April 07, 2023 • 180 Views • 14 min read
Tetiana Stoyko
CTO & Co-Founder
One of the most important steps in the software development process is to choose the tech stack, you are going to use as a basis for the whole project. Yet, what is even more important during making this decision - is to choose the main programming language.
Frankly speaking, in most cases, development teams narrow down to the most popular and obvious solutions like JavaScript, HTML, CSS, or Python. First of all, they are popular for a reason, and it is very easy to find various resources, documentation, guides, and articles about any of these popular languages. Additionally, their popularity results in a large and strong community of developers, who are constantly sharing their experience and trying to somehow upgrade/improve some aspects of their beloved programming language, i.e. there are numerous solutions for any use case when it comes to well-spread languages.
So, let’s examine Python in detail as one of the best possible illustrations of the advantages of commonly used programming languages and try to figure out what are the benefits of Python, what Python is used for, and whether there are any limitations of Python programming language.
First things first, let’s briefly talk about the technology itself. According to Statista, Python is the 4th most used popular programming language worldwide as of 2022. Clearly, this is an important aspect, yet not the most enlightening information about Python. Therefore, to add some more details, Python is a general-purpose object-oriented programming language, which also belongs to high-level interpreted languages.
To make it simple, let’s examine each of these statements:
General-purpose means that there are no limitations of Python or other specifics to using this technology. Thus, Python can be used for most kinds of applications, regardless of the industry they belong to. Yet, to narrow down the potential list of use cases, we can name a few most popular types, among which there are data analysis, DevOps, or web development.
Object-oriented, as the name says, is because Python concentrates on objects, which developers are going to work with. Yet, at the same time, Python supports the possibility of choosing function programming, i.e. concentration on functions to be done.
The High-Level status is another benefit of Python, which makes it more understandable and human-like. Not in the way of behaving as if the program was human, but rather being easily readable, using actual words and definitions as functions and operators. As a result, it is easier for the developers to read and review the code, which is written in “human language”, that is compiled later to suit the processors and other machinery.
Python is Interpreted because the actual source code is compiled into so-called bytecode. Later it is run by Python Virtual Machine (PVM), which translates it into machine code during the runtime.
So, it seems that there are almost no limitations to Python programming language. So, how can we describe it and tell the most suited use cases? Well, the easiest way to do so is to simply name a few apps that use Python.
Among them are Instagram, Reddit, Dropbox, Facebook, and Google. Additionally, there are numerous software solutions and apps, based on Python, yet designed for very specific industries or tasks, so they are not as brandy or well-known as the foregoing.
Anyway, to make it even more simple and more obvious, let’s find out what are the benefits of using Python. Yet, before it, we should say a few words on the limitations of Python.
First of all, despite the high pace of development, the overall Python working process is less effective and much slower than the competitors. One of the major reasons for this is the Interpreted nature of Python. So, while other programming languages are compiled before the run, Python is translated line by line on the run. Clearly, it is much easier and faster to compile the whole code at the very beginning rather than doing so step-by-step.
Additionally, Python does not support multithreading, at least as a basic feature. Instead, it uses Global Interpreter Lock (GIL), which is limited to processing one thread at once. So, on the one hand, it improves the level of threading security and performance of single-threaded apps.
On the flip side, because of GIL, it becomes impossible to use all the features and advantages of modern hardware and perform multiple processes simultaneously. One of the possible solutions to this issue is to use Python asynchronous programming and multiprocessing functionality.
Python struggles with high memory consumption. As a matter of fact, this programming language requires a lot of memory. Despite various solutions for memory management like a garbage collector, Python still shows not the best results in this field. For instance, even if an object is not used and was removed, it won’t return the resources right away.
To cut a long story short, running out of memory is a very common occurrence among Python applications. This is one of the major reasons why Python is not a popular choice for mobile applications development, or front-end apps as well.
Eventually, despite the platform-agnostic and general-purpose nature, Python is not as popular for cross-platform app development. Apart from the previously mentioned issue with the high level of memory consumption, Python is not as competitive as other languages. For instance, most mobile platforms do not use it as a native language. Instead, the most popular ones (Android and iOS) are based on Java, Kotlin, Objective C, or Swift. So, all the foregoing facts result in choosing other programming languages and libraries or frameworks, based on them, for mobile development instead of using Python for the same purposes.
One of the most well-known facts about Python is that it is probably one of the easiest programming languages to learn with a great learning curve. Frankly, it is commonly considered ideal for newcomers, allowing them to learn the overall coding logic and train the “developer mindset” with the use of simple and understandable syntax and other tools, concentrating more on the software development life cycle goals and the ways to achieve them.
Python is one of the oldest programming languages, that are still relevant today. Combined with the fact, that it is also very popular, easy, and has one of the largest development committees, Python seems to be one of the most flexible coding languages.
To rephrase it, Python developers are constantly creating various new add-ons, libraries, frameworks, etc. Additionally, Python is highly compatible with different third-party software solutions. Among them, we can name Django and Flask. To add more, apart from compatible frameworks and libraries, thanks to countless extensions, Python has an opportunity to be ported to other programming languages. For instance, There are versions of Python for Java or .Net like Jython, IronPython, Cython, Gython, and many other “ythons”.
Truth be told, the benefits of Python are not limited to internal extensions and Python-based frameworks or standard libraries. Yet, thanks to them, Python can be easily combined with almost any other programming language, if there will ever is such a requirement. Mainly, this is possible thanks to the previously mentioned plural “ythons”, which allows Python portability, and the Python Virtual Machine, which translates it into the needed code.
As we said before, it is a very flexible platform-agnostic and general-purpose language. So, the list of potential use cases is limited by the developer’s imagination. Yet, truth be told, some common technical Python limitations may bring unwanted challenges during the development of some types of applications.
This is why, despite the independence of this programming language from the platform, it is not as popular for mobile app development, when comparing Python vs JavaScript and related technologies. One of the major reasons is its enormous memory consumption.
However, some enthusiasts are still using it for mobile apps, combining Python with other cross-platform frameworks, even despite that this is not as popular approach, as the major competitors in the field of mobile development.
Among other potential use cases, probably the first one, that comes to mind, is the scientific purpose. It is a well-known fact, that Python is extremely famous among scientists thanks to its adaptivity for researching. For instance, one of the most essential software tools for this field of expertise is the SciPy collection, which includes mathematical algorithms and other useful functions for calculations.
Besides, Python is a great instrument when it comes to process automation. It is suited for writing scripts, that are mainly used for robotic process automation. For instance, Python is commonly used for creating web crawlers. Additionally, these process automation and scripting features are also beloved solutions for testing automation. Many such automation instruments for Quality Assurance are at least partly based on Python and Python-related technologies.
To make use of all the advantages of using Python, you will need to hire a Python developer, who is familiar with its extensions and other technologies, based on Python. Actually, the main benefits of Python are hidden in third-party software and different extensions. In other words, basic Python is very limited in its capabilities.
To be fair, most Python developers have limited experience in working with Python because it is often used as a training language for newcomers. So, despite that, it has one of the biggest dev communities, and it may be challenging to find a truly experienced Python software engineer, who knows how to use the full potential and advantages of using Python. One of the best possible scenarios to do so - is to consider outsourcing. As a matter of fact, it allows you not only to find a required specialist faster but also to get a niche-experienced developer, whose services may be cheaper than alternative applicants from your region.
However, before contacting your outsourcing vendor, check their background. For instance, you can check out our case studies in order to better understand our experience in working with Python.
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Python can be used to build a wide range of software products, including web applications, desktop applications, mobile applications, scientific and numerical computing applications, data analysis and visualization tools, artificial intelligence and machine learning applications, and more.
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