Python is a high-level, general-purpose programming language, which means it can be used to solve any problem that can be written in code.
It is widely used in scientific and specialized applications like data science, artificial intelligence, machine learning, computer science education, computer vision and image processing, medicine, biology, and even astronomy.
Thanks to web development frameworks like Django and Pyramid, Python is quite popular on the web. It is used for back-end development, so the area of web development users do not see, in other words, the server side of an app.
To summarize our introduction:
Both languages are two the most popular programming languages among software developers - comparing them head to head is not going to give you a straight answer about which language is better. But it is good to know which language performs specific tasks better or does things that the other language simply cannot.
Performance & Speed
We can explain it better based on the Pinterest example.
So, for example, Facebook, which generates an enormous amount of data, is more likely to use JS, so the users do not have to wait.
The other side is that processing data and solving machine learning problems is better to choose Python. Python is easy to read and use, even in the complicated situations of handling CPU or using GPUs.
Python might take longer to respond, but there are possibilities for Python to perform quickly if you optimize it accordingly - starting from C programming language with the help of NumPy or by using Cython.
It means that Python provides support for object-oriented programming, functional programming, imperative programming, and procedural programming.
Scalability is considered a significant factor when comparing these two languages - it contributes to the strengths of the languages when managing a massive amount of users and storing a huge amount of data.
Node.js has the already mentioned multithreading. Thanks to this feature, it can improve scalability by increasing the number of threads.
Python uses Global Interpreter Lock (GIL). GIL makes only one thread running at a time. What goes with it is that using multiple processors with threads is harder but not impossible. Python is trying to overcome this issue, and developers can use a multiprocessing library. It offers them functionality for distributing work between multiple processes using multiple CPU cores.
Developers automatically have access to REPL with the installation of Python on their system.
There are two types of data - mutable and immutable. In Python, everything is treated as an object, and Python supports both - mutable and immutable objects.
For instance, the set is a mutable data type, but custom classes are also mutable, plus list, byte array, and dict. Immutable objects such as tuple, string, int, and float also exist.
Reference type means that objects are constituted by multiple properties stored as a reference.
Primitive type - data is neither an object nor has a method.
All primitive values in JS are immutable, but objects and arrays are mutable.
Python raises an exception if a function is called with incorrect parameters. It accepts some additional parameters with the special syntax “*args”.
Both languages support inheritance. The difference lies in their types.
JS is not considered as a pure object-oriented language because it only supports inheritance by relying on a prototype-based inheritance model.
Python, on the other hand, uses a class-based inheritance model.
An important distinction is also the fact that Python does not have a way to inherit from instances, and JS has.
Strongly-typed vs. Weakly-typed
Libraries and Modules
Python comes with many included modules and libraries. Thanks to this, developers can easily perform tasks for all sorts of fields, e.g., data analytics, machine learning, scientific computing, etc.
JS does not have as many modules as Python, but it does include the date, math, JSON, and regex. In addition, you can use extra functionality through the host environment.
It can also build web servers and develop server applications, thanks to Node.js for supporting the back-end side of the project.
However, Python is the best choice for machine learning, artificial intelligence, data visualization, and data analytics. Regarding web development, Python is powerful in the back-end and has several libraries and frameworks like Flask, Django, or Pyramid.
For quite some time, Python was considered a language not suitable for mobile development. It was true in the past. The IT world is changing rapidly, and there are modern solutions that have been developed and changed the way we can see Python.
Python can be used to create several types of programs for multiple platforms. Since Python is cross-platform, it allows the developers to use GUI frameworks like BeeWare and Kivy and transform the code into versions that work not only with iOS and Android but with other platforms as well. As a result, developers do not need to work on two entirely different versions of the same app based on different programming languages.
Summarizing the above:
Is Python the language for mobile development? Yes.
Is it the most suitable option? Probably not, despite the modern solutions available. Python is not iOS or Android native, so many developers hesitate to use it while creating a mobile app. It may cause slow deployment or make it more complex.