在underscore.js中展开嵌套的数组/对象
我有一个如下所示的对象数组（虽然下面的例子只有一个元素在数组中）
[ { "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} ] } ] 我试图平铺每个元素使用underscore.js，所以整体数组看起来像这样：
[ { "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, } ]
我有'load'元素sorting（虽然不是一般），因为那只是一个已知的3字段对象。
扁平CPU数组暗示我。 我的代码如下，以及我的代码生成的输出
我知道我可以写一个js循环，并做到这一点，但我看到了这样的一些非常优雅的下划线解决scheme，我相信它是可能的。 有什么build议吗？
我的代码
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));
我的（错误）输出
[ { 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 }