Is Python a dynamically typed language?

Introduction to Python

Dynamic typing in Python

Python is dynamically typed, which means that variable types are determined and checked at runtime rather than during compilation. In dynamically typed languages like Python, you don’t need to explicitly declare the variable type before using it. Instead, the type is inferred based on the value assigned to the variable.

In dynamic typing, variables can be reassigned to different types of values during the execution of a program. This flexibility allows for more concise and flexible code, as you can use the same variable to store different types of data throughout the program.

Features of dynamic typing

Below are some features of dynamic typing:

• Type inference: In Python, you don’t need to declare the type of a variable explicitly. The interpreter infers the type based on the value assigned to it. If you, for instance, assign an integer to a variable, it becomes an integer type, and if you later assign a string to the same variable, it becomes a string type.

• Runtime type checking: Dynamic typing allows for runtime type checking. This means that the type of a variable is checked during the execution of the program. If an operation is performed on a variable that is not compatible with its current type, a runtime error will occur.

• Flexibility and expressiveness: Dynamic typing offers greater flexibility and expressiveness in writing code. It allows you to easily change the type of a variable or use the same variable to hold different types of data. This flexibility is particularly useful when dealing with complex or evolving data structures.

• Rapid prototyping and iterative development: Dynamic typing simplifies the process of rapid prototyping and iterative development. You can quickly write and test code without the need for explicit type declarations, making it easier to experiment and make changes on the fly.

• Enhanced productivity: The dynamic nature of Python’s typing system often leads to enhanced productivity.

Why Python is dynamically typed?

Python is dynamically typed because its variable types are decided upon and verified while the program is running. Therefore, type inference takes place automatically without requiring explicit type declarations. Variables may be changed from one type to another while a program runs, thanks to the dynamic typing feature, which offers flexibility and expressiveness. It facilitates quick prototyping and makes writing code easier but also necessitates careful planning to prevent potential runtime problems. Python’s dynamic typing finds a balance between practicality and security, and it can be used in conjunction with the optional usage of static typing via type hints for improved type verification.

Example

Let’s look at the code below better understand what dynamic typing is.

Explanation

The code above is explained in detail below:

• Lines 1–3: We have defined three variables two of string type and one of integer type. As you can see from the code, we haven’t defined the datatype of any variable and the code doesn’t throw an error this is because Python is a dynamically typed language. The datatypes of variables are identified at runtime so there is no need to declare it in the code.

• Lines 5–7: We have used the in-built type function to show the datatype of the variables.

Conclusion

As we have seen that Python is dynamically typed and writing code in Python is relatively easy Moreover, we don’t have to define the variable’s datatypes so it will result in a smaller code size. However, one of the main disadvantages of such a language is that debugging becomes very difficult as the variable type is not known until runtime. It can be difficult to spot errors/bugs from type mismatches.