Data Structures in Python

Data Structures

• Lists: ordered, mutable, and can store different data types
  • Indexing: 0-based, support for negative indexing
  • Slicing: list[start:stop:step]
  • Methods: append(), insert(), extend(), sort(), reverse()
• Tuples: ordered, immutable, and can store different data types
  • Similar to lists, but cannot be modified after creation
• Dictionaries: unordered, mutable, and store key-value pairs
  • Methods: keys(), values(), items(), get()
• Sets: unordered, mutable, and store unique values
  • Methods: add(), remove(), union(), intersection()
• Arrays: part of the NumPy library, used for numerical computations
  • Support for vectorized operations and multi-dimensional arrays

Object Oriented Programming

• Classes: define a blueprint for objects
  • Can contain attributes (data) and methods (functions)
  • Support for inheritance and polymorphism
• Objects: instances of classes
  • Can have their own attributes and methods
  • Can be manipulated using class methods
• Inheritance: a class can inherit attributes and methods from a parent class
  • Single and multiple inheritance are supported
• Polymorphism: objects of different classes can be treated as if they were of the same class
  • Achieved through method overriding and method overloading

Decorators

• Functions: reusable blocks of code that take arguments and return values
  • Can be defined inside other functions or classes
  • Can be passed as arguments to other functions
• Decorators: special types of functions that modify or extend the behavior of other functions
  • Defined using the @ symbol before the function name
  • Can be used to implement logging, authentication, and caching

Web Development

• Flask: a micro web framework for building web applications
  • Lightweight and flexible
  • Supports routing, templates, and database integration
• Django: a high-level web framework for building web applications
  • Supports ORM, templates, and authentication
  • Includes an admin interface and support for large-scale applications
• Requests: a library for making HTTP requests in Python
  • Supports GET, POST, PUT, and DELETE requests
  • Allows for custom headers, parameters, and authentication

Machine Learning

• Scikit-learn: a library for machine learning in Python
  • Supports classification, regression, clustering, and more
  • Includes algorithms for supervised and unsupervised learning
• TensorFlow: an open-source library for machine learning and deep learning
  • Supports building and training neural networks
  • Includes tools for visualization and debugging
• Keras: a high-level library for building and training neural networks
  • Supports convolutional and recurrent neural networks
  • Can run on top of TensorFlow, Theano, or CNTK

Data Structures

• Lists:
  • Ordered collections of items that can be of different data types
  • Indexed, with 0-based indexing that supports negative indexing
  • Support slicing, with the format list[start:stop:step]
  • Methods include append() to add elements, insert() to add at a specific position, extend() to add multiple elements, sort() to sort the list, and reverse() to reverse the list
• Tuples:
  • Ordered collections of items that can be of different data types
  • Immutable, meaning they cannot be modified after creation
  • Similar to lists, but cannot be changed after creation
• Dictionaries:
  • Unordered collections of key-value pairs
  • Mutable, meaning they can be modified after creation
  • Methods include keys() to get all keys, values() to get all values, items() to get all key-value pairs, and get() to get a value by key
• Sets:
  • Unordered collections of unique values
  • Mutable, meaning they can be modified after creation
  • Methods include add() to add a value, remove() to remove a value, union() to get the union of two sets, and intersection() to get the intersection of two sets
• Arrays:
  • Part of the NumPy library
  • Used for numerical computations
  • Support vectorized operations and multi-dimensional arrays

Object Oriented Programming

• Classes:
  • Define a blueprint for creating objects
  • Contain attributes (data) and methods (functions)
  • Support inheritance and polymorphism
• Objects:
  • Instances of classes
  • Can have their own attributes and methods
  • Can be manipulated using class methods
• Inheritance:
  • A class can inherit attributes and methods from a parent class
  • Supports single and multiple inheritance
• Polymorphism:
  • Objects of different classes can be treated as if they were of the same class
  • Achieved through method overriding and method overloading

Decorators

• Functions:
  • Reusable blocks of code that take arguments and return values
  • Can be defined inside other functions or classes
  • Can be passed as arguments to other functions
• Decorators:
  • Special types of functions that modify or extend the behavior of other functions
  • Defined using the @ symbol before the function name
  • Can be used to implement logging, authentication, and caching

Web Development

• Flask:
  • A micro web framework for building web applications
  • Lightweight and flexible
  • Supports routing, templates, and database integration
• Django:
  • A high-level web framework for building web applications
  • Supports ORM, templates, and authentication
  • Includes an admin interface and support for large-scale applications
• Requests:
  • A library for making HTTP requests in Python
  • Supports GET, POST, PUT, and DELETE requests
  • Allows for custom headers, parameters, and authentication

Machine Learning

• Scikit-learn:
  • A library for machine learning in Python
  • Supports classification, regression, clustering, and more
  • Includes algorithms for supervised and unsupervised learning
• TensorFlow:
  • An open-source library for machine learning and deep learning
  • Supports building and training neural networks
  • Includes tools for visualization and debugging
• Keras:
  • A high-level library for building and training neural networks
  • Supports convolutional and recurrent neural networks
  • Can run on top of TensorFlow, Theano, or CNTK

Learn about the different data structures in Python, including lists, tuples, dictionaries, and sets. Understand their properties, methods, and use cases.