Python Tuples Explained — Creation, Use Cases and Key Differences from Lists

# --- Creating tuples in different ways ---

# The most common way: parentheses with comma-separated values
employee = ("Alice", 34, "Engineering", 95000.00)

# Tuples can hold mixed types — name, age, department, salary
print("Full employee record:", employee)

# Accessing by index (starts at 0)
print("Name:", employee[0])        # First item
print("Age:", employee[1])         # Second item
print("Department:", employee[2])  # Third item
print("Salary:", employee[3])      # Fourth item

# Negative indexing — count from the end
print("Last item (salary):", employee[-1])   # -1 = last
print("Second to last:", employee[-2])       # -2 = second from end

# --- The comma is what actually makes a tuple ---
just_a_string = ("hello")          # This is NOT a tuple — just a string in parens
actual_tuple  = ("hello",)         # This IS a tuple — note the trailing comma

print("\nType without comma:", type(just_a_string))  # <class 'str'>
print("Type with comma:   ", type(actual_tuple))     # <class 'tuple'>

# You can even skip the parentheses entirely — the comma is enough
colour_rgb = 255, 128, 0           # Still a valid tuple!
print("\nColour tuple:", colour_rgb)
print("Type:", type(colour_rgb))   # <class 'tuple'>

# --- Basic tuple unpacking ---

# We have a tuple holding a geographic coordinate
san_francisco = (37.7749, -122.4194, "San Francisco", "USA")

# Without unpacking — messy and hard to read
print("Latitude (old way):", san_francisco[0])
print("Longitude (old way):", san_francisco[1])

# WITH unpacking — one line, instantly readable
latitude, longitude, city_name, country = san_francisco

print("\nLatitude:", latitude)
print("Longitude:", longitude)
print("City:", city_name)
print("Country:", country)

# --- Unpacking in a loop (very common in real code) ---
print("\n--- Monthly Sales Report ---")
monthly_sales = [
    ("January",  14200),
    ("February", 17800),
    ("March",    21500),
]

# Each item in the list is a tuple — we unpack it directly in the for loop
for month, revenue in monthly_sales:
    print(f"  {month}: ${revenue:,}")   # :, formats numbers with commas

# --- Starred unpacking: grab specific items, collect the rest ---
race_results = ("Amir", "Beatriz", "Chen", "Diana", "Ethan")

# Grab the gold and silver, collect everyone else as 'other_finishers'
gold, silver, *other_finishers = race_results

print("\nGold:", gold)
print("Silver:", silver)
print("Rest of field:", other_finishers)  # This becomes a list

# Swap two variables without a temp variable — tuple magic!
a = 10
b = 20
print(f"\nBefore swap: a={a}, b={b}")
a, b = b, a   # Python creates a tuple (b, a) on the right, then unpacks it
print(f"After swap:  a={a}, b={b}")

# --- Demonstrating immutability ---

# These are the ISO 4217 currency codes — they don't change
currency_codes = ("USD", "EUR", "GBP", "JPY", "AUD")

print("Currency codes:", currency_codes)
print("First code:", currency_codes[0])   # Reading is fine

# Trying to change a value — this WILL raise an error
try:
    currency_codes[0] = "BTC"    # Attempting to overwrite index 0
except TypeError as error:
    print("\nError caught:", error)
    print("Tuples protect you from accidental changes!")

# --- Tuples as dictionary keys (lists can't do this!) ---
# Imagine caching the population of cities by their coordinates
city_population_cache = {
    (40.7128, -74.0060): "New York City — 8.3 million",
    (51.5074, -0.1278):  "London — 9.0 million",
    (35.6762, 139.6503): "Tokyo — 13.9 million",
}

# Look up a city by its (latitude, longitude) key
new_york_coords = (40.7128, -74.0060)
print("\nCity lookup:", city_population_cache[new_york_coords])

# --- What happens if you try to use a list as a dict key? ---
try:
    bad_dict = {[40.7128, -74.0060]: "New York"}   # List as key
except TypeError as error:
    print("\nCan't use a list as a key:", error)

# --- Named tuples for extra readability (bonus feature) ---
from collections import namedtuple

# Define a named tuple 'type' called Point
Point = namedtuple("Point", ["x", "y"])

origin = Point(x=0, y=0)
screen_center = Point(x=960, y=540)

print("\nOrigin:", origin)
print("Screen center x:", screen_center.x)   # Access by name, not just index
print("Screen center y:", screen_center.y)

import sys

# --- Comparing memory usage ---
colours_tuple = ("red", "green", "blue", "yellow", "purple")
colours_list  = ["red", "green", "blue", "yellow", "purple"]

print("Tuple size in memory:", sys.getsizeof(colours_tuple), "bytes")
print("List size in memory: ", sys.getsizeof(colours_list),  "bytes")

# --- Practical example: when to use which ---

# TUPLE: A student's fixed record from a database row
# These values represent one specific moment-in-time snapshot — don't change them!
student_record = ("S-10482", "Maria Gonzalez", "Computer Science", 3.87)
student_id, student_name, major, gpa = student_record
print(f"\nStudent: {student_name} | GPA: {gpa}")

# LIST: A student's current enrolled courses — this changes every semester!
enrolled_courses = ["Algorithms", "Linear Algebra", "Technical Writing"]
enrolled_courses.append("Machine Learning")   # Enrolling in a new class
enrolled_courses.remove("Technical Writing")   # Dropping a class
print("Current courses:", enrolled_courses)

# --- Tuples inside lists: a very common real-world pattern ---
# A leaderboard: list of (rank, name, score) tuples
# The list can grow as more players finish; each entry is an immutable record
leaderboard = [
    (1, "Yuki",   98500),
    (2, "Carlos", 91200),
    (3, "Priya",  87650),
]

print("\n--- Leaderboard ---")
for rank, player_name, score in leaderboard:       # Unpack each tuple in the loop
    print(f"  #{rank}  {player_name:<10}  {score:,} pts")

# Add a new entry to the list (the list is mutable)
leaderboard.append((4, "Omar", 85100))
print("\nUpdated entries:", len(leaderboard), "players")