Alternatives to Jupyter logo

Alternatives to Jupyter

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

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Jupyter is a tool in the Data Science Notebooks category of a tech stack.
Jupyter is an open source tool with 11.7K GitHub stars and 5K GitHub forks. Here’s a link to Jupyter's open source repository on GitHub

Top Alternatives to Jupyter

  • Apache Zeppelin
    Apache Zeppelin

    A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. ...

  • 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! ...

  • IPython
    IPython

    It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing. ...

  • Spyder
    Spyder

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

  • 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. ...

  • RStudio
    RStudio

    An integrated development environment for R, with a console, syntax-highlighting editor that supports direct code execution. Publish and distribute data products across your organization. One button deployment of Shiny applications, R Markdown reports, Jupyter Notebooks, and more. Collections of R functions, data, and compiled code in a well-defined format. You can expand the types of analyses you do by adding packages. ...

  • 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. ...

  • Postman
    Postman

    It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide. ...

Jupyter alternatives & related posts

Apache Zeppelin logo

Apache Zeppelin

190
305
32
A web-based notebook that enables interactive data analytics
190
305
+ 1
32
PROS OF APACHE ZEPPELIN
  • 7
    In-line code execution using paragraphs
  • 5
    Cluster integration
  • 4
    Multi-User Capability
  • 4
    In-line graphing
  • 4
    Zeppelin context to exchange data between languages
  • 2
    Privacy configuration of the end users
  • 2
    Execution progress included
  • 2
    Multi-user with kerberos
  • 2
    Allows to close browser and reopen for result later
CONS OF APACHE ZEPPELIN
    Be the first to leave a con

    related Apache Zeppelin posts

    PyCharm logo

    PyCharm

    27.8K
    23.6K
    451
    The Most Intelligent Python IDE
    27.8K
    23.6K
    + 1
    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
    IPython logo

    IPython

    526
    111
    4
    A command shell for interactive computing in multiple programming languages
    526
    111
    + 1
    4
    PROS OF IPYTHON
    • 1
      Interactive exploration then save to a script
    • 1
      Persistent history between sessions
    • 1
      It's magical are just that
    • 1
      Help in a keystroke
    CONS OF IPYTHON
      Be the first to leave a con

      related IPython posts

      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
      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

      Anaconda logo

      Anaconda

      431
      487
      0
      The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders
      431
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      + 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
          RStudio logo

          RStudio

          408
          449
          10
          Open source and enterprise-ready professional software for the R community
          408
          449
          + 1
          10
          PROS OF RSTUDIO
          • 3
            Visual editor for R Markdown documents
          • 2
            In-line code execution using blocks
          • 1
            Can be themed
          • 1
            In-line graphing support
          • 1
            Latex support
          • 1
            Sophitiscated statistical packages
          • 1
            Supports Rcpp, python and SQL
          CONS OF RSTUDIO
            Be the first to leave a con

            related RStudio posts

            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
            + 1
            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
            Postman logo

            Postman

            94.3K
            80.8K
            1.8K
            Only complete API development environment
            94.3K
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            + 1
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            PROS OF POSTMAN
            • 490
              Easy to use
            • 369
              Great tool
            • 276
              Makes developing rest api's easy peasy
            • 156
              Easy setup, looks good
            • 144
              The best api workflow out there
            • 53
              It's the best
            • 53
              History feature
            • 44
              Adds real value to my workflow
            • 43
              Great interface that magically predicts your needs
            • 35
              The best in class app
            • 12
              Can save and share script
            • 10
              Fully featured without looking cluttered
            • 8
              Collections
            • 8
              Option to run scrips
            • 8
              Global/Environment Variables
            • 7
              Shareable Collections
            • 7
              Dead simple and useful. Excellent
            • 7
              Dark theme easy on the eyes
            • 6
              Awesome customer support
            • 6
              Great integration with newman
            • 5
              Documentation
            • 5
              Simple
            • 5
              The test script is useful
            • 4
              Saves responses
            • 4
              This has simplified my testing significantly
            • 4
              Makes testing API's as easy as 1,2,3
            • 4
              Easy as pie
            • 3
              API-network
            • 3
              I'd recommend it to everyone who works with apis
            • 3
              Mocking API calls with predefined response
            • 2
              Now supports GraphQL
            • 2
              Postman Runner CI Integration
            • 2
              Easy to setup, test and provides test storage
            • 2
              Continuous integration using newman
            • 2
              Pre-request Script and Test attributes are invaluable
            • 2
              Runner
            • 2
              Graph
            • 1
              <a href="http://fixbit.com/">useful tool</a>
            CONS OF POSTMAN
            • 10
              Stores credentials in HTTP
            • 9
              Bloated features and UI
            • 8
              Cumbersome to switch authentication tokens
            • 7
              Poor GraphQL support
            • 5
              Expensive
            • 3
              Not free after 5 users
            • 3
              Can't prompt for per-request variables
            • 1
              Import swagger
            • 1
              Support websocket
            • 1
              Import curl

            related Postman posts

            Noah Zoschke
            Engineering Manager at Segment · | 30 upvotes · 2.9M views

            We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. A public API is only as good as its #documentation. For the API reference doc we are using Postman.

            Postman is an “API development environment”. You download the desktop app, and build API requests by URL and payload. Over time you can build up a set of requests and organize them into a “Postman Collection”. You can generalize a collection with “collection variables”. This allows you to parameterize things like username, password and workspace_name so a user can fill their own values in before making an API call. This makes it possible to use Postman for one-off API tasks instead of writing code.

            Then you can add Markdown content to the entire collection, a folder of related methods, and/or every API method to explain how the APIs work. You can publish a collection and easily share it with a URL.

            This turns Postman from a personal #API utility to full-blown public interactive API documentation. The result is a great looking web page with all the API calls, docs and sample requests and responses in one place. Check out the results here.

            Postman’s powers don’t end here. You can automate Postman with “test scripts” and have it periodically run a collection scripts as “monitors”. We now have #QA around all the APIs in public docs to make sure they are always correct

            Along the way we tried other techniques for documenting APIs like ReadMe.io or Swagger UI. These required a lot of effort to customize.

            Writing and maintaining a Postman collection takes some work, but the resulting documentation site, interactivity and API testing tools are well worth it.

            See more
            Simon Reymann
            Senior Fullstack Developer at QUANTUSflow Software GmbH · | 27 upvotes · 5.1M views

            Our whole Node.js backend stack consists of the following tools:

            • Lerna as a tool for multi package and multi repository management
            • npm as package manager
            • NestJS as Node.js framework
            • TypeScript as programming language
            • ExpressJS as web server
            • Swagger UI for visualizing and interacting with the API’s resources
            • Postman as a tool for API development
            • TypeORM as object relational mapping layer
            • JSON Web Token for access token management

            The main reason we have chosen Node.js over PHP is related to the following artifacts:

            • Made for the web and widely in use: Node.js is a software platform for developing server-side network services. Well-known projects that rely on Node.js include the blogging software Ghost, the project management tool Trello and the operating system WebOS. Node.js requires the JavaScript runtime environment V8, which was specially developed by Google for the popular Chrome browser. This guarantees a very resource-saving architecture, which qualifies Node.js especially for the operation of a web server. Ryan Dahl, the developer of Node.js, released the first stable version on May 27, 2009. He developed Node.js out of dissatisfaction with the possibilities that JavaScript offered at the time. The basic functionality of Node.js has been mapped with JavaScript since the first version, which can be expanded with a large number of different modules. The current package managers (npm or Yarn) for Node.js know more than 1,000,000 of these modules.
            • Fast server-side solutions: Node.js adopts the JavaScript "event-loop" to create non-blocking I/O applications that conveniently serve simultaneous events. With the standard available asynchronous processing within JavaScript/TypeScript, highly scalable, server-side solutions can be realized. The efficient use of the CPU and the RAM is maximized and more simultaneous requests can be processed than with conventional multi-thread servers.
            • A language along the entire stack: Widely used frameworks such as React or AngularJS or Vue.js, which we prefer, are written in JavaScript/TypeScript. If Node.js is now used on the server side, you can use all the advantages of a uniform script language throughout the entire application development. The same language in the back- and frontend simplifies the maintenance of the application and also the coordination within the development team.
            • Flexibility: Node.js sets very few strict dependencies, rules and guidelines and thus grants a high degree of flexibility in application development. There are no strict conventions so that the appropriate architecture, design structures, modules and features can be freely selected for the development.
            See more