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Learning Python Classes

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Learning Python classes Python Classes are like a blueprint for objects outlining

contains affiliate links, meaning when you make a purchase, we receive a small commission.

possible behaviors and states that every object of a certain type could have. For example, if you say, “every customer will have a phone number and an email, and will be able to place and cancel orders”, you just defined a class!

This way, you can talk about customers in a unified way.

Then a specific Customer object is just a realization of this class with a particular state value.

An object-oriented approach is most useful when your code involves complex interactions of many objects.

In real production code, python classes can have dozens of attributes and methods with complicated logic, but the h t t p s ://i t e x a m t o o l s .c o m /l e a r n -p y t h o n -f r e e /p y t h o n -c l a s s e s /

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underlying structure is the same as with the most simple

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Finding Python Classes

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In Python, everything is an object. Numbers, strings,

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DataFrames, even functions are objects. In particular,

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everything you deal with in Python has a class, a blueprint associated with it under the hood.

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The existence of these unified interfaces is why you can use, for example, any DataFrame in the same way.

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You can call type() on any Python object to find out its class. For example, the class of a numpy array is actually called ndarray (for n-dimensional array). import numpy as np a = np.array([1,2,3,4])

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print(type(a)) numpy.ndarray

Classes incorporate information about state and behavior.

State information in Python is contained in attributes and h t t p s ://i t e x a m t o o l s .c o m /l e a r n -p y t h o n -f r e e /p y t h o n -c l a s s e s /

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Take a numpy array: you have already been using some of its methods and attributes!

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For example, every numpy array has an attribute “shape” that you can access by specifying the array’s name followed by a dot and shape.

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import numpy as np a = np.array([1,2,3,4])

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Behavior <–> Methods import numpy as np a = np.array([1,2,3,4]) # reshape method a.reshape(2,2)

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array([[1, 2],

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In this example, you will create an empty

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class Employee . Then you will create an object emp of

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the class Employee by calling Employee() .

Try printing the .name attribute of emp object in the console. What happens? # Create an empty class Employee class Employee:

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pass # Create an object emp of class Employee emp = Employee()

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