纯 Python 加速器 - 快速学习,快速见效
Pure Python Accelerator - Rapid Learning for Quick Results
- 1. Essential Tools
- 2. Intro
- 3. Creating a New Python Project in replit.com
- 2. Variables and Basic Python Concepts
- 1. Intro
- 2. What is Python
- 3. Console Magic Unleashing the Power of Python's Print Function
- 5. Single Quotes vs Double Quotes
- 6. Variables in Python
- 8. Variable Naming Conventions
- 10. Input Function
- 12. Common Errors in Python
- 3. Data Types
- 1. Intro
- 2. Int and Str Data Types
- 4. Float and Boolean Data Types
- 6. String Bulti-In Functions
- 8. Numerical Built-In Functions
- 9. Type Casting
- 4. Operators in Python
- 1. Intro
- 2. The Assignment Operators
- 3. The Arithmetic Operators
- 5. Operator Precedence
- 7. Comparison Operators
- 9. Boolean Operators
- 5. Control Flow in Python
- 1. Intro
- 2. The if Statement
- 3. Hold the Result Of a Condition Into a Variable
- 4. if Body with Multiple Lines
- 5. The else Part
- 7. Multiple Conditions
- 9. Nested if
- 11. Combining Conditions with Boolean Operators
- 6. Writing Your Own Functions
- 1. Intro
- 2. Writing Your First Python Function
- 3. Functions That Accept Parameters
- 4. Returning a Value From a Function
- 5. Setting Default Values For Parameters
- 7. Data Structures in Python - Lists
- 1. Intro
- 2. What Are Lists in Python
- 3. List Indexing
- 4. Inserting New Items Into a List
- 5. Removing Items From a List
- 6. 5- Updating an Item From a List
- 8. Sorting a List
- 9. Finding an Item in a List - The in Keyword
- 10. Slicing a List
- 8. Loops in Python
- 1. Intro
- 2. Why Do We Need Loop Structures
- 3. The for Loop in Python
- 4. Iterating Over a List
- 5. Infinite Loop
- 9. To Do App - Use All You Have Learned Until Now!
- 1. Intro
- 2. How Does the To-do App Work
- 3. Implementing the Main Structure Of the To-do App
- 4. Implementing the add_task() Function
- 5. Implementing the show_tasks() Function
- 6. Implementing the edit_task() Function
- 7. Implementing the delete_task() Function
- 10. Data Structures in Python - Tuples
- 1. Intro
- 2. Tuples vs Lists
- 3. Returning Multiple Values From a Function by Using a Tuple
- 4. Unpacking Tuples
- 5. Advantages of Tuples Over Lists
- 7. A Collection of Collections
- 9. Iterating Over a Collection of Collections
- 11. Data Structures in Python - Sets
- 1. Intro
- 2. How Does a Set Work in Python
- 4. Set Advantages (Case-Study #1)
- 5. Set Advantages (Case-Study #2)
- 6. Set Advantages (Case-Study #3)
- 7. The difference() Function
- 8. The union() Function
- 9. The isdisjoint() Function
- 10. The issubset() Function
- 12. How Does Dictionary work in Python
- 12. Comprehension in Python Filtering and Mapping Lists, Tuples, Sets and Dicts
- 1. Intro
- 2. Mapping a List by Using List Comprehension
- 3. Filtering a List by Using List Comprehension
- 4. Mapping a Dictionary by Using Dictionary Comprehension
- 5. Filtering a Dictionary by Using Dictionary Comprehension
- 13. Classes and Objects
- 1. Intro
- 2. Object-Oriented Programming A Powerful Paradigm for Software Design
- 3. What Are Classes in Python
- 4. What is self
- 5. Encapsulation
- 14. File Input Output
- 1. Intro
- 2. Reading From a File
- 3. Appending a Content To the End of a File
- 4. Replacing the Content
- 5. Iterating Through the Lines of a File
- 6. Writing a List of Lines Into a File
- 15. Exception Handling
- 1. Intro
- 2. Types of Errors
- 3. What is an Exception
- 4. How Does Exception Handling Help Us
- 5. The else Part
- 6. The finally Block
- 7. Types of an Exception
- 16. Task Management System Leverage Your Python Programming Skills All in One
- 1. Intro
- 2. How Does the Task Management System Work
- 3. Implementing the Task Class
- 4. Implementing the create_task() Function
- 5. Implementing the display_tasks() Function
- 6. Implementing the save_tasks() Function
- 7. Implementing the load_tasks() Function
- 8. Implementing the update_task_status() Function
- 9. Put it All Together!
- 10. Testing the Task Management System