Understanding `print(any([]))` and `print(all([]))` in Python

Python has many built-in functions that make working with collections and iterables easy. Among them, any() and all() often confuse beginners when used with empty lists ([]).

• Why does print(any([])) return False?
• Why does print(all([])) return True?

Let’s break this down step by step and understand the logic behind these seemingly counterintuitive results.

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What Are any() and all() in Python?

Before diving into the specific behavior with empty lists, let’s first understand what any() and all() do.

🔹 any(iterable)

• Returns True if at least one element in the iterable is truthy.
• Returns False if the iterable is empty or all elements are falsy.

🔹 all(iterable)

• Returns True if every element in the iterable is truthy.
• Returns False if at least one element is falsy.

Now, let’s see how these functions behave with an empty list ([]).

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Why Does print(any([])) Return False?

When any() is applied to a list, it checks whether at least one element is truthy.

✅ Example: any() with non-empty lists

print(any([0, 0, 1]))  # Output: True (because 1 is truthy)
print(any([False, True, False]))  # Output: True (because True is present)
print(any([0, 0, 0]))  # Output: False (no truthy element)

❌ What happens with an empty list?

print(any([]))  # Output: False

Since there are no elements at all, any() cannot find a single truthy value. Therefore, it returns False.

💡 Key Takeaway:
👉 any([]) → False because there is no truthy element to make it return True.

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Why Does print(all([])) Return True?

The behavior of all([]) is more surprising because we might expect it to return False, like any([]). However, it actually returns True.

✅ Example: all() with non-empty lists

print(all([1, 2, 3]))  # Output: True (all elements are truthy)
print(all([1, 0, 3]))  # Output: False (because 0 is falsy)
print(all([True, False, True]))  # Output: False (because False is present)

❌ What happens with an empty list?

print(all([]))  # Output: True

Here’s why:
– all() checks whether every element in the list is truthy.
– If there are elements and at least one is falsy, it returns False.
– If there are no elements at all, there is nothing that contradicts the condition.

In mathematical logic, an empty set vacuously satisfies any universal condition because there is no counterexample. That’s why all([]) is True.

💡 Key Takeaway:
👉 all([]) → True because there is no falsy element to make it return False.

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Real-World Analogy

Let’s use an analogy to make this clearer:

Imagine a classroom where the teacher asks,
– “Does anyone have their homework?” → (any([]))
– If the classroom is empty (no students), there’s no one to say “Yes”, so the answer is False.

• “Has everyone completed their homework?” → (all([]))
  • If the classroom is empty (no students), then there’s no one to say “No”, so the answer is True by default.

This matches the behavior of any([]) == False and all([]) == True.

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Use Cases of any() and all() in Python

These functions are frequently used in real-world programming:

🔹 Checking if a list contains at least one truthy value (any())

Example: Checking if a user has at least one active subscription.

subscriptions = [False, False, True]  # At least one subscription is active
if any(subscriptions):
    print("User has an active subscription!")

🔹 Ensuring all conditions are met (all())

Example: Checking if a user has filled all required form fields.

form_fields = ["name", "email", "password"]
if all(form_fields):
    print("All fields are filled!")
else:
    print("Please complete the form.")

🔹 Filtering out empty lists

Instead of writing long conditional checks, any() and all() make the code more readable.

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Common Mistakes to Avoid

✅ Mistake 1: Expecting any([]) to return True
– Incorrect: if any([]): print("Truthy!")
– Correct: any([]) is False, so the code block won’t run.

✅ Mistake 2: Assuming all([]) should be False
– Incorrect: Thinking all([]) means “there’s nothing there, so it must be False.”
– Correct: all([]) == True because there’s nothing to contradict the condition.

✅ Mistake 3: Not understanding vacuous truth
– If you’re checking all([]), it means there are no elements that fail the condition, so it evaluates to True logically.

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Conclusion: Understanding the Logic Behind any([]) and all([])

🔑 Key Takeaways:

• any([]) == False → There are no truthy elements, so it can’t return True.
• all([]) == True → There are no falsy elements to make it return False.
• These behaviors align with logical and mathematical reasoning (vacuous truth).
• any() and all() are useful for checking conditions efficiently in real-world applications.

By mastering these concepts, you can write cleaner and more intuitive Python code!

📢 What do you think? Have you ever been confused by any([]) or all([])? Share your thoughts in the comments below! 🚀