Object-oriented programming (OOP).

Python supports object-oriented programming (OOP). The goals of OOP are:

• to organize the code, and
• to re-use code in similar contexts.

Here is a small example: we create a Student class, which is an object gathering several custom functions (methods) and variables (attributes), we will be able to use:

>>>

>>> class Student(object):
...     def __init__(self, name):
...         self.name = name
...     def set_age(self, age):
...         self.age = age
...     def set_major(self, major):
...         self.major = major
...
>>> anna = Student('anna')
>>> anna.set_age(21)
>>> anna.set_major('physics')

In the previous example, the Student class has __init__, set_age and set_major methods. Its attributes are name, age and major. We can call these methods and attributes with the following notation: classinstance.method or classinstance.attribute. The __init__ constructor is a special method we call with: MyClass(init parameters if any).
Now, suppose we want to create a new class MasterStudent with the same methods and attributes as the previous one, but with an additional internship attribute. We won’t copy the previous class, but inherit from it:

>>>

>>> class MasterStudent(Student):
...     internship = 'mandatory, from March to June'
...
>>> james = MasterStudent('james')
>>> james.internship
'mandatory, from March to June'
>>> james.set_age(23)
>>> james.age
23

The MasterStudent class inherited from the Student attributes and methods.
Thanks to classes and object-oriented programming, we can organize code with different classes corresponding to different objects we encounter (an Experiment class, an Image class, a Flow class, etc.), with their own methods and attributes. Then we can use inheritance to consider variations around a base class and re-use code. Ex : from a Flow base class, we can create derived StokesFlow, TurbulentFlow, PotentialFlow, etc.

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