Back-end technologies form the fundamental backbone of every tech stack. Though the back-end of any application remains invisible to the users and that’s where all the magic happens. It’s no secret that Python is one of the friendliest and preferred open-source languages with an emphasis on code readability.
Let’s have a quick look at a few of the key reasons as to why Python is referred to as an ever-green coding language for all backend developers and has held the number one position as the ‘Most Popular Coding Language’ since its nativity in 1991.
Let this case-study become a self-explanatory example in proving Python’s significance.
1. Ease of work
Python is renowned for its simple syntax and shortcode length. This, paired with the fact that there are ample tutorials available on its usage, makes it fairly easy to learn. Moreover, Python being extremely well-designed and versatile is a platform-independent language and can be used on a wide variety of operating systems. This means the programmers can spend a lot of time figuring out the code and how it works on their particular development project.
Python is therefore an ideal backend language due to its simplicity and consistency, where the developers are able to write reliable systems with a vast set of libraries belonging to Machine Learning, Keras, TensorFlow and Scikit-learn. Python’s extensive set of libraries and frameworks can be extremely useful and time-saving, which results in quicker turnover times and more productivity. Data analysis and business analytics using Python have gathered a lot of interest recently.
2. Ample web application frameworks
Python’s countless resources come in many forms, including a wide variety of web application frameworks. Here are just some you can choose from depending on the needs of your web apps such as Django, Flask, and others such as Bottle, Tornado, Hug and CherryPy.
Also, the prominent use cases of Python are Web Development, Artificial Intelligence, Machine learning and its subfields, Data Science, Big Data, Internet of things, Embedded systems, Fastapi, Ethical Hacking. The list is huge!
3. Code Readability & Lesser number of lines
Python reduces the coding load around 4 times by diminishing the coding lines tremendously, say we are using Java for printing a simple ‘Hello World’, we would need to type the following code lines:
whereas, in Python, the code changes to a single line as follows:
The codes in Python are very easy to understand with proper indentation and as the language resembles plain English.
4. Dynamic Typing
In Python, we don’t have to pull our hair and worry about whether the value shall be string, int, float and more. All we need is a simple, dynamic variable, to begin with!
5. Ease of Learning
One of the primary reasons Python is highly appreciated is that it’s instinctive and quite easy to learn, compared to all other programming languages. According to Lifehacker’s poll, it’s the #1 most popular programming language for first-time learners.
But Python doesn’t just facilitate the learning process, its readability but also makes communication among programmers working on the same project later a smoother experience. This means that if another programmer works on later additions to the code, they would face no problem understanding and working with the original code. Although Python is deemed to be slow when compared with other backend languages, like C++ or Java, this fact has not actually slowed down its growth.
6. A Myth that Python is Slower
As Python is an interpreted language. Also, if we run your server on a 1980’s computer then we shall consider Python slower. However, Python is way faster now with Python 3.x performance improvement.
Python vs Golang vs Node
There are a few things to be considered when selecting which might be right for us.
Golang was created keeping scalability in mind. It comes with an in-built concurrency to handle multiple tasks at a particular time. Python uses concurrency but it is not inbuilt as it implements parallelism through threads. This implies if we are going to work with large data sets, then Golang would seem to be a more suitable choice.
Node.js spares the need to create a large monolithic core as we are able to easily create a set of microservices and modules and each of them shall communicate through a lightweight mechanism and run its own very process. This in return helps to easily add an extra microservice and module, resulting in a flexible development process.
Also, any Node.js web app can be easily scaled both horizontally and vertically. To scale it horizontally, we need to add new nodes to the system whereas to scale it vertically, all we need to do is add extra resources to these nodes.
Python is referred to as both CPU and memory unfriendly but with a huge number of libraries, Python performs efficiently all the basic development tasks. Golang comes with inbuilt features and is more suitable for microservices software architectures.
Python outshines when used to write codes for artificial intelligence, data analytics, deep learning, and web development, whereas Golang is mostly preferred for system programming and is loved by developers for cloud computing and cluster computing applications.
4. Community & Library
One of the major advantages of Python is its wide number of libraries and its large supporting community. As we know Golang is still a growing language and does not have the number of libraries and community support that Python commands, but its adoption quality and rate of growth is commendable. It still is expanding every day!
In Node.js, libraries and packages are managed by NPM (Node Package Manager), which is one of the biggest repositories of software libraries. NPM is fast, well-documented, and easy to learn to work with, whereas in Python, packages and libraries are managed by Pip, which stands for ‘Pip installs Python’ and is reliable, easy to use and very fast, so developers find it really handy to work with.
As we know most startups have a limited budget when time is important and is also connected with money. A startup needs to find its supporting investors quickly and craves the best way to grow. Also, since they act in an environment of total uncertainty, hence flexibility matters. While testing out the new ideas, a company needs to be ready to implement any changes as dictated by the current demand from the market. Python is often considered one of the best choices for startups for building the MVP as quickly as possible to attract investments and test the hypotheses as implementing new features becomes easy, creating iterations and scaling the business becomes faster. Also, integrating with other software related to the product becomes easy and effective, even after the product release.
Go-lang or NodeJS or Python, it's like choosing between the top 3 restaurants to eat in our city. Depending on the current need of the situation, we can choose any of the three. Python can lead to a longer delivery roadmap but when considered from a management perspective, this turns out to be the correct decision when considering the long-term benefits.
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