import numpy as np


def findClosestCentroids(X, centroids):
    """returns the closest centroids
    in idx for a dataset X where each row is a single example. idx = m x 1
    vector of centroid assignments (i.e. each entry in range [1..K])
    """

    # Set K
    K = len(centroids)

    # You need to return the following variables correctly.
    idx = np.zeros(X.shape[0], dtype=int)

    # ====================== YOUR CODE HERE ======================
    # Instructions: Go over every example, find its closest centroid, and store
    #               the index inside idx at the appropriate location.
    #               Concretely, idx(i) should contain the index of the centroid
    #               closest to example i. Hence, it should be a value in the
    #               range 1..K
    #
    # Note: You can use a for-loop over the examples to compute this.
    #
    # =============================================================

    return idx
