
        • 7
          Photoshop has 3 JS runtimes built in
        • 7
          Evolution of C
        • 7
          It's fun
        • 7
          Hard not to use
        • 7
          Versitile
        • 7
          Its fun and fast
        • 7
          Nice
        • 7
          Popularized Class-Less Architecture & Lambdas
        • 7
          Supports lambdas and closures
        • 6
          It let's me use Babel & Typescript
        • 6
          Can be used on frontend/backend/Mobile/create PRO Ui
        • 6
          1.6K Can be used on frontend/backend
        • 6
          Client side JS uses the visitors CPU to save Server Res
        • 6
          Easy to make something
        • 5
          Clojurescript
        • 5
          Promise relationship
        • 5
          Stockholm Syndrome
        • 5
          Function expressions are useful for callbacks
        • 5
          Scope manipulation
        • 5
          Everywhere
        • 5
          Client processing
        • 5
          What to add
        • 4
          Because it is so simple and lightweight
        • 4
          Only Programming language on browser
        • 1
          Test
        • 1
          Hard to learn
        • 1
          Test2
        • 1
          Not the best
        • 1
          Easy to understand
        • 1
          Subskill #4
        • 1
          Easy to learn
        • 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
        • 0
          HORRIBLE DOCUMENTS, faulty code, repo has bugs

        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 · 12.6M 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
        Node.js logo

        Node.js

        188.2K
        159.8K
        8.5K
        A platform built on Chrome's JavaScript runtime for easily building fast, scalable network applications
        188.2K
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        PROS OF NODE.JS
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          Npm
        • 1.3K
          Javascript
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          Great libraries
        • 1K
          High-performance
        • 805
          Open source
        • 486
          Great for apis
        • 477
          Asynchronous
        • 423
          Great community
        • 390
          Great for realtime apps
        • 296
          Great for command line utilities
        • 84
          Websockets
        • 83
          Node Modules
        • 69
          Uber Simple
        • 59
          Great modularity
        • 58
          Allows us to reuse code in the frontend
        • 42
          Easy to start
        • 35
          Great for Data Streaming
        • 32
          Realtime
        • 28
          Awesome
        • 25
          Non blocking IO
        • 18
          Can be used as a proxy
        • 17
          High performance, open source, scalable
        • 16
          Non-blocking and modular
        • 15
          Easy and Fun
        • 14
          Easy and powerful
        • 13
          Future of BackEnd
        • 13
          Same lang as AngularJS
        • 12
          Fullstack
        • 11
          Fast
        • 10
          Scalability
        • 10
          Cross platform
        • 9
          Simple
        • 8
          Mean Stack
        • 7
          Great for webapps
        • 7
          Easy concurrency
        • 6
          Typescript
        • 6
          Fast, simple code and async
        • 6
          React
        • 6
          Friendly
        • 5
          Control everything
        • 5
          Its amazingly fast and scalable
        • 5
          Easy to use and fast and goes well with JSONdb's
        • 5
          Scalable
        • 5
          Great speed
        • 5
          Fast development
        • 4
          It's fast
        • 4
          Easy to use
        • 4
          Isomorphic coolness
        • 3
          Great community
        • 3
          Not Python
        • 3
          Sooper easy for the Backend connectivity
        • 3
          TypeScript Support
        • 3
          Blazing fast
        • 3
          Performant and fast prototyping
        • 3
          Easy to learn
        • 3
          Easy
        • 3
          Scales, fast, simple, great community, npm, express
        • 3
          One language, end-to-end
        • 3
          Less boilerplate code
        • 2
          Npm i ape-updating
        • 2
          Event Driven
        • 2
          Lovely
        • 1
          Creat for apis
        • 0
          Node
        CONS OF NODE.JS
        • 46
          Bound to a single CPU
        • 45
          New framework every day
        • 40
          Lots of terrible examples on the internet
        • 33
          Asynchronous programming is the worst
        • 24
          Callback
        • 19
          Javascript
        • 11
          Dependency hell
        • 11
          Dependency based on GitHub
        • 10
          Low computational power
        • 7
          Very very Slow
        • 7
          Can block whole server easily
        • 7
          Callback functions may not fire on expected sequence
        • 4
          Breaking updates
        • 4
          Unstable
        • 3
          Unneeded over complication
        • 3
          No standard approach
        • 1
          Bad transitive dependency management
        • 1
          Can't read server session

        related Node.js posts

        Shared insights
        on
        Node.jsNode.jsGraphQLGraphQLMongoDBMongoDB

        I just finished the very first version of my new hobby project: #MovieGeeks. It is a minimalist online movie catalog for you to save the movies you want to see and for rating the movies you already saw. This is just the beginning as I am planning to add more features on the lines of sharing and discovery

        For the #BackEnd I decided to use Node.js , GraphQL and MongoDB:

        1. Node.js has a huge community so it will always be a safe choice in terms of libraries and finding solutions to problems you may have

        2. GraphQL because I needed to improve my skills with it and because I was never comfortable with the usual REST approach. I believe GraphQL is a better option as it feels more natural to write apis, it improves the development velocity, by definition it fixes the over-fetching and under-fetching problem that is so common on REST apis, and on top of that, the community is getting bigger and bigger.

        3. MongoDB was my choice for the database as I already have a lot of experience working on it and because, despite of some bad reputation it has acquired in the last months, I still believe it is a powerful database for at least a very long list of use cases such as the one I needed for my website

        See more
        Nick Rockwell
        SVP, Engineering at Fastly · | 46 upvotes · 4.1M views

        When I joined NYT there was already broad dissatisfaction with the LAMP (Linux Apache HTTP Server MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

        So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

        React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

        Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

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        HTML5

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        5th major revision of the core language of the World Wide Web
        148.3K
        126.5K
        + 1
        2.2K
        PROS OF HTML5
        • 447
          New doctype
        • 389
          Local storage
        • 334
          Canvas
        • 285
          Semantic header and footer
        • 240
          Video element
        • 121
          Geolocation
        • 106
          Form autofocus
        • 100
          Email inputs
        • 85
          Editable content
        • 79
          Application caches
        • 10
          Easy to use
        • 9
          Cleaner Code
        • 5
          Easy
        • 4
          Websockets
        • 4
          Semantical
        • 3
          Better
        • 3
          Audio element
        • 3
          Modern
        • 2
          Portability
        • 2
          Semantic Header and Footer, Geolocation, New Doctype
        • 2
          Content focused
        • 2
          Compatible
        • 1
          Very easy to learning to HTML
        CONS OF HTML5
        • 1
          Easy to forget the tags when you're a begginner
        • 1
          Long and winding code

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        Jan Vlnas
        Senior Software Engineer at Mews · | 26 upvotes · 388.3K views
        Shared insights
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        HTML5HTML5JavaScriptJavaScriptNext.jsNext.js

        Few years ago we were building a Next.js site with a few simple forms. This required handling forms validation and submission, but instead of picking some forms library, we went with plain JavaScript and constraint validation API in HTML5. This shaved off a few KBs of dependencies and gave us full control over the validation behavior and look. I describe this approach, with its pros and cons, in a blog post.

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        Jonathan Pugh
        Software Engineer / Project Manager / Technical Architect · | 25 upvotes · 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?

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