Python is one of the most popular data science programming languages in the world. It's popular because of its built-in mathematical libraries and functions for solving hard maths problems and performing data analysis. Pandas, Numpy, SciPy, and Matplotlib, among other libraries for data scientists, are valuable for scientific computing.
As popular as it is, there are several disadvantages of using Python as well. Python's main disadvantages are its slowness during execution, problems switching to another language, weakness in mobile app development, excessive memory consumption, and lack of acceptability in the business development industry.
Here are the top 3 reasons why Python is not a good choice for large projects:
1. Using other languages is difficult
Many programmers despise creating code in languages other than their own. This is because they believe that other languages are much more difficult to learn. They may be used to programming in Python, the most user-friendly programming language on the planet. If you are a Python aficionado, you may be encountering this issue. Pythonistas adore the language because it is simple, widely used, and powerful. The fact that Python is easy is one of the main reasons we enjoy it.
2. In the field of business development, this language isn’t used much
Python is a powerful programming language that poses few problems for programmers, and it has sparked a lot of interest in the large-scale web development business. Python has yet to make inroads into corporate development, despite its widespread use. Python's database access limits could be one of the main reasons behind this. Python's database access layer is considered immature and unsophisticated when compared to important technologies like JDBC and ODBC.
3. Slower to execute
Python is substantially slower than other programming languages like Java, C++, PHP, Javascript, Swift, and others when it comes to execution time. This is a major concern for programmers when creating huge programmes with many lines of code. Python is a programming language with dynamic typing. That is, it performs many of the same programming tasks that static coding languages do during runtime compilation.
Read more:
R vs Python: which is the best programming language for data scientists?
What is Pandas in Python? Here's all you should know
3 Python programming frameworks game developers should master
Java vs Python : what are the significant differences
