Book Image

Dancing with Python

By : Robert S. Sutor
Book Image

Dancing with Python

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)
Part I: Getting to Know Python
PART II: Algorithms and Circuits
PART III: Advanced Features and Libraries
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Appendix C: The Complete UniPoly Class
Appendix D: The Complete Guitar Class Hierarchy
Appendix F: Production Notes

10.3 Optimizing your code

Optimizing your software means to write, rewrite, or otherwise process your code so that it runs as efficiently as possible on your intended hardware.

Why did I say “as efficiently as possible” instead of “as fast as possible”? Optimization often involves trade-offs, such as running faster but using more memory or conserving memory while executing a little slower. This section primarily looks at methods to speed up your software.

Code optimization is an entire discipline within computer science and software engineering. The topics I cover here give you a jumping-off point to learn more. You’ll have a better idea of how to write good code and when to make it better. That said, bear in mind this quote from Donald Knuth: [CPA]

The real problem is that programmers have spent far too much time worrying about efficiency in the wrong...