Reasons behind Python’s popularity despite being a slow language

Python is one of the most used programming languages, which might be due to its versatility in the field of machine learning, data science, and AI. 28 years have been passed since this language started operating.

But there is a very common question regarding this language. Why Python is so popular despite being slow? Doesn’t it stop developers to care about this particular limitation or It’s OK? In this article, we will go through every possible reason for this.

Why Python is slow?

Let’s divide the answer into 4 different things. Although there are other major reasons what I am mentioning here is most important.

Code interpretation – The python’s syntaxes and codes are more like pure English. To let the computer understand it, the interpreter put a little bit of extra effort than in the case of a lower level language like C where variable, pointers are already mentioned. Thus, better memory management happens in the C language.

Python is not compiled but interpreted – Python syntax and codes are interpreted at the runtime rather than being compiled. Interpretation is not a slow process but also not as fast as Java and C. So we can say that compilation is a fast process.

Python is a dynamic language – dynamically types means the language has the capability to declare a variable on its own. Unlike languages like C, C++, or Java where are required to declare the variable one by one. Now, leaving less for you to do, python’s interpreter takes these tasks on its own. To access each attribute, tons of lookup is required. It’s tough to optimize the language after being typed dynamically.

No Multithreading – the global interpreter lock prevents multithreading in python. It mandates the interpreter to execute only a single thread within a single process at a time.

Reasons behind Python’s popularity despite being a slow language

Why Python is still popular over these issues?

Users don’t care

Slower performance doesn’t matter that much unless the difference reaches to half a second. We are human and don’t make difference between 0.001 seconds and 0.01 seconds. Normally, it doesn’t matter for too many programmers if the code takes such little more time to execute as long as an endless program is typed or an unlimited loop is executed.

Python is More Productive

The best excuse to put against why python is so popular is that it is a highly productive programming language. Unlike Java, C, C++, it is much more expressive and concise language. Again, being dynamically typed, it takes less time and effort. It’s equally easy to learn and has the steepest learning curve. Also, it requires less code the perform an operation. Python programs are usually slower than Java, but the fact can also be not neglected that they take less time to develop (python codes are 3 to 5 times shorter than Java)

Is speed the only thing that you should consider?

Before starting with the development of an application, you need to consider several hundred factors, the speed might be one of them. But there’re also matters like suitability.

Python’s community is very big and the market is very long. Thus, it is easy to find support and instant developers if required. In addition, Python has rich libraries and frameworks for development purposes. Django is one of them. For Data science and machine learning, libraries like NumPy, Scikit learn and TensorFlow, etc. are important.

Does execution speed matters after Business speed?

These days computer hardware and servers have become the cheapest thing on the earth. Today, development time matters in most of the cases rather than execution time. The reason being the cost of employees has become one of the most expensive things to afford.

Reducing the time of development one can save tons of dollars. That is one of the most important considerations in 2020.

As far as execution speed is concerned, we can minimize it by horizontal scaling. There are more methods to increase the scalability of python.In 2020, when we have the high computing power and multi-core processors that are getting cheaper day by day, the speed and performance issue can easily be committed, but the cost of human labor can suck your pocket to null. Also, the Human cost will keep increasing over time.

Not only the idea will save you a lot of money but will also improve your competitiveness.

Let me ask you a question.

Suppose you are the CEO of a company. Now, what will you choose? 1. Completion of the project in 6 months. 2. Completion of the same project in 4 months with extra pay for servers. 

Comment me your choice for sure.

If execution speed is your concern then you will go with the first option. However, if you focus on quick development with faster innovations, you will go with the 2nd.

That’s the evidential proof as an explanation for python becoming so popular. The time required to build an application is much lesser as compared to other programming languages.

Is the speed only factor that one should consider?

Now, I hope, as we just talk about speed vs business, you are familiar with the fact that there are several factors that you should consider. Though speed is one of then but language suitability matters to a great extent.

Is Python good for speed-intensive applications?

So far, we have discussed, why python is so popular despite being a slow language. Now, what if you strictly require high-speed execution? In this context, I would say Python is not the one you should go with. If you think to still optimize it, that is not going to fulfill the craving of more speed. Here, other programming languages like C, C++, and C Sharp should be used.


Python is widely used even though it is slower, just because it is more productive and the company can optimize expensive resources. There is a rich set of libraries and large community support.

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