- 01Environment Setup (what you'll need)
- 02Variables and print()
- 03Conditionals (if statements)
- 04Loops (for statements)
- 05Writing Your First Function
- 06Working with Lists
- 07Working with Dictionaries (dict)
- 08Loops (while statements)
- 09Working with Strings
- 10Introducing Classes (Object-Oriented Programming)
- 11Error Handling (try...except)
- 12List Comprehensions
- 13Generators and yield
- 14File Handling Basics
- 15The match Statement (Python's switch)
- 16The Conditional (Ternary) Expression
- 17Inheritance (Extending a Class)
- 18Writing Comments
- 19Logical Operators (and, or, not)
- 20Constants (values you agree not to change)
- 21Splitting and Joining Strings (split, join)
- 22Writing None-Safe Code
- 23Searching a List (in and finding the next match)
- 24Transforming a List with map()
- 25Two-Dimensional Lists (grid-shaped data)
- 26Writing a Custom Exception Class
- 27Default Arguments (initial parameter values)
- 28Working with Sets
- 29Checking Correctness with assert (your first step into testing)
- 30Higher-Order Functions (passing a function as an argument)
- 31Stacks and Queues (basic data structures)
- 32Type Conversion (casting) Basics
- 33Intro to Regular Expressions (pattern matching)
- 34The Binary Search Algorithm
- 35Building a Caesar Cipher (a character-shifting cipher)
- 36Understanding How Bubble Sort Works
- 37Building and Displaying Dates (basic year/month/day operations)
- 38Writing Multiple Test Cases Together
- 39Speeding Up Calculations with Memoization (caching)
- 40Normalizing Strings (strip, unifying case)
- 41Shallow Copy vs. Deep Copy
- 42Enum (Enumerated Types) Basics
- 43Flattening a List
- 44Reversing a String and Checking for Palindromes
- 45Pairing Up Two Lists (the zip operation)
- 46Rounding Numbers (floor, ceil, round)
- 47Multi-Line Strings (triple quotes)
- 48Functions That Return Multiple Values (tuples)
- 49Finding the GCD and LCM (the Euclidean algorithm)
- 50Formatting Numbers (padding digits, decimal places)
- 51Cleanup Logic with try/except/finally
- 52Writing Type-Agnostic Functions
- 53The with Statement (Context Managers) Basics
- 54Generating Random Numbers
- 55Bitwise Operators (AND, OR, XOR, shifts)
- 56Class Variables and @staticmethod Basics
- 57Waiting for a Fixed Amount of Time (time.sleep)
- 58Watch Out for Floating-Point Rounding Errors
- 59Type Hints Basics
- 60FizzBuzz (the classic practice problem)
- 61Checking Whether a Number Is Prime
- 62Set Operations (union, intersection, difference)
- 63Converting Number Bases (binary, hex)
- 64Checking Balanced Parentheses (an application of stacks)
- 65Checking Whether Two Words Are Anagrams
- 66Checking Whether a Year Is a Leap Year
- 67Converting Temperature (Celsius to Fahrenheit)
- 68Prime Factorization
- 69[Applied] Build a Household Budget Tool
Shallow Copy vs. Deep Copy
This lesson covers the difference between shallow and deep copies, so you can avoid unexpected bugs when duplicating lists and dictionaries. It's written for anyone searching "Python shallow copy deep copy" or "Python copy deepcopy".
A shallow copy duplicates only the outermost container, while any nested objects inside remain shared with the original. A deep copy duplicates everything all the way down, so changing the copy never affects the original. .copy() makes a shallow copy; copy.deepcopy() makes a deep copy.
The sample code shallow-copies a dictionary, original, into shallow with .copy(), and you can see that modifying the nested part (address["city"]) also changes the original original. In contrast, modifying a deep copy made with copy.deepcopy(original) has no effect on the original data.
"I made a copy, but somehow the original changed too" is a classic beginner bug that happens exactly because this distinction isn't understood. This difference matters most when working with data that has "containers inside containers," like nested lists or dictionaries.
In real development, correctly choosing the right kind of copy matters, for example, when temporarily editing form input while wanting to preserve the original data. Applications that manage a lot of state especially need to understand this distinction.
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