Processing vs Python

Overview

Python

Stacks262.9K

Followers205.4K

Votes6.9K

GitHub Stars69.7K

Forks33.3K

Processing

Stacks193

Followers103

Votes0

GitHub Stars2.9K

Forks806

Processing vs Python: What are the differences?

Introduction: Processing and Python are two programming languages commonly used in the field of creative coding and computer graphics. While both languages are versatile and popular among artists, designers, and hobbyists, there are some key differences between them that can influence the choice of language for specific applications.

Syntax: The syntax of Processing and Python differs significantly. Processing uses a simplified Java-like syntax that is specifically designed for artistic and visual applications. On the other hand, Python has a more general-purpose syntax that is widely used in various domains, including web development, data analysis, and machine learning.
Community and Resources: Python has a larger and more diverse community compared to Processing. Being one of the most popular programming languages, Python has a vast ecosystem of libraries, frameworks, and resources that cater to different needs. However, Processing also has an active community with its own set of libraries and resources tailored specifically for creative coding and visualization.
Integration with External Libraries: Python has seamless integration with external libraries and frameworks, making it possible to harness the power of tools like NumPy, SciPy, and TensorFlow for mathematical computations and machine learning tasks. Processing, on the other hand, has a limited number of libraries and extensions that are specifically developed for visual and artistic applications.
Learning Curve: Processing has been designed with simplicity and ease of use in mind, making it relatively easier to learn for beginners. With its intuitive and visual programming approach, Processing allows novices to quickly create visual effects and interactive animations. Python, while being beginner-friendly as well, has a steeper learning curve due to its wider scope and more complex syntax.
Language Purpose: Processing is primarily designed for visual arts and creative coding projects. Its focus is on providing intuitive tools and libraries that enable artists and designers to create interactive visuals and animations. Python, on the other hand, is a general-purpose language that can be used in a wide range of applications, from web development and data analysis to scientific computing and artificial intelligence.
Performance: Python, being an interpreted language, can be slower compared to Processing, which is compiled into Java bytecode. As a result, complex visual processing tasks and real-time simulations might perform better in Processing, especially when dealing with large data sets or high-performance graphics.

In summary, Processing offers a simplified syntax, a focused community, and an intuitive design ideal for visual arts and creative coding projects. Python, on the other hand, provides a broader scope, a larger community, and seamless integration with external libraries, making it suitable for a wide range of applications beyond visual arts.

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Advice on Python, Processing

Thomas

Talent Co-Ordinator at Tessian

Mar 11, 2020

Decided

In December we successfully flipped around half a billion monthly API requests from our Ruby on Rails application to some new Python 3 applications. Our Head of Engineering has written a great article as to why we decided to transition from Ruby on Rails to Python 3! Read more about it in the link below.

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Comments

Avy

Apr 8, 2020

Needs adviceon

React Native

Python

Flutter

I've been juggling with an app idea and am clueless about how to build it.

A little about the app:

Social network type app ,
Users can create different directories, in those directories post images and/or text that'll be shared on a public dashboard .

Directory creation is the main point of this app. Besides there'll be rooms(groups),chatting system, search operations similar to instagram,push notifications

I have two options:

@{React Native}|tool:2699|, @{Python}|tool:993|, AWS stack or
@{Flutter}|tool:7180|, @{Go}|tool:1005| ( I don't know what stack or tools to use)

722k views722k

Comments

Davit

Apr 11, 2020

Needs advice

Hi everyone, I have just started to study web development, so I'm very new in this field. I would like to ask you which tools are most updated and good to use for getting a job in medium-big company. Front-end is basically not changing by time so much (as I understood by researching some info), so my question is about back-end tools. Which backend tools are most updated and requested by medium-big companies (I am searching for immediate job possibly)?

Thank you in advance Davit

390k views390k

Comments

Detailed Comparison

Python	Processing
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.	It is an open programming language for people who want to program images, animation, and interactions for the web without using Flash or Java applets.
-	Free to download and open source; Interactive programs with 2D, 3D or PDF output; OpenGL integration for accelerated 2D and 3D; For GNU/Linux, Mac OS X, Windows, Android, and ARM; Over 100 libraries extend the core software; Well documented, with many books available
Statistics
GitHub Stars 69.7K	GitHub Stars 2.9K
GitHub Forks 33.3K	GitHub Forks 806
Stacks 262.9K	Stacks 193
Followers 205.4K	Followers 103
Votes 6.9K	Votes 0
Pros & Cons
Pros 1186 Great libraries 966 Readable code 848 Beautiful code 789 Rapid development 692 Large community Cons 53 Still divided between python 2 and python 3 28 Performance impact 26 Poor syntax for anonymous functions 22 GIL 20 Package management is a mess	No community feedback yet
Integrations
Django	C++ Visual Basic Java JavaScript

What are some alternatives to Python, Processing?

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.

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

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.

C#

C# (pronounced "See Sharp") is a simple, modern, object-oriented, and type-safe programming language. C# has its roots in the C family of languages and will be immediately familiar to C, C++, Java, and JavaScript programmers.

Scala

Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.

Elixir

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

Swift

Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.

Related Comparisons

Processing vs Python: What are the differences?

Syntax: The syntax of Processing and Python differs significantly. Processing uses a simplified Java-like syntax that is specifically designed for artistic and visual applications. On the other hand, Python has a more general-purpose syntax that is widely used in various domains, including web development, data analysis, and machine learning.
Community and Resources: Python has a larger and more diverse community compared to Processing. Being one of the most popular programming languages, Python has a vast ecosystem of libraries, frameworks, and resources that cater to different needs. However, Processing also has an active community with its own set of libraries and resources tailored specifically for creative coding and visualization.
Integration with External Libraries: Python has seamless integration with external libraries and frameworks, making it possible to harness the power of tools like NumPy, SciPy, and TensorFlow for mathematical computations and machine learning tasks. Processing, on the other hand, has a limited number of libraries and extensions that are specifically developed for visual and artistic applications.
Learning Curve: Processing has been designed with simplicity and ease of use in mind, making it relatively easier to learn for beginners. With its intuitive and visual programming approach, Processing allows novices to quickly create visual effects and interactive animations. Python, while being beginner-friendly as well, has a steeper learning curve due to its wider scope and more complex syntax.
Language Purpose: Processing is primarily designed for visual arts and creative coding projects. Its focus is on providing intuitive tools and libraries that enable artists and designers to create interactive visuals and animations. Python, on the other hand, is a general-purpose language that can be used in a wide range of applications, from web development and data analysis to scientific computing and artificial intelligence.
Performance: Python, being an interpreted language, can be slower compared to Processing, which is compiled into Java bytecode. As a result, complex visual processing tasks and real-time simulations might perform better in Processing, especially when dealing with large data sets or high-performance graphics.

Processing vs Python

Overview