Think Python. 3rd Edition - Helion
ebook
Autor: Allen B. DowneyISBN: 9781098155407
stron: 328, Format: ebook
Data wydania: 2024-05-24
Księgarnia: Helion
Cena książki: 116,84 zł (poprzednio: 177,03 zł)
Oszczędzasz: 34% (-60,19 zł)
Python is an excellent way to get started in programming, and this clear, concise guide walks you through Python a step at a time—beginning with basic programming concepts before moving on to functions, data structures, and object-oriented design. This revised third edition reflects the growing role of large language models (LLMs) in programming and includes exercises on effective LLM prompts, testing code, and debugging skills.
With this popular hands-on guide at your side, you'll get:
- A grounding in the syntax and semantics of the Python language
- A clear definition of each programming concept, with emphasis on clear vocabulary
- How to work with variables, statements, functions, and data structures in a logical progression
- Techniques for reading and writing files and databases
- A solid understanding of objects, methods, and object-oriented programming
- Debugging strategies for syntax, runtime, and semantic errors
- An introduction to recursion, interface design, data structures, and basic algorithms
- How to use LLMs—including effective prompts, testing code, and debugging
- And more
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Spis treści
Think Python. 3rd Edition eBook -- spis treści
- Preface
- Who Is This Book For?
- Goals of the Book
- Navigating the Book
- Whats New in the Third Edition?
- Getting Started
- Resources for Teachers
- Conventions Used in This Book
- Using Code Examples
- OReilly Online Learning
- How to Contact Us
- Acknowledgments
- 1. Programming as a Way of Thinking
- Arithmetic Operators
- Expressions
- Arithmetic Functions
- Strings
- Values and Types
- Formal and Natural Languages
- Debugging
- Glossary
- Exercises
- 2. Variables and Statements
- Variables
- State Diagrams
- Variable Names
- The import Statement
- Expressions and Statements
- The print Function
- Arguments
- Comments
- Debugging
- Glossary
- Exercises
- 3. Functions
- Defining New Functions
- Parameters
- Calling Functions
- Repetition
- Variables and Parameters Are Local
- Stack Diagrams
- Tracebacks
- Why Functions?
- Debugging
- Glossary
- Exercises
- 4. Functions and Interfaces
- The jupyturtle Module
- Making a Square
- Encapsulation and Generalization
- Approximating a Circle
- Refactoring
- Stack Diagram
- A Development Plan
- Docstrings
- Debugging
- Glossary
- Exercises
- 5. Conditionals and Recursion
- Integer Division and Modulus
- Boolean Expressions
- Logical Operators
- if Statements
- The else Clause
- Chained Conditionals
- Nested Conditionals
- Recursion
- Stack Diagrams for Recursive Functions
- Infinite Recursion
- Keyboard Input
- Debugging
- Glossary
- Exercises
- 6. Return Values
- Some Functions Have Return Values
- And Some Have None
- Return Values and Conditionals
- Incremental Development
- Boolean Functions
- Recursion with Return Values
- Leap of Faith
- Fibonacci
- Checking Types
- Debugging
- Glossary
- Exercises
- 7. Iteration and Search
- Loops and Strings
- Reading the Word List
- Updating Variables
- Looping and Counting
- The in Operator
- Search
- Doctest
- Glossary
- Exercises
- 8. Strings and Regular Expressions
- A String Is a Sequence
- String Slices
- Strings Are Immutable
- String Comparison
- String Methods
- Writing Files
- Find and Replace
- Regular Expressions
- String Substitution
- Debugging
- Glossary
- Exercises
- 9. Lists
- A List Is a Sequence
- Lists Are Mutable
- List Slices
- List Operations
- List Methods
- Lists and Strings
- Looping Through a List
- Sorting Lists
- Objects and Values
- Aliasing
- List Arguments
- Making a Word List
- Debugging
- Glossary
- Exercises
- 10. Dictionaries
- A Dictionary Is a Mapping
- Creating Dictionaries
- The in Operator
- A Collection of Counters
- Looping and Dictionaries
- Lists and Dictionaries
- Accumulating a List
- Memos
- Debugging
- Glossary
- Exercises
- 11. Tuples
- Tuples Are Like Lists
- But Tuples Are Immutable
- Tuple Assignment
- Tuples as Return Values
- Argument Packing
- Zip
- Comparing and Sorting
- Inverting a Dictionary
- Debugging
- Glossary
- Exercises
- 12. Text Analysis and Generation
- Unique Words
- Punctuation
- Word Frequencies
- Optional Parameters
- Dictionary Subtraction
- Random Numbers
- Bigrams
- Markov Analysis
- Generating Text
- Debugging
- Glossary
- Exercises
- Exercise
- 13. Files and Databases
- Filenames and Paths
- f-strings
- YAML
- Shelve
- Storing Data Structures
- Checking for Equivalent Files
- Walking Directories
- Debugging
- Glossary
- Exercises
- 14. Classes and Functions
- Programmer-Defined Types
- Attributes
- Objects as Return Values
- Objects Are Mutable
- Copying
- Pure Functions
- Prototype and Patch
- Design-First Development
- Debugging
- Glossary
- Exercises
- 15. Classes and Methods
- Defining Methods
- Another Method
- Static Methods
- Comparing Time Objects
- The __str__ Method
- The __init__ Method
- Operator Overloading
- Debugging
- Glossary
- Exercises
- 16. Classes and Objects
- Creating a Point
- Creating a Line
- Equivalence and Identity
- Creating a Rectangle
- Changing Rectangles
- Deep Copy
- Polymorphism
- Debugging
- Glossary
- Exercises
- 17. Inheritance
- Representing Cards
- Card Attributes
- Printing Cards
- Comparing Cards
- Decks
- Printing the Deck
- Add, Remove, Shuffle, and Sort
- Parents and Children
- Specialization
- Debugging
- Glossary
- Exercises
- 18. Python Extras
- Sets
- Counters
- defaultdict
- Conditional Expressions
- List Comprehensions
- any and all
- Named Tuples
- Packing Keyword Arguments
- Debugging
- Glossary
- Exercises
- 19. Final Thoughts
- Index