Every programming language has pros and cons. Python has some significant limits as well.

Python's key drawbacks include its slowness during execution, difficulties transitioning to another language, weakness in mobile application development, excessive memory consumption, and lack of acceptance in the corporate development industry. Here are five reasons why Python is not a good choice for massive projects.

1. Slow at Runtime

Python is noticeably slower to execute than other programming languages such as Java, C++, PHP, Javascript, Swift, and others. When building large applications with many lines of code, this is a key worry for programmers.

It is not as near to hardware as C or C++ because it is a high-level coding language. Instead of using a compiler, Python code is executed using an interpreter. The interpreter runs the code line by line, which slows things down.

Python is a dynamically typed programming language. That is, it performs many typical programming behaviors, that static coding languages accomplish during compilation during runtime.

We don't need to declare variable data types when assigning variables in dynamically typed languages. During execution, the variable's data structure is assigned. You may learn more about the distinctions between statically and dynamically typed languages by reading this article.

As a result, whenever the variable is read, written, or referred to, its data type is verified and memory is allocated appropriately.

2. Not Good for Mobile Application Development

Despite the fact that Python is a server-side language, it is not the greatest for developing mobile applications. Python was mostly incompatible with the creation of Android and iOS applications.

Fortunately, significant progress has been done to increase Python's performance in the field of mobile app development. Kivy and Beware are Python libraries that were created to help developers create mobile apps.

3. Difficulty in Using Other Languages

Many programmers dislike writing code in other programming languages. This is due to their perception that other languages are significantly more difficult to utilize. They may be accustomed to coding in Python, the world's most user-friendly programming language.

If you are a die-hard Python enthusiast, you may be experiencing this problem. Pythonistas adore Python because it is easy, popular, and powerful. The major reason we like Python is that it is simple.

When compared to other programming languages such as C++ and Java, Python is extremely simple to learn. Python is more closely related to human language, and we dislike some other languages that are more closely related to hardware.

4. High Memory Consumption

Python is not always the ideal choice for memory-intensive workloads. Python's memory consumption is largely owing to the data types' versatility.

When objects are no longer in scope, Python performs automatic garbage collection. Python seeks to alleviate much of the complexity of dynamic memory that programs like C and C++ require as a result of this feature.

However, dealing with dynamic memory in big and long-running Python systems is problematic.

5. Not used commonly in the Business Development Sector

Python is a strong programming language with few concerns for programmers, and it has created quite a stir in the large-scale web development market. Nonetheless, despite its ubiquity, Python has yet to make inroads into corporate development.

One of the key causes for this could be Python's database access constraints. When compared to major technologies like JDBC and ODBC, Python's database access layer is regarded to be quite immature and unsophisticated.

As a result, it is rarely used in companies that require the seamless interaction of complicated historical data.