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@@ -47,6 +47,7 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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resultMap.put("date", todayDate);
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//时间占比 预先定义好长度为9的数组再向里面添加
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Integer[] timeArray = {0, 0, 0, 0, 0, 0, 0, 0, 0};
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+ //把当天所有行为分别加在一起装进数组
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for (TimeCalculation timeCalculation : timeCalculationMapper.selectList(new QueryWrapper<TimeCalculation>()
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.eq("user_id", userId)
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.eq("date", todayDate))) {
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@@ -85,7 +86,7 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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try {
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List<Map<String, Object>> resultList = new ArrayList<>();
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Integer companyId = userMapper.selectById(request.getHeader("Token")).getCompanyId();
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- //首先获取某日期有截图的人
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+ //首先获取某日期同一个公司下全部有记录的人
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for (Map<String, Object> userMap : timeCalculationMapper.getTodayStatisticsUser(date, companyId)) {
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//对于每一个人 首先记录下姓名和电话号码
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Map<String, Object> map = new HashMap<>();
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@@ -105,6 +106,7 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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resultArray[2] = timeArray[3] + timeArray[4];
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resultArray[3] = timeArray[5];
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resultArray[4] = timeArray[6] + timeArray[7] + timeArray[8];
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+ //将后端的9中行为类型分门别类转换为前端的5种并转换为字符串格式
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String[] stringArray = new String[5];
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for (int i = 0; i < 5; i++) {
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stringArray[i] = convertSecond(resultArray[i]);
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@@ -133,27 +135,35 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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try {
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LocalDate start = LocalDate.parse(startDate, DateTimeFormatter.ofPattern("yyyy-MM-dd"));
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LocalDate end = LocalDate.parse(endDate, DateTimeFormatter.ofPattern("yyyy-MM-dd"));
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- //首先获取数据
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+ //获取时间段内本人全部的工作记录 娱乐6 7 8不计入
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+ Integer[] workType = {-1, 0, 1, 2, 3, 4, 5};
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List<TimeCalculation> dataList = timeCalculationMapper.selectList(new QueryWrapper<TimeCalculation>()
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.eq("user_id", request.getHeader("Token"))
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- .eq("action_type", 0)
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+ .in("action_type", workType)
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.between("date", start, end)
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.orderByAsc("start_time"));
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//先把所有的日期搞到一个list里面
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ArrayList<String> dateList = new ArrayList<>();
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LocalDate currentDate = start;
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+ //从开始日期一直到结束日期的每一天 为了防止死循环最多100天 当然说不定可以再多一点
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for (int i = 0; !currentDate.equals(end.plusDays(1)) || ++i >= 100; currentDate = currentDate.plusDays(1)) {
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+ //把这一天以字符串形式保存到list中
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dateList.add(currentDate.format(DateTimeFormatter.ofPattern("yyyy-MM-dd")));
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}
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List<Map<String, Object>> resultList = new ArrayList<>();
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+ //对于需要的每一天
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for (String date : dateList) {
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Integer total = 0;
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Map<String, Object> dataMap = new HashMap<>();
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+ //返回这一天的日期
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dataMap.put("date", date);
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List<Map<String, Object>> list = new ArrayList<>();
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+ //遍历所有时间记录
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for (TimeCalculation timeCalculation : dataList) {
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+ //如果这一天就是我们需要的那天的话
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if (timeCalculation.getDate().toString().equals(date)) {
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Map<String, Object> map = new HashMap<>();
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+ //把这一天的开始时间和结束时间以小时:分钟的字符串形式以及段时间的长度返回
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map.put("startTime", timeCalculation.getStartTime().format(DateTimeFormatter.ofPattern("HH:mm")));
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map.put("endTime", timeCalculation.getEndTime().format(DateTimeFormatter.ofPattern("HH:mm")));
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Integer todayTime = timeCalculation.getDuration();
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@@ -161,9 +171,10 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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total += todayTime;
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list.add(map);
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}
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+ /*这个时间复杂度巨几把高的for循环可以用某种算法优化 至少计算过的应该排除才对*/
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}
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dataMap.put("time", list);
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- //这里检查如果只有一天记录的话那就再多计算一个当天总工作时间
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+ //这里检查如果只需要一天记录的话 说明是pc端界面那个地方 那就再多计算一个当天总工作时间
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if (dateList.size() == 1) {
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dataMap.put("total", total);
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}
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@@ -190,6 +201,7 @@ public class TimeCalculationServiceImpl extends ServiceImpl<TimeCalculationMappe
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return hour + "小时" + minute + "分" + second + "秒";
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}
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+ //秒数转化为时间字符串 Long参数豪华限定版
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private static String convertSecond(Long time) {
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Long hour = 0L, minute = 0L, second = 0L;
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hour = time / 3600;
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wutt