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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
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 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
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’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
It is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. ...
- 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 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 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
- In-line code execution using blocks19
- In-line graphing support11
- Can be themed8
- Multiple kernel support7
- LaTex Support3
- Best web-browser IDE for Python3
- Export to python code3
- HTML export capability2
- Multi-user with Kubernetes1
related Jupyter posts
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.
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
Python
- Great libraries1.2K
- Readable code963
- Beautiful code847
- Rapid development788
- Large community691
- Open source438
- Elegant393
- Great community282
- Object oriented273
- Dynamic typing221
- Great standard library77
- Very fast60
- Functional programming55
- Easy to learn50
- Scientific computing46
- Great documentation35
- Productivity29
- Matlab alternative28
- Easy to read28
- Simple is better than complex24
- It's the way I think20
- Imperative19
- Very programmer and non-programmer friendly18
- Free18
- Machine learning support17
- Powerfull language17
- Fast and simple16
- Scripting14
- Explicit is better than implicit12
- Ease of development11
- Clear and easy and powerfull10
- Unlimited power9
- Import antigravity8
- It's lean and fun to code8
- Print "life is short, use python"7
- Python has great libraries for data processing7
- High Documented language6
- I love snakes6
- Readability counts6
- Rapid Prototyping6
- Now is better than never6
- Although practicality beats purity6
- Flat is better than nested6
- Great for tooling6
- There should be one-- and preferably only one --obvious6
- Fast coding and good for competitions6
- Web scraping5
- Lists, tuples, dictionaries5
- Great for analytics5
- Beautiful is better than ugly4
- Easy to learn and use4
- Easy to setup and run smooth4
- Multiple Inheritence4
- CG industry needs4
- Socially engaged community4
- Complex is better than complicated4
- Plotting4
- Simple and easy to learn4
- List comprehensions3
- Powerful language for AI3
- Flexible and easy3
- It is Very easy , simple and will you be love programmi3
- Many types of collections3
- If the implementation is easy to explain, it may be a g3
- If the implementation is hard to explain, it's a bad id3
- Special cases aren't special enough to break the rules3
- Pip install everything3
- No cruft3
- Generators3
- Import this3
- Batteries included2
- Securit2
- Can understand easily who are new to programming2
- Should START with this but not STICK with This2
- A-to-Z2
- Because of Netflix2
- Only one way to do it2
- Better outcome2
- Good for hacking2
- Best friend for NLP1
- Sexy af1
- Procedural programming1
- Automation friendly1
- Slow1
- Keep it simple0
- Powerful0
- Ni0
- Still divided between python 2 and python 353
- Performance impact28
- Poor syntax for anonymous functions26
- GIL22
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow12
- Indentations matter a lot8
- Not everything is expression8
- Incredibly slow7
- Explicit self parameter in methods7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Fake object-oriented programming5
- Threading5
- The "lisp style" whitespaces5
- Official documentation is unclear.5
- Hard to obfuscate5
- Circular import5
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- The benevolent-dictator-for-life quit4
- Not suitable for autocomplete4
- Meta classes2
- Training wheels (forced indentation)1
related Python posts
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
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
Anaconda
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
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
- Smart auto-completion112
- Intelligent code analysis93
- Powerful refactoring77
- Virtualenv integration60
- Git integration54
- Support for Django22
- Multi-database integration11
- VIM integration7
- Vagrant integration4
- In-tool Bash and Python shell3
- Plugin architecture2
- Docker2
- Django Implemented1
- Debug mode support docker1
- Emacs keybinds1
- Perforce integration1
- Slow startup10
- Not very flexible7
- Resource hog6
- Periodic slow menu response3
- Pricey for full features1
related PyCharm posts
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?
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.
- Variable Explorer6
- More tools for Python2
- Free with anaconda2
- Intellisense1
- Slow to fire up1
related Spyder posts
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast898
- Light weight746
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness237
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Future Language of The Web12
- Setup is easy12
- Its everywhere12
- Because I love functions11
- JavaScript is the New PHP11
- Like it or not, JS is part of the web standard10
- Easy9
- Can be used in backend, frontend and DB9
- Expansive community9
- Everyone use it9
- Easy to hire developers8
- Most Popular Language in the World8
- For the good parts8
- Can be used both as frontend and backend as well8
- No need to use PHP8
- Powerful8
- Evolution of C7
- Its fun and fast7
- It's fun7
- Nice7
- Versitile7
- Hard not to use7
- Popularized Class-Less Architecture & Lambdas7
- Agile, packages simple to use7
- Supports lambdas and closures7
- Love-hate relationship7
- Photoshop has 3 JS runtimes built in7
- 1.6K Can be used on frontend/backend6
- Client side JS uses the visitors CPU to save Server Res6
- It let's me use Babel & Typescript6
- Easy to make something6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- Client processing5
- What to add5
- Everywhere5
- Scope manipulation5
- Function expressions are useful for callbacks5
- Stockholm Syndrome5
- Promise relationship5
- Clojurescript5
- Only Programming language on browser4
- Because it is so simple and lightweight4
- Easy to learn and test1
- Easy to understand1
- Not the best1
- Subskill #41
- Hard to learn1
- Test21
- Test1
- Easy to learn1
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
- HORRIBLE DOCUMENTS, faulty code, repo has bugs0
related JavaScript posts
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.
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
Node.js
- Npm1.4K
- Javascript1.3K
- Great libraries1.1K
- High-performance1K
- Open source805
- Great for apis486
- Asynchronous477
- Great community424
- Great for realtime apps390
- Great for command line utilities296
- Websockets85
- Node Modules83
- Uber Simple69
- Great modularity59
- Allows us to reuse code in the frontend58
- Easy to start42
- Great for Data Streaming35
- Realtime32
- Awesome28
- Non blocking IO25
- Can be used as a proxy18
- High performance, open source, scalable17
- Non-blocking and modular16
- Easy and Fun15
- Easy and powerful14
- Future of BackEnd13
- Same lang as AngularJS13
- Fullstack12
- Fast11
- Scalability10
- Cross platform10
- Simple9
- Mean Stack8
- Great for webapps7
- Easy concurrency7
- Typescript6
- Fast, simple code and async6
- React6
- Friendly6
- Control everything5
- Its amazingly fast and scalable5
- Easy to use and fast and goes well with JSONdb's5
- Scalable5
- Great speed5
- Fast development5
- It's fast4
- Easy to use4
- Isomorphic coolness4
- Great community3
- Not Python3
- Sooper easy for the Backend connectivity3
- TypeScript Support3
- Blazing fast3
- Performant and fast prototyping3
- Easy to learn3
- Easy3
- Scales, fast, simple, great community, npm, express3
- One language, end-to-end3
- Less boilerplate code3
- Npm i ape-updating2
- Event Driven2
- Lovely2
- Creat for apis1
- Node0
- Bound to a single CPU46
- New framework every day45
- Lots of terrible examples on the internet40
- Asynchronous programming is the worst33
- Callback24
- Javascript19
- Dependency hell11
- Dependency based on GitHub11
- Low computational power10
- Very very Slow7
- Can block whole server easily7
- Callback functions may not fire on expected sequence7
- Breaking updates4
- Unstable4
- Unneeded over complication3
- No standard approach3
- Bad transitive dependency management1
- Can't read server session1
related Node.js posts
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:
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
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.
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
Needs advice on code coverage tool in Node.js/ExpressJS with External API Testing Framework
Hello community,
I have a web application with the backend developed using Node.js and Express.js. The backend server is in one directory, and I have a separate API testing framework, made using SuperTest, Mocha, and Chai, in another directory. The testing framework pings the API, retrieves responses, and performs validations.
I'm currently looking for a code coverage tool that can accurately measure the code coverage of my backend code when triggered by the API testing framework. I've tried using Istanbul and NYC with instrumented code, but the results are not as expected.
Could you please recommend a reliable code coverage tool or suggest an approach to effectively measure the code coverage of my Node.js/Express.js backend code in this setup?
- New doctype447
- Local storage389
- Canvas334
- Semantic header and footer285
- Video element240
- Geolocation121
- Form autofocus106
- Email inputs100
- Editable content85
- Application caches79
- Easy to use10
- Cleaner Code9
- Easy5
- Websockets4
- Semantical4
- Better3
- Audio element3
- Modern3
- Portability2
- Semantic Header and Footer, Geolocation, New Doctype2
- Content focused2
- Compatible2
- Very easy to learning to HTML1
- Easy to forget the tags when you're a begginner1
- Long and winding code1
related HTML5 posts
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.
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?