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Dancing with Python

Dancing with Python

By : Robert S. Sutor
5 (7)
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Dancing with Python

Dancing with Python

5 (7)
By: Robert S. Sutor

Overview of this book

Dancing with Python helps you learn Python and quantum computing in a practical way. It will help you explore how to work with numbers, strings, collections, iterators, and files. The book goes beyond functions and classes and teaches you to use Python and Qiskit to create gates and circuits for classical and quantum computing. Learn how quantum extends traditional techniques using the Grover Search Algorithm and the code that implements it. Dive into some advanced and widely used applications of Python and revisit strings with more sophisticated tools, such as regular expressions and basic natural language processing (NLP). The final chapters introduce you to data analysis, visualizations, and supervised and unsupervised machine learning. By the end of the book, you will be proficient in programming the latest and most powerful quantum computers, the Pythonic way.
Table of Contents (29 chapters)
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2
Part I: Getting to Know Python
10
PART II: Algorithms and Circuits
14
PART III: Advanced Features and Libraries
19
References
20
Other Books You May Enjoy
1
Appendices
4
Appendix C: The Complete UniPoly Class
5
Appendix D: The Complete Guitar Class Hierarchy
7
Appendix F: Production Notes

10.1 Testing your code

The code you write must work in all possible situations for all possible inputs. Therefore, you must devise a test system that assures you that every possibility is covered and the results are correct.

That’s a powerful statement, and you might relax the rules if you are coding something “quick and dirty” to do once or for your own purposes. If you are sharing your code or it will be part of a production environment, testing is essential.

10.1.1 __debug__

By default, the system variable __debug__ is True. This setting allows you to write code like

from src.code.unipoly import UniPoly

x = UniPoly(1, "x", 1)

def square_poly(p):
    if __debug__:
        print(f"Argument {p = }\n")
    return p*p

square_poly(x**2 - 3*x + 7)
Argument p = x**2 - 3*x + 7

x**4 - 6*x**3 + 23*x**2 - 42*x + 49

Note that I imported UniPoly from the specific folder...

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Dancing with Python
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