Limitations of Python

Python is a very popular language. Every programming language has shortcomings so does Python. Following are important shortcomings of Python programming language:

  • Performance and Speed – It has been proved that Python is slow in comparison to C/C++ and Java. Since Python is interpreted language, it can be slower in comparison to compiled languages. Python is interpreted language and the execution of the program is line by line which causes it to slow down. Speed of the Python has been criticized for long and has been addressed in some part in last couple of years.
  • Not backward compatible with 2.x versions – If you are a beginner you should start with 3.x version. Officially Python 2.x version is declared as legacy. Same is not with other languages like Java which is backward compatible. Python 3.x was written to keep future of the language in mind. Python 3.x code is not backward compatible.
  • Mobile development – Python is considered suitable for various type of applications like desktop applications, server side applications, machine learning and artificial intelligence. However, Python is not considered good for mobile development.
  • Memory Consumption – Python requires more memory because it is dynamically typed language. Variable in Python can hold any type of value so sufficient memory need to be reserved. Due to this reason Python is not considered suitable for memory intensive tasks.
  • Web development capability – Python does not come with built-in web development capabilities. Traditional Python libraries are under developed for working with web browsers and enterprise web applications. That is why, developers use Python web frameworks like Django, to develop web applications.
  • No support for comment blocks – Python does not support comment blocks. If you have to write comments for a code then you have to do it for each line. Block comments help programmers to read and understand the piece of code. Block comments also help in creating a well documented code.
  • Inadequate support for Python modules – Python is open source and managed by community. New modules are developed and shared by the community. The quality of the module may vary and may not follow the standards. So whenever you want to use a new module you have to analyze first and pick the right module.
  • Requires more testing effort – Since Python is dynamically typed language it requires more testing. Since variables can hold any type of value, the number of test cases to be tested are more in comparison to the statically typed languages.
  • Database access – Python database access modules are considered underdeveloped. Many limitations are found in Python while working with databases. Due to this reason Python is not considered very much suitable for end-to-end enterprise applications. Python is used only for certain layers of enterprise applications.
  • Runtime errors – Since Python is dynamically typed language, some errors come only during runtime. The ease of assigning any type of value to a variable causes this problem. A piece of code expecting a certain type of value can be passed any type of value as it is allowed in Python. Whereas in other language like Java, type of variable is declared at the beginning itself and program will work with that type of variable only. As mentioned earlier more testing is required else this could result in more runtime errors.