# Here is a list with duplicate names
names = ['Alice', 'Bob', 'Alice', 'Eve', 'Bob', 'Dave']

print('Original list:')
print(names)

# Remove duplicates using a set
unique_names = set(names)

print('Names with duplicates removed:')
print(unique_names)

# Convert the set back to a list to keep working with it as a list
unique_names_list = list(unique_names)

print('Unique names as a list:')
print(unique_names_list)

# Remove duplicates and keep the original order
numbers = [4, 2, 4, 3, 2, 1, 5, 3, 1]
unique_numbers = []

for number in numbers:
    if number not in unique_numbers:
        unique_numbers.append(number)

print('Numbers with duplicates removed, order kept:')
print(unique_numbers)

# Use dictionary keys to remove duplicates and keep order (Python 3.7+)
colors = ['red', 'blue', 'red', 'green', 'blue', 'yellow']
unique_colors = list(dict.fromkeys(colors))

print('Unique colors, order kept:')
print(unique_colors)

# Get input from the user and remove duplicates
user_input = input('Enter a few items separated by commas: ')
items = [item.strip() for item in user_input.split(',')]
unique_items = list(dict.fromkeys(items))

print('Here are your unique items:')
print(unique_items)

# Challenge: Remove duplicates from a list with different types of data
mixed_list = [1, '1', 2, '2', 2, 1, 'one', 'One', 'ONE']
unique_mixed = list(dict.fromkeys(mixed_list))
print('Unique values from a mixed list:')
print(unique_mixed)

# Remove duplicates using a list comprehension
animals = ['cat', 'dog', 'cat', 'bird', 'dog', 'cat', 'fish']
seen = set()
unique_animals = [animal for animal in animals if not (animal in seen or seen.add(animal))]

print('Animals with no duplicates:')
print(unique_animals)

# Remove duplicates from user input numbers, sorted
number_input = input('Enter numbers separated by spaces: ')
numbers_list = [int(num) for num in number_input.split()]
unique_sorted = sorted(set(numbers_list))

print('Sorted set of unique numbers:')
print(unique_sorted)

# Remove duplicates ignoring upper/lowercase letters
cars = ['Toyota', 'toyota', 'Honda', 'HONDA', 'Ford', 'ford']
unique_cars = []
seen = set()
for car in cars:
    lower = car.lower()
    if lower not in seen:
        seen.add(lower)
        unique_cars.append(car)

print('Unique cars, case-insensitive:')
print(unique_cars)

# Mini-project part 1: Clean a contact list
contacts = [
    {'name': 'Amy', 'phone': '123'},
    {'name': 'Bob', 'phone': '234'},
    {'name': 'Amy', 'phone': '123'},
    {'name': 'Eve', 'phone': '345'},
    {'name': 'bob', 'phone': '234'},
]

unique_contacts = []
seen_contacts = set()

for contact in contacts:
    key = (contact['name'].lower(), contact['phone'])
    if key not in seen_contacts:
        unique_contacts.append(contact)
        seen_contacts.add(key)

print('Unique contacts:')
print(unique_contacts)

# Mini-project part 2: Count how many items were removed
before = len(contacts)
after = len(unique_contacts)
removed = before - after
print(f'Removed {removed} duplicates from the contact list.')

# Troubleshooting: Why did this not remove all duplicates?
bad_list = ['apple', 'Apple', 'APPLE', 'apple']
unique_bad = list(set(bad_list))
print('Result:', unique_bad)

# Extra tip: Combine two lists and remove duplicates
list1 = ['A', 'B', 'C', 'C']
list2 = ['C', 'D', 'E', 'A']
combined = list(set(list1 + list2))

print('Combined unique elements:')
print(combined)

# Challenge: Remove duplicates from a text file (lines)
filename = 'sample.txt'

# First, make a small sample file to work with
with open(filename, 'w') as f:
    f.write('cat\n')
    f.write('dog\n')
    f.write('cat\n')
    f.write('fish\n')
    f.write('dog\n')

# Now load lines and remove duplicates
with open(filename, 'r') as f:
    lines = f.readlines()
unique_lines = list(dict.fromkeys(line.strip() for line in lines))

print('Unique lines from file:')
print(unique_lines)

# Recap: Different ways to remove duplicates
print('1. Use set() to remove all duplicates (order does not matter)')
print('2. Use dict.fromkeys() to keep order (Python 3.7+)')
print('3. Use a for-loop to filter duplicates the way you want')