D vs Python

Overview

Python

Stacks262.9K

Followers205.4K

Votes6.9K

GitHub Stars69.7K

Forks33.3K

Stacks777

Followers136

Votes160

D vs Python: What are the differences?

<Write Introduction here>

Syntax: One of the key differences between D and Python is their syntax. D uses a C-like syntax that is more similar to languages such as C++ and Java, making it easier for developers coming from these backgrounds to adapt to D. On the other hand, Python has a more concise and readable syntax that is known for its simplicity and ease of use.
Performance: Another significant difference is in terms of performance. D is known for its high performance as it is a statically-compiled language that allows for better optimization during compilation. Python, on the other hand, is an interpreted language which can result in slower execution speeds compared to D, especially in performance-critical applications.
Memory Management: D provides support for manual memory management through pointers, allowing for more control over memory allocation and deallocation. In contrast, Python uses automatic memory management through garbage collection, which simplifies memory handling but may not be as efficient or flexible as manual management in D.
Type System: D is a statically-typed language, meaning that variable types are checked at compile time, helping to catch errors early in the development process. Python, on the other hand, is a dynamically-typed language where variable types are determined at runtime, providing more flexibility but potentially leading to runtime errors if types are not handled correctly.
Concurrency Support: D comes with built-in support for concurrency through features such as fibers and message passing, making it easier to work on parallel tasks. Python, on the other hand, has a Global Interpreter Lock (GIL) that can limit the ability to effectively utilize multiple CPU cores for concurrency, although Python has libraries like asyncio and threading to handle concurrency.
Community and Ecosystem: Python has a larger and more diverse community with a vast ecosystem of libraries and frameworks, making it easier to find solutions to various problems. D, while growing, has a smaller community and ecosystem, which may limit the availability of resources and support for developers working in D.

In Summary, D and Python differ in syntax, performance, memory management, type system, concurrency support, and community/ecosystem size.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Python, D

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.

263k views263k

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	D
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.	D is a language with C-like syntax and static typing. It pragmatically combines efficiency, control, and modeling power, with safety and programmer productivity.
Statistics
GitHub Stars 69.7K	GitHub Stars -
GitHub Forks 33.3K	GitHub Forks -
Stacks 262.9K	Stacks 777
Followers 205.4K	Followers 136
Votes 6.9K	Votes 160
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	Pros 16 Compile-time function execution 12 Much easier to do Concurrent/Parallel vs C/C++ 12 Productive 12 Makes functional programming style easier 11 Simple but Powerful template-based generics
Integrations
Django	No integrations available

What are some alternatives to Python, D?

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

D vs Python: What are the differences?

<Write Introduction here>

Syntax: One of the key differences between D and Python is their syntax. D uses a C-like syntax that is more similar to languages such as C++ and Java, making it easier for developers coming from these backgrounds to adapt to D. On the other hand, Python has a more concise and readable syntax that is known for its simplicity and ease of use.
Performance: Another significant difference is in terms of performance. D is known for its high performance as it is a statically-compiled language that allows for better optimization during compilation. Python, on the other hand, is an interpreted language which can result in slower execution speeds compared to D, especially in performance-critical applications.
Memory Management: D provides support for manual memory management through pointers, allowing for more control over memory allocation and deallocation. In contrast, Python uses automatic memory management through garbage collection, which simplifies memory handling but may not be as efficient or flexible as manual management in D.
Type System: D is a statically-typed language, meaning that variable types are checked at compile time, helping to catch errors early in the development process. Python, on the other hand, is a dynamically-typed language where variable types are determined at runtime, providing more flexibility but potentially leading to runtime errors if types are not handled correctly.
Concurrency Support: D comes with built-in support for concurrency through features such as fibers and message passing, making it easier to work on parallel tasks. Python, on the other hand, has a Global Interpreter Lock (GIL) that can limit the ability to effectively utilize multiple CPU cores for concurrency, although Python has libraries like asyncio and threading to handle concurrency.
Community and Ecosystem: Python has a larger and more diverse community with a vast ecosystem of libraries and frameworks, making it easier to find solutions to various problems. D, while growing, has a smaller community and ecosystem, which may limit the availability of resources and support for developers working in D.

In Summary, D and Python differ in syntax, performance, memory management, type system, concurrency support, and community/ecosystem size.

D vs Python

Overview