Passing integers for minimax algorithm python

Question

I implemented the following minimax algorithm for the reversi GamePigeon game in python:

def minimaxabp(depth, max_player, game, move, alpha, beta):
if depth == 0 or game.gameOver:
    return game.calcScore()

if (max_player):
    moves = game.getValidMoves()
    bestMove = [-1, -1]
    bestScore = -99999

    for m in moves:
        ga = deepcopy(game)
        ga.doTurn(m[0], m[1])
        score = minimaxabp(depth - 1, not max_player, ga, move, alpha, beta)
        if score > bestScore:
            bestMove[0] = m[0]
            bestMove[1] = m[1]
            bestScore = score

        alpha[0] = max(alpha[0], bestScore)

        if beta[0] <= alpha[0]:
            break

    move[0] = bestMove[0]
    move[1] = bestMove[1]

    return bestScore

else:
    moves = game.getValidMoves()
    bestMove = [-1, -1]
    bestScore = 99999

    for m in moves:
        ga = deepcopy(game)
        ga.doTurn(m[0], m[1])
        score = minimaxabp(depth - 1, not max_player, ga, move, alpha, beta)
        if score < bestScore:
            bestMove[0] = m[0]
            bestMove[1] = m[1]
            bestScore = score

        beta[0] = min(beta[0], bestScore)

        if beta[0] <= alpha[0]:
            break

    move[0] = bestMove[0]
    move[1] = bestMove[1]

    return bestScore

The algorithm works fine if I comment out the two parts that say:

if beta[0] <= alpha[0]:
            break

which basically just turns it into a normal minimax algorithm. Because Python doesn't let you pass integers as references instead of values, I used an integer of length one instead. The alpha-beta pruning implementation looks exactly like every example I can find, so I assume it has to be a problem with the parameters getting passed around. For what it's worth, alpha and beta get declared in the following manner:

alpha = []
    alpha.append(-999999)
    beta = []
    beta.append(999999)