Introduction to Classes

1. Introduction to Classes Intro to Computer Science CS1510, Section 2 Dr. Sarah Diesburg

2. PA09 • New homework - word clouds!

3. Programming Styles • Up until today, we have been programming in a procedural programming style • Series of computational steps to be carried out • We do this by writing functions that operate on data structures • This style of programming is suitable for smaller programming tasks

4. Programming Styles • Classes are part of Object Oriented Programming (OOP) • OOP is a way to think about “objects” in a program (such as variables, functions, etc). • A program becomes less a list of instructions and more a set of objects and how they interact. • Models the “real world” where objects (entities) work together to accomplish tasks

5. Responding to “Messages” • As a set of interacting objects, each object responds to “messages” sent to it. • The interaction of objects via messages makes a high level description of what the program is doing. Start!

6. Everything in Python is an Object • In case you hadn’t noticed, everything in Python is an object. • Thus Python embraces OOP at a fundamental level. • This is in contrast to other programming languages • C is completely procedural • Java is OOP but has some partial non-objects

7. OOP Helps in Software Engineering • Software engineering is the discipline of managing code to ensure its long-term use. • We’ve already seen some code reuse • Counters, accumulators • Can write general functions • We will find the same thing with objects • Some basic objects are even easier to reuse • Strings, list, dictionaries, …

8. More Refactoring • Hiding the details of what the message entails means that changes can be made to the object and the flow of messages (and their results) can stay the same. • Thus the implementation of the message can change but its intended effect stays the same. • This is encapsulation.

9. OOP Principles • Encapsulation: hiding design details to make the program clearer and more easily modified later. • Modularity: the ability to make objects “stand alone” so they can be reused (our modules). I.e. the math module.

10. OOP Principles • Inheritance: create a new object by inheriting (like parent to child) many object characteristics while creating or over-riding for this object. • Polymorphism: (hard) Allow one message to be sent to any object and have it respond appropriately based on the type of object it is. • Where have we seen this already??

11. Class versus Instance • One of the harder things to understand is what a class is and what an instance of a class is. • Consider the analogy of the cookie cutter and a cookie.

12. Class versus Instance • The cutter is a template for “stamping out” cookies, the “cookie” is what is made each time the cutter is used. • One template can be used to make an infinite number of cookies, each one just like the other. • No one confuses a cookie for a cookie cutter, do they?

13. Same in OOP • You define a class as a way to generate new instances of that class. • Both the instances and the classes are themselves objects. • The structure of an instance starts out the same, as dictated by the class. • The instances respond to the messages defined as part of the class.

14. Why a Class? • We make classes because we need more complicated, user-defined data types to construct instances we can use. • Each class has potentially two aspects: • the data (types, number, names) that each instance might contain • the messages that each instance can respond to

15. A First Class • Say we need to make a new university information system • What is this?

16. A First Class • In a university information system, we need information about • Students • Faculty • Courses • Transcripts • Python does not have these • We need to create our own definitions of what a “student” is!

17. A First Class • What should a bundle of information called a “student” should know about in our code? • Name • Student ID • What else…?

18. A First Class • What should a bundle of information called a “student” should know about in our code? • Name • Student ID • What else…? • Could put this information in a tuple, but what’s missing?

19. A First Class • What should a bundle of information called a “student” should know about in our code? • Name • Student ID • What else…? • Could put this information in a tuple, but what’s missing? • It would be nice to pass message to a student object, and have that student object operate on its own data

21. A sample class class Student(object): """Simple Student class.""" def __init__(self,first='', last='', id=0): # init instance self.firstNameStr = first self.lastNameStr = last self.idInt = id def __str__(self): # string representation for printing return "{} {}, ID:{}".format\ (self.firstNameStr, self.lastNameStr, self.idInt)

22. Constructor • When a class is defined, a function is made with the same name as the class • This function is called the constructor. By calling it, you can create an instance of the class. • We can affect this creation (more later), but by default Python can make an instance.

23. A Class is a New Type >>>myLst = [1, 2, 3] type(myLst) => type<‘list’> >>>myStr = ‘abc’ type(myStr) => type<‘str’> >>>s1 = Student(“Jane",“Doe",12345) type(s1) <class '__main__.Student'>

24. Instance Knows its Class • Because each instance has as its type the class that it was made from, an instance “remembers” its class. • This is often called the “instance-of” relationship.

25. “Dot” Reference • We can refer to the attributes of an object by doing a “dot” reference, of the form: object.attribute • The attribute can be a variable or a function. • It is part of the object, either directly or by that object being part of a class.