Clean Python : Elegant Coding in Python

Discover the right way to code in Python. This book provides the tips and techniques you need to produce cleaner, error-free, and eloquent Python projects. Your journey to better code starts with understanding the importance of formatting and documenting your code for maximum readability, utilizing built-in data structures and Python dictionary for improved maintainability, and working with modules and meta-classes to effectively organize your code. You will then dive deep into the new features of the Python language and learn how to effectively utilize them. Next, you will decode key concepts such as asynchronous programming, Python data types, type hinting, and path handling. Learn tips to debug and conduct unit and integration tests in your Python code to ensure your code is ready for production. The final leg of your learning journey equips you with essential tools for version management, managing live code, and intelligent code completion. After reading and using this book, you will be proficient in writing clean Python code and successfully apply these principles to your own Python projects. What You'll Learn Use the right expressions and statements in your Python code Create and assess Python Dictionary Work with advanced data structures in Python Write better modules, classes, functions, and metaclasses Start writing asynchronous Python immediately Discover new features in Python Who This Book Is For Readers with a basic Python programming knowledge who want to improve their Python programming skills by learning right way to code in Python. Table of Contents......Page 4 About the Author......Page 10 About the Technical Reviewer......Page 11 Acknowledgments......Page 12 Introduction......Page 13 Chapter 1: Pythonic Thinking......Page 14 Variables and Functions......Page 15 Function and Method Arguments......Page 18 Expressions and Statements in Your Code......Page 19 Embrace the Pythonic Way to Write Code......Page 22 Consider Using is and is not Whenever You Need to Compare with None......Page 23 Consider Using a Function Instead of a Lambda When Binding to an Identifier......Page 24 Be Consistent with the return Statement......Page 25 Prefer Using ““.startswith() and ””.endswith()......Page 26 Write Explicit Code for Context Manager......Page 27 Use Linting Tools to Improve Python Code......Page 29 Using Docstrings......Page 31 Module-Level Docstrings......Page 34 Make the Class Docstring Descriptive......Page 36 Function Docstrings......Page 37 Some Useful Docstring Tools......Page 38 Use List Comprehensions......Page 39 Don’t Make Complex List Comprehension......Page 41 Should You Use a Lambda?......Page 43 When to Use Generators vs. List Comprehension......Page 44 Why Not to Use else with Loops......Page 45 Why range Is Better in Python 3......Page 48 Frequently Raised Exceptions......Page 50 Leverage finally to Handle Exceptions......Page 52 Create Your Own Exception Class......Page 54 Handle Only Specific Exceptions......Page 56 Watch Out for Third-Party Exceptions......Page 58 Prefer to Have Minimum Code Under try......Page 59 Summary......Page 61 Common Data Structures......Page 62 Use Sets for Speed......Page 63 Access the Data......Page 65 Return the Data......Page 66 Understanding str, Unicode, and byte......Page 68 Use Lists Carefully and Prefer Generators......Page 70 Use zip to Process a List......Page 73 math......Page 75 sys and os......Page 76 __future__......Page 77 When to Use a Dictionary vs. Other Data Structures......Page 78 Counter......Page 79 deque......Page 80 defaultdict......Page 81 ordereddict......Page 82 Ordered Dictionary vs. Default Dictionary vs. Normal Dictionary......Page 83 switch Statement Using Dictionary......Page 85 Ways to Merge Two Dictionaries......Page 86 Pretty Printing a Dictionary......Page 87 Summary......Page 88 Functions......Page 89 Create Small Functions......Page 90 Return Generators......Page 92 Raise Exceptions Instead of Returning None......Page 94 Add Behavior Using the default and keyword Arguments......Page 97 Do Not Return None Explicitly......Page 98 Logging......Page 101 Unit Test......Page 103 Use a Lambda as a Single Expression......Page 104 Right Size of Class?......Page 106 Class Structure......Page 107 __init__......Page 109 Instance Methods......Page 110 Right Ways to Use @property......Page 111 When to Use Static Methods?......Page 114 Use Abstract Class Inheritance the Pythonic Way......Page 116 Use @classmethod to Access Class State......Page 118 Use the public Attribute Instead of private......Page 119 Summary......Page 121 Modules and Metaclasses......Page 122 How Modules Can Help to Organize Code......Page 124 Take Advantage of the __init__ File......Page 127 Import Functions and Classes from Modules in the Right Way......Page 130 Use __all__ to Prevent Imports......Page 132 When to Use Metaclasses......Page 134 Use __new__ for Validating Subclasses......Page 135 Why __slots__ Are Useful......Page 138 Change Class Behavior Using Metaclasses......Page 141 Learn About Python Descriptors......Page 145 Summary......Page 147 Chapter 5: Decorators and Context Managers......Page 149 What Are Decorators, and Why Are They Useful?......Page 150 Understanding Decorators......Page 151 Modify Behavior Using Decorators......Page 154 Using Multiple Decorators......Page 157 Decorators Accept Arguments......Page 158 Consider Using a Library for Decorators......Page 159 Class Decorators for Maintaining State and Validating Parameters......Page 162 Context Managers and Their Usefulness......Page 165 Understanding Context Managers......Page 167 Using contextlib to Build a Context Manager......Page 170 Accessing a Database......Page 171 Writing Tests......Page 172 Shared Resource......Page 173 Remote Connection......Page 174 Summary......Page 175 Understanding Iterators......Page 176 What Are Generators?......Page 179 When to Use Iterators......Page 180 permuations()......Page 183 count()......Page 184 Why Generators Are Useful......Page 185 Take Advantage of the yield Keyword......Page 186 yield from......Page 188 Summary......Page 189 Chapter 7: Utilize New Python Features......Page 190 Asynchronous Programming......Page 191 Introducing async in Python......Page 192 How It Works......Page 196 await......Page 197 Tasks......Page 201 Coroutines......Page 203 Tasks......Page 205 Futures......Page 206 Timeouts......Page 208 Async Generators......Page 209 Async Comprehensions......Page 210 Async Iterators......Page 211 Curio......Page 214 Trio......Page 216 Typing in Python......Page 219 Types in Python......Page 220 Union......Page 221 Tuple......Page 222 Optional......Page 223 How Typing Helps to Write Better Code......Page 224 Typing Pitfalls......Page 225 Type Hinting......Page 226 f-string......Page 227 Keyword Only Arguments......Page 228 Summary......Page 229 Chapter 8: Debugging and Testing Python Code......Page 230 pdb......Page 231 ipdb......Page 232 pudb......Page 233 Use the Logging Module Instead of print in Production Code......Page 236 Classes and Functions in Logging......Page 238 Use the metrics Library for Identifying Bottlenecks......Page 243 How IPython Is Helpful......Page 244 Why Testing Is Important......Page 247 Pytest vs. UnitTest......Page 248 Property Testing......Page 253 How to Create a Report for Testing......Page 254 Automate Unit Tests......Page 255 Run Unit and Integration Tests in Python......Page 256 Use Linting to Make Code Consistent......Page 257 Use Code Coverage to Check for Tests......Page 258 Use virtualenv for Your Project......Page 259 Summary......Page 260 Sphinx......Page 261 Coverage......Page 263 pre-commit......Page 264 Jupyter Lab......Page 265 Flake8/Pylint......Page 266 Index......Page 268