Hello Coders!
Java Vs Python ? A question which every programmer has to ask himself once in life. No worries i will help you decide.
If you want fast compilation, native support and Legacy Support you should probably go with Java but if you want fast development , easy syntax and inclined toward field of Data Science, Machine Learning and AI you should probably go with Python.
Okay , Still Confused ! No worries , i am here to help. Let's take a dive in key features of these languages.
Syntax
Java code is characterized by complexity and verbosity. Curly braces are obligatory to set the boundaries between code blocks. Your code won’t work if you miss a curly brace.
Python code is succinct. It requires neither curly braces nor semicolons. However, indentation is mandatory to divide code into blocks. Indentation provides a major advantage of improved code readability though.
Compilation
Java is a compiled language. So translation into bytecode happens at compile-time, and not at runtime.
Python is an interpreted language. So translation into bytecode happens at runtime.
Execution Speed
Due to prior compilation, Java has faster execution speed.
Python is slower than Java, as it’s an interpreted language, and the determination of data types happens during code execution.
Performance
In most cases, Java is faster than Python, as was proved by Debian Benchmarks. It can tolerate heavy loads.
Python shows lower performance speed than Java does. It isn’t a good option for memory-intensive tasks.
Legacy
Java updates provide backward compatibility that results in a huge legacy codebase. Today, a large percentage of enterprise legacy platforms are coded in Java .
You won’t find many enterprise legacy solutions written in Python. There are several reasons for this, including its scripting nature and rapid overall language updates. However, it’s not uncommon for Python to be used as a "glue" layer that connects different entities of legacy platforms.
Cross-Platform Support
Java Virtual Machine is responsible for the execution of Java bytecode. JVM is available on various platforms allowing Java to be a solid choice for cross-platform development.
It’s possible to execute Python code on any platform where there is a Python interpreter installed. However, Python is not well-suited for native mobile development.
Databases
With the Java Database Connectivity (JDBC) API, Java provides effective database access features. It also offers object-relational mapping (ORM) frameworks like Hibernate and JPA.
Python’s database API is independent of any database engine. Various libraries deliver DB connectivity including psycopg2, SQLAlchemy, and others. Django ORM and PonyORM provide object-relational mapping (ORM) capabilities.
Backend Frameworks
When opting for Java, you’ll be fully equipped with powerful web development frameworks. The most popular options include:
Spring: an open-source framework primarily used in the development of enterprise-level applications.
Hibernate: a framework that implements the Java Persistence API (JPA) to empower applications with an ORM database; struts: a fully-featured framework supported by the Apache Software Foundation (ASF). It allows implementing easy-to-maintain enterprise applications.
Struts: a fully-featured framework supported by the Apache Software Foundation (ASF). It allows implementing easy-to-maintain enterprise applications.
Python frameworks are overtaking Java ones in their popularity and wide-spread usage. The following ones are especially difficult to compete with:
Django: an open-source full-stack framework. Its aim is to deliver all the essential features out-of-the-box instead of providing them as a set of libraries.
Flask: a web development framework provided under the BSD license. Flask is aimed at building solid foundations for web applications.
FastAPI: a framework designed to enable rapid and efficient implementation experience. It enables speedy development of network APIs (including GraphQL) with Python 3.6+.
Development Speed
Due to higher code complexity, Java applications take more time to develop. Implementation of an MVP version can easily take a couple of months. Though Java applications are considered to be robust and highly secure, so they are well worth their time and costs.
Python’s natural simplicity enables rapid development. MVP versions can be implemented within a couple of weeks. So when having a tight schedule and a task at hand that can be well-handled with Python, don’t hesitate to go for it. Apart from that, Python development is more time- and cost-efficient.
Machine Learning Libraries
Though Python is the most popular language in the Machine Learning landscape, Java offers a lot of handy ML libraries with rich capabilities as well. For instance:
Deeplearning4j
Neuroph
Weka
Mallet
MOA
Being the primary language in the Machine Learning industry, Python offers a wide array of ML libraries. The most popular ones include:
TensorFlow
PyTorch
Keras
Scikit-learn
NLTK
I bet your 90 percent confusion is gone , now its time to vanish those remaining 10 percent .
So lets talk about most important factor, "How much money we can make ?"
Being highly popular, both Python and Java offer lots of career opportunities.
On average, around 60 K of job postings for Java and Python software developers are available on the USA job market. So if you master either of these languages, you won’t be out of the job for sure. As for salaries, Java developers can earn around $102 K per annum, whereas Python developers can count on $123 K.
There is no doubt that job prospects and salary size play an essential role when choosing your occupation. But when all is said and done, you need to love what you do. So when deciding on a language to learn, pursue the one that sparks your interest and imagination the most.
Apart from becoming a Software Developer, you can always consider such career paths as Data Scientist, Data Analyst, or Product Manager, where programming skills can come in handy too.
So as know your confusion is gone what are you waiting for!!
""GET SET CODE!!"
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