book

Python How-To

Name: Python How-To
Author: Yong Cui
ISBN: 9781617299742

by Yong Cui

August 2023

Beginner

504 pages

14h 44m

English

Manning Publications

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inside front cover
Python How-To
Copyright
dedication
contents
front matter
prefaceacknowledgmentsabout this bookWho should read this bookHow this book is organized: A road mapAbout the appendicesAbout the codeliveBook discussion forumOther online resourcesabout the authorabout the cover illustration
1 Developing a pragmatic learning strategy
1.1 Aiming at becoming a pragmatic programmer1.1.1 Focusing on writing readable Python code1.1.2 Considering maintainability even before you write any code1.2 What Python can do well or as well as other languages1.3 What Python can’t do or can’t do well1.4 What you’ll learn in this book1.4.1 Focusing on domain-independent knowledge1.4.2 Solving problems through synthesis1.4.3 Learning skills in contextSummary
Part 1 Using built-in data models
2 Processing and formatting strings
2.1 How do I use f-strings for string interpolation and formatting?2.1.1 Formatting strings before f-strings2.1.2 Using f-strings to interpolate variables2.1.3 Using f-strings to interpolate expressions2.1.4 Applying specifiers to format f-strings2.1.5 Discussion2.1.6 Challenge2.2 How do I convert strings to retrieve the represented data?2.2.1 Checking whether strings represent alphanumeric values2.2.2 Casting strings to numbers2.2.3 Evaluating strings to derive their represented data2.2.4 Discussion2.2.5 Challenge2.3 How do I join and split strings?2.3.1 Joining strings with whitespaces2.3.2 Joining strings with any delimiters2.3.3 Splitting strings to create a list of strings2.3.4 Discussion2.3.5 Challenge2.4 What are the essentials of regular expressions?2.4.1 Using regular expressions in Python2.4.2 Creating the pattern with a raw string2.4.3 Understanding the essentials of a search pattern2.4.4 Dissecting the matches2.4.5 Knowing the common methods2.4.6 Discussion2.4.7 Challenge2.5 How do I use regular expressions to process texts?2.5.1 Creating a working pattern to find the matches2.5.2 Extracting the needed data from the matches2.5.3 Using named groups for text processing2.5.4 Discussion2.5.5 ChallengeSummary
3 Using built-in data containers
3.1 How do I choose between lists and tuples?3.1.1 Using tuples for immutability and using lists for mutability3.1.2 Using tuples for heterogeneity and using lists for homogeneity3.1.3 Discussion3.1.4 Challenge3.2 How do I sort lists of complicated data using custom functions?3.2.1 Sorting lists using the default order3.2.2 Using a built-in function as the sorting key3.2.3 Using custom functions for more complicated sorting needs3.2.4 Discussion3.2.5 Challenge3.3 How do I build a lightweight data model using named tuples?3.3.1 Understanding alternative data models3.3.2 Creating named tuples to hold data3.3.3 Discussion3.3.4 Challenge3.4 How do I access dictionary keys, values, and items?3.4.1 Using dynamic view objects (keys, values, and items) directly3.4.2 Being cautious with the KeyError exception3.4.3 Avoiding KeyError with a hygiene check first: The non-Pythonic way3.4.4 Using the get method to access a dictionary item3.4.5 Watching for the setdefault method’s side effect3.4.6 Discussion3.4.7 Challenge3.5 When do I use dictionaries and sets instead of lists and tuples?3.5.1 Taking advantage of the constant lookup efficiency3.5.2 Understanding hashable and hashing3.5.3 Discussion3.5.4 Challenge3.6 How do I use set operations to check the relationships between lists?3.6.1 Checking whether a list contains all items of another list3.6.2 Checking whether a list contains any element of another list3.6.3 Dealing with multiple set objects3.6.4 Discussion3.6.5 ChallengeSummary

4 Dealing with sequence data
4.1 How do I retrieve and manipulate subsequences with slice objects?4.1.1 Taking advantage of the full features of slicing4.1.2 Not confusing slices with ranges4.1.3 Using named slice objects to process sequence data4.1.4 Manipulating list items with slicing operations4.1.5 Discussion4.1.6 Challenge4.2 How do I use positive and negative indexing to retrieve items?4.2.1 Positive indexing starts from the beginning of the list4.2.2 Negative indexing starts from the end of the list4.2.3 Combining positive and negative indices as needed4.2.4 Discussion4.2.5 Challenge4.3 How do I find items in a sequence?4.3.1 Checking an item’s presence4.3.2 Using the index method to locate the item4.3.3 Finding substrings in a string4.3.4 Finding an instance of custom classes in a list4.3.5 Discussion4.3.6 Challenge4.4 How do I unpack a sequence? Beyond tuple unpacking4.4.1 Unpacking short sequences with one-to-one correspondence4.4.2 Retrieving consecutive items using the starred expression4.4.3 Denoting unwanted items with underscores to remove distraction4.4.4 Discussion4.4.5 Challenge4.5 When should I consider data models other than lists and tuples?4.5.1 Using sets where membership is concerned4.5.2 Using deques if you care about first-in-first-out4.5.3 Processing multidimensional data with NumPy and Pandas4.5.4 Discussion4.5.5 ChallengeSummary
5 Iterables and iterations
5.1 How do I create common data containers using iterables?5.1.1 Getting to know iterables and iterators5.1.2 Inspecting iterability5.1.3 Using iterables to create built-in data containers5.1.4 Discussion5.1.5 Challenge5.2 What are list, dictionary, and set comprehensions?5.2.1 Creating lists from iterables using list comprehension5.2.2 Creating dictionaries from iterables using dictionary comprehension5.2.3 Creating sets from iterables using set comprehension5.2.4 Applying a filtering condition5.2.5 Using embedded for loops5.2.6 Discussion5.2.7 Challenge5.3 How do I improve for-loop iterations with built-in functions?5.3.1 Enumerating items with enumerate5.3.2 Reversing items with reversed5.3.3 Aligning iterables with zip5.3.4 Chaining multiple iterables with chain5.3.5 Filtering the iterable with filter5.3.6 Discussion5.3.7 Challenge5.4 Using optional statements within for and while loops5.4.1 Exiting the loops with the break statement5.4.2 Skipping an iteration with the continue statement5.4.3 Using else statements in the for and while loops5.4.4 Discussion5.4.5 ChallengeSummary
Part 2 Defining functions
6 Defining user-friendly functions
6.1 How do I set default arguments to make function calls easier?6.1.1 Calling functions with default arguments6.1.2 Defining functions with default arguments6.1.3 Avoiding the pitfall of setting default arguments for mutable parameters6.1.4 Discussion6.1.5 Challenge6.2 How do I set and use the return value in function calls?6.2.1 Returning a value implicitly or explicitly6.2.2 Defining functions returning zero, one, or multiple values6.2.3 Using multiple values returned from a function call6.2.4 Discussion6.2.5 Challenge6.3 How do I use type hints to write understandable functions?6.3.1 Providing type hinting to variables6.3.2 Using type hinting in function definitions6.3.3 Applying advanced type-hinting skills to function definitions6.3.4 Discussion6.3.5 Challenge6.4 How do I increase function flexibility with *args and **kwargs?6.4.1 Knowing positional and keyword arguments6.4.2 Accepting a variable number of positional arguments6.4.3 Accepting a variable number of keyword arguments6.4.4 Discussion6.4.5 Challenge6.5 How do I write proper docstrings for a function?6.5.1 Examining the basic structure of a function's docstring6.5.2 Specifying the function's action as the summary6.5.3 Documenting the parameters and the return value6.5.4 Specifying any exceptions possibly raised6.5.5 Discussion6.5.6 ChallengeSummary
7 Using functions beyond the basics
7.1 How do I use lambda functions for small jobs?7.1.1 Creating a lambda function7.1.2 Using lambdas to perform a small one-time job7.1.3 Avoiding pitfalls when using lambda functions7.1.4 Discussion7.1.5 Challenge7.2 What are the implications of functions as objects?7.2.1 Storing functions in a data container7.2.2 Sending functions as arguments to higher-order functions7.2.3 Using functions as a return value7.2.4 Discussion7.2.5 Challenge7.3 How do I check functions’ performance with decorators?7.3.1 Decorating a function to show its performance7.3.2 Dissecting the decorator function7.3.3 Wrapping to carry over the decorated function’s metadata7.3.4 Discussion7.3.5 Challenge7.4 How can I use generator functions as a memory-efficient data provider?7.4.1 Creating a generator to yield perfect squares7.4.2 Using generators for their memory efficiency7.4.3 Using generator expressions where applicable7.4.4 Discussion7.4.5 Challenge7.5 How do I create partial functions to make routine function calls easier?7.5.1 “Localizing” shared functions to simplify function calls7.5.2 Creating a partial function to localize a function7.5.3 Discussion7.5.4 ChallengeSummary
Part 3 Defining classes
8 Defining user-friendly classes
8.1 How do I define the initialization method for a class?8.1.1 Demystifying self: The first parameter in __init__8.1.2 Setting proper arguments in __init__8.1.3 Specifying all attributes in __init__8.1.4 Defining class attributes outside the __init__ method8.1.5 Discussion8.1.6 Challenge8.2 When do I define instance, static, and class methods?8.2.1 Defining instance methods for manipulating individual instances8.2.2 Defining static methods for utility functionalities8.2.3 Defining class methods for accessing class-level attributes8.2.4 Discussion8.2.5 Challenge8.3 How do I apply finer access control to a class?8.3.1 Creating protected methods by using an underscore as the prefix8.3.2 Creating private methods by using double underscores as the prefix8.3.3 Creating read-only attributes with the property decorator8.3.4 Verifying data integrity with a property setter8.3.5 Discussion8.3.6 Challenge8.4 How do I customize string representation for a class?8.4.1 Overriding __str__ to show meaningful information for an instance8.4.2 Overriding __repr__ to provide instantiation information8.4.3 Understanding the differences between __str__ and __repr__8.4.4 Discussion8.4.5 Challenge8.5 Why and how do I create a superclass and subclasses?8.5.1 Identifying the use scenario of subclasses8.5.2 Inheriting the superclass's attributes and methods automatically8.5.3 Overriding the superclass's methods to provide customized behaviors8.5.4 Creating non-public methods of the superclass8.5.5 Discussion8.5.6 ChallengeSummary
9 Using classes beyond the basics
9.1 How do I create enumerations?9.1.1 Avoiding a regular class for enumerations9.1.2 Creating an enumeration class9.1.3 Using enumerations9.1.4 Defining methods for the enumeration class9.1.5 Discussion9.1.6 Challenge9.2 How do I use data classes to eliminate boilerplate code?9.2.1 Creating a data class using the dataclass decorator9.2.2 Setting default values for the fields9.2.3 Making data classes immutable9.2.4 Creating a subclass of an existing data class9.2.5 Discussion9.2.6 Challenge9.3 How do I prepare and process JSON data?9.3.1 Understanding JSON’s data structure9.3.2 Mapping data types between JSON and Python9.3.3 Deserializing JSON strings9.3.4 Serializing Python data to JSON format9.3.5 Discussion9.3.6 Challenge9.4 How do I create lazy attributes to improve performance?9.4.1 Identifying the use scenario9.4.2 Overriding the __getattr_ special method to implement lazy attributes9.4.3 Implementing a property as a lazy attribute9.4.4 Discussion9.4.5 Challenge9.5 How do I define classes to have distinct concerns?9.5.1 Analyzing a class9.5.2 Creating additional classes to isolate the concerns9.5.3 Connecting related classes9.5.4 Discussion9.5.5 ChallengeSummary
Part 4 Manipulating objects and files
10 Fundamentals of objects
10.1 How do I inspect an object’s type to improve code flexibility?10.1.1 Checking an object’s type using type10.1.2 Checking an object’s type using isinstance10.1.3 Checking an object’s type generically10.1.4 Discussion10.1.5 Challenge10.2 What’s the lifecycle of instance objects?10.2.1 Instantiating an object10.2.2 Being active in applicable namespaces10.2.3 Tracking reference counts10.2.4 Destructing the object10.2.5 Discussion10.2.6 Challenge10.3 How do I copy an object?10.3.1 Creating a (shallow) copy10.3.2 Noting the potential problem of a shallow copy10.3.3 Creating a deep copy10.3.4 Discussion10.3.5 Challenge10.4 How do I access and change a variable in a different scope?10.4.1 Accessing any variable: The LEGB rule for name lookup10.4.2 Changing a global variable in a local scope10.4.3 Changing an enclosing variable10.4.4 Discussion10.4.5 Challenge10.5 What’s callability, and what does it imply?10.5.1 Distinguishing classes from functions10.5.2 Revisiting the higher-order function map10.5.3 Using callable as the key argument10.5.4 Creating decorators as classes10.5.5 Discussion10.5.6 ChallengeSummary
11 Dealing with files
11.1 How do I read and write files using context management?11.1.1 Opening and closing files: Context manager11.1.2 Reading data from a file in different ways11.1.3 Writing data to a file in different ways11.1.4 Discussion11.1.5 Challenge11.2 How do I deal with tabulated data files?11.2.1 Reading a CSV file using csv reader11.2.2 Reading a CSV file that has a header11.2.3 Writing data to a CSV file11.2.4 Discussion11.2.5 Challenge11.3 How do I preserve data as files using pickling?11.3.1 Pickling objects for data preservation11.3.2 Restoring data by unpickling11.3.3 Weighing the pros and cons of pickling11.3.4 Discussion11.3.5 Challenge11.4 How do I manage files on my computer?11.4.1 Creating a directory and files11.4.2 Retrieving the list of files of a specific kind11.4.3 Moving files to a different folder11.4.4 Copying files to a different folder11.4.5 Deleting a specific kind of files11.4.6 Discussion11.4.7 Challenge11.5 How do I retrieve file metadata?11.5.1 Retrieving the filename-related information11.5.2 Retrieving the file's size and time information11.5.3 Discussion11.5.4 ChallengeSummary
Part 5 Safeguarding the codebase
12 Logging and exception handling
12.1 How do I monitor my program with logging?12.1.1 Creating the Logger object to log application events12.1.2 Using files to store application events12.1.3 Adding multiple handlers to the logger12.1.4 Discussion12.1.5 Challenge12.2 How do I save log records properly?12.2.1 Categorizing application events with levels12.2.2 Setting a handler’s level12.2.3 Setting formats to the handler12.2.4 Discussion12.2.5 Challenge12.3 How do I handle exceptions?12.3.1 Handling exceptions with try. . .except. . .12.3.2 Specifying the exception in the except clause12.3.3 Handling multiple exceptions12.3.4 Showing more information about an exception12.3.5 Discussion12.3.6 Challenge12.4 How do I use else and finally clauses in exception handling?12.4.1 Using else to continue the logic of the code in the try clause12.4.2 Cleaning up the exception handling with the finally clause12.4.3 Discussion12.4.4 Challenge12.5 How do I raise informative exceptions with custom exception classes?12.5.1 Raising exceptions with a custom message12.5.2 Preferring built-in exception classes12.5.3 Defining custom exception classes12.5.4 Discussion12.5.5 ChallengeSummary
13 Debugging and testing
13.1 How do I spot problems with tracebacks?13.1.1 Understanding how a traceback is generated13.1.2 Analyzing a traceback when running code in a console13.1.3 Analyzing a traceback when running a script13.1.4 Focusing on the last call in a traceback13.1.5 Discussion13.1.6 Challenge13.2 How do I debug my program interactively?13.2.1 Activating the debugger with a breakpoint13.2.2 Running code line by line13.2.3 Stepping into another function13.2.4 Inspecting pertinent variables13.2.5 Discussion13.2.6 Challenge13.3 How do I test my functions automatically?13.3.1 Understanding the basis for testing functions13.3.2 Creating a TestCase subclass for testing functions13.3.3 Setting up the test13.3.4 Discussion13.3.5 Challenge13.4 How do I test a class automatically?13.4.1 Creating a TestCase subclass for testing a class13.4.2 Responding to test failures13.4.3 Discussion13.4.4 ChallengeSummary
Part 6 Building a web app
14 Completing a real project
14.1 How do I use a virtual environment for my project?14.1.1 Understanding the rationale for virtual environments14.1.2 Creating a virtual environment for each project14.1.3 Installing packages in the virtual environment14.1.4 Using virtual environments in Visual Studio Code14.1.5 Discussion14.1.6 Challenge14.2 How do I build the data models for my project?14.2.1 Identifying the business needs14.2.2 Creating helper classes and functions14.2.3 Creating the Task class to address these needs14.2.4 Discussion14.2.5 Challenge14.3 How do I use SQLite as my application’s database?14.3.1 Creating the database14.3.2 Retrieving records from the database14.3.3 Saving records to the database14.3.4 Updating a record in a database14.3.5 Deleting a record from the database14.3.6 Discussion14.3.7 Challenge14.4 How do I build a web app as the frontend?14.4.1 Understanding the essential features of streamlit14.4.2 Understanding the app’s interface14.4.3 Tracking user activities using session state14.4.4 Setting up the sidebar14.4.5 Showing the tasks14.4.6 Showing a task’s details14.4.7 Creating a new task14.4.8 Organizing your project14.4.9 Running the app14.4.10 Discussion14.4.11 ChallengeSummary
Appendix A. Learning Python with REPL in IDLE
A.1 Installing Python on your computerA.2 Using REPL with IDLEA.3 Using REPL in TerminalA.4 Using REPL in Visual Studio Code
Appendix B. Managing Python packages with pip
B.1 Installing pip on your computerB.2 Installing and updating individual packagesB.3 Installing multiple packagesB.4 Uninstalling packages
Appendix C. Using Jupyter Notebook: A web-based interactive Python editor
C.1 The essential ideas behind Jupyter NotebookC.2 Installing Jupyter Notebook and its variationsC.3 The essential operations of Jupyter Notebook
Appendix D. Integrating version control into your project
D.1 The brief rationale for using version controllingD.2 The typical workflow of a projectD.3 Facilitating the collaborative work with a version control systemD.4 Highlighting the key terminologies
Appendix E. Preparing your package for public distribution
E.1 Selecting PyPI as the distribution targetE.2 Preparing the filesE.3 Registering a TestPyPI accountE.4 Installing, archiving, and uploading toolsE.5 Distributing your packageE.6 Testing your package
Appendix F. solutions to the challenges
index
inside back cover

Overview

Have you ever asked yourself, “How do I do that in Python?” If so, you’ll love this practical collection of the most important Python techniques.

Python How-To includes over 60 detailed answers to questions like:

How do I join and split strings?
How do I access dictionary keys, values, and items?
How do I set and use the return value in function calls?
How do I process JSON data?
How do I create lazy attributes to improve performance?
How do I change variables in a different namespace?

…and much more!

Python How-To walks you through the most important coding techniques in Python. Whether you’re doing data science, building web applications, or writing admin scripts, you’ll find answers to your “how-to” questions in this book. Inside you’ll find important insights into both Python basics and deep-dive topics to help you skill-up at any stage of your Python career. Author Yong Cui’s clear and practical writing is instantly accessible and makes it easy to take advantage of Python’s versatile tools and libraries. Perfect to be read both from cover to cover, and whenever you need help troubleshooting your code.

About the Technology
Python How-To uses a simple but powerful method to lock in 63 core Python skills. You’ll start with a question, like “How do I find items in a sequence?” Next, you’ll see an example showing the basic solution in crystal-clear code. You’ll then explore interesting variations, such as finding substrings or identifying custom classes. Finally, you’ll practice with a challenge exercise before moving on to the next How-To.

About the Book
This practical guide covers all the language features you’ll need to get up and running with Python. As you go, you’ll explore best practices for writing great Python code. Practical suggestions and engaging graphics make each important technique come to life. Author Yong Cui’s careful cross-referencing reveals how you can reuse features and concepts in different contexts.

What's Inside
How to:

Join and split strings
Access dictionary keys, values, and items
Set and use the return value in function calls
Process JSON data
Create lazy attributes to improve performance
Change variables in a different namespace

…and much more.

About the Reader
For beginning to intermediate Python programmers.

About the Author
Dr. Yong Cui has been working with Python in bioscience for data analysis, machine learning, and tool development for over 15 years.

Quotes
Insightful, with practical and immediate application.
- James Matlock, Wake Technical Community College

Useful examples that correctly answer the basic 'how-to' questions you ask yourself while programming.
- Vitosh K. Doynov, DHL Global Forwarding

Written from the developer’s point of view! Cui does a masterful job helping the reader understand elegant Pythonic solutions.
- Chris Villanueva, Fulton-Nevets, Domestic Holdings

I loved how the challenges reinforce each topic.
- Chris Kardell, DEBS

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