TheAlgorithms/Python · error · Exception

must have the same size

Error message

must have the same size

What it means

Raised by Vector.__add__ in linear_algebra/src/lib.py:83 when the two vectors being added have different lengths. The method compares len(self) with len(other) and, on mismatch, raises a bare Exception with the terse message 'must have the same size'. Vector addition is only defined component-wise for equal dimensions.

Source

Thrown at linear_algebra/src/lib.py:83

    def __str__(self) -> str:
        """
        returns a string representation of the vector
        """
        return "(" + ",".join(map(str, self.__components)) + ")"

    def __add__(self, other: Vector) -> Vector:
        """
        input: other vector
        assumes: other vector has the same size
        returns a new vector that represents the sum.
        """
        size = len(self)
        if size == len(other):
            result = [self.__components[i] + other.component(i) for i in range(size)]
            return Vector(result)
        else:
            raise Exception("must have the same size")

    def __sub__(self, other: Vector) -> Vector:
        """
        input: other vector
        assumes: other vector has the same size
        returns a new vector that represents the difference.
        """
        size = len(self)
        if size == len(other):
            result = [self.__components[i] - other.component(i) for i in range(size)]
            return Vector(result)
        else:  # error case
            raise Exception("must have the same size")

    def __eq__(self, other: object) -> bool:
        """
        performs the comparison between two vectors
        """

View on GitHub (pinned to f5988cc097)

Solutions

1. Check len(v1) == len(v2) before applying + (both Vector and plain list sizes).
2. Find the construction site of the shorter vector — usually one list lost or gained an element.
3. Pad the shorter vector with zeros if that is semantically valid for your use case.
4. Since this is a bare Exception, catch it narrowly (see defense) or validate beforehand rather than blanket except.

Example fix

// before
v = Vector([1, 2, 3]) + Vector([1, 2])  # Exception: must have the same size

// after
v1, v2 = Vector([1, 2, 3]), Vector([1, 2])
if len(v1) != len(v2):
    raise ValueError(f"dimension mismatch: {len(v1)} vs {len(v2)}")
v = v1 + v2

def same_size(v1, v2) -> bool:
    return len(v1) == len(v2)

if not same_size(a, b):
    raise ValueError(f"cannot add: sizes {len(a)} and {len(b)} differ")
result = a + b

from linear_algebra.src.lib import Vector

def is_vector_of(obj, n: int) -> bool:
    return isinstance(obj, Vector) and len(obj) == n

try:
    result = a + b
except Exception as e:  # library raises bare Exception
    if "same size" in str(e):
        raise ValueError(f"vector size mismatch: {len(a)} vs {len(b)}") from e
    raise

When it happens

Trigger: Using the + operator between Vector instances of different dimensions: Vector([1, 2, 3]) + Vector([1, 2]). Also hit indirectly when one vector was built from a truncated list or a loop that produced fewer components.

Common situations: Merging feature vectors of different schema versions, one-hot vectors built from vocabularies of different sizes, or slicing a vector and forgetting to slice the other operand to match.

Related errors

• vector must have the same size as the number of columns of t
• index out of range
• Vector is empty
• matrix must have the same dimension!
• matrices must have the same dimension!

AI-assisted analysis of TheAlgorithms/Python@f5988cc097 (2026-08-14). Data as JSON: /api/errors/087dc0832a3ae35d. Report an issue: GitHub.