Python One-Liners PDF
Preview Python One-Liners
PYTHON ONE-LINERS Write Concise, Eloquent Python Like a Professional by Christian Mayer San Francisco PYTHON ONE-LINERS. Copyright © 2020 by Christian Mayer. All rights reserved. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval system, without the prior written permission of the copyright owner and the publisher. ISBN-10: 1-7185-0050-5 ISBN-13: 978-1-7185-0050-1 Publisher: William Pollock Production Editors: Janelle Ludowise and Kassie Andreadis Cover Illustration: Rob Gale Interior Design: Octopod Studios Developmental Editors: Liz Chadwick and Alex Freed Technical Reviewer: Daniel Zingaro Copyeditor: Sharon Wilkey Compositor: Danielle Foster Proofreader: James Fraleigh Indexer: JoAnne Burek For information on distribution, translations, or bulk sales, please contact No Starch Press, Inc. directly: No Starch Press, Inc. 245 8th Street, San Francisco, CA 94103 phone: 1.415.863.9900; [email protected] www.nostarch.com The Library of Congress issued the following Cataloging-in-Publication Data for the first edition: Names: Mayer, Christian (Computer Scientist), author. Title: Python one-liners: write concise, eloquent Python like a professional / Christian Mayer. Description: San Francisco : No Starch Press, Inc., 2020. | Includes index. Identifiers: LCCN 2020001449 (print) | LCCN 2020001450 (ebook) | ISBN 9781718500501 | ISBN 9781718500518 (ebook) Subjects: LCSH: Python (Computer program language) Classification: LCC QA76.73.P98 M39 2020 (print) | LCC QA76.73.P98 (ebook) | DDC 005.13/3--dc23 LC record available at https://lccn.loc.gov/2020001449 LC ebook record available at https://lccn.loc.gov/2020001450 No Starch Press and the No Starch Press logo are registered trademarks of No Starch Press, Inc. Other product and company names mentioned herein may be the trademarks of their respective owners. Rather than use a trademark symbol with every occurrence of a trademarked name, we are using the names only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The information in this book is distributed on an “As Is” basis, without warranty. While every precaution has been taken in the preparation of this work, neither the author nor No Starch Press, Inc. shall have any liability to any person or entity with respect to any loss or damage caused or alleged to be caused directly or indirectly by the information contained in it. To my wife Anna About the Author Christian Mayer is a doctor of computer science and the founder and maintainer of the popular Python site https://blog.finxter.com/ and its associated newsletter, which has 20,000 active subscribers and is still growing. His rapidly growing websites help tens of thousands of students improve their coding skills and online businesses. Christian is also the author of the Coffee Break Python series of self-published books. About the Technical Reviewer Dr. Daniel Zingaro is an assistant teaching professor of computer science and award-winning teacher at the University of Toronto. His main area of research is computer science education, where he studies how students learn (and sometimes don’t learn) computer science material. He is the author of Algorithmic Thinking (forthcoming from No Starch Press). BRIEF CONTENTS Acknowledgments Introduction Chapter 1: Python Refresher Chapter 2: Python Tricks Chapter 3: Data Science Chapter 4: Machine Learning Chapter 5: Regular Expressions Chapter 6: Algorithms Afterword Index CONTENTS IN DETAIL ACKNOWLEDGMENTS INTRODUCTION Python One-Liner Example A Note on Readability Who Is This Book For? What Will You Learn? Online Resources 1 PYTHON REFRESHER Basic Data Structures Numerical Data Types and Structures Booleans Strings The Keyword None Container Data Structures Lists Stacks Sets Dictionaries Membership List and Set Comprehension Control Flow if, else, and elif Loops Functions Lambdas Summary 2 PYTHON TRICKS Using List Comprehension to Find Top Earners The Basics The Code How It Works Using List Comprehension to Find Words with High Information Value The Basics The Code How It Works Reading a File The Basics The Code How It Works Using Lambda and Map Functions The Basics The Code How It Works Using Slicing to Extract Matching Substring Environments The Basics The Code How It Works Combining List Comprehension and Slicing The Basics The Code How It Works Using Slice Assignment to Correct Corrupted Lists The Basics The Code How It Works Analyzing Cardiac Health Data with List Concatenation The Basics The Code How It Works
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