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In Python programming, decomposition refers to breaking down a complex problem or task into smaller, more manageable parts or components. This process is often used in software development to make code more modular, readable, and maintainable. By decomposing a problem, we can create smaller units of code, typically functions or classes, that handle specific aspects of the overall task. There are two main types of decomposition: 

1. Functional Decomposition: 

   In functional decomposition, we break down a problem into functions, where each function performs a specific sub-task. Each function is responsible for a particular operation or aspect of the overall functionality. This approach promotes code reuse, as functions can be called from different parts of the program. 

   def process_data(data): 

   # code for processing data 

   def analyze_data(data): 

   # code for analyzing data 

   def visualize_data(data): 

   # code for visualizing data 

   # Main program data = get_data() 

   process_data(data) 

   analyze_data(data) 

   visualize_data(data)  

2. Object-Oriented Decomposition: 

   In object-oriented decomposition, we break down a problem into classes and objects. Each class represents a concept or entity related to the problem, and objects are instances of these classes. This approach helps encapsulate data and behavior within objects, providing a way to model real-world entities. 

   class DataProcessor: 

   def process_data(self, data): 

   # code for processing data 

   class DataAnalyzer: 

   def analyze_data(self, data): 

   # code for analyzing data 

   class DataVisualizer: 

   def visualize_data(self, data): 

   # code for visualizing data 

   # Main program 

   data_processor = DataProcessor() 

   data_analyzer = DataAnalyzer() 

   data_visualizer = DataVisualizer() 

   data = get_data() 

   data_processor.process_data(data) 

   data_analyzer.analyze_data(data) 

   data_visualizer.visualize_data(data)  

Decomposition is a fundamental principle in software design that helps manage complexity, improve code organization, and enhance code reuse. It also facilitates collaboration among developers working on different parts of a system.

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