product-inventory-management-after.git

			@@ -4,29 +4,42 @@
			import com.baomidou.mybatisplus.core.metadata.IPage;
			import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
			import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
			import com.ruoyi.common.utils.DateUtils;
			import com.ruoyi.common.utils.SecurityUtils;
			import com.ruoyi.common.utils.poi.ExcelUtil;
			import com.ruoyi.procurementrecord.dto.ProcurementRecordOutPageDto;
			import com.ruoyi.framework.security.LoginUser;
			import com.ruoyi.production.dto.*;
			import com.ruoyi.production.mapper.SalesLedgerSchedulingMapper;
			import com.ruoyi.production.mapper.SalesLedgerWorkMapper;
			import com.ruoyi.production.mapper.SpeculativeTradingInfoMapper;
			import com.ruoyi.production.pojo.SalesLedgerScheduling;
			import com.ruoyi.production.pojo.SalesLedgerWork;
			import com.ruoyi.production.pojo.SpeculativeTradingInfo;
			import com.ruoyi.production.service.SalesLedgerSchedulingService;
			import com.ruoyi.project.system.domain.SysUser;
			import com.ruoyi.project.system.mapper.SysUserMapper;
			import com.ruoyi.sales.mapper.LossMapper;
			import com.ruoyi.sales.mapper.SalesLedgerProductMapper;
			import com.ruoyi.sales.pojo.Loss;
			import com.ruoyi.sales.pojo.SalesLedgerProduct;
			import lombok.RequiredArgsConstructor;
			import lombok.extern.slf4j.Slf4j;
			import org.springframework.beans.BeanUtils;
			import org.springframework.beans.factory.annotation.Autowired;
			import org.springframework.stereotype.Service;
			import org.springframework.util.CollectionUtils;

			import javax.servlet.http.HttpServletResponse;
			import java.math.BigDecimal;
			import java.math.RoundingMode;
			import java.time.LocalDate;
			import java.time.format.DateTimeFormatter;
			import java.util.ArrayList;
			import java.util.Arrays;
			import java.util.List;
			import java.util.Set;
			import java.util.concurrent.atomic.AtomicInteger;
			import java.util.concurrent.atomic.AtomicReference;
			import java.util.stream.Collectors;

			/**
			@@ -61,13 +74,37 @@
			.map(SalesLedgerWork::getFinishedNum)
			.reduce(BigDecimal.ZERO, BigDecimal::add));
			// 状态 = 数量和完工数量比较
			if(i.getSchedulingNum().compareTo(i.getSuccessNum()) == 0){
			if(i.getSchedulingNum().compareTo(new BigDecimal(0)) == 0){
			i.setStatus("未完成");
			} else if(i.getSchedulingNum().compareTo(i.getSuccessNum()) == 0){
			i.setStatus("已完成");
			}else{
			i.setStatus("未完成");
			i.setStatus("生产中");
			}
			// 计算生产总量 = 规格 * 数量 / 1000
			String[] split = i.getSpecificationModel().split("\\*");
			if(split.length == 2 && isNumeric(split[0]) && isNumeric(split[1])){
			BigDecimal multiply = new BigDecimal(split[0])
			.multiply(new BigDecimal(split[1])
			.multiply(i.getQuantity()).divide(new BigDecimal(1000),2, RoundingMode.CEILING));
			i.setTotalProduction(multiply);
			}

			});
			return list;
			}

			public static boolean isNumeric(String str) {
			if (str == null \|\| str.isEmpty()) {
			return false;
			}
			// 遍历字符串的每个字符，检查是否为数字
			for (int i = 0; i < str.length(); i++) {
			if (!Character.isDigit(str.charAt(i))) {
			return false;
			}
			}
			return true;
			}

			@Override
			@@ -95,20 +132,151 @@

			private final SysUserMapper sysUserMapper;

			private final SpeculativeTradingInfoMapper speculativeTradingInfoMapper;

			@Override
			public int productionDispatch(ProductionDispatchAddDto productionDispatchAddDto) {
			SysUser sysUser = sysUserMapper.selectUserById(productionDispatchAddDto.getSchedulingUserId());
			if(sysUser == null) throw new RuntimeException("排产人不存在");
			SalesLedgerScheduling salesLedgerScheduling = SalesLedgerScheduling.builder()
			.salesLedgerId(productionDispatchAddDto.getSalesLedgerId())
			.salesLedgerProductId(productionDispatchAddDto.getSalesLedgerProductId())
			.schedulingUserId(productionDispatchAddDto.getSchedulingUserId())
			.schedulingUserName(sysUser.getNickName())
			.schedulingNum(productionDispatchAddDto.getSchedulingNum())
			.schedulingDate(LocalDate.parse(productionDispatchAddDto.getSchedulingDate(), DateTimeFormatter.ISO_LOCAL_DATE))
			.status(1)
			.build();
			return salesLedgerSchedulingMapper.insert(salesLedgerScheduling);
			public String productionDispatch(List<ProductionDispatchAddDto> productionDispatchAddDtoList) {
			int i = 0;
			int successNum = 0;
			LoginUser loginUser = SecurityUtils.getLoginUser();
			for (ProductionDispatchAddDto productionDispatchAddDto : productionDispatchAddDtoList) {
			SysUser sysUser = sysUserMapper.selectUserById(productionDispatchAddDto.getSchedulingUserId() == null ? loginUser.getUser().getUserId() : productionDispatchAddDto.getSchedulingUserId());
			if(sysUser == null){
			i++;
			continue;
			}
			// 获取空余炒机
			String[] split = productionDispatchAddDto.getSpeculativeTradingName().split(",");
			if(split != null && split.length == 0){
			i++;
			continue;
			}
			List<SpeculativeTradingInfo> speculativeTradingInfos = speculativeTradingInfoMapper.selectList(new LambdaQueryWrapper<SpeculativeTradingInfo>()
			.in(SpeculativeTradingInfo::getName, Arrays.asList(split))
			.orderByAsc(SpeculativeTradingInfo::getSort));
			if(CollectionUtils.isEmpty(speculativeTradingInfos)){
			i++;
			continue;
			}
			AtomicReference<String> name = new AtomicReference<>(""); //需要绑定的炒机
			//通过规格型号和排产数量计算本次生产产量
			String[] split1 = productionDispatchAddDto.getSpecificationModel().split("\\*");
			if(split1.length != 2){
			i++;
			continue;
			}
			// 本次生产产量
			BigDecimal productionNum = new BigDecimal(split1[0])
			.multiply(new BigDecimal(split1[1]).multiply(productionDispatchAddDto.getSchedulingNum()));
			// 多个炒机情况
			if(speculativeTradingInfos.size() > 1){
			for (SpeculativeTradingInfo speculativeTradingInfo : speculativeTradingInfos) {
			// 获取该炒机正在排产量
			BigDecimal schedulingNumBySpeculativeTradingName = getSchedulingNumBySpeculativeTradingName(speculativeTradingInfo.getName());
			// 如果该炒机总量(单位kg需要乘1000) - 正在排产量 >=本次生产产量就分配此炒机
			if(speculativeTradingInfo.getWorkLoad().multiply(new BigDecimal(1000)).subtract(schedulingNumBySpeculativeTradingName).compareTo(productionNum) >= 0){
			name.set(speculativeTradingInfo.getName());
			break;
			}
			}
			}else{
			// 单个炒机情况
			name.set(speculativeTradingInfos.get(0).getName());
			}
			if(name.get().isEmpty()){
			i++;
			continue;
			}
			SalesLedgerScheduling salesLedgerScheduling = SalesLedgerScheduling.builder()
			.salesLedgerId(productionDispatchAddDto.getSalesLedgerId())
			.salesLedgerProductId(productionDispatchAddDto.getSalesLedgerProductId())
			.speculativeTradingName(name.get())
			.schedulingUserId(sysUser.getUserId())
			.schedulingUserName(sysUser.getNickName())
			.schedulingNum(productionDispatchAddDto.getSchedulingNum())
			.schedulingDate(productionDispatchAddDto.getSchedulingDate() == null ? LocalDate.now() : LocalDate.parse(productionDispatchAddDto.getSchedulingDate(), DateTimeFormatter.ofPattern("yyyy-MM-dd")))
			.status(1)
			.build();
			salesLedgerSchedulingMapper.insert(salesLedgerScheduling);
			successNum++;
			}

			return "派工成功数量" + successNum + "，失败数量" + i;
			}

			private final SalesLedgerProductMapper salesLedgerProductMapper;

			/**
			*通过炒机名称获取当天正在排产量
			* @return
			*/
			public BigDecimal getSchedulingNumBySpeculativeTradingName(String speculativeTradingName){
			LambdaQueryWrapper<SalesLedgerScheduling> queryWrapper = new LambdaQueryWrapper<>();
			queryWrapper.eq(SalesLedgerScheduling::getSpeculativeTradingName, speculativeTradingName)
			.eq(SalesLedgerScheduling::getSchedulingDate, LocalDate.now());
			List<SalesLedgerScheduling> salesLedgerSchedulings = salesLedgerSchedulingMapper.selectList(queryWrapper);
			if(CollectionUtils.isEmpty(salesLedgerSchedulings)){
			return BigDecimal.ZERO;
			}
			List<Long> collect = salesLedgerSchedulings.stream().map(SalesLedgerScheduling::getSalesLedgerProductId).collect(Collectors.toList());
			List<SalesLedgerProduct> salesLedgerProducts = salesLedgerProductMapper.selectList(new LambdaQueryWrapper<SalesLedgerProduct>()
			.in(SalesLedgerProduct::getId, collect));
			if(CollectionUtils.isEmpty(salesLedgerProducts)) return BigDecimal.ZERO;
			AtomicInteger totalNum = new AtomicInteger(0); //总数
			salesLedgerSchedulings.forEach(item ->{
			List<SalesLedgerProduct> collect1 = salesLedgerProducts.stream()
			.filter(j -> j.getId().equals(item.getSalesLedgerProductId()))
			.collect(Collectors.toList());
			if(!CollectionUtils.isEmpty(collect1)){
			SalesLedgerProduct salesLedgerProduct = collect1.get(0);
			// 根据产品规格 * 排产数量获取本次生产产量并累计
			String[] split = salesLedgerProduct.getSpecificationModel().split("\\*");
			BigDecimal productionNum = new BigDecimal(split[0])
			.multiply(new BigDecimal(split[1]).multiply(item.getSchedulingNum()));
			totalNum.addAndGet(productionNum.intValue());
			}
			});
			// 需要 / 损耗率
			Loss loss = lossMapper.selectOne(new LambdaQueryWrapper<Loss>().last("limit 1"));
			BigDecimal lossNum = loss == null ? new BigDecimal(6) : loss.getRate(); //没有损耗率则默认为6

			return new BigDecimal(totalNum.get()).multiply(new BigDecimal(100)).divide(lossNum, 2,RoundingMode.HALF_UP);
			}

			private final LossMapper lossMapper;


			/**
			*通过批量炒机名称获取当天正在排产量
			* @return
			*/
			public BigDecimal getSchedulingNumBySpeculativeTradingNameList(List<String> speculativeTradingName){
			LambdaQueryWrapper<SalesLedgerScheduling> queryWrapper = new LambdaQueryWrapper<>();
			queryWrapper.in(SalesLedgerScheduling::getSpeculativeTradingName, speculativeTradingName)
			.eq(SalesLedgerScheduling::getSchedulingDate, LocalDate.now());
			List<SalesLedgerScheduling> salesLedgerSchedulings = salesLedgerSchedulingMapper.selectList(queryWrapper);
			if(CollectionUtils.isEmpty(salesLedgerSchedulings)){
			return BigDecimal.ZERO;
			}
			List<Long> collect = salesLedgerSchedulings.stream().map(SalesLedgerScheduling::getSalesLedgerProductId).collect(Collectors.toList());
			List<SalesLedgerProduct> salesLedgerProducts = salesLedgerProductMapper.selectList(new LambdaQueryWrapper<SalesLedgerProduct>()
			.in(SalesLedgerProduct::getId, collect));
			if(CollectionUtils.isEmpty(salesLedgerProducts)) return BigDecimal.ZERO;
			AtomicInteger totalNum = new AtomicInteger(0); //总数
			salesLedgerSchedulings.forEach(item ->{
			List<SalesLedgerProduct> collect1 = salesLedgerProducts.stream()
			.filter(j -> j.getId().equals(item.getSalesLedgerProductId()))
			.collect(Collectors.toList());
			if(!CollectionUtils.isEmpty(collect1)){
			SalesLedgerProduct salesLedgerProduct = collect1.get(0);
			// 根据产品规格 * 排产数量获取本次生产产量并累计
			String[] split = salesLedgerProduct.getSpecificationModel().split("\\*");
			BigDecimal productionNum = new BigDecimal(split[0])
			.multiply(new BigDecimal(split[1]).multiply(item.getSchedulingNum()));
			totalNum.addAndGet(productionNum.intValue());
			}
			});
			return new BigDecimal(totalNum.get());
			}

			@Override
			@@ -120,14 +288,16 @@
			// salesLedgerWorkLambdaQueryWrapper.in(SalesLedgerWork::getSalesLedgerSchedulingId, collect)
			// .ne(SalesLedgerWork::getStatus, 1);
			// List<SalesLedgerWork> salesLedgerWorks = salesLedgerWorkMapper.selectList(salesLedgerWorkLambdaQueryWrapper);
			// list.getRecords().forEach(i -> {
			// // 获取完成数量
			// i.setSuccessNum(salesLedgerWorks
			// .stream()
			// .filter(j -> j.getSalesLedgerSchedulingId().equals(i.getId()))
			// .map(SalesLedgerWork::getFinishedNum)
			// .reduce(BigDecimal.ZERO, BigDecimal::add));
			// });
			list.getRecords().forEach(i -> {
			// 计算生产总量 = 规格 * 数量 / 1000
			String[] split = i.getSpecificationModel().split("\\*");
			if(split.length == 2 && isNumeric(split[0]) && isNumeric(split[1])){
			BigDecimal multiply = new BigDecimal(split[0])
			.multiply(new BigDecimal(split[1])
			.multiply(i.getSuccessNum()).divide(new BigDecimal(1000),2, RoundingMode.CEILING));
			i.setTotalProduction(multiply);
			}
			});
			return list;
			}

			@@ -171,6 +341,7 @@
			.remark(processSchedulingDto.getRemark())
			.type(processSchedulingDto.getType())
			.loss(processSchedulingDto.getLoss())
			.receive(processSchedulingDto.getReceive())
			.salesLedgerProductId(salesLedgerScheduling.getSalesLedgerProductId())
			.schedulingUserId(salesLedgerScheduling.getSchedulingUserId())
			.schedulingUserName(sysUser.getNickName())