- 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
Default Arguments (initial parameter values)
This lesson covers how to write default arguments in Python, so you can set an initial value used whenever an argument is omitted. It's written for anyone searching "Python default arguments tutorial".
Writing = value after a function parameter sets a "default value" that's automatically used whenever the caller omits that argument. Think of it like an order form — leave a field blank, and you get the usual default set. This means the function doesn't need to check for omission internally every time, keeping the function simple and easy for callers to use.
The sample code defines a function, def greet(name="Guest"):, where calling greet("Alice") uses that value, while calling greet() with the argument omitted falls back to the default, "Guest".
A common beginner mistake, when setting defaults on multiple parameters, is forgetting that parameters without a default must come first. Writing def f(a, b="x", c): — a parameter without a default appearing after one that has one — is a syntax error. There's also a well-known pitfall where using a list or dict as a default value can lead to unexpected behavior, so be careful there too.
In real development, default arguments are commonly used when designing a function where only some settings need to be changeable, or one with optional features. It's an essential technique for designing an API that's pleasant to use.
💡 The Python engine may take a few seconds to load the first time you run code.
