Python has become more popular than Java. Java is also one of the top trending courses in IT. The trend is likely caused because of Python’s great use for testing, and Java’s better use for production code. There is more testing than production code.
Java is a statically typed and compiled language, and Python is a dynamically typed and interpreted language. This single distinction makes Java quicker at runtime and less difficult to debug, however, Python is less difficult to use and less difficult to read.
Python has won popularity, in giant part, due to its communicatively; humans simply hold close it easier. With it, the libraries for Python are huge, so a new programmer will now not have to begin from scrape. Java is historic and nevertheless significantly used, so it additionally has a lot of libraries and a team of humans for support.
Now, let’s seem into depth, which includes some code examples to illustrate the variations between Python and Java.

Overview of Python

Python used to be first launched in 1991. It is an interpreter, a high-level, typical purpose programming language. It is Object-Oriented. Designed via Guido van Rossum, Python genuinely has a graph philosophy headquartered around code readability. The Python neighborhood will grade every other’s code-based totally on how Pythonic the code is.

Read: Beginner Tips For Learning Python Programming

When to use Python

Python’s libraries allow a programmer to get started out rapidly. Rarely will they want to begin from scratch? If a programmer wants to bounce into desktop learning, there’s a library for that. If they desire to create a fascinating chart, there’s a library for that. If they want to have an improvement bar proven in their CLI, there’s a library for that.
Generally, Python is the Lego of the programming languages; locate a container with orders on how to use it and get to work. There is little that wishes to begin from scratch.

Because of its readability, Python is great for:

1. New programmers
2. Getting ideas down fast
3. Sharing code with others

Java overview

Java is old. Java is a general-purpose programming language that utilizes classes and, like Python, is object-oriented.

Java was once developed by way of James Gosling at Sun Microsystems, launched in 1995 as a phase of Sun Microsystem’s Java Platform. Java modified the internet trip from easy textual content pages to pages with video and animation.

When to use Java

Java is designed to run anywhere. It makes use of its Java Virtual Machine (JVM) to interpret compiled code. The JVM acts as its very own interpreter and error detector.
With its ties to Sun Microsystems, Java used to be the most extensively used server-side language. Though no longer the case, Java reigned for a lengthy whilst and garnered a giant community, so it continues to have a lot of support.
Programming in Java can be effortless due to the fact Java has many libraries constructed on the pinnacle of it, making it convenient to locate code already written for a precise purpose.

WHO USES PYTHON & JAVA?

Python is regularly used with new programmers or junior developers coming into a records science role. The large desktop mastering libraries, TensorFlow and PyTorch, are each written in Python. Python has notable statistics processing libraries with Pandas and Dask and top records visualization skills with programs such as Matplotlib and Seaborn.
Java is used a lot for net development. It is extra frequent amongst senior-level programmers. It lets in for asynchronous programming and has a respectable Natural Language Processing community.
Both languages can be used in API interactions and for computer learning. Java is higher developed for constructing internet applications. Python’s Flask library is nevertheless solely capable to build the fundamentals to a Python-based UI however is excellent for developing a Python back-end with an API endpoint.

Python vs Java in code

Let’s see how Java and Python work differently.

Syntax

Because Python is an interpreted language, its syntax is more concise than Java, making getting started easier and testing programs on the fly quick and easy. You can enter lines right in the terminal, where Java needs to compile the whole program in order to run.

Type python and then 3+2 and the computer responds with 5.

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python

3+2

5

Consider doing this with Java. Java has no command line interpreter (CLI), so, to print 5 like we did above, we have to write a complete program and then compile it. Here is Print5.java:

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public class Print5 {

       public static void main(String[] args) {

        System.out.println("3+2=" + (Integer.toString(3+2)));

       }

}

To compile it, type javac Print5.java and run it with java Print5.

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java Print5

3+2=5

With Java, we had to make a complete program to print 5. That includes a class and a main function, which tells Java where to start.

We can also have a main function with Python, which you usually do when you want to pass it arguments. It looks like this:

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def main():

  print('3+2=', 3+2)

if __name__== "__main__":

  main()

Classes

Python code runs top to bottom—unless you tell it where to start. But you can also make classes, like possible with Java, like this:

Python Class

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class Number:

  def __init__(self, left, right):

      self.left = left

      self.right = right

number = Number(3, 2)

print("3+2=", number.left + number.right)

The class, Number, has two member variables left and right. The default constructor is __init__. We instantiate the object by calling the constructor number = Number(3, 2). We can then refer to the variables in the class as number.left and number.right. Referring to variables directly like this is frowned upon in Java. Instead, getter and setter functions are used as shown below.

Here is how you would do that same thing In Java. As you can see it is wordy, which is the main complaint people have with Java. Below we explain some of this code.

Java Class with Getter and Setter functions

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class PrintNumber {

      int left;

      int right;

      PrintNumber(int left, int right) {

          this.left = left;

          this.right = right;

      }

      public int getleft() {

          return left;

      }

      public int getRight() {

          return right;

      }

}

public class Print5 {

      public static void main(String[] args) {

          PrintNumber printNumber = new PrintNumber (3,2);

          String sum = Integer.toString(printNumber.getleft()

                + printNumber.getRight() );

          System.out.println("3+2=" + sum);

      }

}

Python is gentle in its treatment of variables. For example, it can print dictionary objects automatically. With Java it is necessary to use a function that specifically prints a dictionary. Python also casts variables of one type to another to make it easy to print strings and integers.

On the other hand, Java has strict type checking. This helps avoid runtime errors. Below we declare an array of Strings called args.

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String[] args

You usually put each Java class in its own file. But here we put two classes in one file to make compiling and running the code simpler. We have:

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class PrintNumber {

    int left;

    int right;

}

That class has two member variables left and right. In Python, we did not need to declare them first. We just did that on-the-fly using the self object.

In most cases Java variables should be private, meaning you cannot refer to them directly outside of the class. Instead you use getter functions to retrieve their value. Like this.

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public int getleft() {

    return left;

}

So, in the main function, we instantiate that class and retrieve its values:

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public int getleft() {

    return left;

}

public static void main(String[] args) {

    PrintNumber printNumber = new PrintNumber (3,2);

    String sum = Integer.toString(printNumber.getleft()

         + printNumber.getRight() );

}

Where Python is gentle in its treatment of variables, Java is not.

For example, we cannot concatenate and print numbers and letters like “3+2=” + 3 + 2. So, we have to use the function above to convert each integer to a string Integer.toString(), and then print the concatenation of two strings.

Learn both Python & Java

Both programming languages are appropriate for many humans and have massive communities in the back of them. Learning one does now not suggest you can’t examine the other—many programmers project into more than one language. And studying a couple of cans support the appreciation of programming languages altogether.
By many measures, Python is the easier one to learn, and migrating to Java afterward is possible.

Read: Top 10 Python Training Institutes in Bangalore

Python programming language is a simple, sophisticated, and straightforward algorithm that can perplex Python developers – mainly newbies. However, at some point in any Data Scientist or programming aspirant’s career, it is probable that the aspirant has to choose a new language and enhance their skills.

Especially, Python is an object-oriented, interpreted programming language. Its advanced concept in data structures, blended with dynamic binding and dynamic typing, makes it a most fascinating language to avail as a glue or scripting language to bridge existing services or components and for Rapid application development.

Aspirants often commit certain mistakes which are quite common while using this high-level programming language. In this article, let’s discuss the 10 most atrocious Python mistakes aspirants often make.

The Top 10 Awful Python  Mistakes Newbies Make

1. Defining Main Function in Python

This is the most common mistake made by coding aspirants. As mentioned in the introduction part since Python programming is a high-level scripting language, one can define functions that could be called in REPL mode.

Example:

def super_fun()

print (“Good morning”)

super_fun()

With the help of the above example, we can execute the super_fun function when it’s called from the CLI python no_main_func.py. However, if the programmer wants to use the code again as a module in a book, what would be the case?

No main func

import no_main_func

Good morning

The super_fun is now executed accordingly when the script is imported. This is a simple example, but if you are executing some heavy computational operations, or giving rise to an activity that creates multiple threads. In this case, Aspirants want to avoid running the code automatically on import, so this is how one can ward off the same.

def super_fun():

print(“Good morning”)

if_name_==”_main_”:

# execute only if run as a script

super_fun()

As you can see, unexpected behaviors have been prevented when you import it as a module.

2. The boolean mess

Like in every other programming language, the doubt of what’s supposed to be contemplated as a Boolean “true” value is a most common confusion in Python too.

Let us understand with the help of an example:

>>> 0 == False

True

>>> 0.0 == False

True

>>> [] == False

False

>>> {} == False

False

>>> set() == False

False

>>> bool(None) == False

True

>>> None == False

False

>>> None == True

False

In the above example, the zero value for any numeric data type is appraised to be false. However, empty collections such as sets, lists, or dictionaries are true. This can be tedious as a variable can be kept undefined and later incorporated in a contrast that will deliver an unpredicted outcome.

3. Misusing Python Scope Rules

Python scope resolution is built on the LEGB rule, that is, contemplated as an abbreviation of Local, Enclosing, Global, and Built-in. Seems easy-peasy, isn’t it? Actually, there are certain subtleties to the way it runs in Python programming language that delivers coders the common error and this is one of the most atrocious python mistakes that freshers do.

4. Misunderstanding Function Arguments by Reference And Value

The high-level programming language Python has a weird way of incorporating arguments in functions and methods. Aspiring coders who are shifting to Python from other languages like C++ or Java may misunderstand the way that the interpreter runs with arguments.

5. Class Variables Confusions

Object-oriented programming intends to put together problems in a way that reflects the real world, however, it can become tedious to newbies in the coding space.

6. Updating a list while iterating over it

Removing a thing or any item from an array or list while iterating over it could be problematic, which is familiar to the majority of experienced software developers. However, most of the time it becomes cumbersome for aspirants. Sometimes professional Python developers could face problems by this in code that is more complicated.

7. Ineffectiveness in understanding the differences between Python 2 & Python 3

Freshers fail to understand the actual difference between Python 2 & Python 3 since the two versions are quite similar. In Python 3, the exception object could not be accessed beyond the scope of the except block. The primary reason is that it would grasp a reference cycle with the stack frame in memory till the garbage collector continues to operate.

 

8. Float Data Types

This is one more addition to the 10 most atrocious Python mistakes. Beginners misunderstand float as a simple type. For instance, the below-mentioned example highlights the difference between defining the identifier of float types and simple types.

>>> a = 10

>>> b = 10

>>>

>>> id(a) == id(b)

True

>>> c = 10.0

>>> d = 10.0

>>>

>>> id(c) == id(d)

False

>>> print(id(a), id(b))

9788896 9788896

>>> print(id(c), id(d))

140538411157584 140538410559728

Find another example below, an easy arithmetic operation that is simple to solve, but you will get the unpredicted results because of the comparison operator.

>>> a = (0.3 * 3) + 0.1

>>> b = 1.0

>>> a == b

False

Programmers can avoid the same with the help of the following function mentioned in the example below:

def super_fun(a:float, b:float):

return True if abs(a-b) < 1e-9 else False

if __name__ == “__main__”:

# execute only if run as a script

print(super_fun((0.3*3 + 0.1),1.0))

9. Perplexity over how Python binds variables in closures

Beginners often get confused over this because Python’s late binding attribute states that the values of variables exploited in closures could be looked up at the time while calling the inner function.

10. Name collision with Python Standard Library Modules

One of the interesting things about this high-level language is the opulence of library modules. If beginners are not avoiding it smartly, names get clash between one of your modules and the one which already exists in the library.