127. Custom Sorting Functions

In Python, custom sorting of complex data structures can be achieved by using the sorted() function or the sort() method with a custom comparison function. Python’s sorting mechanism is based on the key parameter, which is a function that transforms the items before sorting. Here's a series of examples that demonstrate how to use custom sorting functions to sort complex data structures:

1. Sorting List of Tuples by Second Element

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data = [(1, 'apple'), (3, 'orange'), (2, 'banana')]

# Sorting by the second element of each tuple
sorted_data = sorted(data, key=lambda x: x[1])
print(sorted_data)  # Output: [(1, 'apple'), (2, 'banana'), (3, 'orange')]

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2. Sorting a List of Dictionaries by Multiple Keys

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data = [
    {'name': 'John', 'age': 25, 'city': 'New York'},
    {'name': 'Jane', 'age': 22, 'city': 'Los Angeles'},
    {'name': 'Alice', 'age': 30, 'city': 'Chicago'}
]

# Sorting by age, then by name
sorted_data = sorted(data, key=lambda x: (x['age'], x['name']))
print(sorted_data)
# Output: [{'name': 'Jane', 'age': 22, 'city': 'Los Angeles'}, {'name': 'John', 'age': 25, 'city': 'New York'}, {'name': 'Alice', 'age': 30, 'city': 'Chicago'}]

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3. Sorting Objects by Multiple Attributes

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class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __repr__(self):
        return f"Person(name={self.name}, age={self.age})"

people = [Person('John', 25), Person('Alice', 30), Person('Bob', 25)]

# Sorting by age, then by name
sorted_people = sorted(people, key=lambda x: (x.age, x.name))
print(sorted_people)
# Output: [Person(name=Bob, age=25), Person(name=John, age=25), Person(name=Alice, age=30)]

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4. Sorting Strings by Length

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words = ['apple', 'banana', 'pear', 'cherry', 'kiwi']

# Sorting by length of the string
sorted_words = sorted(words, key=len)
print(sorted_words)  # Output: ['kiwi', 'pear', 'apple', 'banana', 'cherry']

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5. Sorting List of Tuples in Descending Order

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data = [(1, 'apple'), (3, 'orange'), (2, 'banana')]

# Sorting by the first element in descending order
sorted_data = sorted(data, key=lambda x: x[0], reverse=True)
print(sorted_data)  # Output: [(3, 'orange'), (2, 'banana'), (1, 'apple')]

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6. Sorting with a Custom Comparison Function Using cmp_to_key

In Python 3, cmp functions have been removed. However, you can still use them with functools.cmp_to_key.

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from functools import cmp_to_key

def compare_tuples(a, b):
    return a[0] - b[0]  # Compare by the first element

data = [(1, 'apple'), (3, 'orange'), (2, 'banana')]

sorted_data = sorted(data, key=cmp_to_key(compare_tuples))
print(sorted_data)  # Output: [(1, 'apple'), (2, 'banana'), (3, 'orange')]

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7. Sorting List of Dictionaries by String Length

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data = [
    {'name': 'John', 'age': 25},
    {'name': 'Jane', 'age': 22},
    {'name': 'Alexander', 'age': 30}
]

# Sorting by length of the name field
sorted_data = sorted(data, key=lambda x: len(x['name']))
print(sorted_data)  
# Output: [{'name': 'Jane', 'age': 22}, {'name': 'John', 'age': 25}, {'name': 'Alexander', 'age': 30}]

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8. Sorting Dates in a List of Tuples

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from datetime import datetime

dates = [
    ('2024-01-01', 'New Year'),
    ('2023-12-25', 'Christmas'),
    ('2024-07-04', 'Independence Day')
]

# Convert string to datetime and sort
sorted_dates = sorted(dates, key=lambda x: datetime.strptime(x[0], '%Y-%m-%d'))
print(sorted_dates)  
# Output: [('2023-12-25', 'Christmas'), ('2024-01-01', 'New Year'), ('2024-07-04', 'Independence Day')]

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9. Sorting List of Mixed Types (Integers and Strings)

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data = [3, 'banana', 1, 'apple', 2, 'cherry']

# Sorting by type first, then by value
sorted_data = sorted(data, key=lambda x: (isinstance(x, str), x))
print(sorted_data)  
# Output: [1, 2, 3, 'apple', 'banana', 'cherry']

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10. Custom Sorting with Tuple and Custom Comparator

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data = [(5, "task5"), (2, "task2"), (3, "task3"), (1, "task1")]

# Custom comparator function to sort by the second element in reverse order
def custom_comparator(x):
    return -len(x[1])

# Sorting using the custom comparator
sorted_data = sorted(data, key=custom_comparator)
print(sorted_data)  
# Output: [(5, 'task5'), (3, 'task3'), (2, 'task2'), (1, 'task1')]

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These examples show how to sort complex data structures using custom sorting logic, such as by multiple keys, object attributes, string lengths, or through custom comparison functions. By leveraging Python's sorted() function and key parameter, you can easily sort data based on a variety of criteria without writing complex sorting algorithms from scratch.