用Python语言写一个完全背包算法，不导入库就可以使用，并且输出所放物品和价值，代码简洁

当然可以。完全背包算法（0-1 Knapsack Problem）是一个经典的动态规划问题，我们可以通过循环和条件判断来实现。这里是一个简单的Python代码示例：

def knap_sack(weights, values, capacity):
    n = len(weights)
    dp = [[0 for _ in range(capacity + 1)] for _ in range(n + 1)]

    # 构建动态规划表
    for i in range(1, n+1):
        for w in range(1, capacity + 1):
            if weights[i - 1] <= w:
                dp[i][w] = max(values[i - 1] + dp[i - 1][w - weights[i - 1]], dp[i - 1][w])
            else:
                dp[i][w] = dp[i - 1][w]

    # 找出最优解并记录物品
    selected_items = []
    w = capacity
    for i in reversed(range(n)):
        if dp[i][w] != dp[i - 1][w]:
            selected_items.append((i, weights[i], values[i]))
            w -= weights[i]
    
    return dp[n][capacity], selected_items

# 示例输入
weights = [2, 3, 4, 5]
values = [6, 9, 7, 10]
capacity = 8
max_value, items = knap_sack(weights, values, capacity)

print(f"最大价值：{max_value}")
print("选择的物品及价值：")
for item in items:
    print(f"物品 {item[0]+1}，重量 {item[1]}，价值 {item[2]}")

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