Python vs Groovy

Differences Between Python vs Groovy

Python is a general-purpose programming language which is interpreted and focus on “readable-code” like feature. It was first released in 1991 by Guido van Rossum.

Groovy is an object-oriented, static and dynamic language whose feature is similar to Python. It was first released on January 2007.

Python has the support for various type programming paradigm and provides the developer with enormous standardized libraries. Python is object-oriented, imperative, procedural and functional in nature.

Groovy is compatible with Java syntax, build for the Java platform. It can be utilized equally well as a programming and scripting language. Just like Java, it can be compiled to JVM bytecode and work efficiently with other Java code and its libraries. There is a process called AST i.e. Abstract Syntax Tree, which allows the developer to hook into its compilation process and can alter to its own requirement.

Python has a great deal of usage on the web development ecosystem. It’s docile in nature, any naïve programmer can get along with its syntax. Also, its collection of massive libraries which provide a set of features to achieve a complex task makes it the most appreciable tool for software writing.

Just like Java, Groovy uses a bracket syntax. Its resemblance with Java language makes it highly popular among Java users. It is object-oriented in nature and can be converted to bytecode for JVM, which makes it highly compatible among Java users. Most of the Java code is also syntactically valid Groovy code.

Python can be effectively utilized to automate the functionalities. Its usage is enhanced in the last few years, ranging from data analysis to infrastructure management. Since its docile in nature, any naïve programmer needs to focus on business logic rather than spending too much of time learning language syntax feature.

From version 2 onwards, Groovy can be compiled statically and performance is near to Java. Although Groovy code is syntactically valid with Java, but it appears to be more compact than Java code because it does not require all the elements which Java needs. This one aspect of Groovy makes it possible for Java programmer, to learn it gradually. It has a native support for markup language like HTML, using DOM syntax. Similar to a scripting language like Perl and Ruby, Groovy is parsed, compiled and generated before its execution.

Python has built-in support for multi-thread and concurrency like a requirement. With Groovy has support for GPars, a developer can include concurrency feature in his/her program effectively. Python provides concurrency, but the developer must take care of isolation, and do a resource management, since its resource-intensive in nature. But an efficient programmer can cope with this constraint easily.

Head to Head Comparison Between Python and Groovy (Infographics)

Below is the top 8 difference between Python and Groovy:

Key Differences Between Python and Groovy

Both Python vs Groovy performance are recommended options in the business. Let us examine some of the key difference between Python and Groovy:

• Python is scripting in nature, this has to be interpreted whereas Groovy is an object-oriented programming language for Java platform, can be converted to bytecode for JVM.
• Python has readable code, hence it is flexible and docile in nature whereas Groovy has more object orientation in nature, having a curly bracket like syntax.
• Python does not provide built-in concurrency mechanism whereas Groovy with GPars gives several high-level.
• Python has a better set of tools for creating games since its GUI kits are considerably stronger than Groovy.
• Python binding and application styling are a little better for creating applications than Groovy but at the same time, groovy is strong in object-oriented programming, which allows meeting design related complexity with ease.
• Python community is very stable and diverse but when it comes to innovation it’s slower than Groovy, whereas Groovy community although less in size, but coming up with more features.
• Python still gains an upper hand when it comes to explicit syntax and thus is more readable whereas Groovy is concise, fast and easy to set up.
• Python is a preferred language among data scientist especially for machine learning whereas Groovy is an ideal choice for object-oriented programming.
• A Python approach is more directly toward programming and thus makes everything obvious to programmers whereas Groovy code is readable and concise similar to Java, although less code required to achieve complex tasks.
• Python is easy to adapt to meet standard programming requirement but can be tricky for complex web development whereas, with Groovy, Grail-like web framework, one can achieve complex feature with efficient object-oriented design

Python and Groovy Comparison Table

As you can see there are many comparison between Python and Groovy. Let’s look at the top Comparison between Python vs Groovy –

Conclusion

Both Groovy vs Python languages have their usage in the diverse area of technology whether its web development, machine learning etc. Groovy arriving from the Java-like a streak makes it a capable contender for the future. Python, on the other hand, has its own streak of capabilities in the multiple areas. One of them is Machine learning, which is latest on the artificial intelligence forte. Apart from these advantages, both Groovy vs Python has their own set of community, which provides support on multiple use-cases.

At the end of the day, it’s the developer’s ability to perceive language concepts and dealing with the complexity that stands out. Groovy can provide you with the same speed and performance which Python can deliver, and vice-versa. It’s projected requirement and developer’s comfort level with a certain language, which would decide the usage. Project requirement might suit the Python, but if the developer has a stronger sense of understanding for Groovy, that won’t be too good for the project. Thus, usage and performance of a language lie on the above-mentioned aspects which need to balance out. The final choice of technology selection to build a complex application would eventually boil down to expertise and business need.

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