[英]flattening nested arrays/objects in underscore.js
我有一個對象數組,如下所示(雖然下面的例子只有一個元素在數組中)
[
{
"uptime":0,
"load":{"x":0.11,"y":0.22,"z":0.33},
"cpu":[
{"u":111,"n":112,"s":113,"i":114,"q":115},
{"u":211,"n":212,"s":213,"i":214,"q":215}
]
}
]
我試圖使用underscore.js來展平每個元素,所以整個數組看起來像這樣:
[
{
"uptime":0,
"load_x": 0.11
"load_y": 0.03
"load_z": 0.01,
"cpu1_u": 111,
"cpu1_n": 112,
"cpu1_s": 113,
"cpu1_i": 114,
"cpu1_q": 115,
"cpu2_u": 211,
"cpu2_n": 212,
"cpu2_s": 213,
"cpu2_i": 214,
"cpu2_q": 215,
}
]
我已經對'load'元素進行了排序(雖然不是一般),因為那只是一個已知的3字段對象。
盡管如此,扁平化cpu陣列也使我望而卻步。 我的代碼如下,以及我的代碼生成的輸出
我知道我可以寫一個js循環並完成它,但我已經看到了一些非常優雅的下划線解決方案,我確信它可能。 有什么建議嗎?
我的守則
var profiles = [
{
"uptime":0,
"load":{"x":0.11,"y":0.22,"z":0.33},
"cpu":[
{"u":111,"n":112,"s":113,"i":114,"q":115},
{"u":211,"n":212,"s":213,"i":214,"q":215}
]
}
];
var flat = _.map(profiles, function(profile) {
var p = _.extend(_.omit(profile, 'load'), {
load_1: Math.round(100*profile.load.x)/100,
load_5: Math.round(100*profile.load.y)/100,
load_15: Math.round(100*profile.load.z)/100
});
var cpuid = 0;
var cpuobject =
_.map(p.cpu, function(cpu) {
cpuid++;
return _.object(
_.map(cpu, function(val, key) {
var arr = ['cpu'+cpuid+'_'+key, val];
return arr;
})
);
});
return _.extend(_.omit(p, 'cpu'), cpuobject);
});
console.log(JSON.stringify(flat));
我(錯)輸出
[
{
0: {
cpu1_u: 233264700,
cpu1_n: 0,
cpu1_s: 64485200,
cpu1_i: 1228073616,
cpu1_q: 86100
},
1: {
cpu2_u: 233264700,
cpu2_n: 0,
cpu2_s: 64485200,
cpu2_i: 1228073616,
cpu2_q: 86100
},
uptime: 0,
load_1: 0.11,
load_5: 0.03,
load_15: 0.01
}
]
例如:
flatten = function(x, result, prefix) {
if(_.isObject(x)) {
_.each(x, function(v, k) {
flatten(v, result, prefix ? prefix + '_' + k : k)
})
} else {
result[prefix] = x
}
return result
}
a =
{
"uptime":0,
"load":{"x":0.11,"y":0.22,"z":0.33},
"cpu":[
{"u":111,"n":112,"s":113,"i":114,"q":115},
{"u":211,"n":212,"s":213,"i":214,"q":215}
]
}
result = flatten(a, {})
{
"uptime": 0,
"load_x": 0.11,
"load_y": 0.22,
"load_z": 0.33,
"cpu_0_u": 111,
"cpu_0_n": 112,
"cpu_0_s": 113,
"cpu_0_i": 114,
"cpu_0_q": 115,
"cpu_1_u": 211,
"cpu_1_n": 212,
"cpu_1_s": 213,
"cpu_1_i": 214,
"cpu_1_q": 215
}
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.