Java vs Python

Computer science is crucial to our lives today, and programming languages play a fundamental role. These languages act as a programmer’s toolbox. However, choosing a language can be challenging, especially when deciding between the two most popular options: Java and Python.

When comparing Java vs. Python speed, Python is easier to use and read, but being an interpreted language, it’s slower as it executes code line-by-line. Running on the JVM (Java Virtual Machine) as a compiled language, Java offers a faster runtime. The choice depends on the programmer’s goals. Programmers widely use Java and Python as general-purpose languages for desktop and web applications. Although the two have many similarities, they also have significant differences, which make one programming language ideal over the other. 

Understanding the key differences between Python vs. Java can help you make an informed decision. Python is an interpreted language that executes code line by line, making it ideal for scripting and rapid development due to its clean and readable syntax. Java, a compiled language, converts code into bytecode and is run by the Java Virtual Machine (JVM). This ensures strong performance and cross-platform compatibility, making Java a preferred choice for large-scale enterprise applications.

Both of these object-oriented programming languages offer significant cross-platform support and extensive libraries. However, they excel in different applications. Recent trends show that Python is becoming more popular than Java, likely because of its great use for experimentation. However, Java is better for production code.

Java overview

Java remains one of the most popular programming languages in the world. First created in 1995 by James Gosling at Sun Microsystems, Oracle owns Java today. Over three billion devices run Java, using this programming language for everything from mobile apps to web apps and games to web servers.

When first created, the intention was for Java to be WORA — write once, run anywhere. It is a statically typed and compiled language. 

Based on its history and plethora of available libraries, Java does offer a large community when in need of support. This ongoing support can make programming in Java reasonably straightforward. If a programmer is looking for code, Java’s libraries make it easy to find code previously written for a specific purpose. 

Java continues to be a popular programming language based on its simplicity and ease of use. It is also open-source and free. 

Most common use cases for Java

Java has many applications but is often used for web development. The most common applications for Java include:

• Desktop GUI apps 
• Enterprise solutions 
• Embedded systems 
• Web applications 
• Scientific applications
• Financial sector server applications
• Android applications
• Software tools

These use cases show how versatile and robust the Java programming language is. According to StackShare, nearly 10,000 corporations use Java in their tech stacks, including Google, Uber, Instagram, Netflix, and Airbnb. However, there are billions of active Java virtual machines globally. Real-world use cases are seen across many industries, including real estate, eCommerce, healthcare, retail, and more.

Python overview

First released in 1991, Python also has an impressive history. Developed by Guido van Rossum at the National Research Institute for Mathematics and Computer Science in the Netherlands, Python is considered a powerful programming language. 

Python was designed to be highly readable to fulfill general purposes upon its creation. It is a dynamically typed and interpreted language. 

Based on its vast libraries, Python allows programmers to get started quickly. For example, if a programmer is interested in machine learning, there’s a library for that. A minimal amount of code needs to be started from scratch, so this programming language is ideal for beginners. However, it’s also great for sharing code with others.

Most common use cases for Python

Python also has many use cases. Concerning use cases, Python is excellent for big data. There are many reasons for this, including:

• Available Python packages 
• Machine learning algorithms
• Python’s active community
• Licensing structure 
• Data visualization (e.g. Matplotib)

The most common applications for Python include:

• Machine learning 
• Image processing 
• Scientific and numeric computing 
• Language development 
• Learning applications

Python applications are now mainstream, with a presence across many different industries — and the applications are increasing each day. Many of the companies discussed above, that use Java, also use Python. These include Netflix, Google, Instagram, Spotify, Dropbox, and Quora. 

Aside from web application development, data science, and AI, Python has a strong presence in the gaming industry. This programming language uses Python libraries like PyGame and PySoy to develop Battlefield 2 and other successful games.

Is Java faster than Python?

The speed of a programming language comes from the processing time it takes to read and execute the program. The speed of each depends on the implementation, but Java typically reads and executes much faster. Historically, Java was up to 25+ times faster, but that has since changed following the release of Python 3. Regardless, Java still runs significantly faster in almost every circumstance, so it remains the dominant choice for enterprise-level software development.  

Compared to Java, Python sacrifices some performance to be a more flexible option known for its high-level programming features. Unlike Java, which must be compiled with each change, developers can make changes to Python on the fly as needed. This ability to adapt quickly makes Python the ideal choice for data analytics, where variables might frequently change.

In short, if you’re developing efficient code execution that is scalable to enterprise-level applications, Java is the clear choice. If you need to apply extensive scripts or require agility and flexibility in development, and execution speed is less of a factor, Python will likely suit your purposes much better.

Java vs. Python – Biggest differences in code

Unlike Python, Java is one of the two official programming languages used for Android. However, Python has gained popularity simply because people grasp it more easily. 

Type of programming language 

Both programming languages are high-level. Python is an interpreted programming language, which means it can convert human-readable code into machine-readable code. In comparison, Java is what’s known as a compiled programming language. Java code is initially compiled into a binary bytecode, which can then run on any platform or device with Java Virtual Machine (JVM). However, because JVM is a software-based interpreter, Java can be considered a compiled and interpreted language. 

Programming paradigms 

Both Java and Python support several programming paradigms. Both are object-oriented. 

In addition:

• Python supports imperative, functional, and procedural programming paradigms. 
• Java was initially developed as a concurrent, class-based programming language and is still heavy on classes.

Readability 

Code readability is a major selling point for Python, as this programming language keeps code clean, concise, and readable. These benefits are one of the core reasons why many developers prefer Python. Developers can avoid writing additional code to keep applications maintainable. 

As Java releases new versions, new language features are included to simplify the software development process. For example, Java 9 developers can structure software applications with modules. Java modules are for better package distributions and enhanced security.

Performance 

The performance of a programming language is crucial. It determines how efficiently a program runs, handles concurrent tasks, and responds to user interactions, affecting user experience and system reliability. In programming, the choice of language impacts application performance, influencing everything from security to scalability. 

Security

Malicious software and hackers are ever-present threats to web applications. Automated code injections, such as webworms, are particularly insidious, finding their way into any systems that unknowingly allow them access. These worms carry malicious code that injects commands or malicious scripts to modify stored SQL data. Active hackers often use specialized malicious programs to find their way into systems and gain access to source code.

Java has integrated security features that safeguard it from hackers and code injections much more effectively than Python. While Python doesn’t have Java’s built-in security, its agility and ease of use make it particularly desirable for web development. Users often develop or purchase external security to better protect Python-based applications.

Ecosystem and tooling

Python and Java both have an immense collection of libraries, frameworks, and developer tools available for users to take advantage of. Both can utilize REST and CRUD API frameworks, though they may each take a slightly different route to get there. Beyond API access, each language has specialized toolkits. Some expand a language’s capabilities, others simplify the development process.

Python’s effectiveness in machine learning and data analytics has led to the emergence of several commercial and open-source frameworks that leverage its agility and dynamic number-crunching abilities. Frameworks like FLASK and Streamlit empower developers to quickly build, scale, and share applications. Tools like Scrapy and libraries like Beautiful Soup enable Python applications to extract data from web pages while employing powerful tools like pandas or SQLAlchemy to manage and analyze the extracted information.

Java has long been a widely preferred web application development language, and a dedicated community has created numerous integrated developer environments to add greater simplicity and agility to Java programming. Visual Studio Code (VS Code) has been a staple for Java development for years, simplifying code writing and enabling developers to switch between multiple languages quickly. The open-source IDE NetBeans gives developers a more streamlined environment to build and roll out Java applications, with an array of onboard dynamic and static libraries to expand development capabilities.

Parallelism and hyperthreading

When comparing Python vs. Java in terms of parallelism and hyperthreading capabilities, most developers agree that Java has a distinct advantage. Java’s ability to run parallel processes and multitask has made it a solid choice for scalability and enterprise-level applications for decades. As a compiled language, compared to Python, which is an interpreted language, Java applications don’t have to contend with a global interpreter lock (GIL), which limits Python’s ability to hyperthread.

It’s clear that Python is a solid choice for producing agile serial functionality in an application. However, when your application needs the capacity to run concurrent cores and perform multiple simultaneous functions, Java has Python beat hands-down.

Mobile App Development 

Unlike Python, Java is one of the official programming languages of the world’s most popular operating system. Many developers today count on Java to build apps and games for Android. 

In comparison, developers lack any options to use Python to build native mobile apps for mobile platforms. It is still possible to develop Python-based apps using libraries like Kivy. However, to deliver an optimal user experience, a significant amount of time and effort is required to build Python-based apps. 

Agile and DevOps

Enterprises continue to adopt agile development methodologies to rapidly deliver high-quality software applications. To do so, organizations often opt for DevOps to accelerate development, testing, and deployment processes. 

Both Java and Python make this possible. The difference is that Java features a static type system, making it easier for programmers to simplify refactoring — while Python allows developers to automate refactoring via a dynamic type system. Python has an edge in that it enables programmers to experiment with ideas based on its simple and expressive syntax. 

Learning curve – Which is easier to learn?

Beginners tend to favor Python over Java. Python’s syntax is relatively straightforward, making this language a more user-friendly option. 

Java is more complex and challenging, showcasing a high entry point. It takes time to fully understand and utilize the capabilities of Java.

The overall consensus is that while Python is easier to learn, learning Java is far from impossible — it just takes longer. While some argue Java can lead to higher quality code, an experienced Python developer can also benefit from the same functionalities associated with Java. Outstanding developers benefit from learning both languages, especially since each language excels at different applications. 

Key Python vs. Java comparisons

Aspect	Python	Java
Syntax	• Created for readability and simplicity. • Blocks defined by indents. • Dynamic typing, which usually requires less code, but may lead to runtime errors.	• Verbose, typically requiring several lines of code for simple blocks. • Uses bracers to explicitly define blocks. • Statically typed, requiring more code at compile time.
Performance	• Interpreted code and dynamic typing, generally making it slower when running. • More suited for rapid development rather than application performance.	• Compiling to bytecode and JVM execution typically helps Java to run faster. • Ideal for application performance.
Scalability	• Scalable, but may experience global interpreter lock (GIL) performance bottlenecks. • Often requires integrated frameworks like Django or Flask for web scaling.	• Highly scalable, assisted by multithreading capabilities and concurrency support. • Enterprise-grade framework integrations support large applications.
Community Support	• Robust community, with many libraries and frameworks for a wide array of tasks. • Community forums offer frequent updates and conduct active discussions.	• Loyal, established community with extensive libraries and frameworks. • Strong enterprise support and numerous community resources.
Typical Use Cases	• Data science, machine learning, web development, and scripting. • Quick development times, prototyping, and rollouts.	• Enterprise applications, web applications, and Android mobile apps. • Suitable for large-scale systems such as financial services and processing large amounts of data.
Learning Curve	• Simple syntax makes Python an ideal language for beginners.	• Complex syntax and concepts give Java a much steeper learning curve.
Platform Dependency	• Works across multiple platforms, but different systems may have issues with certain libraries.	• JVM enables Java to run on just about any platform without having to modify the code to fit different platform requirements.

Which language is used more?

For many years, Java reigned supreme in the world of web application development. However, Python slid past Java on all the charts. Today, more developers create in Python than Java by a respectable margin.

Statistics vary by source, but most show Python with a respectable lead, as reported by Stackoverflow, Statista, and GitHub.

According to the Tiobe Index, Python overtook Java for the first time in 2021, and the gap has only widened since. The dramatic rise in Python’s use can be credited to its becoming the preferred language for teaching and the popularity of Python frameworks, such as TensorFlow, for machine learning. Python now boasts considerably more users, and its ease of use continues to propel it upwards in the charts. 

Java’s rigorous syntax rules may also contribute to it falling behind Python, but it remains highly popular for enterprise application development due to its security and scalability. Many loyal Java developers argue that Java’s greater stability gives it an edge, unlike Python, which tests syntax during the runtime. In Java, developers must test and review all of the code before running. This testing process means the code must be very well-written, which has the benefit of reducing the likelihood of application crashes. 

Which language should you use first?

For beginners, the question remains — which programming language should be used first?

Python is the clear choice for most new programmers. Offering a straightforward syntax, Python is a good starting point, especially among those most interested in deep learning, machine learning, and the AI field as a whole. For data analysis and visualization, Python offers advantages.

With that in mind, some prefer to start with Java, as it’s often challenging to transition to languages like Java after focusing primarily on Python. In contrast, taking the leap from Java to Python is rather comfortable. Java has a vast range of libraries and frameworks to lean on during the initial learning process. 

The best language to learn for each programmer will depend on the individual. For those interested in programming, Python is an excellent choice. A programmer can see how far they can go with Python before branching out. For those who plan to pursue a career in computer science, it may be best to jump right in and learn Java first.

Why?

Because Java will help a programmer understand the inner workings of programming. Leaping from Java to Python after will allow programmers to see how this programming language makes things easier, yet they will still hold that core knowledge and skill. Learning Java is also the preferred option when the goal is to make mobile apps. Once a programmer learns Java for Android, they can easily switch to Swift to move into iOS as well. So, while Java requires more initial time and effort to learn, the ongoing benefits of learning this programming language are significant. 

When Java and Python are used together

Both Python and Java are well-suited for many people. After all, they both have large communities behind them. 

Since Python is simpler to understand and implement in most cases today, most programmers lean towards this programming language. Those interested in learning multiple languages will often migrate to Java afterward—but in this case, it is advantageous to learn Java first.

When a programmer utilizes both Java and Python within a single application, they can effectively combine these two languages to accomplish a greater objective. After all, both Java and Python are object-oriented programming languages.

For example, one could be used for typical subtasks, while you can use the other for expanding the customization of an application you’re developing. 

Another example would be using a Python-Java interpreter like Jython, which translates Python source code directly into Java bytecode. The advantage here is speed. 

Other tools include:

• JPype: Allows Python to run Java commands. 
• Jepp: Java embedded Python. 
• JCC: A C++ code generator for calling Java from Python/C++.

So, when it comes to Java vs. Python, it’s clear why these two programming languages are so popular. While Python is easier to learn and use, Java is generally more efficient and optimal for debugging. When a programmer’s top priority is development speed, Python is ideal,due to its ease of use and flexibility, especially at a smaller scale. If the goal is to create a large-scale, stable application that executes more quickly, Java is the better choice.

Learn how LogicMonitor’s DevOps and Monitoring solutions can help fit Java and Python into your DevOps strategy. Discover ways to streamline development and operations to enhance efficiency and application performance.pment speed, Python is ideal, but if the top priority is stability over all else, Java is the better choice.