Python Dynamic Typing: Flexible Variable Types

One of the standout features of Python language is that it is a dynamically typed language. The compiler-based languages C/C++, Java, etc. are statically typed. Let us try to understand the difference between static typing and dynamic typing.

In a statically typed language, each variable and its data type must be declared before assigning it a value. Any other type of value is not acceptable to the compiler, and it raises a compile-time error.

Let us take the following snippet of a Java program −

Here, var is declared as an integer variable. When we try to assign it a string value, the compiler gives the following error message −

/MyClass.java:4: error: incompatible types: String cannot be converted to int
   x="Hello";
     ^
1 error

A variable in Python is only a label, or reference to the object stored in the memory, and not a named memory location. Hence, the prior declaration of type is not needed. Because it's just a label, it can be put on another object, which may be of any type.

In Java, the type of the variable decides what it can store and what not. In Python it is the other way round. Here, the type of data (i.e. object) decides the type of the variable. To begin with, let us store a string in the variable in check its type.

So, var is of string type. However, it is not permanently bound. It's just a label; and can be assigned to any other type of object, say a float, which will be stored with a different id() −

or a tuple. The var label now sits on a different object.

We can see that the type of var changes every time it refers to a new object. That's why Python is a dynamically typed language.

Dynamic typing feature of Python makes it flexible compared to C/C++ and Java. However, it is prone to runtime errors, so the programmer has to be careful.

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