Python One-Liners: Write Concise, Eloquent Python Like a Professional

Python One-Liners: Write Concise, Eloquent Python Like a Professional

by Christian Mayer
Python One-Liners: Write Concise, Eloquent Python Like a Professional

Python One-Liners: Write Concise, Eloquent Python Like a Professional

by Christian Mayer

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Overview

Python programmers will improve their computer science skills with these useful one-liners.

Python One-Liners will teach you how to read and write "one-liners": concise statements of useful functionality packed into a single line of code. You'll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book's five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You'll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You'll also learn how to:
  • Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution
  • Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics
  • Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
  • Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators
  • Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting

  • By the end of the book, you'll know how to write Python at its most refined, and create concise, beautiful pieces of "Python art" in merely a single line.

    Product Details

    ISBN-13: 9781718500501
    Publisher: No Starch Press
    Publication date: 06/02/2020
    Pages: 216
    Sales rank: 508,567
    Product dimensions: 6.90(w) x 9.20(h) x 0.70(d)

    About the Author

    Christian Mayer has a PhD in computer science and is the founder of the popular Python site Finxter (https://blog.finxter.com). Mayer is also the author of the Coffee Break Python series.

    Table of Contents

    Acknowledgments xvii

    Introduction xix

    Python One-Liner Example xx

    A Note on Readability xxi

    Who Is This Book For? xxii

    What Will You Learn? xxii

    Online Resources xxiii

    1 Python Refresher 1

    Basic Data Structures 2

    Numerical Data Types and Structures 2

    Booleans 2

    Strings 4

    The Keyword None 5

    Container Data Structures 6

    Lists 6

    Stacks 8

    Sets 9

    Dictionaries 10

    Membership 11

    List and Set Comprehension 12

    Control Flow 12

    If, else, and elif 13

    Loops 13

    Functions 14

    Lambdas 15

    Summary 16

    2 Python Tricks 17

    Using List Comprehension to Find Top Earners 18

    The Basics 18

    The Code 20

    How It Works 20

    Using List Comprehension to Find Words with High Information Value 21

    The Basics 21

    The Code 21

    How It Works 22

    Reading a File 22

    The Basics 22

    The Code 23

    How It Works 23

    Using Lambda and Map Functions 24

    The Basics 24

    The Code 25

    How It Works 26

    Using Slicing to Extract Matching Substring Environments 26

    The Basics 26

    The Code 28

    How It Works 29

    Combining List Comprehension and Slicing 29

    The Basics 29

    The Code 30

    How It Works 30

    Using Slice Assignment to Correct Corrupted Lists 31

    The Basics 31

    The Code 32

    How It Works 32

    Analyzing Cardiac Health Data with List Concatenation 33

    The Basics 33

    The Code 35

    How It Works 35

    Using Generator Expressions to Find Companies That Pay Below Minimum Wage 35

    The Basics 35

    The Code 36

    How It Works 36

    Formatting Databases with the zip() Function 37

    The Basics 37

    The Code 38

    How It Works 39

    Summary 39

    3 Data Science 41

    Basic Two-Dimensional Array Arithmetic 42

    The Basics 42

    The Code 45

    How It Works 45

    Working with NumPy Arrays: Slicing, Broadcasting, and Array Types 46

    The Basics 46

    The Code 51

    How It Works 52

    Conditional Array Search, Filtering, and Broadcasting to Detect Outliers 53

    The Basics 53

    The Code 54

    How It Works 55

    Boolean Indexing to Filter Two-Dimensional Arrays 57

    The Basics 57

    The Code 58

    How It Works 58

    Broadcasting, Slice Assignment, and Reshaping to Clean Every i-th Array Element 60

    The Basics 60

    The Code 62

    How It Works 63

    When to Use the sort() Function and When to Use the argsort() Function in NumPy 64

    The Basics 64

    The Code 66

    How It Works 66

    How to Use Lambda Functions and Boolean Indexing to Filter Arrays 68

    The Basics 68

    The Code 68

    How It Works 69

    How to Create Advanced Array Filters with Statistics, Math, and Logic 70

    The Basics 70

    The Code 73

    How It Works 74

    Simple Association Analysis: People Who Bought X Also Bought Y 74

    The Basics 74

    The Code 75

    How It Works 76

    Intermediate Association Analysis to Find Bestseller Bundles 77

    The Basics 77

    The Code 77

    How It Works 78

    Summary 79

    4 Machine Learning 81

    The Basics of Supervised Machine Learning 82

    Training Phase 82

    Inference Phase 83

    Linear Regression 83

    The Basics 83

    The Code 86

    How It Works 87

    Logistic Regression in One Line 89

    The Basics 89

    The Code 92

    How It Works 93

    K-Means Clustering in One Line 94

    The Basics 94

    The Code 97

    How It Works 97

    K-Nearest Neighbors in One Line 100

    The Basics 100

    The Code 101

    How It Works 102

    Neural Network Analysis in One Line 104

    The Basics 104

    The Code 108

    How It Works 109

    Decision-Tree Learning in One Line 111

    The Basics 111

    The Code 112

    How It Works 113

    Get Row with Minimal Variance in One Line 113

    The Basics 113

    The Code 114

    How It Works 115

    Basic Statistics in One Line 116

    The Basics 116

    The Code 118

    How It Works 118

    Classification with Support-Vector Machines in One Line 119

    The Basics 120

    The Code 121

    How It Works 122

    Classification with Random Forests in One Line 123

    The Basics 123

    The Code 124

    How It Works 125

    Summary 126

    5 Regular Expressions 127

    Finding Basic Textual Patterns in Strings 128

    The Basics 128

    The Code 130

    How It Works 131

    Writing Your First Web Scraper with Regular Expressions 132

    The Basics 132

    The Code 133

    How It Works 133

    Analyzing Hyperlinks of HTML Documents 134

    The Basics 134

    The Code 136

    How It Works 137

    Extracting Dollars from a String 137

    The Basics 138

    The Code 138

    How It Works 139

    Finding Nonsecure HTTP URLs 140

    The Basics 140

    The Code 140

    How It Works 141

    Validating the Time Format of User Input, Part 1 141

    The Basics 142

    The Code 142

    How It Works 143

    Validating Time Format of User input, Part 2 143

    The Basics 143

    The Code 144

    How It Works 144

    Duplicate Detection in Strings 145

    The Basics 145

    The Code 146

    How It Works 146

    Detecting Word Repetitions 147

    The Basics 147

    The Code 147

    How It Works 148

    Modifying Regex Patterns in a Multiline String 148

    The Basics 149

    The Code 149

    How It Works 149

    Summary 150

    6 Algorithms 151

    Finding Anagrams with Lambda Functions and Sorting 152

    The Basics 152

    The Code 153

    How It Works 153

    Finding Palindromes with Lambda Functions and Negative Slicing 154

    The Basics 154

    The Code 155

    How It Works 155

    Counting Permutations with Recursive Factorial Functions 156

    The Basics 156

    The Code 158

    How It Works 158

    Finding the Levenshtein Distance 159

    The Basics 159

    The Code 160

    How It Works 160

    Calculating the Powerset by Using Functional Programming 162

    The Basics 162

    The Code 164

    How It Works 165

    Caesar's Cipher Encryption Using Advanced Indexing and List Comprehension 165

    The Basics 165

    The Code 166

    How It Works 167

    Finding Prime Numbers with the Sieve of Eratosthenes 168

    The Basics 168

    The Code 169

    How It Works 170

    Calculating the Fibonacci Series with the reduce() Function 174

    The Basics 174

    The Code 175

    How It Works 175

    A Recursive Binary Search Algorithm 176

    The Basics 177

    The Code 178

    How It Works 179

    A Recursive Quicksort Algorithm 180

    The Basics 180

    The Code 181

    How It Works 181

    Summary 182

    Afterword 183

    Index 185

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