Python Iterables Part 2: Advanced Functions and Transformations

Understanding map()

# Basic syntax: map(transformation_function, iterable)

# Simple temperature conversion example
celsius_temps = [0, 10, 20, 30, 40]

def to_fahrenheit(c):
    """Convert Celsius to Fahrenheit"""
    return (c * 9/5) + 32

# Converting all temperatures at once
fahrenheit_temps = list(map(to_fahrenheit, celsius_temps))

print("Temperature Conversion:")
for c, f in zip(celsius_temps, fahrenheit_temps):
    print(f"{c}°C = {f}°F")
                

Let's break down what makes map() special:

• It's memory efficient - it transforms items one at a time
• It creates an iterator, not a list (use list() to see all results)
• It can work with any function that takes one argument

Real-World Example: Data Cleaning

# Cleaning messy user data
raw_data = [
    '  John Smith  ',
    'JANE DOE',
    'bob wilson',
    '  Alice Brown  '
]

def clean_name(name):
    """Standardize a name by:
    1. Removing extra spaces
    2. Capitalizing first letters
    3. Converting rest to lowercase"""
    return name.strip().title()

# Clean all names at once
clean_names = list(map(clean_name, raw_data))

print("\nCleaned Names:")
for original, cleaned in zip(raw_data, clean_names):
    print(f"Original: '{original}' → Cleaned: '{cleaned}'")
                

Understanding filter()

# Basic syntax: filter(condition_function, iterable)

# Example: Finding prime numbers
def is_prime(n):
    """Check if a number is prime"""
    if n < 2:
        return False
    for i in range(2, int(n ** 0.5) + 1):
        if n % i == 0:
            return False
    return True

numbers = range(1, 20)
primes = list(filter(is_prime, numbers))

print(f"Prime numbers up to 20: {primes}")

# Practical Example: Error Log Analysis
log_entries = [
    "INFO: System started",
    "ERROR: Database connection failed",
    "INFO: Processing file",
    "ERROR: Memory overflow",
    "WARNING: High CPU usage"
]

def is_error(entry):
    """Check if log entry is an error"""
    return entry.startswith("ERROR")

# Finding all error messages
errors = list(filter(is_error, log_entries))

print("\nError Messages Found:")
for error in errors:
    print(f"- {error}")
                

Combining map() and filter()

# Processing student grades
students = [
    {'name': 'Alice', 'grade': 85, 'attendance': 0.95},
    {'name': 'Bob', 'grade': 92, 'attendance': 0.88},
    {'name': 'Charlie', 'grade': 78, 'attendance': 0.92},
    {'name': 'Diana', 'grade': 95, 'attendance': 0.85},
]

# First filter for high performers, then get their names
honor_roll = list(map(
    lambda s: s['name'],
    filter(
        lambda s: s['grade'] >= 90 and s['attendance'] >= 0.9,
        students
    )
))

print("\nHonor Roll Students:")
for student in honor_roll:
    print(f"- {student}")
                

Basic and Advanced Sorting

# Basic sorting
numbers = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
sorted_numbers = sorted(numbers)
print(f"Sorted numbers: {sorted_numbers}")

# Custom sorting with key function
books = [
    {'title': 'Python Basics', 'year': 2020, 'rating': 4.5},
    {'title': 'Advanced Python', 'year': 2019, 'rating': 4.8},
    {'title': 'Python Cookbook', 'year': 2021, 'rating': 4.6}
]

# Sorting by multiple criteria
def book_sort_key(book):
    """Sort books by rating (descending) then year (ascending)"""
    return (-book['rating'], book['year'])

sorted_books = sorted(books, key=book_sort_key)

print("\nBooks by Rating (then Year):")
for book in sorted_books:
    print(f"{book['title']}: {book['rating']}★ ({book['year']})")

# Case-insensitive sorting
names = ['alice', 'Bob', 'charlie', 'David']
sorted_names = sorted(names, key=str.lower)
print(f"\nSorted names: {sorted_names}")
                

Using enumerate() Effectively

# Basic enumeration
tasks = ['Review code', 'Write tests', 'Update docs']

print("Today's Tasks:")
for index, task in enumerate(tasks, start=1):
    print(f"{index}. {task}")

# Practical Example: Finding Word Positions
def find_word_positions(text, target):
    """Find all positions of a word in text"""
    words = text.split()
    return [
        pos 
        for pos, word in enumerate(words) 
        if word.lower() == target.lower()
    ]

text = "The quick brown fox jumps over the lazy fox"
fox_positions = find_word_positions(text, "fox")
print(f"\n'Fox' appears at positions: {fox_positions}")

# Creating indexed dictionaries
colors = ['red', 'green', 'blue']
color_dict = {
    index: color 
    for index, color in enumerate(colors)
}
print(f"\nColor lookup: {color_dict}")