我有一个嵌套的对象数组,如下所示:
var matchs = [
{
id: 10689,
sport: 'Tennis',
players: [
{
id: 22,
name:'Rafa Nadal',
country: 'Spain',
odds: [
{id: 1, bookie_1: 1.60},
{id: 2, bookie_2: 1.61},
{id: 3, bookie_3: 1.62},
]
},
{
id: 23,
name:'Roger Federer',
country: 'Spain',
odds: [
{id: 4, bookie_1: 2.60},
{id: 5, bookie_2: 2.61},
{id: 6, bookie_3: 2.62},
]
}
]
},
{
id: 12389,
sport: 'Tennis',
players: [
{
id: 45,
name:'Fernando Verdasco',
country: 'Spain',
odds: [
{id: 7, bookie_1: 2.60},
{id: 8, bookie_2: 2.61},
{id: 9, bookie_3: 2.62},
]
},
{
id: 65,
name:'Andy Murray',
country: 'Spain',
odds: [
{id: 10, bookie_1: 1.60},
{id: 11, bookie_2: 1.61},
{id: 12, bookie_3: 1.62},
]
}
]
}
];
我想使用normalizr来简化数组并与redux一起使用。我已经阅读了Normalizr文档,但它有一些例子,我不知道我做错了什么。
我尝试了以下代码但没有成功。我得到的结果是一个未定义的数组。
import { normalize, schema } from 'normalizr';
const match = new schema.Entity('matchs');
const player = new schema.Entity('players');
const odd = new schema.Entity('odds');
match.define({
player: [player],
odd: [odd]
});
console.log(normalize(matchs, [match]));
我需要这样的东西:
{
result: "123",
entities: {
"matchs": {
"123": {
id: "123",
players: [ "1","2" ],
odds: [ "1", "2" ]
}
},
"players": {
"1": { "id": "1", "name": "Rafa Nadal" },
"2": { "id": "2", "name": "Andy Murray" }
},
"odds": {
"1": { id: "1", "bookie_1": "1.20" }
"2": { id: "2", "bookie_2": "1.21" }
"3": { id: "3", "bookie_3": "1.22" }
}
}
}
答案 0 :(得分:0)
我认为这就是你需要的
const odd = new schema.Entity('odds');
const player = new schema.Entity('players' , { odds: [ odd]});
const match = new schema.Entity('matchs', {players: [player]});
但结果会有所不同,因为你的json的结构是这样的,我的意思是,赔率键是玩家的孩子,而不是匹配,因此结果就是这样。
只需看一下控制台
答案 1 :(得分:0)
我无法仅使用normalizr找到直接的解决方案,所以我唯一的选择是在传递给规范器之前对数据进行预格式化。
const preformattedData = data.map(sport => {
const oddArrays = sport.players.map(player => player.odds || []);
return {
...sport,
odds: [].concat.apply([], oddArrays)
}
})
const odd = new schema.Entity('odds')
const player = new schema.Entity('players',
{
odds: [ odd ]
}
)
const sport = new schema.Entity('sports',
{
players: [ player ],
odds: [odd]
}
)
const normalizedData = normalize(preformattedData, [ sport ]);
答案 2 :(得分:-1)
您可以通过调整流程和合并策略来获得所需的结果。我没有时间为您做腿部工作,但是我在这里详细解释了这种方法: