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Scientific Computing with Python - Second Edition

You're reading from  Scientific Computing with Python - Second Edition

Product type Book
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Pages 392 pages
Edition 2nd Edition
Languages
Authors (3):
Claus Führer Claus Führer
Profile icon Claus Führer
Jan Erik Solem Jan Erik Solem
Olivier Verdier Olivier Verdier
View More author details

Table of Contents (23) Chapters

Preface Getting Started Variables and Basic Types Container Types Linear Algebra - Arrays Advanced Array Concepts Plotting Functions Classes Iterating Series and Dataframes - Working with Pandas Communication by a Graphical User Interface Error and Exception Handling Namespaces, Scopes, and Modules Input and Output Testing Symbolic Computations - SymPy Interacting with the Operating System Python for Parallel Computing Comprehensive Examples About Packt Other Books You May Enjoy References

8.1.4 Attributes and methods

One of the main reasons for working with classes is that objects can be grouped together and bound to a common object. We saw this already when looking at rational numbers; denominator and numerator are two objects that we bound to an instance of the class RationalNumber. They are called attributes of the instance. The fact that an object is an attribute of a class instance becomes apparent from the way they are referenced, which we have used tacitly before:

​_<object>.attribute

Here are some examples of instantiation and attribute reference:

q = RationalNumber(3, 5) # instantiation
q.numerator              # attribute access
q.denominator

a = array([1, 2])        # instantiation
a.shape

z = 5 + 4j               # instantiationstepz.imag

Once an instance is defined, we can set, change, or delete attributes of that particular instance. The syntax is the same as for regular variables:

q = RationalNumber(3, 5) 
r = RationalNumber(7, 3)
q.numerator...
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