Why Python’s Dynamic Typing Makes Coding Faster: A Beginner’s Guide

This article introduces dynamic typing, strong typing, and the internal workings of the Python interpreter for beginners.

Python is a dynamic, strongly typed, interpreted language. Although these terms may sound abstract and intimidating, they are easy to understand, which contributes to the language’s user‑friendly nature. Let’s break them down.

Dynamic Language

Computer programming languages are divided into two major camps: dynamic languages and static languages.

Static Languages

Static languages include C, C++, Java, and Go. A defining feature of static languages is that variable types must be defined in the source code. Once a developer defines a variable as a certain data type (e.g., the variable cat is a string), it remains that type forever; the type cannot change at runtime.

Dynamic Languages

For dynamic languages, the interpreter infers variable types at runtime (the interpreter and runtime will be detailed later). This greatly changes what we can and cannot do. Dynamic languages include Python, JavaScript, Ruby, and PHP.

In Python, variable assignment can be as simple as:

cat = "Mooney"

Python’s runtime reads Mooney and allocates appropriate memory. Unlike C++, there is no need to pre‑declare that Mooney is a string before performing a print operation.

cat = "Mooney"
print(cat)
cat = "Seth"
print(cat)
cat = ["Seth", "Mooney"]
print(cat)

The above code produces the following output:

Mooney
Seth
[Seth, Mooney]

Strong Typing

This directly refers to memory and how it can—or cannot—be changed. While Python values can change, they cannot change in unexpected ways, otherwise errors are raised. The best illustration is:

integer + integer = success
string + string = success
integer + string = error

You can change a variable’s type, but you must do so explicitly via conversion.

Python Interpreter

The code above runs because Python’s runtime is at work.

Python’s runtime refers to the tools used to write and run Python code. It includes the command line, integrated development environments (IDE) such as VS Code or Jupyter Notebook, and web servers like Django and Flask. The runtime also includes CPython—the default bytecode interpreter for Python.

CPython reads and interprets Python source code line by line (hence Python is an interpreted language). Before execution, CPython compiles the source code into bytecode. The Python Virtual Machine (PVM) then executes the bytecode. Because CPython handles code execution, it also manages Python’s memory, including allocation and garbage collection.

CPython provides a standard library containing modules and packages for tasks such as I/O, networking, and data manipulation.

Python’s internals give developers flexible and expressive programming capabilities, making it suitable for a wide range of tasks, including scripting, web development, and data analysis.