Python Ultimate Tutorial

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Documentation

• Python Documentation: https://docs.python.org/3/
• PEP 8: https://www.python.org/dev/peps/pep-0008/
• Google Style Guide: https://google.github.io/styleguide/pyguide.html

Installation

• Installing Anaconda: https://docs.anaconda.com/anaconda/install/
• Installing Jupyter: https://jupyter.org/install
• Online Jupyter notebook from Google: https://colab.research.google.com/
• Installing Python: https://www.python.org/downloads/

Python 3.9

Table of content

• 1. Setting up the environment with Jupyter Notebook

• 2. A simple Introduction to Python

• 3. Create a calculator with Python

  • 3.1. Numbers
  • 3.2. Strings
  • 3.3. Lists
  • 3.4. First Steps Towards Programming

• 4. Control Flow Tools

  • 4.1. if Statements
  • 4.2. for Statements
  • 4.3. The range() Function
  • 4.4. break and continue Statements, and else Clauses on Loops
  • 4.5. pass Statements
  • 4.6. Defining Functions
  • 4.7. More on Defining Functions
    • 4.7.1. Default Argument Values
    • 4.7.2. Keyword Arguments
    • 4.7.3. Special parameters
    • 4.7.3.1. Positional-or-Keyword Arguments
    • 4.7.3.2. Positional-Only Parameters
    • 4.7.3.3. Keyword-Only Arguments
    • 4.7.3.4. Function Examples
    • 4.7.3.5. Recap
    • 4.7.4. Arbitrary Argument Lists
    • 4.7.5. Unpacking Argument Lists
    • 4.7.6. Lambda Expressions
    • 4.7.7. Documentation Strings
    • 4.7.8. Function Annotations
  • 4.8. Intermezzo: Coding Style

• 5. Data Structures

  • 5.1. More on Lists
    • 5.1.1. Using Lists as Stacks
    • 5.1.2. Using Lists as Queues
    • 5.1.3. List Comprehensions
    • 5.1.4. Nested List Comprehensions
  • 5.2. The del statement
  • 5.3. Tuples and Sequences
  • 5.4. Sets
  • 5.5. Dictionaries
  • 5.6. Looping Techniques
  • 5.7. More on Conditions
  • 5.8. Comparing Sequences and Other Types

• 6. Modules

  • 6.1. More on Modules
    • 6.1.1. Executing modules as scripts
    • 6.1.2. The Module Search Path
    • 6.1.3. “Compiled” Python files
  • 6.2. Standard Modules
  • 6.3. The dir() Function
  • 6.4. Packages
    • 6.4.1. Importing * From a Package
    • 6.4.2. Intra-package References
    • 6.4.3. Packages in Multiple Directories

• 7. Input and Output

  • 7.1. Fancier Output Formatting
    • 7.1.1. Formatted String Literals
    • 7.1.2. The String format() Method
    • 7.1.3. Manual String Formatting
    • 7.1.4. Old string formatting
  • 7.2. Reading and Writing Files
    • 7.2.1. Methods of File Objects
    • 7.2.2. Saving structured data with json

• 8. Errors and Exceptions

  • 8.1. Syntax Errors
  • 8.2. Exceptions
  • 8.3. Handling Exceptions
  • 8.4. Raising Exceptions
  • 8.5. Exception Chaining
  • 8.6. User-defined Exceptions
  • 8.7. Defining Clean-up Actions
  • 8.8. Predefined Clean-up Actions

• 9. Classes

  • 9.1. A Word About Names and Objects
  • 9.2. Python Scopes and Namespaces
    • 9.2.1. Scopes and Namespaces Example
  • 9.3. A First Look at Classes
    • 9.3.1. Class Definition Syntax
    • 9.3.2. Class Objects
    • 9.3.3. Instance Objects
    • 9.3.4. Method Objects
    • 9.3.5. Class and Instance Variables
  • 9.4. Random Remarks
  • 9.5. Inheritance
    • 9.5.1. Multiple Inheritance
  • 9.6. Private Variables
  • 9.7. Odds and Ends
  • 9.8. Iterators
  • 9.9. Generators
  • 9.10. Generator Expressions

• 10. Brief Tour of the Standard Library

  • 10.1. Operating System Interface
  • 10.2. File Wildcards
  • 10.3. Command Line Arguments
  • 10.4. Error Output Redirection and Program Termination
  • 10.5. String Pattern Matching
  • 10.6. Mathematics
  • 10.7. Internet Access
  • 10.8. Dates and Times
  • 10.9. Data Compression
  • 10.10. Performance Measurement
  • 10.11. Quality Control
  • 10.12. Batteries Included

• 11. Brief Tour of the Standard Library — Part II

  • 11.1. Output Formatting
  • 11.2. Templating
  • 11.3. Working with Binary Data Record Layouts
  • 11.4. Multi-threading
  • 11.5. Logging
  • 11.6. Weak References
  • 11.7. Tools for Working with Lists
  • 11.8. Decimal Floating Point Arithmetic

• 12. Virtual Environments and Packages

  • 12.1. Introduction
  • 12.2. Creating Virtual Environments
  • 12.3. Managing Packages with pip

• 13. PEP 8 - Style Guide for Python code

  • 13.1. Introduction

  • 13.2. A Foolish Consistency is the Hobgoblin of Little Minds

  • 13.3. Code Lay-out

    • 13.3.1. Indentation
    • 13.3.2. Tabs or Spaces?
    • 13.3.3. Maximum Line Length
    • 13.3.4. Should a Line Break Before or After a Binary Operator?
    • 13.3.5. Blank Lines
    • 13.3.6. Source File Encoding
    • 13.3.7. Imports
    • 13.3.8. Module Level Dunder Names

  • 13.4. String Quotes

  • 13.5. Whitespace in Expressions and Statements

    • 13.5.1. Pet Peeves
    • 13.5.2. Other Recommendations

  • 13.6. When to Use Trailing Commas

  • 13.7. Comments

    • 13.7.1. Block Comments
    • 13.7.2. Inline Comments
    • 13.7.3. Documentation Strings

  • 13.8. Naming Conventions

    • 13.8.1. Overriding Principle
    • 13.8.2. Descriptive: Naming Styles
    • 13.8.3. Prescriptive: Naming Conventions
      • 13.8.3.1. Names to Avoid
      • 13.8.3.2. ASCII Compatibility
      • 13.8.3.3. Package and Module Names
      • 13.8.3.4. Class Names
      • 13.8.3.5. Type Variable Names
      • 13.8.3.6. Exception Names
      • 13.8.3.7. Global Variable Names
      • 13.8.3.8. Function and Variable Names
      • 13.8.3.9. Function and Method Arguments
      • 13.8.3.10. Method Names and Instance Variables
      • 13.8.3.11. Constants
      • 13.8.3.12. Designing for Inheritance
    • 13.8.4. Public and Internal Interfaces

  • 13.9. Programming Recommendations

    • 13.9.1. Function Annotations
    • 13.9.2. Variable Annotations

• 14. [BONUS] Google Python Style Guide

  • 14.1. Background

  • 14.2. Python Language Rules

    • 14.2.1. Lint
    • 14.2.2. Imports
    • 14.2.3. Packages
    • 14.2.4. Exceptions
    • 14.2.5. Global variables
    • 14.2.6. Nested/Local/Inner Classes and Functions
    • 14.2.7. Comprehensions & Generator Expressions
    • 14.2.8. Default Iterators and Operators
    • 14.2.9. Generators
    • 14.2.10. Lambda Functions
    • 14.2.11. Conditional Expressions
    • 14.2.12. Default Argument Values
    • 14.2.13. Properties
    • 14.2.14. True/False Evaluations
    • 14.2.16. Lexical Scoping
    • 14.2.17. Function and Method Decorators
    • 14.2.18. Threading
    • 14.2.19. Power Features
    • 14.2.20. Modern Python: Python 3 and from __future__ imports
    • 14.2.21. Type Annotated Code

  • 14.3. Python Style Rules

    • 14.3.1. Semicolons
    • 14.3.2. Line length
    • 14.3.3. Parentheses
    • 14.3.4. Indentation
    • 14.3.4.1. Trailing commas in sequences of items?
    • 14.3.5. Blank Lines
    • 14.3.6. Whitespace
    • 14.3.7. Shebang Line
    • 14.3.8. Comments and Docstrings
      • 14.3.8.1. Docstrings
      • 14.3.8.2. Modules
      • 14.3.8.3. Functions and Methods
      • 14.3.8.4. Classes
      • 14.3.8.5. Block and Inline Comments
      • 14.3.8.6. Punctuation, Spelling, and Grammar
    • 14.3.10. Strings
      • 14.3.10.1. Logging
      • 14.3.10.2. Error Messages
    • 14.3.11. Files and Sockets
    • 14.3.12. TODO Comments
    • 14.3.13. Imports formatting
    • 14.3.14. Statements
    • 14.3.15. Accessors
    • 14.3.16. Naming
      • 14.3.16.1. Names to Avoid
      • 14.3.16.2. Naming Conventions
      • 14.3.16.3. File Naming
      • 14.3.16.4. Guidelines derived from Guido’s Recommendations
    • 14.3.17. Main
    • 14.3.18. Function length
    • 14.3.19. Type Annotations
      • 14.3.19.1. General Rules
      • 14.3.19.2. Line Breaking
      • 14.3.19.3. Forward Declarations
      • 14.3.19.4. Default Values
      • 14.3.19.5. NoneType
      • 14.3.19.6. Type Aliases
      • 14.3.19.7. Ignoring Types
      • 14.3.19.8. Typing Variables
      • 14.3.19.9. Tuples vs Lists
      • 14.3.19.10. TypeVars
      • 14.3.19.11. String types
      • 14.3.19.12. Imports For Typing
      • 14.3.19.13. Conditional Imports
      • 14.3.19.14. Circular Dependencies
      • 14.3.19.15. Generics
      • 14.3.19.16. Build Dependencies

  • 14.4. Parting Words

• 15. Python libraries

• 16. Python integretions with other technologies

• 17. Python Web technologies

• 18. Python Machine Learning

• 19. Python automation

• 20. Python modules

• 21. Python coding challenges