Are you a non-technical person? Here's a question for you then. When you sit with paper to cut, what do you prefer- a super sharp knife or a pair of scissors? What about when you cut fruits? The answer changes based on the situation. Right?
So, you would have to choose between the tools depending on the situation. Similarly, we need to select a language based on the project in software development too. Everything depends on the kind of project.
However, MarsDevs focuses on the pros and cons of using Python as a language for web development in this blog.
Python is one of the most potent and advanced languages for web designing and development. Also known to be highly efficient and adaptable, Python for websites offers you dynamic typing capabilities.
It is versatile, and the developers can create scientific and system applications using games, graphics, web applications, etc. Thus the websites that you start with Python are almost always high functioning and thriving.
There is one more benefit of using Python to create websites. You can easily use and distribute it for free. Also, it is an open-source product like Perl, Linux, and Apache. So, you can get any coding information you need on the internet.
In addition, Python gives your business flexibility in the marketplace in this world of digital systems. Now you can readily interact with other industry sectors.
Python has a name among the small companies. However, companies like Google, Microsoft, Dropbox, etc., also build their websites using Python. Even four out of five developers claim that Python is their primary language!
The different fields that use Python can include web development, AI (artificial intelligence), deep learning, etc.
Python is web-ready but is it the right choice for you? While the web development community primarily divides itself based on their opinion regarding the effectiveness of Python as a language for excellent websites, let us weigh in respect to the pros and cons now.
Python is extremely easy to use for your web projects. Why?
If you compare it to other languages, Python does not limit itself in its world. It is flexible. Thus, you can use Python to integrate several implementations and languages in the programming process efficiently.
As it has multiple paradigms, it supports numerous programming styles. These styles include functional, object-oriented, procedural, etc. Flexibility is the reason Python is so famous among startups nowadays.
Developers call Python a productive language. Well, how can a language be productive? The reason it is practical is the simplicity of the language.
This simplicity allows the developers to focus on solving the real problem. You would not need hours to understand the syntax. You can write less code and get more results instead.
Consider the traditional languages like C or C++. Every time you run the program on a different platform, you need to change the code. This is not the case with Python. You write once, and that's it. You can run it anywhere.
Do you want to represent some data through the website of the app you create? Python is a super-efficient option for developers in that case.
Firstly, each unit of an Asynchronous code runs separately. So you can write and maintain the code better. One of the reasons it does not take a lot of effort to write or keep this code is that there are no deadlocks or any other confusing issues.
You have several packages and libraries to develop numeric applications, imaging libraries, toolkits like MayaVi, etc.
However, the most common ones include SciPy or Scientific Numeric Library, Pandas or Data Analytics Library, iPython or Command Shell, Numeric Python or Fundamental Numeric Package, and Natural Language Toolkit or Library for Mathematical and Text Analysis.
We all know Machine Learning is gaining importance fast, and rightfully so. More developers want to incorporate them into their projects. It is easy if you choose the correct programming language.
Its an open source technology so you can use it per your requirements and the python community is always there to help you.
According to Jean Francis Puget, python is the top language for AI and machine learning projects. So, you know the right way now.
Apart from these advantages we mentioned above, there are some limitations to Python. Let us address those.
But this was an advantage. That's what you are thinking. Right? While simplicity is an advantage, it is also one of the critical drawbacks.
When you have a program that habituates itself with a simple syntax, switching languages with a more complex syntax like Java gets tough.
You can be stress-free when you choose Python for programming. However, when you interact with the database, it can often lag.
This is because Python's database access layer is not as well developed as popular technologies like ODBC.
We already know that Python is a dynamically typed language. Thus, the data type of any variable can change without notice.
As a variable containing an integer might hold a string later, you are more prone to run-time errors.
Python as a programming language uses a large memory. This is to provide simplicity to the developer. While it seems reasonable, this can be an issue if you prefer memory optimization.
Python is an interpreted programming language. Thus, it is slower than others.
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