greater_wms/location_statistics/services.py

from django.db.models import Count, Q
from django.utils import timezone
from bin.models import LocationModel
from .models import LocationStatistics, LocationGroupStatistics

class LocationStatisticsService:
    """货位统计服务类"""
    TARGET_LOCATION_TYPES = ['T5', 'T4', 'S4', 'T2', 'T1']

    @staticmethod
    def calculate_location_statistics(warehouse_code=None, layer=None):
        """
        计算货位统计信息
        
        Args:
            warehouse_code: 仓库代码，如果为None则统计所有仓库
            layer: 楼层，如果为None则统计所有楼层
        """
        # 构建查询条件
        # 构建查询条件 - 只统计指定的货位类型
        filters = {
            'is_active': True,
            'location_type__in': LocationStatisticsService.TARGET_LOCATION_TYPES
        }
        if warehouse_code:
            filters['warehouse_code'] = warehouse_code
        if layer is not None:
            filters['layer'] = layer
        
        # 获取所有符合条件的货位
        locations = LocationModel.objects.filter(**filters)
        
        # 按仓库和楼层分组统计
        statistics_data = {}
        
        for location in locations:
            key = f"{location.warehouse_code}_{location.layer}"
            if key not in statistics_data:
                statistics_data[key] = {
                    'warehouse_code': location.warehouse_code,
                    'warehouse_name': location.warehouse_name,
                    'layer': location.layer,
                    'location_types': {},
                    'groups': {},
                    'total': 0,
                    'used': 0,
                    'available': 0
                }

            status = (location.status or '').lower()
            is_used = status in {'occupied', 'reserved'}
            is_available = status == 'available'

            # 统计货位类型
            loc_type = location.location_type
            if loc_type not in statistics_data[key]['location_types']:
                statistics_data[key]['location_types'][loc_type] = {
                    'total': 0, 'used': 0, 'available': 0
                }

            statistics_data[key]['location_types'][loc_type]['total'] += 1
            statistics_data[key]['total'] += 1

            # 根据状态统计
            if is_used:
                statistics_data[key]['location_types'][loc_type]['used'] += 1
                statistics_data[key]['used'] += 1
            elif is_available:
                statistics_data[key]['location_types'][loc_type]['available'] += 1
                statistics_data[key]['available'] += 1

            # 统计货位组
            group = location.location_group
            if group not in statistics_data[key]['groups']:
                statistics_data[key]['groups'][group] = {
                    'total': 0,
                    'used': 0,
                    'available': 0,
                    'types': {}
                }

            statistics_data[key]['groups'][group]['total'] += 1
            if is_used:
                statistics_data[key]['groups'][group]['used'] += 1
            elif is_available:
                statistics_data[key]['groups'][group]['available'] += 1

            # 统计组内货位类型分布
            group_types = statistics_data[key]['groups'][group]['types']
            if loc_type not in group_types:
                group_types[loc_type] = {'total': 0, 'used': 0, 'available': 0}

            group_types[loc_type]['total'] += 1
            if is_used:
                group_types[loc_type]['used'] += 1
            elif is_available:
                group_types[loc_type]['available'] += 1
        
        return statistics_data
    
    @staticmethod
    def save_statistics_to_db(statistics_data):
        """将统计结果保存到数据库"""
        current_time = timezone.now()
        
        # 先将之前的最新标记清除
        LocationStatistics.objects.filter(is_latest=True).update(is_latest=False)
        
        statistics_objects = []
        group_statistics_objects = []
        
        for key, data in statistics_data.items():
            # 计算使用率
            utilization_rate = 0
            if data['total'] > 0:
                utilization_rate = round((data['used'] / data['total']) * 100, 2)
            
            # 创建主统计对象
            stat = LocationStatistics(
                warehouse_code=data['warehouse_code'],
                warehouse_name=data['warehouse_name'],
                layer=data['layer'],
                statistic_time=current_time,
                is_latest=True,
                total_locations=data['total'],
                total_used=data['used'],
                total_available=data['available'],
                utilization_rate=utilization_rate
            )
            
            # 设置各类型货位统计
            loc_types = data['location_types']
            for loc_type, counts in loc_types.items():
                if loc_type == 'T5':
                    stat.t5_total = counts['total']
                    stat.t5_used = counts['used']
                    stat.t5_available = counts['available']
                elif loc_type == 'T4':
                    stat.t4_total = counts['total']
                    stat.t4_used = counts['used']
                    stat.t4_available = counts['available']
                elif loc_type == 'S4':
                    stat.s4_total = counts['total']
                    stat.s4_used = counts['used']
                    stat.s4_available = counts['available']
                elif loc_type == 'T2':
                    stat.t2_total = counts['total']
                    stat.t2_used = counts['used']
                    stat.t2_available = counts['available']
                elif loc_type == 'T1':
                    stat.t1_total = counts['total']
                    stat.t1_used = counts['used']
                    stat.t1_available = counts['available']
            
            statistics_objects.append(stat)
            
            # 创建货位组统计对象
            for group_name, group_data in data['groups'].items():
                group_utilization = 0
                if group_data['total'] > 0:
                    group_utilization = round((group_data['used'] / group_data['total']) * 100, 2)
                
                group_stat = LocationGroupStatistics(
                    warehouse_code=data['warehouse_code'],
                    warehouse_name=data['warehouse_name'],
                    layer=data['layer'],
                    location_group=group_name,
                    total_locations=group_data['total'],
                    used_locations=group_data['used'],
                    available_locations=group_data['available'],
                    utilization_rate=group_utilization,
                    location_type_breakdown=group_data.get('types', {}),
                    statistic_time=current_time
                )
                group_statistics_objects.append(group_stat)
        
        # 批量保存
        LocationStatistics.objects.bulk_create(statistics_objects)
        LocationGroupStatistics.objects.bulk_create(group_statistics_objects)
        
        return len(statistics_objects)
    
    @staticmethod
    def get_latest_statistics(warehouse_code=None, layer=None):
        """获取最新统计信息"""
        filters = {'is_latest': True}
        if warehouse_code:
            filters['warehouse_code'] = warehouse_code
        if layer is not None:
            filters['layer'] = layer
        
        return LocationStatistics.objects.filter(**filters).order_by('warehouse_code', 'layer')
    
    @staticmethod
    def get_statistics_by_time_range(start_time, end_time, warehouse_code=None, layer=None):
        """按时间范围获取统计信息"""
        filters = {
            'statistic_time__gte': start_time,
            'statistic_time__lte': end_time
        }
        if warehouse_code:
            filters['warehouse_code'] = warehouse_code
        if layer is not None:
            filters['layer'] = layer
        
        return LocationStatistics.objects.filter(**filters).order_by('statistic_time', 'warehouse_code', 'layer')