Ramda - 通过多个分组转换数组

Question

我正在尝试使用 ramda 完成以下操作：

这是 array 的示例：

[
  {
    id: 1,
    value: "ON",
    type: "TYPE_1"
  },
  {
    id: 1,
    value: "OFF",
    type: "TYPE_1"
  },
  {
    id: 2,
    value: "ON",
    type: "TYPE_1"
  }, {
    id: 3,
    value: "OFF",
    type: "TYPE_2"
  },
  {
    id: 3,
    value: "OFF",
    type: "TYPE_2"
  },
  {
    id: 3,
    value: "OFF",
    type: "TYPE_2"
  }
]

这是我想要的样子：

[
 {
  name: "TYPE_1"
  enabled: 2,
  disabled: 0,
 },
 {
  name: "TYPE_2",
  enabled: 0,
  disabled: 1
 }
]

基本上我需要按 type 和 id 分组，它们的组合可以重复但只占一个。

这是我已经尝试过的：

pipe(
  groupBy(prop('type')),
  map(applySpec({
    name: pipe(head, prop('type')),
    enabled: reduce((acc, item) => item.value === "ON" ? add(acc, 1) : acc, 0),
    disabled: reduce((acc, item) => item.value === "OFF" ? add(acc, 1) : acc, 0) 
  })),
  values,
)(list)

但它不起作用，因为 returns 以下内容：

[
 {
  name: "TYPE_1",
  enabled: 2,
  disabled: 1
 },
 {
  type: "TYPE_2",
  enabled: 0,
  disabled: 3
]

缺少的部分将仅占每个 type 中的每个 id。

Answer 1

试试这个：

const transform = applySpec({
  name: head,
  enabled: pipe(last, filter(propEq('value', 'ON')), length),
  disabled: pipe(last, filter(propEq('value', 'OFF')), length),
})
const fn = pipe(groupBy(prop('type')), toPairs, map(transform))

demo

Answer 2

您需要再次按 id 分组，从每个子组中取出头部，展平，然后应用规范：

const { pipe, groupBy, prop, values, map, applySpec, head, ifElse, any, always, filter, propEq, length } = R

const fn = pipe(
  groupBy(prop('type')),
  values,
  map(pipe(
    groupBy(prop('id')),
    values,
    map(applySpec({
      name: pipe(head, prop('type')),
      value: ifElse(any(propEq('value', 'ON')), always('ON'), always('OFF')),
    })),
    applySpec({
      name: pipe(head, prop('name')),
      enabled: pipe(filter(propEq('value', 'ON')), length),
      disabled: pipe(filter(propEq('value', 'OFF')), length),
    })
  )),
)

const arr = [{"id":1,"value":"ON","type":"TYPE_1"},{"id":1,"value":"OFF","type":"TYPE_1"},{"id":2,"value":"ON","type":"TYPE_1"},{"id":3,"value":"OFF","type":"TYPE_2"},{"id":3,"value":"OFF","type":"TYPE_2"},{"id":3,"value":"OFF","type":"TYPE_2"}]

const result = fn(arr)

console.log(result)

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.0/ramda.js"></script>

Answer 3

这是另一种方法，与 OriDrori 的方法略有不同。它符合给定的情况，但我仍然不确定一般规则，因此这可能实际上没有正确捕获要求。

const extract = pipe (
  groupBy (toString),              // {JSON_key1: [{id, value, type}, {id, value, type}, ...] JSON_key2: [{id, value, type}, ...], ...}
  map (head),                      // {JSON_key1: {id, value, type}, JSON_key2: {id, value, type}, ...}
  values,                          // [{id, value, type}, {id, value, type}, ...]
  groupBy (prop ('type')),         // {TYPE_1: [{id, value, type}, {id, value, type}, ...], "TYPE_2":[{id, value, type}]}
  map (countBy (prop ('value'))),  // {TYPE_1: {ON: 2, OFF: 1}, TYPE_2: {OFF: 1}}
  toPairs,                         // [[TYPE_1, {ON: 2, OFF: 1}], [TYPE_2, {OFF: 1}]]
  map (applySpec ({
    type: nth(0), 
    enabled: pathOr(0, [1, 'ON']), 
    disabled: pathOr(0, [1, 'OFF'])
  }))                              // [{type: "TYPE_1", enabled: 2, disabled: 1}, {type: "TYPE_2", enabled: 0, disabled: 1}]
) 

const data = [{id: 1, value: "ON", type: "TYPE_1"}, {id: 1, value: "OFF", type: "TYPE_1"}, {id: 2, value: "ON", type: "TYPE_1"}, {id: 3, value: "OFF", type: "TYPE_2"}, {id: 3, value: "OFF", type: "TYPE_2"}, {id: 3, value: "OFF", type: "TYPE_2"}];

console .log (extract (data))

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.0/ramda.js"></script>
<script> const {pipe, groupBy, toString, map, head, values, prop, countBy, 
                toPairs, applySpec, nth, pathOr} = R </script>

Ramda 的toString 不是特别快。如果您愿意，可以将管道的第一行替换为如下内容：

  groupBy (({id, value, type}) => `${id}|${value}|${type}`),

此外，map(applySpec) 行感觉有点复杂。我们可以用这样的东西替换它们：

  map (([type, {OFF: disabled = 0, ON: enabled = 0}]) => ({type, enabled, disabled}))

请注意小型、相对简单的单个转换管道的样式。这对我来说是 Ramda 的甜蜜点。 Ramda 旨在支持许多不同风格的函数式编程，但这种风格是最核心的。

Ramda - 通过多个分组转换数组

Ramda - Transform array by multiple groupings

javascript

ecmascript-6

ramda.js