# This first approach work, relying on repeated calls to list methods,
# but it is not as efficient if invoked on really big data sets

def removeAll(data, val):
    while val in data:
        data.remove(val)


# This second approach is far more efficient in practice, but also
# more intricate in terms of an algorithm. We scan through the data, 
# consolidating all the non-matches toward the left side of the list,
# and then eventually shrinking the list to only those elements.


def removeAll(data, val):
    opening = 0   # next place we will put a non-match
    scan = 0      # index at which we are scanning
    while scan < len(data):
        if data[scan] != val:
            data[opening] = data[scan]
            opening += 1
        scan += 1

    # at this point, all the desired contents are where we want.
    # just need to pop the garbage at the end
    for extra in range(scan-opening):
        data.pop()