Best Way To Learn Python 4th Edition By Mark Lutz

best way to learn python

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Introduction: Best Way To Learn Python

Feel Free To Download the best way to learn Python Fourth Edition Pdf, If you’ve bought this book (Download Free Best Way To Learn Python Fourth Edition), you may already know what Python is and why it’s an important tool to learn. If you don’t, you probably won’t be sold on Python until you’ve learned the language by reading the rest of this book and have done a project or two. But before we jump into details, the first few pages of this book will briefly introduce some of the main reasons behind Python’s popularity. To begin sculpting a definition of Python, this chapter takes the form of a question-and-answer session, which poses some of the most common questions asked by beginners.

Why Do People Use Python?
Because there are many programming languages available today, this is the usual first question of newcomers. Given that there are roughly 1 million Python users out there at the moment, there really is no way to answer this question with complete accuracy; the choice of development tools is sometimes based on unique constraints or personal preference.
But after teaching Python to roughly 225 groups and over 3,000 students during the last 12 years, some common themes have emerged. The primary factors cited by Python users seem to be these:

The Best Way To Learn Python Software quality
For many, Python’s focus on readability, coherence, and software quality in general sets it apart from other tools in the scripting world. Python code is designed to be readable, and hence reusable and maintainable—much more so than traditional scripting languages. The uniformity of Python code makes it easy to understand, even if you did not write it. In addition, Python has deep support for more advanced software reuse mechanisms, such as object-oriented programming (OOP).

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Table Of Contents For Best Way To Learn Python

Part I. Getting Started With Best Way To Learn Python

1. A Python Q&A Session

Why Do People Use Python?
Best Way To Learn Python Software Quality
Developer Productivity
Is Python a “Scripting Language”
OK, but What’s the Downside?
Who Uses Python Today?
What Can I Do with Python?
Systems Programming
GUI
Internet Scripting
Component Integration
Database Programming
Rapid Prototyping
Numeric and Scientific Programming
Gaming, Images, Serial Ports, XML, Robots, and More
How Is Python Supported?
What Are Python’s Technical Strengths?
It’s Object-Oriented
It’s Free
It’s Portable
It’s Powerful
It’s Mixable
It’s Easy to Use
It’s Easy to Learn
It’s Named After Monty Python
How Does Python Stack Up to Language X?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

2. How Python Runs Programs

Introducing the Python Interpreter
Program Execution
The Programmer’s View
Python’s View
Execution Model Variations
Python Implementation Alternatives
Execution Optimization Tools
Frozen Binaries
Other Execution Options
Future Possibilities?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

3. How You Run Program

Best Way To Learn Python Interactive Prompt
Running Code Interactively
Why the Interactive Prompt?
Using the Interactive Prompt
System Command Lines and Files
A First Script
Running Files with Command Lines
Using Command Lines and Files
Unix Executable Scripts (#!)
Clicking File Icons
Clicking Icons on Windows
The input Trick
Other Icon-Click Limitations
Module Imports and Reloads
The Grander Module Story: Attributes
import and reload Usage Notes
Using exec to Run Module Files
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part I Exercises

Part II. Types and Operations
4. Introducing Python Object Types

Why Use Built-in Types?
Python’s Core Data Types
Numbers
Strings
Sequence Operations
Immutability
Type-Specific Methods
Getting Help
Other Ways to Code Strings
Pattern Matching
Lists
Sequence Operations
Type-Specific Operations
Bounds Checking
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

5. Numeric Types

Numeric Type Basics
Numeric Literals
Built-in Numeric Tools
Python Expression Operators
Numbers in Action
Variables and Basic Expressions
Numeric Display Formats
Comparisons: Normal and Chained
Division: Classic, Floor, and True
Integer Precision
Complex Numbers
Hexadecimal, Octal, and Binary Notation
Bitwise Operations
Other Built-in Numeric Tools
Other Numeric Types
Decimal Type
Fraction Type
Sets
Booleans
Numeric Extensions
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

6. The Dynamic Typing Interlude

The Case of the Missing Declaration Statements
Variables, Objects, and References
Types Live with Objects, Not Variables
Objects Are Garbage-Collected
Shared References
Shared References and In-Place Changes
Shared References and Equality
Dynamic Typing Is Everywhere
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

7. Strings

String Literals
Single- and Double-Quoted Strings Are the Same
Escape Sequences Represent Special Bytes
Raw Strings Suppress Escapes
Triple Quotes Code Multiline Block Strings
Strings in Action
Basic Operations
Indexing and Slicing
String Conversion Tools
Changing Strings
String Methods
String Method Examples: Changing Strings
String Method Examples: Parsing Text
Other Common String Methods in Action
The Original string Module (Gone in 3.0)
String Formatting Expressions
Advanced String Formatting Expressions
Dictionary-Based String Formatting Expressions
String Formatting Method Calls
The Basics
Adding Keys, Attributes, and Offsets
Adding Specific Formatting
Comparison to the % Formatting Expression
Why the New Format Method?
General Type Categories
Types Share Operation Sets by Categories
Mutable Types Can Be Changed In-Place
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

8. Lists and Dictionaries

Lists
Lists in Action
Basic List Operations
List Iteration and Comprehensions
Indexing, Slicing, and Matrixes
Changing Lists In-Place
Dictionaries
Dictionaries in Action
Basic Dictionary Operations
Changing Dictionaries In-Place
More Dictionary Methods
A Languages Table
Dictionary Usage Notes
Other Ways to Make Dictionaries
Dictionary Changes in Python 3.0
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

9. Tuples, Files, and Everything Else

Tuples
Tuples in Action
Why Lists and Tuples?
Files
Opening Files
Using Files
Files in Action
Other File Tools
Type Categories Revisited
Object Flexibility
References Versus Copies
Comparisons, Equality, and Truth
Python 3.0 Dictionary Comparisons
The Meaning of True and False in Python
Python’s Type Hierarchies
Type Objects
Other Types in Python
Built-in Type Gotchas
Assignment Creates References, Not Copies
Repetition Adds One Level Deep
Beware of Cyclic Data Structures
Immutable Types Can’t Be Changed In-Place
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part II Exercises

Part III. Statements and Syntax
10. Introducing Python Statements

Python Program Structure Revisited
Python’s Statements
A Tale of Two ifs
What Python Adds
What Python Removes
Why Indentation Syntax?
A Few Special Cases
A Quick Example: Interactive Loops
A Simple Interactive Loop
Doing Math on User Inputs
Handling Errors by Testing Inputs
Handling Errors with try Statements
Nesting Code Three Levels Deep
Chapter Summary
Test Your: Quiz
Test Your Knowledge:

11. Assignments, Expressions, and Prints

Assignment Statements
Assignment Statement Forms
Sequence Assignments
Extended Sequence Unpacking in Python 3.0
Multiple-Target Assignments
Augmented Assignments
Variable Name Rules
Expression Statements
Expression Statements and In-Place Changes
Print Operations
The Python 3.0 print Function
The Python 2.6 print Statement
Print Stream Redirection
Version-Neutral Printing
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

12. if Tests and Syntax Rules

if Statements
General Format
Basic Examples
Multiway Branching
Python Syntax Rules
Block Delimiters: Indentation Rules
Statement Delimiters: Lines and Continuations
A Few Special Cases
Truth Tests
The if/else Ternary Expression
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

13. while and for Loops

while Loops
General Format
Examples
break, continue, pass, and the Loop else
General Loop Format
pass
continue
break
Loop else
for Loops
General Format
Examples
Loop Coding Techniques
Counter Loops: while and range
Nonexhaustive Traversals: range and Slices
Changing Lists: range
Parallel Traversals: zip and map
Generating Both Offsets and Items: enumerate
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

14. Iterations and Comprehensions, Part 1

Iterators: A First Look
The Iteration Protocol: File Iterators
Manual Iteration: iter and next
Other Built-in Type Iterators
List Comprehensions: A First Look
List Comprehension Basics
Using List Comprehensions on Files
Extended List Comprehension Syntax
Other Iteration Contexts
New Iterables in Python 3.0
The range Iterator
The map, zip, and filter Iterators
Multiple Versus Single Iterators
Dictionary View Iterators
Other Iterator Topics
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

15. The Documentation Interlude

Python Documentation Sources
# Comments
The dir Function
Docstrings: __doc__
PyDoc: The help Function
PyDoc: HTML Reports
The Standard Manual Set
Web Resources
Published Books
Common Coding Gotchas
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers 90
Test Your Knowledge: Part III Exercises

Part IV. Functions
16. Function Basics

Why Use Functions?
Coding Functions
def Statements
def Executes at Runtime
A First Example: Definitions and Calls
Definition
Calls
Polymorphism in Python
A Second Example: Intersecting Sequences
Definition
Calls
Polymorphism Revisited
Local Variables
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

17. Scopes

Python Scope Basics
Scope Rules
Name Resolution: The LEGB Rule
Scope Example
The Built-in Scope
The global Statement
Minimize Global Variables
Minimize Cross-File Changes
Other Ways to Access Globals
Scopes and Nested Functions
Nested Scope Details
Nested Scope Examples
The nonlocal Statement
nonlocal Basics
nonlocal in Action
Why nonlocal?
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

18. Arguments

Argument-Passing Basics
Arguments and Shared References
Avoiding Mutable Argument Changes
Simulating Output Parameters
Special Argument-Matching Modes
The Basics
Matching Syntax
The Gritty Details
Keyword and Default Examples
Arbitrary Arguments Examples
Python 3.0 Keyword-Only Arguments
The min Wakeup Call!
Full Credit
Bonus Points
The Punch Line…
Generalized Set Functions
Emulating the Python 3.0 print Function
Using Keyword-Only Arguments
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

19. Advanced Function Topics

Function Design Concepts
Recursive Functions
Summation with Recursion
Coding Alternatives
Loop Statements Versus Recursion
Handling Arbitrary Structures
Function Objects: Attributes and Annotations
Indirect Function Calls
Function Introspection
Function Attributes
Function Annotations in 3.0
Anonymous Functions: lambda
lambda Basics
Why Use lambda?
How (Not) to Obfuscate Your Python Code
Nested lambdas and Scopes
Mapping Functions over Sequences: map
Functional Programming Tools: filter and reduce
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

20. Iterations and Comprehensions, Part 2

List Comprehensions Revisited: Functional Tools
List Comprehensions Versus map
Adding Tests and Nested Loops: filter
List Comprehensions and Matrixes
Comprehending List Comprehensions
Iterators Revisited: Generators
Generator Functions: yield Versus return
Generator Expressions: Iterators Meet Comprehensions
Generator Functions Versus Generator Expressions
Generators Are Single-Iterator Objects
Emulating zip and map with Iteration Tools
Value Generation in Built-in Types and Classes
3.0 Comprehension Syntax Summary
Comprehending Set and Dictionary Comprehensions
Extended Comprehension Syntax for Sets and Dictionaries
Timing Iteration Alternatives
Timing Module
Timing Script
Timing Results
Timing Module Alternatives
Other Suggestions
Function Gotchas
Local Names Are Detected Statically
Defaults and Mutable Objects
Functions Without returns
Enclosing Scope Loop Variables
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers
Test Your Knowledge: Part IV Exercises

Part V. Modules
21. Modules: The Big Picture

Why Use Modules?
Python Program Architecture
How to Structure a Program
Imports and Attributes
Standard Library Modules
How Imports Work
1. Find It
2. Compile It (Maybe)
3. Run It
The Module Search Path
Configuring the Search Path
Search Path Variations
The sys.path List
Module File Selection
Advanced Module Selection Concepts
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

22. Module Coding Basics

Module Creation
Module Usage
The import Statement
The from Statement
The from * Statement
Imports Happen Only Once
import and from Are Assignments
Cross-File Name Changes
import and from Equivalence
Potential Pitfalls of the from Statement
Module Namespaces
Files Generate Namespaces
Attribute Name Qualification
Imports Versus Scopes
Namespace Nesting
Reloading Modules
reload Basics
reload Example
Chapter Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Answers

 

Part IX. Appendixes of Best Way To Learn Python

A. Installation and Configuration
B. Solutions to End-of-Part Exercises
Index

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