Python Vs Java: Outlining The Major Differences

Python vs Java has always been a long heated debate, and it still doesn’t have one settled winner. Both are modern-day, in-demand, compelling programming languages used majorly in all types of website development services and stand next to none. Java vs Python, these languages are object-oriented and continuously used for software development purposes. In fact, the two languages have constantly emerged as the top; they’re trendy! But what is the exact difference between Python vs Java?

In technical terms, Python’s syntax is easier to comprehend and can be understood by the masses. Java, however, is based on C/C++ and relies on traditional rules. Java’s code readability is sensitive. Misuse of a mere semicolon can result in a syntax error. At the same time, Python is human-like, based on English. There are countless differences like these; keep reading as we’ll discuss them in further detail.

Structure Of Languages

Both are obviously, high-level programming languages but what distinguishes them is their coding structure. Python is an interpreted language, and developers have to depend on ‘Python’ exclusive interpreters. There are a few nitpicks in-between, but they’re worth it. CPython, an interpreter, requires a .py extension, and you can execute line-by-line code by looking at the file on CPython yourself simultaneously.

While Java is a compiling language and has its own JVM (Java Virtual Machine), the compiler is easy to use and is cross-platform supported. Also, the source code of Java is converted into a bytecode – instruction set for JVM. It’s a simple three-way process for Java. Any compiler converts source code to bytecode. Then, the JVM uses bytecode and compiles it in a machine-readable form. After execution, you have a Java program at your disposal!

Programming Paradigm

Programming paradigms make it easier to classify languages in ‘boxes.’ Is the language imperative? Is it structured? In this case, both are object-oriented languages relying on their own internal (encapsulated) state and public interfaces. Python’s structure is diverse and adaptable to different programming states; imperative, functional, procedural. Use different programming types accordingly.

Java isn’t any less, either. Granted that it started with limited features, the programming language has evolved. On their latest updated version – Java 8, there’s support for important functional programming concepts such as lambda expressions. The update showcased Java’s support for functions.  And as always, Java is concurrent, class-based, and object-oriented. In the rivalry of Java vs Python, the latter clearly ones in this case.

Ease Of Readability

From a developer’s perspective, knowing the syntax format is essential before delving into any language. Python, in particular, emphasizes ‘code readability,’ and their IDE (Integrated Development Environment) makes it clear. As mentioned, Python was specifically designed to attract emerging coders – figuring out the syntax does not take much time, unlike Java.

For instance, you can clearly see a side-by-side comparison of the two languages here. Python comes across as simple, easily comprehensible, and is executed faster. It’s plain English. Even the hashtag on the side symbolizes ‘comments’ and does not have any significance. Hence, Python has always been marketed as a beginner-level language that is easy to understand yet powerful. Python is being taught at middle schools as well. Its syntax makes programming easy for everyone.

With Java, it’s a different story. Before executing a code, you need to be aware of concepts such as class, object, instance variables, and methods. It is case-sensitive software, so you always to be alert. But on Java 9, there are improvements. For a better user experience, they introduced ‘modules.’ With modules, developers can organize the code into categories and create separate packages. Modules ease the compiling process, but organizing the code takes a lot of time nonetheless.

Whitespace

Whitespace refers to typography in the UI of programming languages. And you might have guessed it; Python includes whitespace as a part of its syntax – it plays an integral role. For nesting and loops, you can apply tabs and full colons, respectively. Now, not everyone’s a fan of whitespace in Python. Parsing whitespace is someone’s own aesthetic preference; using black lines isn’t necessary.

Meanwhile, Java does not rely on whitespace at all. Semicolons, parentheses, and curly braces account for Java’s directory.

Key Factor: Duck Typing

Duck-typing sets the two languages apart. Now, duck-typing depends on dynamic typing, where the class or object does not have much significance. Fortunately, Python is a dynamic language, and duck typing is a major part of it. Meaning that Python isn’t dependent on variable deceleration.

Interestingly, duck-typing’s concept is applicable to Python. Essentially, duck-typing is based on the philosophy – ‘if it quacks like a duck, it is a duck,’ and metaphorically means that you do not check for attributes in variables.

Framework

Frameworks are an abstraction that allows the user to develop applications without dealing with low-level details such as sockets, protocols, etc. It is a well-known fact that writing code or developing an application is a complex and tiring process; however, it becomes a tad bit easier by using this certain feature.

Now, Java Frameworks are, indeed, the templates of pre-written code through which you can add your own code. Java receives praise for its large number of Frameworks. The most popular ones are Spring, Hibernate, etc. However, Python has fewer options for Frameworks as compared to Java. The most popular high-level Frameworks in Python are Django, TurboGears, and Web2py.

If you are planning to become a UI/UX designer soon, then having knowledge of Python vs Java frameworks will help you understand the underlying mechanism of your app or website in a much better manner.

Speed and Performance

According to experts, both Java and Python lack in the department of speed. The speed required to facilitate high-performance computing and coding is not currently available. Nonetheless, it is important to mention that Java Virtual Machine (JVM) speeds up Java code execution through just-in-time (JIT) compilation. The Bytecode compiles into the Native Machine Code much quicker through the assistance of this JIT compiler. Additionally, through supporting concurrency, Java allows software applications to run much faster as compared to Python.

On the other hand, the coders can quicken Python code execution with the help of several implementations of the programming language. For example, they can use Jython to compile the given Python code into Java bytecode. Similarly, Cython is available for developers to compile Python code into C/C++ code. Although these implementations are an advantage and sometimes optimizes the execution rate for developers, it is essential to mention that it is slower since it uses an interpreter and also determines the data type at run time.

Data Science

Simply put, Python is the standard language for doing data science today. Enterprises and corporations prefer Python for development. It can vary from scientific computing, big data to artificial intelligence projects. While there are places that exist, such as academia, where R might be more popular, you would be surprised to find out that most data science roles expect you to be experienced in Python instead of languages like Scala and Java. As mentioned above, it is the most preferred programming language for machine learning and data science. A report shows that a large sum of data scientists and machine learning programmers have shown a preference towards Python instead of the usual use of Java while working on sentiment analysis.

Nevertheless, many machine learning programmers opt for Java when working on projects close to network security. This can consist of projects such as cyber-attack prevention and fraud detection.

The Function of Agile and DevOps

There has been a continuous increase in enterprises and businesses adopting the so-called agile development methodology to accelerate the deliverance of high-quality software applications. Similarly, numerous organizations nowadays go for DevOps to increase software development along with testing and deployment processes.

Aforementioned, Both Java and Python allow enterprises to embrace new project management methodologies like agile and DevOps. Since Java contains a static type system, it is quite easy for programmers to uncomplicate refactoring. On the other hand, Python helps developers to simplify refactoring by featuring a dynamic type system. Additionally, Python’s easy-to-use and expressive syntax rules give Python programmers access to experiment with diverse ideas.

Python has always had a prominent presence in the agile space. While Python has gained popularity and success for several reasons, one of the main reasons for this popularity is the rise of the DevOps movement.

Conclusion

We can conclude that both Java and Python languages are beneficial on their own. Python is simple and concise, whereas Java is quick and more convenient. While Python coding is dynamic, Java coding is static.

Middle schoolers prefer using Python for writing their first ‘for loop’ or ‘while loop’ and outstanding machine learning engineers. At the same time, users prefer Java for coding more than Python. Both of these seem plausible. Nonetheless, it entirely depends on the user to decide the best language out of these two. It really is up to you to choose a particular language for your next project!

Best Web Development Languages To Learn in 2021

Programming languages prove to be the bridge between the user and the device through which operating systems and applications are developed. There is an immense number of coding languages that serve different purposes.

Most of the in-demand jobs offered by agencies that offer website development services require an individual to know at least one programming skill. From data analytics to developing websites, programming languages have wide-ranging applicability. Even most modern web design trends require designers to at least have a basic level understanding of programming to create the required designs and then relay to the developer the exact trajectory through which they are required to be coded.

If you, too, are aiming to pursue a career in any of these in-demand industries, then you need to develop your skills for one or more of these programming languages to give you an edge over your peers for the near future.

But what programming language should I opt for? This is perhaps the most difficult question of them all. If you choose the wrong language to learn for programming, you will be left ruing your chances very soon, so you will need to know about the most trending programming languages today.

Here, we present a list of the best programming languages to learn in 2020, along with their pros and cons, to make you aware of their importance in the coding world.

1.  Python:

Python programing web development languages

Python came into being in 1991 by Guido Van Rossum, an open-source, free-to-download programming language with good features for beginners who have no or low coding knowledge. It is mostly useful for data analysis, deep learning, and machine learning. If you are interested in Artificial Intelligence, you should definitely consider learning Python.

Pros:

  1. There are libraries where the user may find already written programs that are useful on different grounds.
  2. It is simple to read, easy to understand, and requires less coding than other programming languages.
  3. Python is versatile. One can write some part of the code in C++ or C as well. On top of that, it allows you to write programs for any OS, such as Linux, Windows, or Mac.

Cons:

  1. Python lacks when it comes to execution. The step-by-step execution sometimes takes longer, making it speed limited.
  2. It is not recommended for mobile app development.
  3. Huge enterprises avoid using Python since it has underdeveloped database layers.

2.  Java

Java programing web development languages

Java, invented in 1996 and owned by Oracle Corporation, is a widely-used programming language around the globe. It is generally known for its Object-Oriented Programming capabilities. It is complex as compared to Python.

Till now, it was the preferred programming language for Android until Kotlin superseded it. But still, Java has a lot of importance in the world of coding even now.

Pros:

  1. Java uses automatic memory allocation and is simpler as compared to C++ or C.
  2. It is independent of the platform. It can easily work on any operating system.

Cons:

  1. Java consumes more memory as compared to other programming languages that make it a bit slower than others.
  2. The garbage collector runs to manage memory. When it runs, it affects application performance.

3.  JavaScript

Java Script Programing website development languages

JavaScript makes it to the third position in the list of top programming languages due to its ease while designing web browsers. It has applications in web designing as well. This coding language is considered one of the most important front-end programming languages out there. If you are becoming a UI/UX designer, learning this language is imperative for you.

Pros:

  1. JavaScript is fast, easy-to-understand, and easy-to-learn with support from almost all web browsers.
  2. Due to lesser coding, JavaScript improves application performance.
  3. JavaScript provides an extensive interface to developers helping them design an eye-catching webpage.

Cons:

  1. It is difficult to detect errors in JavaScript, i.e., debugging is not that easy.
  2. The code written in JavaScript is visible to the audience. This can be the cause of security breaches and code thefts.

4.  SWIFT

Swift Programing framework

Swift is an open-source programming language by Apple in 2014 and is suitable for Mac and Linux. It’s an emerging coding language mainly due to its simplicity. It is as simple as the English language itself. It is fast and secure and gives an amazing and elegant outlook to the applications it helps develop.

Pros:

  1. Swift is an effective programming language against errors with enhanced readability.
  2. Apple claims that Swift is about 2.6 times faster than Objective-C and 8.4 times faster than Python.

Cons:

  1. Swift proves to be good for nothing when it comes to older versions of iOS and its applications.
  2. Although it is an open-source programming language, the community is not that developed compared to other coding languages.

5.  Go

Go programing language development framework

To overcome the challenges faced by developers while writing code, Google decided to develop the Go programming language. Go is considered to be highly agile and suitable for developing scalable web entities. A surge has been observed in its demand and is expected to grow more by 2021.

Pros:

  1. Go programming language provides the facility of smart coding that requires fewer code lines.
  2. The ease of use and the adoptive environment this language provides makes it outshine other programming languages.
  3. Errors are no more a problem as the language consists mainly of single-line codes.

Cons:

  1. Go lacks library support since it is a new and young language paving for its future acceptance.
  2. The language lags because go does not provide any GUI library.
  3. Go is not as versatile as other programming languages since it is suitable and recommended only for Google-based applications.

6.  R

R programing

R, invented in New Zealand at the University of Auckland by Ross IhakaR and Robert Gentleman, is a programming language developed with a principal focus on Machine Learning and is mostly suitable for Data Analysis. It is an open-source software environment that provides users with exceptional statistical features.

Pros:

  1. R is a versatile language that can work on Mac, Linux as well as Windows.
  2. The quality of the graphs that R provides is just extraordinary.
  3. It is compatible with other programming languages as well.

Cons:

  1. R consumes more memory as compared to other programming languages. While dealing with Big Data, R is not a good choice.
  2. R is less secure and not the best choice for designing webpages and web applications.
  3. It is slower than other programming languages like Python.
  4. One needs to have coding expertise since the language is difficult to work with.
  5. Programmers with no or low coding experience with packages may find trouble while dealing with algorithms.

7.  Kotlin

Kotlin

Just like Google developed Go, it also introduced the world with Kotlin programming language in 2011. Codes written in Kotlin can work well on Java and vice versa. Kotlin is also comparable to Python in many ways, so learning Kotlin won’t be a major issue for you if you already know about Python.

It is open-source with no license requirement and provides a friendly environment to the developers, and works efficiently. Google has declared that Kotlin is its official programming language.

Pros:

  1. A developer doesn’t need to learn a new IDE as Kotlin has IDE support.
  2. The maintenance is easy and avoids bugs to the maximum.
  3. It is a mature language that is reliable and secure to use.

Cons:

  1. Learning resources are confined since Kotlin is actually not Java.
  2. There is a variation in compilation speeds when we compare Java with Kotlin. Java is good for a clean building, while Kotlin is best for creating incremental builds.
  3. Switching from Java to Kotlin can prove difficult for some developers who are already coding with Java.

8.  Scala

Scala development framework

Scala is yet another effort to overcome the challenges faced by Java programmers. It is not only an object-oriented programming language but a functional programming language as well. It was released in 2004 and aimed at easing the issues that developers face when they require a high standard language without too many complexities.

Pros:

  1. It is fast and efficient since it evaluates a variable as per requirement.
  2. It provides hybrid features of both Object-Oriented programming and functional programming.
  3. Scala is an excellent choice for analyzing data.
  4. With Scala, codes are of better quality. There is a lesser coding requirement with minimal bugs.

Cons:

  1. It becomes complicated for developers due to the mix-up of object-oriented and functional features.
  2. It will require time and money to train workers to learn the features of Scala. The reason behind this is simple; Scala developers are not in-demand.
  3. Resources are limited as the community is not that huge.

IN A NUTSHELL:

Although there are a plethora of top programming languages, it is a crystal-clear fact that Python and Java rule the coding world. All coding languages have their own distinct pros and cons. The final choice depends on the developer’s needs and requirements to go for the best possible option.