JSON vs Python

Overview

Python

Stacks262.8K

Followers205.4K

Votes6.9K

GitHub Stars69.7K

Forks33.3K

JSON

Stacks2.0K

Followers1.6K

Votes9

JSON vs Python: What are the differences?

JSON serves as a lightweight data interchange format, facilitating efficient data transmission between systems, while Python offers a rich ecosystem for data manipulation, analysis, and automation. Let's explore the key differences between them.

Syntax: In JSON, all strings must be enclosed in double quotes, whereas Python allows the use of both double and single quotes for defining strings. Additionally, JSON requires the use of colons to separate keys and values, while Python uses an equal sign for assignment in dictionaries.
Data Types: Another notable difference lies in the available data types. Python supports a wider range of data types such as lists, tuples, sets, and more, whereas JSON has a more limited set of data types, mainly consisting of strings, numbers, booleans, arrays, and objects. Python's broader range of data types allows for more versatile and complex data structures.
Functionality: JSON and Python also differ in terms of functionality. Python is a general-purpose programming language with a wide array of built-in functions and libraries to perform various tasks. On the other hand, JSON is primarily used for data interchange between systems and does not have built-in functions or support for programming logic.
Comments: Comments play an essential role in code documentation and explanations. While Python allows the inclusion of comments using the hash (#) symbol, JSON does not have a direct way of including comments within its syntax. JSON files are typically used for data representation rather than code documentation.
Encoding: JSON is designed to be a language-independent data format, allowing data to be easily transmitted and interpreted across different programming languages. In contrast, Python is a programming language itself, with its own syntax and grammar. Python code needs to be executed within a Python interpreter, while JSON can be parsed and interpreted by various programming languages.
Whitespace Handling: Python's syntax considers whitespace indentation to indicate block structure and scope. On the other hand, JSON does not handle whitespace in the same way. JSON does not interpret whitespace, and it does not affect the structure or meaning of the data. In Python, incorrect indentation can lead to syntax errors, while JSON is whitespace-agnostic.

In summary, JSON provides a simple and human-readable format for representing structured data, making it a preferred choice for APIs, configuration files, and data storage. Python, on the other hand, empowers developers with versatile libraries and frameworks for parsing, generating, and manipulating JSON data seamlessly.

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Advice on Python, JSON

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	JSON
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.	JavaScript Object Notation is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language.
Statistics
GitHub Stars 69.7K	GitHub Stars -
GitHub Forks 33.3K	GitHub Forks -
Stacks 262.8K	Stacks 2.0K
Followers 205.4K	Followers 1.6K
Votes 6.9K	Votes 9
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 5 Simple 4 Widely supported
Integrations
Django	MongoDB PostgreSQL MySQL JavaScript JSON Server JSONlite

What are some alternatives to Python, JSON?

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

JSON vs Python: What are the differences?

Syntax: In JSON, all strings must be enclosed in double quotes, whereas Python allows the use of both double and single quotes for defining strings. Additionally, JSON requires the use of colons to separate keys and values, while Python uses an equal sign for assignment in dictionaries.
Data Types: Another notable difference lies in the available data types. Python supports a wider range of data types such as lists, tuples, sets, and more, whereas JSON has a more limited set of data types, mainly consisting of strings, numbers, booleans, arrays, and objects. Python's broader range of data types allows for more versatile and complex data structures.
Functionality: JSON and Python also differ in terms of functionality. Python is a general-purpose programming language with a wide array of built-in functions and libraries to perform various tasks. On the other hand, JSON is primarily used for data interchange between systems and does not have built-in functions or support for programming logic.
Comments: Comments play an essential role in code documentation and explanations. While Python allows the inclusion of comments using the hash (#) symbol, JSON does not have a direct way of including comments within its syntax. JSON files are typically used for data representation rather than code documentation.
Encoding: JSON is designed to be a language-independent data format, allowing data to be easily transmitted and interpreted across different programming languages. In contrast, Python is a programming language itself, with its own syntax and grammar. Python code needs to be executed within a Python interpreter, while JSON can be parsed and interpreted by various programming languages.
Whitespace Handling: Python's syntax considers whitespace indentation to indicate block structure and scope. On the other hand, JSON does not handle whitespace in the same way. JSON does not interpret whitespace, and it does not affect the structure or meaning of the data. In Python, incorrect indentation can lead to syntax errors, while JSON is whitespace-agnostic.

JSON vs Python

Overview