Nativefier vs Python

Overview

Python

Stacks262.9K

Followers205.4K

Votes6.9K

GitHub Stars69.7K

Forks33.3K

Nativefier

Stacks29

Followers95

Votes2

Nativefier vs Python: What are the differences?

Installation: Nativefier is a command-line tool that allows you to easily create a desktop application version of any website using web technologies, and it requires installation and usage from the terminal/command prompt. On the other hand, Python is a programming language that can be used to create a variety of applications, including desktop applications using frameworks like PyQt or Tkinter. Python requires installation of Python and any necessary libraries, and the application needs to be written in Python code.
Platform Support: Nativefier is platform agnostic and can be used on Windows, macOS, and Linux. It leverages Electron to create cross-platform desktop applications. Python, on the other hand, is also cross-platform and supports Windows, macOS, and Linux. However, the specific desktop framework used may have some platform dependencies.
Ease of Use: Nativefier provides a simple command-line interface for creating desktop applications from websites. It provides a set of options, such as customizing the window title, specifying icons, and setting platform-specific behaviors. Python, on the other hand, requires writing code to create the desktop application. Although frameworks like PyQt and Tkinter simplify the process, it still requires more effort compared to using Nativefier.
Customization: Nativefier provides a limited set of customization options through command-line options. These options include specifying the name, icon, user agent, and other properties of the application. Python, on the other hand, allows for much more flexibility and customization through the use of different libraries and frameworks. The appearance, behavior, and features of a Python-based desktop application can be fully customized according to the developer's requirements.
Performance: Nativefier applications are essentially web applications running in an Electron shell, and they may have some performance overhead compared to native applications. Python applications, when properly optimized and using appropriate libraries, can achieve faster performance as they are compiled and executed natively.
Integration with Web Technologies: Nativefier allows integration with web technologies more easily since it creates a web view of the website. This means that the application can leverage JavaScript, HTML, CSS, and other web technologies seamlessly. Python, on the other hand, requires additional effort and libraries to integrate with web technologies. Although it is possible to use frameworks like Flask or Django to create web-based desktop applications, it may require more development effort compared to using Nativefier.

In Summary, Nativefier is a command-line tool for creating web-based desktop applications with limited customization options, while Python allows for more flexibility, customization, and integration with web technologies, albeit with more development effort.

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Advice on Python, Nativefier

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	Nativefier
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.	Nativefier is a command line tool that allows you to easily create a desktop application for any web site with succinct and minimal configuration. Apps are wrapped by Electron in an OS executable (.app, .exe, etc.) for use on Windows, OSX and Linux.
Statistics
GitHub Stars 69.7K	GitHub Stars -
GitHub Forks 33.3K	GitHub Forks -
Stacks 262.9K	Stacks 29
Followers 205.4K	Followers 95
Votes 6.9K	Votes 2
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 2 Has a better Javascript support, and is much faster
Integrations
Django	No integrations available

What are some alternatives to Python, Nativefier?

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

Nativefier vs Python: What are the differences?

Installation: Nativefier is a command-line tool that allows you to easily create a desktop application version of any website using web technologies, and it requires installation and usage from the terminal/command prompt. On the other hand, Python is a programming language that can be used to create a variety of applications, including desktop applications using frameworks like PyQt or Tkinter. Python requires installation of Python and any necessary libraries, and the application needs to be written in Python code.
Platform Support: Nativefier is platform agnostic and can be used on Windows, macOS, and Linux. It leverages Electron to create cross-platform desktop applications. Python, on the other hand, is also cross-platform and supports Windows, macOS, and Linux. However, the specific desktop framework used may have some platform dependencies.
Ease of Use: Nativefier provides a simple command-line interface for creating desktop applications from websites. It provides a set of options, such as customizing the window title, specifying icons, and setting platform-specific behaviors. Python, on the other hand, requires writing code to create the desktop application. Although frameworks like PyQt and Tkinter simplify the process, it still requires more effort compared to using Nativefier.
Customization: Nativefier provides a limited set of customization options through command-line options. These options include specifying the name, icon, user agent, and other properties of the application. Python, on the other hand, allows for much more flexibility and customization through the use of different libraries and frameworks. The appearance, behavior, and features of a Python-based desktop application can be fully customized according to the developer's requirements.
Performance: Nativefier applications are essentially web applications running in an Electron shell, and they may have some performance overhead compared to native applications. Python applications, when properly optimized and using appropriate libraries, can achieve faster performance as they are compiled and executed natively.
Integration with Web Technologies: Nativefier allows integration with web technologies more easily since it creates a web view of the website. This means that the application can leverage JavaScript, HTML, CSS, and other web technologies seamlessly. Python, on the other hand, requires additional effort and libraries to integrate with web technologies. Although it is possible to use frameworks like Flask or Django to create web-based desktop applications, it may require more development effort compared to using Nativefier.

Nativefier vs Python

Overview