Python supports multiple programming paradigms — procedural, object-oriented,…

Python supports multiple programming paradigms such as procedural, object-oriented, and functional programming. This flexibility allows developers to solve problems using different approaches depending on the requirements of the system.

1. Procedural Programming in Python
   Python allows programs to be written as a sequence of instructions using functions, loops, and conditional statements. This approach is simple and suitable for small scripts or tasks such as data processing.

Example:

def add(a, b):
    return a + b

print(add(5, 3))

1. Object-Oriented Programming Support
   
   Python provides classes, objects, inheritance, encapsulation, and polymorphism. These features help in modelling real-world entities and organizing large software systems into reusable modules.

Example:

class Student:
    def __init__(self, name):
        self.name = name

1. Functional Programming Features
   
   Python also supports functional programming through lambda expressions and higher-order functions such as map(), filter(), and reduce(). This style is useful for data transformation and concise coding.

Example:

nums = [1,2,3]
squares = list(map(lambda x: x*x, nums))

1. Effect on Maintainability
   
   Multiple paradigms improve code readability and modularity. Developers can choose the best paradigm for each task, which makes the system easier to maintain.

2. Impact on Performance
   
   Python’s abstraction may reduce execution speed compared to low-level languages, but it increases development speed and productivity.

3. Influence on Software Architecture
   
   In large systems, object-oriented design helps create modular and scalable architectures. Functional programming helps handle data processing tasks efficiently.

Thus, Python’s multi-paradigm nature improves flexibility, maintainability, and collaboration in modern software development.