Differences Between Python vs Scala
Python and Scala are the two major languages for Data Science, Big Data, Cluster computing. Python is an interpreted high-level object-oriented programming language. It is a dynamically typed language. It has an interface to many OS system calls and supports multiple programming models, including object-oriented, imperative, functional and procedural paradigms. Scala is also an object-oriented programming language. It is used to provide support for functional programming and a strong static type system. Scala gets its name as a blend of ‘scalable’ and ‘language’, where it can scale according to the number of users, and here, everything is an expression. It smoothly integrates the features of object-oriented and functional languages.
Let us study much more about Python and Scala in detail:
Both Python and Scala are the general-purpose programming languages that support the Object-Oriented model to create applications. Both Python and Scala languages are playing a very crucial role in the growth and future of data science projects. But at the same point in time, both Python vs Scala have a few pros and cons.
Pros and Cons of Python and Scala
Following are some pros and cons of python and scala:
Python (Pros and Cons)
Scala (Pros and Cons)
Head to Head Comparison Between Python and Scala (Infographics)
Below is the top 9 comparison Between Python and Scala:
Key Differences Between Python and Scala
The differences between Python and Scala are explained in the below-mentioned points:
- Python is a dynamically typed interpreted language, whereas Scala is a statically typed compiled language.
- For development, Python seems more productive, and it doesn’t need compilation for most cases which makes development faster and rapid. In the case of Scala, a compilation is too slow; thus, the development of the Scala application takes more time.
- Python has huge libraries as per the different task complexities. In the case of Scala, its libraries are small.
- Python has a lot of available platforms, but CPython is mostly used, whereas, for Scala, applications run in JVM.
- In the case of Python, the low level can be achieved by extending using C and C++. For Scala, it is not easy to achieve a low level and mostly rely on JVM.
- Python has decent memory usage, whereas Scala has more memory consumption.
- Python is much easier to learn than Scala.
- Being a dynamic language, Python executes slowly than Scala
- Python is less complex to test because of being dynamic, whereas being static; Scala is good for testing
- Python is a mature language, and its usage continues to grow. But in the case of Scala, it doesn’t have widespread use or knowledge base.
Python and Scala Comparison Table
Following is the set of points that shows the comparison between Python and Scala.
|BASIS FOR COMPARISON||Python||Scala|
|Definition||Python is a dynamically typed Object Oriented Programming language so that we don’t need to specify objects.||Scala is a statically typed Object Oriented Programming language, and thus we need to specify the type of variables and objects in Scala.|
|Performance||Python being a dynamically typed language, creates extra work for the interpreter at the runtime. It has to decide the data types during runtime.||Scala being a statically typed language, uses the JVM, and thus, it is 10 times faster than Python. Thus while dealing with large data process, Scala should be considered instead of Python.|
|Platform||Python has an interface to many OS system calls and libraries. It has many interpreters.||Scala is based on JVM, and its source code is compiled to Java Byte Codes then executed by JVM. It is basically a compiled language, and all source codes are compiled before execution.|
|Simplicity||Python is easy to learn and use. Its English-like syntax contributes to its popularity. It is easy for developers to write code in Python.||Scala is less difficult to learn than Python. However, for concurrent and scalable systems, Scala plays a much bigger and important role than Python.|
|Concurrency||Python doesn’t support proper multithreading, though it supports heavyweight process forking.||Scala has a list of asynchronous libraries and reactive cores, and hence it is a better choice for implementing concurrency.|
|Type of Safety||Python language is dynamically typed and highly prone to bugs whenever there is any change to the existing code. However, it can be used for small-scale projects, but it doesn’t provide scalable feature support.||Scala is a statically typed language that provides an interface to catch compile-time errors. Thus refactoring code in Scala is much easier and ideal than Python.|
|Testing||Being a dynamic programming language, the testing process and its methodologies are much complexes in Python.||Scala is a statically typed language, and thus testing is much better in Scala.|
|Support||Python’s Community is huge compared to Scala||Both are open source, and Scala also has good community support. But still, it is lesser than Python.|
|Advanced Features||Python has proper data science tools and libraries for Machine learning and Natural Language Processing (NLP). Scala does not have that many tools to work on machine learning and NLP.||Scala has various existential types, macros and implicit. The syntax with advanced features may be a little hard as compared to usual functions. Frameworks and libraries, however, allow the developers to make good use of these features.|
After comparing Python vs Scala over a range of factors, it can be concluded that the selection of any of the language depends entirely on the features that best fit the project needs as each one has its own pros and cons. So, before deciding on a language for programming, developers should learn and analyze different Python and Scala language artefacts. Thus, based on the project need, time of work, and other discussed aspects, any one of these languages should be selected to reach the desired goal.
This has been a guide to the Differences Between Python vs Scala. We also discuss the Python vs Scala head to head comparison, key differences, and infographic and comparison table.You may also look at the following articles to learn more –