3 Reasons why Python is not suitable for big projects (2024)

FAQs

3 Reasons why Python is not suitable for big projects? ›

Mobile Application Development

However Python is strong in desktop and server platforms, that is it is an excellent server-side language but for mobile development, Python is not a very good language which means it is a weak language for mobile development. It is very rarely used for mobile development.

Mobile Application Development

However Python is strong in desktop and server platforms, that is it is an excellent server-side language but for mobile development, Python is not a very good language which means it is a weak language for mobile development. It is very rarely used for mobile development.

In big projects, Python isn't forbidden. But it might not be the only language that's used. You can use Python like glue to piece together parts in C, Go, or Clojure. If you've already reached your build-it-yourself point, remember that no one language is the Holy Grail.

Here are some of the drawbacks of Python. Not Very Fast: Python is much slower than more efficient languages like C and Java. Python is interpreted and dynamically-typed, so the run-time compiler has a lot of work to do.

One of the main disadvantages of Python is that it is slower than compiled languages such as C++ or Java. This is because Python is an interpreted language, which means that each line of code is executed one at a time by the interpreter.

Mobile app development

While it serves as an excellent server-side language, Python is rarely seen on the client-side. Besides that, it is rarely ever used to develop mobile applications. Neither Android nor iOS support Python as an official programming language.

It's expensive to have to rebuild complex systems over and over when a platform language changes, and Python has changed rapidly over the past decade. This is why most enterprise, or what you might call “professional”, software development is not using Python.

Both small-scale and large-scale web applications can benefit from Python's scalability and better performance. Python's flexibility and simplicity make it ideal for developers of any level.

Python's pros include its simplicity, wide range of libraries and frameworks, and strong community support. On the other hand, its cons involve potential performance limitations, dynamic typing, and slower execution speed compared to compiled languages.

It is significantly stress-free and easy to code a program using Python, but when it comes to interacting with the database, Python lags behind. It has an underdeveloped and primitive database layer in contrast to other more popular technologies such as ODBC and JDBC.

What are the disadvantages of modules in Python? ›

However, using modules in your Python projects also has its drawbacks. One potential downside is the lack of organization and encapsulation. Without a hierarchy, it can be more difficult to keep your code organized, especially as the size and complexity of the project increases.

Python is the best choice for building machine learning models due to its ease of use, extensive framework library, flexibility and more. Python brings an exceptional amount of power and versatility to machine learning environments.

Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.

A variable name cannot start with a number. A variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and _ ) Variable names are case-sensitive (age, Age and AGE are three different variables) A variable name cannot be any of the Python keywords.