# Object-Oriented Programming in Python

Course Level: Advanced  
_(6 hours)_

Object-oriented programming is the dominant programming paradigm in Python and can be used to improve the structure of your data science code. Here, we will learn how to model real-world entities using classes, how to create class instances, and how to attach data and behaviour to these objects. The main ideas of object-oriented design (inheritance, polymorphism, encapsulation, abstraction) are covered, and you will learn how to extend existing classes from well-known data science packages.

[Download course details](/content/training/course/object-oriented-programming-python-class-instance/assets/course-outline.pdf)

## Course Details

### Outline

- **Object-oriented design**: An introduction to the aims and mindset of object-oriented programming, the most dominant programming paradigm in Python.
- **Classes in Python**: How to define classes, and how to use these to create instances.
- **Methods and attributes for instances and classes**: How to attach data and behaviour to classes and their instances.
- **Inheritance, Composition, Polymorphism**: A brief introduction to best practices for creating flexible object-oriented code.
- **Extending classes from well-known data science packages**: How to take existing classes and add new features to them.

### Learning outcomes

**Session 1:**  
_By the end of session 1 participants will…_

- understand how to model real-world (and more abstract) objects using classes
- be able to define classes in Python
- understand how to make class instances
- understand instance methods and attributes

**Session 2:**  
_By the end of session 2 participants will…_

- understand how inheritance can help with code reuse
- be able to define class and static methods
- understand how to use composition to make classes that contain other objects
- understand how OOP and inheritance makes it easier to write polymorphic code

_This course does not include:_

- using object-relational mappings to interact with databases, see our [Intro to SQL with Python](/content/training/course/python-sql-databases-pandas-sqlalchemy/index.html) course for this
- advanced OOP ideas (design patterns, metaclasses)
- unified modelling language or other graphical ways to represent how classes/instances interact
- a comparison of the programming paradigms that are available in Python
- an introduction to Pandas, Numpy or Matplotlib, see our [Intro to Python](/content/training/course/python-introduction-visualisation-manipulation/index.html) course for this

### Prior knowledge

The course will assume a basic understanding of popular Python libraries including NumPy, Pandas and Matplotlib, as well as common data types like Pandas `DataFrame`s. The course will also make use of basic programming concepts like defining functions and running `for` loops. Completion of our [Intro to Python](/content/training/course/python-introduction-visualisation-manipulation/index.html) and [Programming with Python](/content/training/course/python-programming-control-flow-functions/index.html) (or equivalent experience) would provide a suitable background.