What is IPython and what are its top alternatives?
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. ...
- Shell
A shell is a text-based terminal, used for manipulating programs and files. Shell scripts typically manage program execution. ...
- PowerShell
A command-line shell and scripting language built on .NET. Helps system administrators and power-users rapidly automate tasks that manage operating systems (Linux, macOS, and Windows) and processes. ...
- GNU Bash
The Bourne Again SHell is an sh-compatible shell that incorporates useful features from the Korn shell (ksh) and C shell (csh). It is intended to conform to the IEEE POSIX P1003.2/ISO 9945.2 Shell and Tools standard. ...
IPython alternatives & related posts
- In-line code execution using blocks18
- In-line graphing support10
- Can be themed7
- Multiple kernel support6
- Best web-browser IDE for Python3
- Export to python code3
- LaTex Support2
- HTML export capability1
- 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 code948
- Beautiful code835
- Rapid development780
- Large community682
- Open source426
- Elegant385
- Great community278
- Object oriented268
- Dynamic typing214
- Great standard library75
- Very fast56
- Functional programming51
- Scientific computing43
- Easy to learn43
- Great documentation33
- Matlab alternative26
- Productivity25
- Easy to read25
- Simple is better than complex21
- It's the way I think18
- Imperative17
- Free15
- Very programmer and non-programmer friendly15
- Powerful14
- Machine learning support14
- Powerfull language14
- Fast and simple13
- Scripting12
- Explicit is better than implicit9
- Clear and easy and powerfull8
- Ease of development8
- Unlimited power8
- Import antigravity7
- It's lean and fun to code6
- Print "life is short, use python"6
- Python has great libraries for data processing5
- Fast coding and good for competitions5
- There should be one-- and preferably only one --obvious5
- High Documented language5
- I love snakes5
- Although practicality beats purity5
- Flat is better than nested5
- Great for tooling5
- Readability counts4
- Rapid Prototyping4
- Web scraping3
- Plotting3
- Multiple Inheritence3
- Complex is better than complicated3
- Beautiful is better than ugly3
- Now is better than never3
- Lists, tuples, dictionaries3
- Socially engaged community3
- Great for analytics3
- CG industry needs3
- Generators2
- Simple and easy to learn2
- Import this2
- No cruft2
- Easy to learn and use2
- List comprehensions2
- Pip install everything2
- Special cases aren't special enough to break the rules2
- If the implementation is hard to explain, it's a bad id2
- If the implementation is easy to explain, it may be a g2
- Easy to setup and run smooth2
- Many types of collections2
- Flexible and easy1
- Powerful language for AI1
- Shitty1
- It is Very easy , simple and will you be love programmi1
- Batteries included1
- Can understand easily who are new to programming1
- Should START with this but not STICK with This1
- A-to-Z1
- Only one way to do it1
- Because of Netflix1
- Better outcome1
- Good for hacking1
- Powerful0
- Still divided between python 2 and python 351
- Performance impact28
- Poor syntax for anonymous functions26
- GIL21
- Package management is a mess19
- Too imperative-oriented14
- Hard to understand12
- Dynamic typing12
- Very slow11
- Not everything is expression8
- Indentations matter a lot7
- Explicit self parameter in methods7
- Incredibly slow7
- Requires C functions for dynamic modules6
- Poor DSL capabilities6
- No anonymous functions6
- Official documentation is unclear.5
- The "lisp style" whitespaces5
- Fake object-oriented programming5
- Hard to obfuscate5
- Threading5
- Circular import4
- The benevolent-dictator-for-life quit4
- Lack of Syntax Sugar leads to "the pyramid of doom"4
- 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
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
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
- Smart auto-completion109
- Intelligent code analysis91
- Powerful refactoring76
- Virtualenv integration58
- Git integration52
- Support for Django21
- Multi-database integration11
- VIM integration7
- Vagrant integration4
- In-tool Bash and Python shell3
- Plugin architecture2
- Docker2
- Debug mode support docker1
- Perforce integration1
- Emacs keybinds1
- Slow startup9
- Not very flexible6
- Resource hog5
- 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 Explorer5
- More tools for Python2
- Free with anaconda2
- Intellisense1
- Slow to fire up1
related Spyder posts
Shell
related Shell posts
related PowerShell posts
I currently work helpdesk and have been for about 6 years. I am looking to become more valuable, and I can't decide what route to take? Python is of interest, and so is PowerShell. What are some recommendations? Maybe something that would benefit a helpdesk position or even get into a network administrator.
Objective: I am trying to build a custom service that will create VMs in Azure, based on inputs taken from a web interface. I want the backend code that interacts with Azure to be PowerShell.
Ask: Hoping to find help with deciding the simplest architecture of tools to achieve this.
What I have so far with my Limited Knowledge: I am new to Azure and Jenkins. I arrived at Jenkins coz it can run PowerShell and has API that can be called to trigger a job. Although integrating with it over the web seems problematic since its on-prem network. I hear it is possible using the VPN. For the Web, I hope to use Azure Web App with Python/Node.js that I can manage to make API calls to Jenkins.
Is there a better way? I just need help getting the right directions; I will walk the way.
- Customizable3
- Powerful scripting language3
- Widely adopted2
- Cross platform0
- Too Slow1
related GNU Bash posts
Recently I've switched from GNU Bash to Oh My ZSH and I'm happy with the way I can customize the environment, picking between options by tab and seeing git status or hardware status while typing commands and a beautiful UI that's easy on eyes. Also ability to turn-off case-sensitivity comes in handy. I don't think if I will go back!
Out of curiosity, when my coding instructor for Python did some commands on his computer, he told me learning any sort of terminal command interface (e.g. GNU Bash, PowerShell, Zsh ) will make me understand systems and how computers work and would make me know the basics of systems programming (although I am more into web development). I immediately went curious, out of my time, and looked up some command line interfaces to learn. It gave me bash, shell, zsh, powershell, etc. All these are really confusing, and they all seem the same. I want to be a terminal dweller, so which of the terminal related things should I learn? I think Bash, since it can replace Powershell on Windows, and has all the Linux/macOS systems.