It is true that when you sit down to write code in python, obviously it takes fewer lines, fewer keystrokes, and simpler APIs, but efficiency and speed is very essential to a programmer after spending hours debugging a code error.
Python is one of the most popular programming languages and coding is outdated and you have to know that increase in Machine Learning and AI applications have reduced coding knowledge to it’s bare minimum. For example: I have worked with Azure Machine Learning Studio where I had to load data to the machine and it’s algorithms display a lot of data metrics you can use to make analytical decisions.
The disadvantages of Python as a programming language
- Precision and Speed
One of the tradeoffs for being an interpreted language is that Python code runs more slowly than that of most compiled languages.
Python is slower than C or C++. But of course, Python is a high-level language. Sometimes plotting graphs with Matplotlib could take some time before you are shown error feedback as display message.
2. Mobile Development
Python is not a very good language for mobile development. It is seen as a weak language for mobile computing. Better learning paths like SWIFT for iOS and Kotlin for Android programming, also Java Script for web development (Html, CSS, React).
3. Power Consumption
Python is a power-hungry language.
4. Runtime Errors
Python programmers cited several issues with the design of the language. Because the language is dynamically typed, it requires more testing and has errors that only show up at runtime.
5. Memory Consumption
Python is not a good choice for memory intensive tasks. Due to the flexibility of the data-types, Python’s memory consumption is also high.
6. Low availability of UI / Visual component
If you want to make a 3D graphic game or a software with attractive UI, then most of the time you have to choose from Java, C++, C#, Swift, Delphi etc. not Python. Cause available GUI Library / Frameworks for Python are not yet that rich.
7. Database Access
Python has limitations with database access. As compared to the popular technologies like JDBC and ODBC, the Python’s database access layer is found to be bit underdeveloped and primitive. However, it cannot be applied in the enterprises that need smooth interaction of complex legacy data.
8. Python is Not suitable for Low Level programming
Python is not suitable for low level programming. When you are dealing with low level programming e.g., System programming, OS Development, Kernel, Embedded systems; you need something like NASM, C, C++. For Dealing with hardware, Python is not a good choice at all.
Be intentional in your life decisions. Python will be helpful if you are in the data science career path.
Front end language, Back-end language and Database Language. You have to be a Nerd to learn programming. Coding should exist as a hobby and career.
Conclusively, spending a few days getting to learn python and doing a few python example project tutorials is probably a good idea if you are in the data science career path.