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JSON vs Java: What are the differences?
Introduction
JSON (JavaScript Object Notation) and Java are two distinct technologies used in software development. While both JSON and Java are commonly used for storing and transmitting data, there are several key differences between them. In this article, we will explore these differences in detail.
Syntax: The syntax of JSON and Java differs significantly. JSON is a lightweight data-interchange format that uses a simple and concise syntax, primarily using key-value pairs. On the other hand, Java is a programming language with its own syntax, which includes a wider range of constructs such as classes, methods, and control flow statements.
Data Types: JSON supports a limited set of basic data types, including strings, numbers, booleans, null, arrays, and objects. It does not directly support more complex data types, such as dates or custom classes. In contrast, Java has a rich set of built-in data types and supports the creation of custom-defined data types using classes and interfaces.
Execution: JSON is a data interchange format and does not have an execution environment of its own. It is commonly used for data transmission between different programming languages. On the other hand, Java is a programming language that is compiled into bytecode and executed in a Java Virtual Machine (JVM). Java programs can be executed independently on any device with a JVM.
Functionality: JSON focuses on data representation and does not offer built-in functionality for operations such as complex calculations or database access. Java, being a programming language, provides extensive functionality through its standard libraries and frameworks, allowing developers to perform complex tasks such as mathematical calculations, file handling, networking, and database operations.
Error Handling: JSON does not have built-in mechanisms for error handling. It assumes well-formed input without any explicit error reporting or exception handling. While JSON parsers may provide error messages or throw exceptions in case of syntax errors, it is generally the responsibility of the consuming application to handle such errors. In Java, error handling is an integral part of the language, with a structured exception handling mechanism that allows developers to catch, handle, or propagate exceptions.
Extensibility: JSON by itself does not support extensibility. Modifications to the JSON structure require changing the key-value pairs directly. In contrast, Java is highly extensible through the use of classes, interfaces, and inheritance. Developers can create new classes or extend existing ones to add new functionality or modify behavior, making Java a powerful and flexible programming language.
In summary, JSON and Java differ in terms of syntax, data types, execution environment, functionality, error handling, and extensibility. While JSON primarily focuses on data representation and interchange, Java provides a comprehensive programming language with a wide range of features and functionalities.
Hi everyone.
I am willing to build a used car sales platform, which will have a lot of stock/photos and will rely a lot on the back end functions and data generating. Java seems to be a good choice, but what other options can I consider that can also be easily scalable as well as a little faster to write?
Thank you
Firstly, you must know that java and python are both amazing languages. But I recommend python mainly because of the variety of modules and packages available to do almost anything. If you are planning on adding graphs, you can use the matplotlib library and to add photos, use the pillow module. And just note that both of these aren't available by default, so you need to install them through pip.
Hi, Kamal! I don't know if your question is still relevant. But I would like to introduce you to our solution, perhaps it will be useful for future projects. We have developed a web application constructor that can be used to create almost any website or application https://falconspace.site/. The entire development stack is reduced to SQL only. The platform is easy to configure and make subsequent changes if necessary.
Hi. Currently, I have a requirement where I have to create a new JSON file based on the input CSV file, validate the generated JSON file, and upload the JSON file into the application (which runs in AWS) using API. Kindly suggest the best language that can meet the above requirement. I feel Python will be better, but I am not sure with the justification of why python. Can you provide your views on this?
Python is very flexible and definitely up the job (although, in reality, any language will be able to cope with this task!). Python has some good libraries built in, and also some third party libraries that will help here. 1. Convert CSV -> JSON 2. Validate against a schema 3. Deploy to AWS
- The builtins include json and csv libraries, and, depending on the complexity of the csv file, it is fairly simple to convert:
import csv
import json
with open("your_input.csv", "r") as f:
csv_as_dict = list(csv.DictReader(f))[0]
with open("your_output.json", "w") as f:
json.dump(csv_as_dict, f)
The validation part is handled nicely by this library: https://pypi.org/project/jsonschema/ It allows you to create a schema and check whether what you have created works for what you want to do. It is based on the json schema standard, allowing annotation and validation of any json
It as an AWS library to automate the upload - or in fact do pretty much anything with AWS - from within your codebase: https://aws.amazon.com/sdk-for-python/ This will handle authentication to AWS and uploading / deploying the file to wherever it needs to go.
A lot depends on the last two pieces, but the converting itself is really pretty neat.
I would use Go. Since CSV files are flat (no hierarchy), you could use the encoding/csv package to read each row, and write out the values as JSON. See https://medium.com/@ankurraina/reading-a-simple-csv-in-go-36d7a269cecd. You just have to figure out in advance what the key is for each row.
This should be pretty doable in any language. Go with whatever you're most familiar with.
That being said, there's a case to be made for using Node.js since it's trivial to convert an object to JSON and vice versa.
I am trying to make Roblox game which requires Lua. I quite don't want to go with Lua just because other tools just might let me do more projects later on. I heard that Python is most similar to Lua, but I am still not sure which tool to use. Java, I think it will help me with many stuff later on for websites, projects, and more!
Since you are trying to make a Roblox game, you have no other option than to use Lua, since Roblox only allows coding in Lua. Yes, you've heard right, Python is identical and as easy as Lua, although Lua is easier than Python. Beginning from Lua and then escalating to Python is recommended. Java is only helpful when you are creating a heavy, big-budget, enterprise-level product, otherwise, Python would suffice.
If you really hate lua check out roblox-ts, a tool that compiles typescript code into roblox lua. https://github.com/roblox-ts/roblox-ts
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
Go with Python definetly. It's used everywhere by web developers for backend developments : API, website backend, workers... but also by data scientists (lot lot of resources, models and libraries in Python it's language #1). For the web parts, best web framework are in Python : https://stackshare.io/microframeworks (Flask #2 and Django #3). Java is good but trend is not great in terms of popularity amongs developers and tech leaders.
As per my experience java is most wanted for web development as of now. micro service is evolving . with frameworks like spring boot supports rapid development. Spring boot + Docker + kubernetes great combination.
I would recommend learning HTML, CSS, and JavaScript (most important). JavaScript forms the backbone of web development. And, there are many popular and widely used frameworks like Angular and React that heavily rely on the knowledge of JavaScript. The number of job opportunities are much more when it comes to javascript.
I would recommend Python as the programming language and as you are a new developer, Flask to start with. It gives you a solid understanding on the web patterns such as REST and will get you up and running in no time. However, I suggest you to read and study on front-end technologies like (React or Vue) and databases (SQL and NoSQL) and probably some NodeJS as well. First grasp the concepts (which Python is ideal for) then it does not really matter the language as such.
1 code deploys for both: Android and iOS. There is a huge community behind React Native. And one of the best things is Expo. Expo uses React Native to make everything even more and more simple. Awesome technologies. Some other important thing is that while using React Native, you are reusing all JavaScript knowledge you have in your team. You can move easily a frontend dev to develop mobile applications.
A huge PRO of Expo, is that it includes a full building process. You run 1 line in the terminal, and 10 minutes after you have 2 builds done. Double check EAS Expo.
C# and .Net were obvious choices for us at LiveTiles given our investment in the Microsoft ecosystem. It enabled us to harness of the .Net framework to build ASP.Net MVC, WebAPI, and Serverless applications very easily. Coupled with the high productivity of Visual Studio, it's the native tongue of Microsoft technology.
Node.js has been growing in popularity, and the ability to access the global pool of Javascript developers is great. There is a decreased amount of effort for people to work across the frontend and backend, and the language itself is easy and works well for many common use cases.
Go was the other serious candidate, but it just hasn't been implemented in as many Production systems yet, and the best Go engineers I've known have been hackers, whereas we're building a robust analytics platform that requires more caution. Type safety is easily added with TypeScript, and NPM is awesomely handy.
When developing a new blockchain, we as a team chose Go lang over Java and other candidates, due to Go being (a) natively suited to concurrency - there are primitives in the language itself (goroutines, channels) that really help with reasoning about concurrency (b) super fast - build time, running, testing are all much faster that Java, this gives a far superior developer experience (c) shorter and stricter than Java - code is much shorter (less verbose), and there is usually one good way to do things, and even the code formatter that is bundled with Go is very opinionated - over a short time this makes reading other people's code far smoother than having to deal with different styles.
You should be aware that Go presently (v1.13) lacks Generics.
From cross platform development point of view: Using kotlin multiplatform is more convenient than java for implementing cross platform code, since it can be converted to be used in iOS (swift) projects, and it can be easily learned if you already know swift. It still an experimental feature but it helped so far to unify a lot of the common code between our iOS and Android projects. And it is more future proof than java regarding support and maintain multiplatform converting.
We needed to incorporate Big Data Framework for data stream analysis, specifically Apache Spark / Apache Storm. The three options of languages were most suitable for the job - Python, Java, Scala.
The winner was Python for the top of the class, high-performance data analysis libraries (NumPy, Pandas) written in C, quick learning curve, quick prototyping allowance, and a great connection with other future tools for machine learning as Tensorflow.
The whole code was shorter & more readable which made it easier to develop and maintain.
The decision behind choosing a server side technology is never an easy one. Every single language has it's pro's and con's around each.
For me, this decision came down to a couple simple points: 1. Node is a web tech first class citizen, designed around handling web events, in a web technology world 2. Asynchronous
The thing about Python and Java is that they TOO can handle these, and handle these very well. Java for instance powers most of Twitter and Netflix's architecture. Where Python is what's behind giants like Instagram and Patreon. Certainly, you can't go wrong. Heck, Ruby powered GitHub and GitLab, and those things see HUGE traffic.
But this project is a web technology first. And node feels right at home as it itself is a web technology. This decision was more about homogeneous synergy than most anything else. I need it to be screaming fast, asynchronous, and play extremely well with web standards.
Node fits the bill on every front.
I work at Stream and I'm immensely proud of what our team is working on here at the company. Most recently, we announced our Android SDK accompanied by an extensive tutorial for Java and Kotlin. The tutorial covers just about everything you need to know when it comes to using our Android SDK for Stream Chat. The Android SDK touches many features offered by Stream Chat – more specifically, typing status, read state, file uploads, threads, reactions, editing messages, and commands. Head over to https://getstream.io/tutorials/android-chat/ and give it a whirl!
Pros of Java
- Great libraries599
- Widely used445
- Excellent tooling400
- Huge amount of documentation available395
- Large pool of developers available334
- Open source208
- Excellent performance202
- Great development157
- Used for android150
- Vast array of 3rd party libraries148
- Compiled Language60
- Used for Web52
- High Performance46
- Managed memory46
- Native threads44
- Statically typed43
- Easy to read35
- Great Community33
- Reliable platform29
- Sturdy garbage collection24
- JVM compatibility24
- Cross Platform Enterprise Integration22
- Universal platform20
- Good amount of APIs20
- Great Support18
- Great ecosystem14
- Backward compatible11
- Lots of boilerplate11
- Everywhere10
- Excellent SDK - JDK9
- It's Java7
- Cross-platform7
- Static typing7
- Mature language thus stable systems6
- Better than Ruby6
- Long term language6
- Portability6
- Clojure5
- Vast Collections Library5
- Used for Android development5
- Most developers favorite4
- Old tech4
- History3
- Great Structure3
- Stable platform, which many new languages depend on3
- Javadoc3
- Testable3
- Best martial for design3
- Type Safe2
- Faster than python2
- Job0
Pros of JSON
- Simple5
- Widely supported4
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Cons of Java
- Verbosity33
- NullpointerException27
- Nightmare to Write17
- Overcomplexity is praised in community culture16
- Boiler plate code12
- Classpath hell prior to Java 98
- No REPL6
- No property4
- Code are too long3
- Non-intuitive generic implementation2
- There is not optional parameter2
- Floating-point errors2
- Java's too statically, stronglly, and strictly typed1
- Returning Wildcard Types1
- Terrbible compared to Python/Batch Perormence1
Cons of JSON
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