🔃 Python Sort a List – Ascending, Descending, Custom Key

🧲 Introduction – Why Learn List Sorting?

Sorting is a fundamental operation in Python programming. Whether you need to sort:

• 🔢 Numbers
• 🅰️ Strings
• 🧱 Tuples or objects
• 🧪 Custom conditions

Python provides powerful and flexible sorting tools using .sort() and sorted().

🎯 In this guide, you’ll learn:

• How to sort a list in Python (ascending and descending)
• Difference between sort() and sorted()
• Sort strings, tuples, dictionaries, and objects
• Use custom key functions for advanced sorting
• Best practices for clean, reliable code

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✅ 1. Sort a List of Numbers – Ascending

nums = [5, 2, 9, 1]
nums.sort()
print(nums)  # [1, 2, 5, 9]

✅ list.sort() sorts the list in place.

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🔄 2. Sort a List of Numbers – Descending

nums = [5, 2, 9, 1]
nums.sort(reverse=True)
print(nums)  # [9, 5, 2, 1]

✅ Add reverse=True to flip the order.

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📤 3. Use sorted() – Returns a New List

nums = [5, 2, 9, 1]
new_nums = sorted(nums)
print(new_nums)   # [1, 2, 5, 9]
print(nums)       # Original remains unchanged

✅ Use sorted() when you don’t want to modify the original list.

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🧠 4. Sort Strings Alphabetically

words = ["banana", "apple", "cherry"]
words.sort()
print(words)  # ['apple', 'banana', 'cherry']

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🔠 Case-Insensitive Sort

words = ["Banana", "apple", "Cherry"]
words.sort(key=str.lower)
print(words)  # ['apple', 'Banana', 'Cherry']

✅ Use key=str.lower to ignore case sensitivity.

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🧮 5. Sort by Length of Words

words = ["a", "apple", "banana"]
words.sort(key=len)
print(words)  # ['a', 'apple', 'banana']

✅ Pass any function to key for custom sort criteria.

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🧱 6. Sort a List of Tuples by Second Value

items = [(1, 'b'), (3, 'a'), (2, 'c')]
items.sort(key=lambda x: x[1])
print(items)  # [(3, 'a'), (1, 'b'), (2, 'c')]

✅ Use lambda functions for advanced sorting logic.

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🧰 7. Sort List of Dictionaries by a Key

people = [{"name": "Alice", "age": 30}, {"name": "Bob", "age": 25}]
people.sort(key=lambda x: x["age"])
print(people)  # [{'name': 'Bob', ...}, {'name': 'Alice', ...}]

✅ Sort complex structures like JSON or database records.

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🏗️ 8. Sort Custom Objects with attrgetter

from operator import attrgetter

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

people = [Person("Alice", 30), Person("Bob", 25)]
people.sort(key=attrgetter("age"))

for p in people:
    print(p.name, p.age)

✅ Cleaner and faster than lambda x: x.attr.

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🧪 9. Stable Sort – Order is Preserved for Equal Items

data = [(2, 'a'), (1, 'b'), (1, 'c')]
sorted_data = sorted(data, key=lambda x: x[0])
print(sorted_data)  # [(1, 'b'), (1, 'c'), (2, 'a')]

✅ Python uses Timsort – a stable sorting algorithm.

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📘 Best Practices

✅ Do This	❌ Avoid This
Use .sort() to sort in-place	Expecting .sort() to return a new list
Use sorted() for non-destructive sort	Overwriting original list unnecessarily
Use key with lambda or functions	Using nested loops for sorting
Use attrgetter for object attributes	Writing long lambda chains unnecessarily

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📌 Summary – Recap & Next Steps

Python makes sorting intuitive and powerful. You can sort numbers, strings, tuples, dictionaries, and objects with ease using sort() and sorted().

🔍 Key Takeaways:

• ✅ Use .sort() for in-place sorting
• ✅ Use sorted() to get a new list
• ✅ Use key functions to customize sorting
• ✅ Use reverse=True for descending order
• ✅ Python’s sort is stable and fast (Timsort)

⚙️ Real-World Relevance:
Used in data processing, search filters, leaderboards, sorting records, and ranking systems.

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❓ FAQ – Python Sort a List

❓ What is the difference between sort() and sorted()?

• sort() changes the original list
• sorted() returns a new sorted list

❓ How do I sort in descending order?

✅ Use reverse=True:

sorted(data, reverse=True)

❓ Can I sort by multiple keys?

✅ Yes, use a tuple in key:

data.sort(key=lambda x: (x[0], x[1]))

❓ Does sorting change the original list?

• sort() – ✅ Yes
• sorted() – ❌ No (non-destructive)

❓ Can I sort a list of dictionaries?

✅ Yes, using key=lambda x: x["field"]

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