With regards to learning an object-oriented programming language, you may want to consider either Java or Python. While Python can be more easy to use than Java, as it has a more instinctive coding style, the two programming languages do have their one of a kind favorable circumstances for software engineers and end clients. In any case, in the event that you are simply starting your way towards a programming profession, you should need to begin by learning Python, as it is less complex. Then again, comprehend both will give you edge over your colleagues. In light of that, here are the primary similarities and contrasts.
Java
Java is unique in its own way and for an advanced programmer, no problem to use. The first Java version 1.0 was released in 1995. By 2004, Java 5.0 was released; this version saw the insertion of generics into the Java language, providing Java with more efficient code and type safety. To date, the latest version of Java is SE 8, and it made its debut in 2014.
Currently, it is widely used as the key programming platform on smartphones and tablets. Additionally, Java programming language forms a large part of the basis for Android’s operating systems. Java syntax is primarily a derivative from C++ and combines universal, organized and object oriented programming that offers automatic memory management. Using Java byte-code is advantageous to porting since it has similarities to machine code. Other benefits to Java include:
The features of Java language can be expressed below:
simple. Java was designed with a small number of language constructs so that programmers could learn it quickly. It eliminates several language features available in C/C++ that are associated with poor programming practices or rarely used: goto statements, header files, structures, operator overloading, multiple inheritance and pointers.
object-oriented. Java is an OOPL that supports the construction of programs that consist of collections of collaborating objects. These objects have a unique identity, encapsulate attributes and operations, and are instances of classes related by inheritance and polymorphism.
distributed. Java is designed to support various levels of network connectivity. Java applications are network aware: TCP/IP support is built into Java class libraries. They can open and access remote objects on the Internet.
interpreted. Java is compiled to bytecodes, which are interpreted by a Java run-time environment.
robust. Java is designed to eliminate certain types of programming errors. Java is strongly typed, which allows extensive compile-time error checking. It does not support memory pointers, which eliminates the possibility of overwriting memory and corrupting data. In addition, its automatic memory management (garbage collection) eliminates memory leaks and other problems associated with dynamic memory allocation/de-allocation.
secure. Java is designed to be secure in a networked environment. The Java run-time environment uses a bytecode verification process to ensure that code loaded over the network does not violate Java security constraints.
architecture neutral. Java applications that are compiled to bytecodes can be interpreted by any system that implements the Java Virtual Machine. Since the Java Virtual Machine is supported across most operating systems, this means that Java applications are able to run on most platforms.
portable. In addition to supporting architecture neutrality, Java ensures that other implementation-dependent aspects of language specification are eliminated. For example, Java specifies the sizes of primitive data types and their arithmetic behavior.
high performance. Although Java is an interpreted language, it was designed to support “just-in-time” compilers, which dynamically compile bytecodes to machine code.
multithreaded. Java supports multiple threads of execution (a.k.a., lightweight processes), including a set of synchronization primitives. This makes programming with threads much easier.
dynamic language. Java supports dynamic loading of classes (a.k.a. “load on demand”), dynamic compilation, and automatic memory management (garbage collection).
simple. Java was designed with a small number of language constructs so that programmers could learn it quickly. It eliminates several language features available in C/C++ that are associated with poor programming practices or rarely used: goto statements, header files, structures, operator overloading, multiple inheritance and pointers.
object-oriented. Java is an OOPL that supports the construction of programs that consist of collections of collaborating objects. These objects have a unique identity, encapsulate attributes and operations, and are instances of classes related by inheritance and polymorphism.
distributed. Java is designed to support various levels of network connectivity. Java applications are network aware: TCP/IP support is built into Java class libraries. They can open and access remote objects on the Internet.
interpreted. Java is compiled to bytecodes, which are interpreted by a Java run-time environment.
robust. Java is designed to eliminate certain types of programming errors. Java is strongly typed, which allows extensive compile-time error checking. It does not support memory pointers, which eliminates the possibility of overwriting memory and corrupting data. In addition, its automatic memory management (garbage collection) eliminates memory leaks and other problems associated with dynamic memory allocation/de-allocation.
secure. Java is designed to be secure in a networked environment. The Java run-time environment uses a bytecode verification process to ensure that code loaded over the network does not violate Java security constraints.
architecture neutral. Java applications that are compiled to bytecodes can be interpreted by any system that implements the Java Virtual Machine. Since the Java Virtual Machine is supported across most operating systems, this means that Java applications are able to run on most platforms.
portable. In addition to supporting architecture neutrality, Java ensures that other implementation-dependent aspects of language specification are eliminated. For example, Java specifies the sizes of primitive data types and their arithmetic behavior.
high performance. Although Java is an interpreted language, it was designed to support “just-in-time” compilers, which dynamically compile bytecodes to machine code.
multithreaded. Java supports multiple threads of execution (a.k.a., lightweight processes), including a set of synchronization primitives. This makes programming with threads much easier.
dynamic language. Java supports dynamic loading of classes (a.k.a. “load on demand”), dynamic compilation, and automatic memory management (garbage collection).
Python
Python was first released in 1989. As a high-level programming language, it makes a strong case for readable code. In addition to supporting object-oriented programming, it also supports imperative and functional programming. This multi-paradigm language is also structure supportive. It offers ‘meta-programming’ and ‘logic programming,’ as well as ‘magic methods.’ Other features include:
- Strongly typed - Duck typing
- Uses whitespace to convey the beginning and end of blocks of code.
- Programs are small and therefore run much faster
- You need less code to create a program
- It is slow in execution
- Compiles native bytecode
- Object-oriented programming is optional
- You can assign a string to a variable that once held an integer
- Easier to read and understand relative to Java
- It's not supported across a wide variety of platforms
KEY DIFFERENCES: DUCK TYPING
The biggest difference between the two languages is that Java is a statically typed and Python is a dynamically typed.
Python is strongly but dynamically typed. This means names in code are bound to strongly typed objects at runtime. The only condition on the type of object a name refers to is that it supports the operations required for the particular object instances in the program. For example, I might have two types Person and Car that both support operation "run", but Car also supports "refuel". So long as my program only calls "run" on objects, it doesn't matter if they are Person or Car. This is called "duck typing" after the expression "if it walks like a duck and talks like a duck, it's a duck".
This makes Python very easy to write and not too bad to read, but difficult to analyze. Static type inference in Python is a known hard problem. The lack of type information in function signatures combined with support for operator overloading and just-in-time loading of modules at runtime means that the most common type inference algorithms have nothing to work with until the point in the program's execution when the types are known anyway. The Hindley-Milner algorithm that is commonly used in functional languages like Haskell and ML depends on being able to know, for example, that certain operations are restricted to particular types. These languages also typically have function signatures that "seed" the algorithm with the type information for their arguments.
In Python, names have no strong binding to their type, and thanks to duck typing, function arguments can be used to pass in any object whose interface supports the operations required by the function. There is no reasonable way to determine the type of an argument in this case, which can be very powerful and convenient, and is a lot like how we use objects in the real world. In the real world I don't generally care if I have a rock or a hammer: both have "hit()" interfaces that result in similar consequences when called.
Classes in object-oriented languages are meant to model concepts, but concepts are purely mental constructs that are essentially attitudes toward the concrete stuff of reality. Duck typing reflects this fact nicely. An object doesn't have to "be" a particular type, it just has to be useable where a thing of that type might be useable. This can lead to surprises, but it's a more accurate reflection of the categorical fluidity of human thought than is the rigid hierarchy imposed by more restrictive type systems.
OTHER DIFFERENCES
Both of these development programs come with their strong suits. While Java allows you to enjoy cross-platform support, you can still execute Python on at least 10 different operating systems. You need to determine what your end goal is before you decide on which program to use. Java, however, is not recommended for beginners as it is a more complex program. Python is more tolerating and forgiving as you can take shortcuts such as reusing an old variable.
Additionally, many users find Python easier to read and understand than Java. At the same time, Java code can be written once and executed from anywhere. A benefit to the Java platform is that it lets you download questionable code and run it in a secure environment, which cannot affect its host system. Furthermore, Java is network-centric, meaning you can create network-based applications.
Whichever you choose to learn is based upon your preferences, determination, and background. If you already comprehend the basics of Python, you might want to expand upon your knowledge before moving on to Java. However, if you have the time and will, learning Java allows you to program for a wide variety of environments that might make it more fulfilling in the long run.
I will start with Python
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