Easy

题目描述

给你一个数组 items,其中 items[i] = [typei, colori, namei] 描述第 i 件物品的类型、颜色以及名称。

另给你一条由两个字符串 ruleKeyruleValue 表示的检索规则。

如果第 i 件物品能满足下述条件之一,则认为该物品与给定的检索规则 匹配

  • ruleKey == "type"ruleValue == typei
  • ruleKey == "color"ruleValue == colori
  • ruleKey == "name"ruleValue == namei

统计并返回 匹配检索规则的物品数量

示例 1:

输入:items = [["phone","blue","pixel"],["computer","silver","lenovo"],["phone","gold","iphone"]], ruleKey = "color", ruleValue = "silver"
输出:1
解释:只有一件物品匹配检索规则,这件物品是 ["computer","silver","lenovo"] 。

示例 2:

输入:items = [["phone","blue","pixel"],["computer","silver","phone"],["phone","gold","iphone"]], ruleKey = "type", ruleValue = "phone"
输出:2
解释:只有两件物品匹配检索规则,这两件物品分别是 ["phone","blue","pixel"] 和 ["phone","gold","iphone"] 。注意,["computer","silver","phone"] 未匹配检索规则。

提示:

  • 1 <= items.length <= 10^4
  • 1 <= typei.length, colori.length, namei.length, ruleValue.length <= 10
  • ruleKey 等于 "type""color""name"
  • 所有字符串仅由小写字母组成

解题思路

这是一道简单的数组遍历题目。我们需要根据给定的规则键和规则值,统计有多少个物品满足匹配条件。

解题思路:

  1. 直接遍历:遍历每个物品,根据 ruleKey 确定要比较的属性索引,然后判断对应的值是否等于 ruleValue

  2. 索引映射:可以使用哈希表将规则键映射到对应的索引位置,这样代码更简洁:

    • "type" 对应索引 0
    • "color" 对应索引 1
    • "name" 对应索引 2
  3. 条件判断:也可以直接使用 if-else 语句判断规则键的类型。

推荐解法:使用索引映射的方法,代码简洁且易于理解。时间复杂度为 O(n),其中 n 是物品数量,空间复杂度为 O(1)。

对于每个物品,我们只需要检查对应规则键位置的值是否与规则值相等即可。

代码实现

class Solution {
public:
    int countMatches(vector<vector<string>>& items, string ruleKey, string ruleValue) {
        unordered_map<string, int> ruleMap = {{"type", 0}, {"color", 1}, {"name", 2}};
        int index = ruleMap[ruleKey];
        int count = 0;
        
        for (const auto& item : items) {
            if (item[index] == ruleValue) {
                count++;
            }
        }
        
        return count;
    }
};
class Solution:
    def countMatches(self, items: List[List[str]], ruleKey: str, ruleValue: str) -> int:
        rule_map = {"type": 0, "color": 1, "name": 2}
        index = rule_map[ruleKey]
        
        return sum(1 for item in items if item[index] == ruleValue)
public class Solution {
    public int CountMatches(IList<IList<string>> items, string ruleKey, string ruleValue) {
        var ruleMap = new Dictionary<string, int> {
            {"type", 0}, {"color", 1}, {"name", 2}
        };
        int index = ruleMap[ruleKey];
        int count = 0;
        
        foreach (var item in items) {
            if (item[index] == ruleValue) {
                count++;
            }
        }
        
        return count;
    }
}
var countMatches = function(items, ruleKey, ruleValue) {
    const ruleMap = {"type": 0, "color": 1, "name": 2};
    const index = ruleMap[ruleKey];
    
    return items.reduce((count, item) => {
        return item[index]

复杂度分析

复杂度类型复杂度说明
时间复杂度O(n)需要遍历所有 n 个物品
空间复杂度O(1)只使用常数级别的额外空间