Java v/s Python: Key differences

Programming is the pinnacle of technology, and every company invests in software solutions. There has been no better time to become a developer, but which programming language to choose? Java and Python are popular programming languages with a wide range of applications. While Java is the faster language between the two, it can be challenging to learn for a beginner. Python’s simple learning advantage is shadowed by its slow performance.

Each programming language is well-established, platform-independent, and has a large supportive community. However, the similarities end here, and each language has its different use. This article covers the Python versus Java differences in detail. Let’s take a closer look at each language’s pros, cons, and scope.

Java: Introduction

Java has been around since 1995 and is one of the most popular programming languages for enterprise software development. As a general-purpose, object-oriented programming language, Java is compiled, unlike Python, which is why it’s faster.

Java code gets directly converted into machine code without needing a compiler, making it quick and efficient. It also gives better control over hardware aspects like CPU usage. For years, Java has been widely used for big data, web development, and android app development, but now it is also gaining traction in the cloud and the Internet of Things development. NASA, Google, and Facebook are some companies that build their products using Java.

Python: Introduction 

Guido van Rossum created Python in 1991. His focus was on creating a more readable programming language. This simplicity of learning is one of the driving forces behind the popularity of Python. Due to its more concise syntax, it is easier to code and test programs in Python than in Java. It supports a variety of programming styles giving developers the freedom to follow their own choice. This is why Python is suitable not only for object-oriented programming but also for reflective and functional programming.

Python is highly popular among backend and app developers and is the preferred choice for data science and machine learning applications. The availability of extensive libraries like Scikit-learn and Pandas is why it is used in some of the most significant applications such as Google Search and YouTube.

Key Differences between Java and Python 

1. Speed

Speed and efficiency are the two biggest reasons to use Java for application development. As many of the processes of Java run automatically, you don’t have to micromanage how everything works. It is a high-level language and uses automatic memory allocation.

Because of its dynamically typed and interpreted nature, Python executes the code line by line, making it slow. The extra work this programming language does when running code makes it less suitable for applications requiring speed and performance.

2. Versatility 

It is challenging to match Python’s versatility for Java. Java indeed finds more adoption for enterprise application development, but Python offers so much flexibility that it encourages open experimentation. Programmers love Python because it allows them the freedom to build more versatile applications. Python is the most suitable language for you if you want to do many things without worrying about speed. According to Computer Weekly, “Although there might be a better solution for any given problem, Python will always get the job done well.”

3. Syntax

Java is a strictly typed language. Developers have to explicitly declare variable types, which is not easy for beginners. The statically typed nature of Java makes it difficult to learn. Here is an example of Java code syntax:

public class Fruit {

 String name;

 String color;

 public Fruit(String name, String color){

 this.color=color;

 this.name=name;

 }

 public void myfunction()

 {

 System.out.println(“Hello I’m a :” +name);

 }

 public void mycolor()

 {

 System.out.println(“Hello my color is:” + color);

 }

On the other hand, Python is a dynamically typed language that does not require explicitly declaring variables. The variables are interpreted at the run time. This freedom makes Python syntax more like the English language. Here is the example of Python syntax for the same class we defined above in Java:

class Fruit:

 def_init_(mysillyobject, name, color);

 mysillyobject.name=name

 mysillyobject.color=color

 def myfunction(abc) :

 print(“hello I’m a “+ abc.name)

 def mycolor(abc) :

 print(“hello my Color is ” + abc.color)

p1 = Fruit (“Apple”, “red”)

p1.myfunction()

Conclusion 

Java and Python are capable and popular programming languages. Whichever programming language you choose, there are enough tools and community support available to help you along your journey.

As a beginner, your focus should be on learning and building things as soon as possible. For this, Python is the most suitable programming language because of its easy-to-follow syntax and availability of extensive libraries. However, if your end goal is to build enterprise-level applications, Java offers scalability, security, and speed.

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5 simple tricks to improve your logic in coding

Programming has several elements. It’s not just syntax to instruct processors to act on, but smartly put together logic that achieves the most complex operations. Developers are in a niche where continuous learning is the only way to remain relevant. Keeping getting better at logical coding, that is, developing logic, is an essential requirement.

Learning programming languages gives you the skills to write code with correct syntax, but the core functionality is based on data structures, algorithms, and different programming paradigms. Logic building is another requisite to be able to solve problems efficiently.

In this article, we explore ways to improve your logic in coding.

1. Master the concepts for better programming 

When you are given a problem to solve programmatically, you have to understand the context of the solution by breaking it down to the basic building blocks. The secret to writing logic for any problem is having in-depth knowledge of algorithms and working on sample problems as much as possible. Coding practice will expose you to challenges that will help you write better logic. 

All the theoretical knowledge you gain from reading articles, blogs, tutorials, and other essential developer toolkits will build your concepts. Applying concepts can quickly solve challenges you will face in your professional career. Practice the concept you learn. That’s how you improve your logical programming.

2. Get solutions evaluated by other developers

Programming assignments can involve challenges that other developers might have dealt with. Check for solutions available online. It is not to copy and paste the code but to learn how to handle programming challenges. This is especially true in understanding the logic behind the solutions because developers sharing their solutions in communities and forums explain why a certain logic is used and how it was built.

Your focus must be on the “why” because if you want to improve your logical programming, you need to know how a program’s logic functions and affects the outcome. Several resources to learn are available on GitHub. You can participate in open-source projects to learn from them as well.

A mistake most learners commit is to keep wasting their time on a problem. There’s no harm in learning from available solutions. Learning how others build logic to solve a problem will allow you to re-enact the process if required.

3. Pen and paper approach

One way to become stronger in logical coding is to practice on paper. If you start coding on the IDE directly, your attention will be divided between syntax, formatting, and logic. However, when you write the pseudo code or algorithm on paper, you focus only on getting the logic right. The pen and paper approach is what made Google the mammoth of search engines. It’s an inspiring story of two of the best Google engineers, Jeff Dean and Sanjay Ghemawat, who changed the company’s course for the better. The legend is that the two engineers maintain a text in which they solve the biggest challenges of writing logic on paper. If the approach is good enough for them, it’s suitable for any other developer.

4. Follow step-by-step approach

Like every other skill, you must take things step-by-step to improve your logical coding ability. Gradually moving up the challenge is how you will improve logic in your programs. Start from basic and then move on to advanced problems. For instance, you can practice in a set of 10 problems – 5 easy ones, 3 medium levels, and 2 hard questions.

It would help if you did not give up when faced with such challenges or lose confidence in your skills. Complex programming challenges will keep arising; your focus must be on learning. If you plan to get good at logical coding, you must face complex problems with optimism. Refer to the solutions in books and other resources if you get stuck. Keep in mind that developers are occupationally required to solve challenging problems strategically step-by-step, which is why they are some of the highest-paid professionals.

5. Keep learning new things

As a software developer, you will be expected to solve myriad challenges throughout your career. This is why you must keep learning new things as your career progresses. Taking the same solution path to solving problems repeatedly will limit your creativity and intuition.

Programmers can only expand their logic-building skills by tackling new challenges and topics. Delve into unknown territories and explore new ways to solve problems. Don’t be too rigid in your learning. Accept that there is no set way to build logic to solve a problem. There can be multiple approaches to solving a problem. You must keep trying new issues and algorithms to improve your logic-building skills.

Conclusion 

Be consistent at implementing these simple tricks, and you will gradually improve your logical coding skills. Patience and continuous learning must be your virtue when enhancing your programming skills.

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Top 6 web design tools for developers in 2022

Web design tools do more than just format the text and images within a web page. Modern web development transforms concepts into live, revenue-driven websites and applications. It requires action that goes beyond raw editing and HTML syntax. Modern web design tools are compelling software applications that can transform any idea into reality within the web space.

The decision can be mind-boggling when cornered to choosing between all the available web design tools. To help you with the choice, we have compiled a list of the top six web design tools for developers in 2022.

Let’s get started.

1. Sketch

Sketch is only for macOS designers as it does not support other operating systems. Still, it is one of the most popular web design tools among designers because it includes many features without being complicated to use. As a native macOS app, it looks like Apple’s Xcode IDE that iOS developers and designers use.

Besides the essential functions like constraint resizing and vector editing, Sketch offers many more tools to generate designs based on concepts and export them directly into a development project. For example, designers can use its Smart Layout functionality to create designs with adaptive resizing characteristics by default. It also offers options for teams through its collaborative tools.

2. Figma

If you are part of a large design team, then Figma is your best web design tool. Its increasing popularity is because of its capability to let designers collaborate on a design.

Figma is one of the most comprehensive web design tools available as a drag-and-drop editor to build anything from interfaces to website designs. Developers can directly include code snippets in the design with this tool. From ideation to implementation, it is the tool you can use to keep the design process running smoothly while keeping track of all the revisions made along the way. 

You get a homogenized set of tools for font and color designing that you can use to create interfaces that stand out.

While Figma offers value for single-developer projects, it’s much more beneficial for teams or projects that scale with time.

3. Affinity Designer

Adobe might be the industry leader in the web designing sector, but Serif’s Affinity Designer gives Adobe a run for its money.  

Affinity Designer has built a vast user base because of his stellar design principles and attractive pricing model. This web design tool is available for Macs, Windows, and iPad. It offers all features you get with Adobe Illustrator or any other web design tool for a fraction of money. You can work with vectors, rasterization, create layers, and more. While Affinity Designer offers designers all the editing and conceptualization features expected from a quality web design tool, it lacks cloud-based infrastructure. As such, you have no option to store your work or share it with other designers and all stakeholders through the cloud.

4. Google Web Designer

One of the most underrated web design tools is Google Web Designer. It is a free webpage design tool that developers can use to create interactive and engaging websites. You can create HTML5-based interactive web designs using this tool. The designs and motion graphics created using Google Web Designer are compatible with any device and run seamlessly on desktops, laptops, and smartphones. Developers can simultaneously edit HTML, CSS, and JavaScript directly from the editing screen. It gives you the freedom from the requirement to open each file individually.

5. InVision Studio

InVision Studio markets itself as a “screen design” app, and its functionalities and capabilities justify its campaign. It is a web design tool that offers an intuitive layer-based editor for all web design needs. You can do much more than web design, prototyping, and creating animations with InVision Studio. For instance, you can link artboards with screens together with a single click. This is an excellent feature for building animations as part of the design process.

Another great feature of this web design tool is its shared component libraries and global syncing options. These two features allow the entire team to work on a project within InVision Studio.

6. CodePen or JSFiddle 

For web designers, one crucial requirement is to be able to write and test the code snippet quickly without impacting the workflow of the entire project. This approach accelerates the design process.

CodePen and JSFiddle are two excellent text editors that work for testing HTML, CSS, and JavaScript. Before implementing it into your main project, you can test the code snippet and see how it affects your design in a live environment. You can also create a shareable link to the code snippets you are trying for other designers and developers to work on. Both these text editors are included in our list of top web design tools in 2022 because of the online IDE environment they offer to facilitate the design process.

Conclusion

For web design projects, like any other development project, time and resources are of importance. Familiarizing yourself with multiple web design tools allows you to select the best tool according to the project’s requirements without wasting too much time on research.

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REST & APIs: why you should be interested

We will explain Representational State Transfer (REST) principles to learn and what benefits you can get from learning.

Before 2000, Application Program Interface (or API as commonly known), was designed to be secure which was also very complex to develop and harder to maintain. A group of researchers, led by Roy Fielding, came up with the idea of REST (Representational State Transfer) which brought out the true power and potential of APIs in 2000. The purpose was to create communication between two servers that are located worldwide. They came up with principles, constraints and properties that constituted a resource-oriented architecture, client-server-based architecture, and interface uniformity which required no state preservation.

These were easily implemented using Hypertext Transfer Protocol (HTTP). It became a game-changer for the API landscape. The APIs developed under REST use less bandwidth. It is simple to develop and since the communication is supported via the internet, it is not required for the servers to be connected physically.

What is REST?

Rest stands for Representational State Transfer which is an architectural style that has gained popularity in recent years because of its simplicity and scalability. SOAP (Simple Object Access Protocol) was the de-facto way of accessing resources and communicating over the web before REST gained popularity.

RESTful APIs have also given various trends like cloud computing and microservices-based architecture. They have made communication and computing easy. Many companies prefer developers with REST knowledge as they help them develop products that are scalable, easy to maintain and make their products reach out to the world because of the power of the internet.

REST Resource

Every content in the REST architecture is considered as a resource. The resource is parallel to the object in the object-oriented programming world. They can be represented as text files, HTML pages, images or any other dynamic data. Every resource is identified globally using a URI.

What is URI?

URI is a short form of Uniform Resource Identifier used for identifying every resource of the REST architecture. Format of URI is:

<protocol>://<service-name>/<ResourceType>/<ResourceID>

There are two types of URI:

URN: Uniform Resource Name identifies the resource using a name that is unique and constant.

These follow the urn scheme and are usually prefixed with urn:

Examples:

 urn:isbn:1234567890 is used for the identification of books based on the ISBN.

 urn:mpeg:mpeg7:schema:2001 is the default namespace rule for metadata of MPEG-7 video.

It can easily be translated into a URL by using “resolver”once a URN identifies a document after which the document can be downloaded.


URL:
Uniform Resource Locator contains the information about fetching of a resource from its location.

Examples:

 http://abc.com/samplePage.html
ftp://sampleServer.com/sampleFile.zip
file:///home/interviewbit/sampleFile.txt

URLs start with a protocol like FTP, HTTP, etc and they have the information of the network hostname (sampleServer.com) and the path to the document(/samplepage.html).

Why should you care about REST?

In this section, we will discuss why REST principles are important and why it’s worth learning more about them.

  1. Easy to understand and implement

       2. Makes your application more scalable

There are multiple reasons behind REST which help make an application more scalable:

  • Stateless on the server side
  •  Faster data interchange format
  •  Caching is easier
  • Easy to modify
  • A layered system that organizes each type of server
  • Code on demand

Conclusion

In this article, we have tried to express why we value REST and why we believe you should value it as well. We hope that after reading this, the reasons to get interested in REST standards are now more clear to you and can serve as a motivation to learn more about the topic.

4 reasons why Python’s popularity is still soaring

Python is one of the fastest-growing programming languages that continue to soar in popularity. According to Tiobe, a software quality assurance company that indexes the popularity of programming languages every month, the popularity of Python is at an all-time high. 

The programming language yet again topped in its August 2022 rankings. When so many new technologies are emerging every day in the software development industry, one might wonder why the popularity of Python is still soaring.

According to the Tiobe index report, Python seems unstoppable because it’s hard to find a field of programming in which the programming language is not used extensively nowadays. From web development to data science, it has applications in every domain.

First developed by Guido van Rossum in the 1980s, Python started seeing a significant uptick in its adoption when Python 2.0 was released in 2000. It had many important new features such as cycle-detecting garbage collector, memory management, and support for Unicode. The most recent Python 3.0 was released as a backward-incompatible update in 2008. The release corrected some fundamental design flaws in the language and made it much more robust and fit for modern software development.

In this post, we look closely at why Python continues to grow in popularity.

1. Simplicity

One distinctive feature of Python from other programming languages is its simplicity. The ease of learning, understanding, and use make it easy to adopt. People with little or no software development experience can use Python to build applications. It is one of the most studied programming languages in the world, as we discovered by JetBrains’ State of Developer Ecosystem research. The simplicity of adoption is a major driving force behind the increasing popularity of Python. Universities, online schools, and companies are using Python as the first programming language to teach the fundamental coding principles to students and employees. Anything can be achieved using Python, whether it’s web development, writing scripts to automate tasks, or analyzing vast amounts of data. Given its scope of application, Python keeps attracting newcomers.

Here are some quality Python learning resources.

2. Versatility

If you are an experienced programmer, you will appreciate not only Python’s fully featured object-oriented approach but also its versatility and cross-platform compatibility. Not many languages can combine OOPS and cross-platform compatibility like Python. Most experienced programmers use Python to write admin scripts or “duct tape” code that can bind applications together in a toolchain. This feature is important as it allows freedom to test code without building an environment from scratch to run the code. Unsurprisingly, Python has many applications in DevOps and testing automation.

Not only on-premise environments but cloud platforms also support Python, given its incredible applications. You can deploy Python on any operating system, including Windows, Linux, Mac, or any cloud platform. Even some of the popular cloud platforms offer Python as a cloud-based “function as a service,” for instance, AWS Lambda, Azure Functions, and Google Cloud Functions.

3. Open-source and extensible 

Python is an open-source programming language. It implies it has zero start-up costs and no barriers to entry. Anyone can download the interpreter and development tools to start building Python applications. It is another reason why Python continues to grow in popularity even when premium alternatives are available. Another benefit that works in its favor is how extensible Python is. Hundreds of thousands of freely available open-source packages further extend Python’s core functionality for application development. With a simple “pip install,” you can import and use any Python library or package. Due to its vast community support and growing popularity, Python has dethroned JavaScript as the most discussed programming language on the popular developer community platform, Stack Overflow.

4. Data Science applications 

Modern websites and applications produce a humongous amount of data. This is why data has become the single most valuable commodity today. But raw data is not helpful, and Python offers a wide array of options to collect, analyze, and represent data in meaningful information.

There are several Python libraries dedicated to data science and numeric computation. NumPy, TensorFlow, Keras, PyTorch, Pandas, Scikit-learn, and PySpark are the Python libraries used for data analysis, machine learning, significant data transformations, and neural networks. The JetBrains survey we mentioned above found that 49% of the respondents use Python for data analytics and 42% for machine learning applications. Due to its scope of use in modern AI and machine learning applications, Python developers are in high demand and will continue to be so for the foreseeable future.

Conclusion 

These are some of the significant reasons why Python is growing at such a fast pace. Its incredible applications in modern software development and AI and machine learning further boost its popularity among beginners and experienced developers. As a Python developer, you can explore almost any domain of software development.

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