TheAlgorithms/Python · error · ValueError

differentiate() requires a function as input for func

Error message

differentiate() requires a function as input for func

What it means

Raised by differentiate() in maths/dual_number_automatic_differentiation.py when the func argument is not callable. The routine drives automatic differentiation by evaluating func(Dual(position, 1)) and reading the resulting dual parts, so it must receive an actual function; anything else fails the callable(func) check with ValueError.

Source

Thrown at maths/dual_number_automatic_differentiation.py:119

    >>> differentiate(lambda y: 0.5 * (y + 3) ** 6, 3.5, 4)
    7605.0
    >>> differentiate(lambda y: y ** 2, 4, 3)
    0
    >>> differentiate(8, 8, 8)
    Traceback (most recent call last):
        ...
    ValueError: differentiate() requires a function as input for func
    >>> differentiate(lambda x: x **2, "", 1)
    Traceback (most recent call last):
        ...
    ValueError: differentiate() requires a float as input for position
    >>> differentiate(lambda x: x**2, 3, "")
    Traceback (most recent call last):
        ...
    ValueError: differentiate() requires an int as input for order
    """
    if not callable(func):
        raise ValueError("differentiate() requires a function as input for func")
    if not isinstance(position, (float, int)):
        raise ValueError("differentiate() requires a float as input for position")
    if not isinstance(order, int):
        raise ValueError("differentiate() requires an int as input for order")
    d = Dual(position, 1)
    result = func(d)
    if order == 0:
        return result.real
    return result.duals[order - 1] * factorial(order)


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    def f(y):
        return y**2 * y**4

View on GitHub (pinned to f5988cc097)

Solutions

1. Pass a callable: differentiate(lambda x: x ** 2, 3.0, 1) or a named def.
2. If you have a string expression, first convert it with eval in a controlled namespace or use a symbolic library — do not hand the raw string to differentiate().
3. Drop the parentheses when passing named functions: f not f(x).

Example fix

# before
differentiate('x**2', 3.0, 1)   # ValueError

# after
differentiate(lambda x: x ** 2, 3.0, 1)  # 6.0

if not callable(func):
    raise TypeError(f'func must be callable, got {type(func).__name__}')

def is_func(f) -> bool:
    return callable(f)

try:
    d = differentiate(func, position, order)
except ValueError as e:
    if 'function as input' in str(e):
        raise TypeError('pass a lambda or def, not an expression result') from e
    raise

When it happens

Trigger: Calling differentiate('x**2', 3.0, 1), differentiate(42, 2.0, 1), or passing a result instead of a function like differentiate(x**2, 2.0, 1).

Common situations: Passing a string expression instead of a lambda; passing the already-computed value instead of the function object; passing an object whose class lacks __call__; confusion between a function reference f and a call f(x).

Related errors

• differentiate() requires a float as input for position
• differentiate() requires an int as input for order
• Both points must have the same dimension.
• Monogons and Digons are not polygons in the Euclidean space
• All values must be greater than 0

AI-assisted analysis of TheAlgorithms/Python@f5988cc097 (2026-08-14). Data as JSON: /api/errors/64e19f437fc8860a. Report an issue: GitHub.