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396 lines
17 KiB
JavaScript
396 lines
17 KiB
JavaScript
import { flush, groupBy, isEmpty, isNotEmpty, pick, unique, uniqWith } from '@/utils/commons';
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import dayjs from 'dayjs';
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import { formatGroupSize } from './useProductsSets';
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// Shoulder Season 平季; peak season 旺季
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export const isFullYearOrLonger = (year, startDate, endDate) => {
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// Parse the dates
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const start = dayjs(startDate, 'YYYY-MM-DD');
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const end = dayjs(endDate, 'YYYY-MM-DD');
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// Create the start and end dates for the year
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const yearStart = dayjs(`${year}-01-01`, 'YYYY-MM-DD');
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const yearEnd = dayjs(`${year}-12-31`, 'YYYY-MM-DD');
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// Check if start is '01-01' and end is '12-31' and the year matches
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const isFullYear = start.isSame(yearStart, 'day') && end.isSame(yearEnd, 'day');
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// Check if the range is longer than a year
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const isLongerThanYear = end.diff(startDate, 'year') >= 1;
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const isLongerThan12M = end.diff(startDate, 'month') >= 11;
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return isFullYear || isLongerThanYear || isLongerThan12M;
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};
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const uniqueBySub = (arr) => {
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const sortedArr = arr.sort((a, b) => b.length - a.length);
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const uniqueArr = [];
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sortedArr.forEach((currentSubArr) => {
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const isSubsetOfUnique = uniqueArr.some((uniqueSubArr) => {
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return currentSubArr.every((item) => uniqueSubArr.includes(item));
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});
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if (!isSubsetOfUnique) {
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uniqueArr.push(currentSubArr);
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}
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});
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return uniqueArr;
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}
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export const chunkBy = (use_year, dataList = [], by = []) => {
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const dataRollSS = dataList.map((rowp, ii) => {
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const quotation = rowp.quotation.map((quoteItem) => {
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return {
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...quoteItem,
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quote_season: isFullYearOrLonger(use_year, quoteItem.use_dates_start, quoteItem.use_dates_end) ? 'SS' : 'PS',
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};
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});
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return { ...rowp, quotation };
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});
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// 人等分组只取平季, 因为产品只一行
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const allQuotesSS = dataRollSS.reduce((acc, rowp) => acc.concat(rowp.quotation.filter((q) => q.quote_season === 'SS')), []);
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const allQuotesPS = dataRollSS.reduce((acc, rowp) => acc.concat(rowp.quotation.filter((q) => q.quote_season === 'PS')), []);
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const allQuotesSSS = isEmpty(allQuotesSS) ? allQuotesPS : allQuotesSS;
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const allQuotesSSS2 = [].concat(allQuotesSS, allQuotesPS);
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const PGroupSizeSS = allQuotesSSS.reduce((aq, cq) => {
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aq[cq.WPI_SN] = aq[cq.WPI_SN] || [];
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aq[cq.WPI_SN].push(`${cq.group_size_min}-${cq.group_size_max}`);
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// aq[cq.WPI_SN].push([cq.group_size_min, cq.group_size_max]);
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// aq[cq.WPI_SN].push(cq.group_size_min);
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aq[cq.WPI_SN] = unique(aq[cq.WPI_SN]);
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aq[cq.WPI_SN] = aq[cq.WPI_SN].slice().sort((a, b) => a.split('-')[0] - b.split('-')[0]);
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return aq;
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}, {});
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// debug:
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// PGroupSizeSS['5098'] = ['1-1000'];
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// PGroupSizeSS['5099'] = ['1-2', '3-4'];
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const PGroupSizePS = allQuotesPS.reduce((aq, cq) => {
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aq[cq.WPI_SN] = aq[cq.WPI_SN] || [];
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aq[cq.WPI_SN].push(`${cq.group_size_min}-${cq.group_size_max}`);
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// aq[cq.WPI_SN].push([cq.group_size_min, cq.group_size_max]);
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// aq[cq.WPI_SN].push(cq.group_size_min);
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aq[cq.WPI_SN] = unique(aq[cq.WPI_SN]);
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aq[cq.WPI_SN] = aq[cq.WPI_SN].slice().sort((a, b) => a.split('-')[0] - b.split('-')[0]);
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return aq;
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}, {});
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// 补全产品旺季的人等分组 (当旺季和平季的人等不完全一致时)
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const allWPI = unique(allQuotesSSS2.map((ele) => ele.WPI_SN));
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for (const WPI of allWPI) {
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// for (const WPI in PGroupSizeSS) {
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// if (Object.prototype.hasOwnProperty.call(PGroupSizeSS, WPI)) {
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const element = PGroupSizeSS[WPI] || [];
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const elementP = PGroupSizePS[WPI] || [];
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const diff = (elementP || []).filter((ele, index) => !element.includes(ele));
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PGroupSizeSS[WPI] = element.concat(diff);
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// }
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}
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// console.log('PGroupSizeSS', PGroupSizeSS, '\nPGroupSizePS', PGroupSizePS, '\nallQuotesSSS', allQuotesSSS2)
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// const maxGroupSize = Math.max(...allQuotesSSS.map((q) => q.group_size_max));
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// const maxSet = maxGroupSize === 1000 ? Infinity : maxGroupSize;
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const _SSMinSet = uniqWith(Object.values(PGroupSizeSS), (a, b) => a.join(',') === b.join(','));
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// const uSSsizeSetArr = (_SSMinSet)
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const uSSsizeSetArr = uniqueBySub(_SSMinSet);
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// console.log('_SSMinSet', _SSMinSet, '\n uSSsizeSetArr', uSSsizeSetArr)
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// * 若不重叠分组, 则上面不要 uniqueBySub
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for (const key in PGroupSizeSS) {
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if (Object.prototype.hasOwnProperty.call(PGroupSizeSS, key)) {
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const element = PGroupSizeSS[key];
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const findSet = uSSsizeSetArr.find((minCut) => element.every((v) => minCut.includes(v)));
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PGroupSizeSS[key] = findSet;
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}
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}
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// console.log('PGroupSizeSS -- ', PGroupSizeSS)
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const [SSsizeSets, PSsizeSets] = [uSSsizeSetArr, []].map((arr) => {
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const _arr = structuredClone(arr);
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const arrSets = _arr.map((keyMinMaxStrs) =>
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keyMinMaxStrs.reduce((acc, curr, idx, minMaxArr) => {
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const curArr = curr.split('-').map(val => parseInt(val, 10));
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acc.push(curArr);
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// const _max = idx === minsArr.length - 1 ? maxSet : Number(minsArr[idx + 1]) - 1;
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// acc.push([Number(curr), _max]);
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return acc;
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}, [])
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);
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return arrSets;
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});
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// console.log('uSSsizeSetArr', uSSsizeSetArr);
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const [SSsizeSetsMap, PSsizeSetsMap] = [uSSsizeSetArr, []].map((arr) => {
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const _arr = structuredClone(arr);
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const SetsMap = _arr.reduce((acc, keyMinMaxStrs, ii, strArr) => {
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const _key = keyMinMaxStrs.join(',');
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// console.log(_key);
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const _value = keyMinMaxStrs.reduce((acc, curr, idx, minMaxArr) => {
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const curArr = curr.split('-').map((val) => parseInt(val, 10));
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acc.push(curArr);
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return acc;
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}, []);
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return { ...acc, [_key]: _value };
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}, {});
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return SetsMap;
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});
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// console.log('SSsizeSetsMap', SSsizeSetsMap);
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const compactSizeSets = {
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SSsizeSetKey: uSSsizeSetArr.map((s) => s.join(',')).filter(isNotEmpty),
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sizeSets: SSsizeSets,
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SSsizeSetsMap,
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};
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// console.log('sizeSets -- ', SSsizeSets, '\nSSsizeSetKey', compactSizeSets.SSsizeSetKey, '\nSSsizeSetsMap', SSsizeSetsMap)
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const chunkSS = structuredClone(dataRollSS).map((rowp) => {
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const pkey = (PGroupSizeSS[rowp.info.id] || []).join(',') || compactSizeSets.SSsizeSetKey[0]; // todo:
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let unitCnt = { '0': 0, '1': 0 }; // ? todo: 以平季的为准
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const _quotation = rowp.quotation.map((quoteItem) => {
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unitCnt[quoteItem.unit_id]++;
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quoteItem.quote_size = pkey;
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quoteItem.quote_col_key = formatGroupSize(quoteItem.group_size_min, quoteItem.group_size_max);
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quoteItem.use_dates_start = quoteItem.use_dates_start.replace(/-/g, '.');
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quoteItem.use_dates_end = quoteItem.use_dates_end.replace(/-/g, '.');
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return quoteItem;
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});
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const quote_chunk_flat = groupBy(_quotation, (quoteItem2) => by.map((key) => quoteItem2[key]).join('@') || '#');
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const quote_chunk = Object.keys(quote_chunk_flat).reduce((qc, ckey) => {
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const ckeyArr = ckey.split('@');
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if (isEmpty(qc[ckeyArr[0]])) {
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qc[ckeyArr[0]] = ckeyArr[1] ? { [ckeyArr[1]]: quote_chunk_flat[ckey] } : quote_chunk_flat[ckey];
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} else {
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qc[ckeyArr[0]][ckeyArr[1]] = (qc[ckeyArr[0]][ckeyArr[1]] || []).concat(quote_chunk_flat[ckey]);
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}
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return qc;
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}, {});
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const _quotationTransposeBySize = Object.keys(quote_chunk).reduce((accBy, byKey) => {
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const byValues = quote_chunk[byKey];
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const groupTablesBySize = groupBy(byValues, 'quote_size');
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const transposeTables = Object.keys(groupTablesBySize).reduce((accBy, sizeKeys) => {
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const _sizeRows = groupTablesBySize[sizeKeys];
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const rowsByDate = groupBy(_sizeRows, qi => `${qi.use_dates_start}~${qi.use_dates_end}`);
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const _rowsFromDate = Object.keys(rowsByDate).reduce((accDate, dateKeys) => {
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const _dateRows = rowsByDate[dateKeys];
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const rowKey = _dateRows.map(e => e.id).join(',');
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const keepCol = pick(_dateRows[0], ['WPI_SN', 'WPP_VEI_SN', 'currency', 'unit_id', 'unit_name', 'use_dates_start', 'use_dates_end', 'weekdays', 'quote_season']);
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const _colFromDateRow = _dateRows.reduce((accCols, rowp) => {
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// const _colRow = pick(rowp, ['currency', 'unit_id', 'unit_name', 'use_dates_start', 'use_dates_end', 'weekdays', 'child_cost', 'adult_cost']);
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return { ...accCols, [rowp.quote_col_key]: rowp };
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}, {...keepCol, originRows: _dateRows, rowKey });
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accDate.push(_colFromDateRow);
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return accDate;
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}, []);
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return { ...accBy, [sizeKeys]: _rowsFromDate };
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}, {});
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return { ...accBy, [byKey]: transposeTables };
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}, {});
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// console.log(_quotationTransposeBySize);
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return {
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...rowp,
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unitCnt,
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unitSet: Object.keys(unitCnt).reduce((a, b) => unitCnt[a] > unitCnt[b] ? a : b),
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sizeSetsSS: pkey,
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_quotationTransposeBySize,
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quotation: _quotation,
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quote_chunk,
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};
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});
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const allquotation = chunkSS.reduce((a, c) => a.concat(c.quotation), []);
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// 取出两季相应的时效区间
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const SSRange = unique((allquotation || []).filter((q) => q.quote_season === 'SS').map((qr) => `${qr.use_dates_start}~${qr.use_dates_end}`));
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const PSRange = unique((allquotation || []).filter((q) => q.quote_season === 'PS').map((qr) => `${qr.use_dates_start}~${qr.use_dates_end}`));
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// const transposeDataSS = chunkSS
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return {
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chunk: chunkSS,
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// dataSource: chunkSS,
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SSRange,
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PSRange,
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...compactSizeSets, // { SSsizeSetKey, sizeSets }
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};
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};
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/**
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* 按[单位, 人等]拆分表格
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* @use D J B R 8
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*/
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export const splitTable_SizeSets = (chunkData) => {
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const { SSRange, PSRange, SSsizeSetKey, SSsizeSetsMap, chunk } = chunkData;
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// console.log('---- chunk', chunk);
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const bySizeUnitSetKey = groupBy(chunk, pitem => ['unitSet', 'sizeSetsSS', ].map((key) => pitem[key]).join('@'));
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// agencyProducts.J.
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// console.log('bySizeSetKey', bySizeUnitSetKey);
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const tables = Object.keys(bySizeUnitSetKey).map((sizeSetsUnitStr) => {
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const [unitSet, sizeSetsStr] = sizeSetsUnitStr.split('@');
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const _thisSSsetProducts = bySizeUnitSetKey[sizeSetsUnitStr];
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const _subTable = _thisSSsetProducts.map(({ info, sizeSetsSS, _quotationTransposeBySize, unitSet, ...pitem }) => {
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const transpose = _quotationTransposeBySize['#'][sizeSetsSS];
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const _pRow = transpose.map((quote, qi) => ({ ...quote, rowSpan: qi === 0 ? transpose.length : 0 }));
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return { info, sizeSetsSS, unitSet, rows: _pRow, transpose };
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});
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return { cols: SSsizeSetsMap[sizeSetsStr], colsKey: sizeSetsStr, unitSet, sizeSetsUnitStr, data: _subTable };
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});
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// console.log('---- tables', tables);
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const tablesQuote = tables.map(({ cols, colsKey, unitSet, sizeSetsUnitStr, data }, ti) => {
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const _table = data.reduce((acc, prow) => {
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const prows = prow.rows.map((_q) => ({ ..._q, info: prow.info, dateText: `${_q.use_dates_start}~${_q.use_dates_end}` }));
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return acc.concat(prows);
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}, []);
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return { cols, colsKey: sizeSetsUnitStr, data: _table }; // `${unitSet}@${colsKey}`
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});
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// console.log('---- tablesQuote', tablesQuote);
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return tablesQuote;
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};
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/**
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* 按季度分列 [平季, 旺季]
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* @use Q 7 6
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*/
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export const splitTable_Season = (chunkData) => {
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const { SSRange, PSRange, SSsizeSetKey, SSsizeSetsMap, chunk } = chunkData;
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// console.log(chunkData);
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const tablesQuote = chunk.map((pitem) => {
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const { quote_chunk } = pitem;
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// const bySeason = groupBy(pitem.quotation, (ele) => ele.quote_season);
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const rowSeason = Object.keys(quote_chunk).reduce((accp, _s) => {
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const bySeasonValue = groupBy(quote_chunk[_s], (ele) => ['adult_cost', 'child_cost', 'group_size_min', 'group_size_max', 'unit_id'].map((k) => ele[k]).join('@'));
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// console.log('---- bySeasonValue', _s, bySeasonValue);
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const byDate = groupBy(quote_chunk[_s], (ele) => `${ele.use_dates_start}~${ele.use_dates_end}`);
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// console.log('---- byDate', _s, byDate);
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const subHeader = Object.keys(bySeasonValue).length >= Object.keys(byDate).length ? 'dates' : 'priceValues';
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// console.log('---- subHeader', _s, subHeader);
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let valuesArr = [];
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switch (subHeader) {
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case 'priceValues':
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valuesArr = Object.keys(bySeasonValue).reduce((accv, valKey) => {
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const valRows = bySeasonValue[valKey];
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const valRow = pick(valRows[0], ['adult_cost', 'child_cost', 'currency', 'unit_id', 'unit_name', 'group_size_min', 'group_size_max']);
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// valRow.dates = valRows.map((v) => pick(v, ['id', 'use_dates_end', 'use_dates_start']));
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valRow.rows = [valRows[0]];
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valRow.originRows = valRows;
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valRow.rowKey = valRows.map((v) => v.id).join(',');
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valRow.headerDates = valRows.map((v) => pick(v, ['use_dates_end', 'use_dates_start']));
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accv.push(valRow);
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return accv;
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}, []);
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break;
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case 'dates':
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valuesArr = Object.keys(byDate).reduce((accv, dateKey) => {
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const valRows = byDate[dateKey];
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const valRow = pick(valRows[0], ['use_dates_end', 'use_dates_start']);
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valRow.rows = valRows;
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valRow.originRows = valRows;
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valRow.rowKey = valRows.map((v) => v.id).join(',');
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valRow.headerDates = [pick(valRows[0], ['use_dates_end', 'use_dates_start'])];
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accv.push(valRow);
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return accv;
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}, []);
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break;
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default:
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break;
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}
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const valUnderSeason = Object.keys(bySeasonValue).reduce((accv, valKey) => {
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const valRows = bySeasonValue[valKey];
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const valRow = pick(valRows[0], ['adult_cost', 'child_cost', 'currency', 'unit_id', 'unit_name', 'group_size_min', 'group_size_max']);
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// valRow.dates = valRows.map((v) => pick(v, ['id', 'use_dates_end', 'use_dates_start']));
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valRow.rows = valRows;
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valRow.rowKey = valRows.map(v => v.id).join(',');
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accv.push(valRow);
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return accv;
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}, []);
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return { ...accp, [_s]: valUnderSeason, [_s + 'Data']: valuesArr };
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}, {});
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return { info: pitem.info, ...rowSeason, rowKey: pitem.info.id };
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});
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// console.log('---- tablesQuote', tablesQuote);
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return tablesQuote;
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};
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export const splitTable_D = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource);
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// console.log(chunked);
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const tables = addCityRow4Split(splitTable_SizeSets(chunked));
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const splitTable_J = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource);
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// console.log(chunked);
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const tables = addCityRow4Split(splitTable_SizeSets(chunked));
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const splitTable_Q = (use_year, dataSource) => {
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const chunked = chunkBy(use_year, dataSource, ['quote_season']);
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return addCityRow4Season(splitTable_Season(chunked));
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};
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export const splitTable_7 = (use_year, dataSource) => {
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const chunked = chunkBy(use_year, dataSource, ['quote_season']);
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return addCityRow4Season(splitTable_Season(chunked));
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};
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export const splitTable_R = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource);
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// console.log(chunked);
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const tables = addCityRow4Split(splitTable_SizeSets(chunked));
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const splitTable_8 = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource);
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// console.log(chunked);
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const tables = addCityRow4Split(splitTable_SizeSets(chunked));
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const splitTable_6 = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource, ['quote_season']);
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const tables = splitTable_Season(chunked);
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const splitTable_B = (use_year, dataSource, retTableOnly = true) => {
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const chunked = chunkBy(use_year, dataSource);
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// console.log(chunked);
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const tables = addCityRow4Split(splitTable_SizeSets(chunked));
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return retTableOnly ? tables : { ...chunked, tables };
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};
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export const addCityRow4Season = (table) => {
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const byCity = groupBy(table, (ele) => `${ele.info.city_id}@${ele.info.city_name}`);
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const withCityRow = Object.keys(byCity).reduce((acc, cityIdName) => {
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const [cityId, cityName] = cityIdName.split('@');
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acc.push({ info: { product_title: cityName, isCityRow: true,}, use_dates_end: '', use_dates_start: '', quote_season: 'SS', rowSpan: 1, rowKey: `c_${cityId}` });
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return acc.concat(byCity[cityIdName]);
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}, []);
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return withCityRow;
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};
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export const addCityRow4Split = (splitTables) => {
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const tables = splitTables.map(table => {
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return { ...table, data: addCityRow4Season(table.data)}
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});
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return tables;
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};
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