Python is an object-orientated, multi-paradigm, high-level programming language that has rocketed to popularity since its inception in 1989 and release in 1991.
Python’s recent most incarnation, Python 3.0, was released in 2008. Since then, its meteoric rise shows no signs of abatement – Python now ranks as the world’s most popular programming language.
But is this Python deserved of its position at the top of the food chain?
What are the pros and cons of Python?
Table of Contents
How Popular is Python?
According to Statista, Python is indeed the most popular programming language in the world right now.
A 2019 Stack Over Flow developer study found Python to be the most in-demand programming language for the 3rd year in a row. 42% of respondents also said that Python was their preferred programming language, comprehensively Java.
TIOBE, who rank programming languages have similarly found huge increases in the use of Python over the last 3 to 4 years.
Python is used by many global corporations and massive multinational entities and organisations.
Python is not just a commercial programming language used for commercial brands and businesses, it’s a multi-purpose language used across science, education, health, engineering and virutally all other industries.
Here are some prolific use case examples of Python:
- Netflix uses Python for its recommendation engine
- Python is widely used across the healthcare industry
- Google uses Python for multiple purposes
- Python is the leading programming language amongst machine learning and AI developers and programmers
- Instagram uses Python in its Explore feature amongst other parts of the site
- Python is regularly used to model climates and other complex natural environments
All-in-all, the popularity of Python is far from hearsay. It’s a serious programming language right now and looks set to be one of the most important programming languages of the future owing to its cutting-edge machine learning and artificial intelligence functionality.
Let’s take a closer look at the pros and cons of Python:
The Pros and Cons of Python
So what are the pros and cons of Python?
Pros of Python
Versatility and Flexibility
Python is versatile and neat. It’s exceptionally easy to read and has intuitive syntax and formatting. Despite having a relatively calm learning curve, Python is still versatile and feature-rich. It’s become the de-facto programming language in many industries due to its combined versatility and accessibility. Python can be easily learnt by programming professionals who do not know Python itself but are well-versed in older programming languages.
Much of this versatility and flexibility is created by the frameworks and modules available for Python, which are tremendously diverse. But, the language itself is also intrinsically easy to work with and supports both procedural and object-oriented paradigms.
Quick to Write and Easy to Manage
Python is speedy to write with. It has an English-like syntax that simplifies the relationship between different objects. Another benefit of Python’s quick coding speed is that it’s dynamically typed and does not require curly braces to define blocks.
Since lines of code are executed one by one, it’s also easier to debug Python compared to compiled languages.
Availability of Libraries and Frameworks
One of Python’s most powerful advantages is its massive availability of libraries and frameworks covering everything from statistics to data science, operating systems, web tools and services.
Many high-level programming tasks have been scripted into libraries which makes the creation of complex code much simpler.
Python has a particularly strong suit in data science, AI and machine learning:
- TensorFlow, Keras and Scikit-learn are all superb for machine learning purposes
- NumPy and SciPy used for high-level scientific computing
- Seaborn and Matplotlib are both excellent for data analysis and visualisation
Some of Python’s most popular frameworks are:
Django
A widely used framework for web apps and services and a vast array of mid-sized projects. There are plenty of highly useful built-in features that allow you to reuse code and modify code coherents. It works very well with MySQL, Oracle, and other databases.
Pyramid
Designed for scalable projects. Pyramid is designed to accelerate the production of small web apps into much larger ones. It’s superb for beginner, novice and experienced Python coders alike.
TurboGears
With several components like WebOb, Repoze and Genshi, TurboGears is designed for the production of web apps that are easily maintainable. Excellent for small, mid-sized or enterprise-wide web app projects.
Flask
Defined as a microframework designed for small, streamlined solutions and applications. Flask is very simple and easy to get to grips with and is also ideally suited for prototype creation.
Want to improve your data skills?
See the best data engineering & data science books
Integration
Python integrates with enterprise-wide databases and software via Enterprise Application Integration (EAI). Python can also call through Java, C++, C and Java via Jython. It’s easily integrable with PHP, and .NET, so can harmonise easily with newer and older protocols, formats and technologies.
It’s worth mentioning that Python’s standard library is also very strong, diverse and easy to access and implement. By using Python frameworks and following simple guides, it’s straightforward for even the novice programmer to create complex programs and applications.
Asynchronous Coding
Python’s asynchronous coding style is flexible and easy to handle across complex coding. This multi-dimensional style is interleaving and allows programmers to avoid deadlocks and productivity bottlenecks.
Productive
Via the service of Python’s exceptional frameworks and libraries, Python is one of the most productive programming languages. Its free-flowing, accurate but humanistic syntax combines with its rich and deep functionality to create a programming language fit for the rigours of modern programming.
Strong Community Backing
Python is backed by a huge community that works tirelessly to keep frameworks and libraries up to date.
Python’s backing extends to academia and education too – the language is incredibly well supported amongst courses, boot camps and school, college and university curriculums.
Career Possibilities
Python is the most likely programming language to land you a job. Its integration with traditional or existing systems means it has retrospective compatibility with pretty much any IT system, new or old. Python can act as a ‘glue language’ – it’s not a prohibitive programming language and has wide commercial and business appeal.
In fact, Python is the most in-demand programming language amongst companies recruiting in programming right now.
Moreover, Python is the programming language of the future since it’s already really well supported by AI and ML-related libraries and frameworks.
Cons of Python
Python, like any other programming language, has some drawbacks!
Slow Execution Time
Python has been widely criticised for being slow. As an interpreted language, it’s bound to be slower than compiled languages, which can make native Python code slower to execute. In benchmark studies, Python does come out slower than some compiled programming languages like C, but the differences are often negligible.
However, for very large applications where speed is of the utmost importance, this can still be a problem.
Not Always Mobile Friendly
Python is friendly on the server side but is seldom used on the client-side. It’s also infrequently used for mobile app development. This is largely down to security issues rather than the intrinsic qualities of the language.
Moreover, Android and iOS do not support Python for app development in their programming language databases.
Still Relatively Modern
Programming languages like Java and C are the veterans of the programming language scene whereas Python is still relatively new. This means that Python is still not always chosen for various applications, even when it could be the superior choice compared to older programming languages. Programmers skilled in Python are still an upcoming demographic, even despite its rising popularity.
Design Issues
The dynamically typed nature of Python is easy to debug, but errors often only show up at runtime. This is because programmers don’t need to declare the variables as they code. So long as you’re constantly testing your code, this needn’t be an issue.
Summary
Python’s popularity is rising – that much is for sure. As an exceptionally clear and neat programming language with deep functionality and plenty of established uses in machine learning and AI, Python is well-established a powerful and flexible language for complex futuristic applications.
Despite its evident depth and complexity, Python is also one of the simplest high-level programming languages to learn, and in many ways, the most beginner-friendly of all modern programming languages.
Perhaps the greatest asset to Python is its many frameworks and libraries. The stock Python libraries are already brilliant, but the 3rd-party support really brings it alive and transforms it into the most exciting programming language right now.
FAQ
What is Python Used For?
Python is a general-purpose programming language that is not just confined to web or software development. Python is an eclectic, multi-paradigm programming language. It’s a high-level programming language, so can’t be used in hardware development.
How Easy is Python to Learn?
Python has a remarkably clean and neat syntax that closely mirrors the English language. This makes it particularly intuitive to beginner programmers. Also, Python doesn’t use squiggly brackets which makes the code easier to read in general.
Is Python Slow?
On a technical benchmark level, it is often slower to execute Python compared to other programming languages such as Java or C. However, the difference is likely negligible. Python is used in many global services and applications that are exceptionally complex.
