Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
20
About Packt
22
References

3.7 Checking the type of a variable

The direct way to see the type of a variable is to use the command type:

label = 'local error'
type(label) # returns str
x = [1, 2] # list
type(x) # returns list

However, if you want to test for a variable to be of a certain type, you should use isinstance (instead of comparing the types with type):

isinstance(x, list) # True

The reason for using isinstance becomes apparent after having read about the concept of subclassing and inheritance in Section 8.5Subclassing and inheritance. In short, often different types share some common properties with some basic type. The classical example is the type bool, which is derived by subclassing from the more general type int. In this situation, we see how the command isinstance can be used in a more general way:

test = True
isinstance(test, bool) # True
isinstance(test, int) # True
type(test) == int # False
type(test) == bool...