Python Programming - Student & Professional Series: 3 Laminated Quickstudy Reference Guides pdf baixar

Three best-selling guides created for developers of all skill levels to find the essentials of Python in the fastest reference guides for writing code. Python Programming with key concepts behind Python logic, syntax, and operation. Standard Library covering the most used modules and the methods available in each module. Python with AI adds skills to deliberately direct AI tools to explain unfamiliar code, navigate libraries faster, design cleaner architecture, and write better tests (no vibe coding). Author Berajah Jayne created the original best-selling Python Language guide that has been the #1 seller in the Python category. Author Robin Nixon worked with computers in the 80s and started developing websites in the 90s becoming an expert and writing over 40 programming books and over 500 articles for top computer magazines. With his expertise in the field and writing to his audience in our succinct and organized QuickStudy format you get quality actionable content, more than you will find per page in any book or website. Designed for quick access to the facts you need, these inexpensive tools are an easy add to your programming toolbox. As our programming reference guides climb in sales to best-selling status, it is clear that print is not dead and these handy desktop tools are an unbeatable value.
Three 6 page laminated guides include:

Python Programming Language

• History & Key Features
• Language Structure
  • Naming Conventions
• Variables & Data Types
  • Common Data Types
  • Type Hints & Static Typing (Python 3.5+)
  • Unions
  • Reserved Keywords
• Importing Modules
• Console Input & Output
  • Display Output
  • Convert Output
  • Control Print Behavior
• Strings
  • Concatenation & Repetition
  • Get String Length
  • Access Characters & Slices
  • Escape Characters
  • String Formatting
• Operators
  • Arithmetic Operators
  • Comparison Operators
  • Logical Operators
  • Assignment Operators
  • Bitwise Operators
  • Membership Operators
  • Identity Operators
  • Assignment Expressions (Python 3.8+)
• Statements
  • Simple Statements
  • Compound Statements
  • Expressions vs. Statements
  • Multiline Statements
• Functions
  • Variable-Length Arguments
• Flow Control
  • Basic if Statement
  • The if ... else Statement
  • Using if ... elif ... else
  • One-Line if Statement
  • Check Multiple Conditions
  • Structural Pattern Matching (Python 3.10+)
  • asyncio for Asynchronous Programming (Python 3.7+)
• Looping
• Object-Oriented Programming (OOP)
  • Classes & Objects
  • Inheritance
  • Polymorphism
  • Method Overriding
  • self Type (Python 3.11+)
  • dataclasses Module (Python 3.7+)
  • Generators

Python Standard Library

• General Functionality
• Date/Time Processing
• OS Module
  • File Operations
  • Process Control
  • Environment Variables & System Info
  • Properties of the DirEntry Class: Use DirEntry_Instance.x
  • The pathlib Module: Use pathlib.x
  • Properties of the Purepath Class: PurePath_Instance.x
• Process & Thread Management
• Debugging Functionality
  • PDB Module
  • Debugging for the PDB Module
• Mathematic and Numeric Operations
  • Math Module
• Iterable and Iterator Operations
  • Collections Module
  • Classes of the Collections Module
  • Itertools Module

Python with Generative AI

• AI & Your Development Environment
  • VS Code: Your AI Command Center
  • Jupyter Notebooks with AI Assistance
  • Setting Up AI API Keys
  • Token Costs
  • Copyright & AI-Generated Code
• AI Assistance Core Use Cases
  • Code Completion & Refactoring
  • Code Search & Retrieval
  • Library & API Familiarization
  • Code Conversion & Translation
• AI for Specific Coding Tasks
  • Authentication & Integration
  • AI for Testing
  • AI for Regex & String Handling
• AI as Debugging Partner
  • Diagnosing Errors & Exceptions
  • Reading Stack Traces with AI
  • Multilevel Stack Traces
  • Context is Key
• AI for Code Design & Planning
  • System Design via Conversation
  • Data Models & Class Design
• AI for Advanced Python
  • From Code Assistant to Engineering Partner
• AI-Assisted Docs & Commenting
  • Commenting What Matters
  • Markdown & README Generation
• AI in Responsible Python Development
  • Hallucination Risks
  • Lack of Long-term Memory
  • Other Limitations
  • When Not to Trust Autocomplete
• AI Prompt Hygiene & Version Control
  • Always Check Your Diffs
  • Use .gptignore or Equivalent for Sharing
• AI-Assisted Security
  • Safe Coding
• AI-Assisted Optimization
  • Improving Performance
• AI for Maintaining Legacy Code
  • Reading & Understanding Old Code
  • Refactoring & Modernization
  • Risk Reduction & Safe Refactoring
• Top Prompts
• Popular AI Assistants