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Python all(): Check if all elements are truthy

The built-in all() function returns True if every element in an iterable is truthy; otherwise it returns False. It evaluates elements lazily and short-circuits on the first falsy value, making it efficient for large or streaming data.

Syntax

all(iterable)

Parameter: Any iterable (list, tuple, set, dict, generator, etc.).

Returns: True if all elements are truthy, False otherwise. For an empty iterable, all([]) returns True by definition.

Truthiness rules

• Falsy: False, None, numeric zero (0, 0.0), empty containers ([], (), {}, set(), ""), and objects with __bool__ returning False.
• Truthy: Everything else, including non-zero numbers, non-empty strings, and non-empty containers.

Quick examples

print(all([1, 2, 3]))             # True
print(all([1, 0, 3]))             # False (0 is falsy)
print(all(["a", "b", ""]))        # False (empty string is falsy)
print(all([]))                    # True (empty iterable)
print(all(x > 0 for x in [2, 4])) # True (generator lazily evaluated)

Short-circuiting and generators

all() consumes the iterable lazily. With generators or comprehensions, evaluation stops at the first falsy element, which saves time and memory.

def valid_row(row):
    return all(field is not None and field != "" for field in row)

# Stops as soon as a field is None or empty
row = ["id123", "Alice", None, "NY"]
print(valid_row(row))  # False

Common use cases

• Validation: Ensure all required fields are present.
• Constraints: Verify all numbers meet a condition (e.g., non-negative).
• Flags: Confirm all toggles are enabled before proceeding.

numbers = [3, 5, 7]
print(all(n > 0 for n in numbers))  # True

Pitfalls and caveats

• Dicts iterate keys: all({1: True, 0: True}) evaluates keys (1 and 0), not values. Use all(d.values()) to check values.
• Empty iterable is True: This is by design; combine with a non-emptiness check if needed.
• String truthiness: Non-empty strings are truthy; ensure you check content (e.g., whitespace) explicitly.

d = { "a": True, "b": False }
print(all(d))          # True (keys "a" and "b" are truthy)
print(all(d.values())) # False (checks the actual boolean values)

Performance notes

• Laziness: Avoids evaluating the entire iterable when a falsy element appears early.
• Memory efficiency: Pair with generators to avoid building intermediate lists.
• Complex predicates: Cache or simplify expensive checks to benefit from short-circuiting.

Comparison with any()

• all(): True if every element is truthy; empty iterable yields True.
• any(): True if at least one element is truthy; empty iterable yields False.

vals = [0, "", None, 5]
print(any(vals))  # True (5 is truthy)
print(all(vals))  # False (0, "", None are falsy)

FAQ

Does all() work with custom objects?

Yes. If an object defines __bool__() (or __len__()), its truthiness is used.

How do I ensure non-empty and all truthy?

Combine checks: iterable and all(iterable) or len(iterable) > 0 and all(...).

Can I stop early on failure with logging?

Use a loop to log the failing element, or wrap the predicate to log before returning False.

Related keywords

Python all, truthiness, short-circuit evaluation, generators, validation, iterable, any vs all, boolean context, performance

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