diff --git a/maths/euclidean_distance.py b/maths/euclidean_distance.py
new file mode 100644
index 000000000000..6e0da6370219
--- /dev/null
+++ b/maths/euclidean_distance.py
@@ -0,0 +1,62 @@
+from typing import Iterable, Union
+
+import numpy as np
+
+Vector = Union[Iterable[float], Iterable[int], np.ndarray]
+VectorOut = Union[np.float64, int, float]
+
+
+def euclidean_distance(vector_1: Vector, vector_2: Vector) -> VectorOut:
+    """
+    Calculate the distance between the two endpoints of two vectors.
+    A vector is defined as a list, tuple, or numpy 1D array.
+    >>> euclidean_distance((0, 0), (2, 2))
+    2.8284271247461903
+    >>> euclidean_distance(np.array([0, 0, 0]), np.array([2, 2, 2]))
+    3.4641016151377544
+    >>> euclidean_distance(np.array([1, 2, 3, 4]), np.array([5, 6, 7, 8]))
+    8.0
+    >>> euclidean_distance([1, 2, 3, 4], [5, 6, 7, 8])
+    8.0
+    """
+    return np.sqrt(np.sum((np.asarray(vector_1) - np.asarray(vector_2)) ** 2))
+
+
+def euclidean_distance_no_np(vector_1: Vector, vector_2: Vector) -> VectorOut:
+    """
+    Calculate the distance between the two endpoints of two vectors without numpy.
+    A vector is defined as a list, tuple, or numpy 1D array.
+    >>> euclidean_distance_no_np((0, 0), (2, 2))
+    2.8284271247461903
+    >>> euclidean_distance_no_np([1, 2, 3, 4], [5, 6, 7, 8])
+    8.0
+    """
+    return sum((v1 - v2) ** 2 for v1, v2 in zip(vector_1, vector_2)) ** (1 / 2)
+
+
+if __name__ == "__main__":
+
+    def benchmark() -> None:
+        """
+        Benchmarks
+        """
+        from timeit import timeit
+
+        print("Without Numpy")
+        print(
+            timeit(
+                "euclidean_distance_no_np([1, 2, 3], [4, 5, 6])",
+                number=10000,
+                globals=globals(),
+            )
+        )
+        print("With Numpy")
+        print(
+            timeit(
+                "euclidean_distance([1, 2, 3], [4, 5, 6])",
+                number=10000,
+                globals=globals(),
+            )
+        )
+
+    benchmark()