359 lines
15 KiB
Python
359 lines
15 KiB
Python
"""库存计算相关函数"""
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from services.db import query
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from services.cache import RefreshableCache, register_cache
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# ⚠️ 特殊成本价规则：以下商品不使用库存表中的成本价，使用单独指定的正确成本价。
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# 键为商品编码，值为正确成本价。
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SPECIAL_COST_PRICES = {
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'POZ-FM-0184-TM-SM': 0.055, # 库存表55 → 正确0.055
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'POZ-XFS-9014-TM-MD': 0.062, # 库存表31.32 → 正确0.062
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'POZ-FM-9742-TM-MD': 0.181, # 库存表28.08 → 正确0.181
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'POZ-MM-0580-TM-MD': 0.22, # 库存表26 → 正确0.22
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'POZ-SKS-3374-LD': 0.1, # 库存表25 → 正确0.1
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'POZ-SKS-3367-LD': 0.1, # 库存表25 → 正确0.1
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'POZ-SKS-3350-LD': 0.1, # 库存表25 → 正确0.1
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'POZ-SKS-3343-LD': 0.1, # 库存表25 → 正确0.1
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}
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# 以下商品的库存总数量不统计20号仓库。
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EXCLUDE_WAREHOUSE_20_PRODUCTS = {
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'POZ-03033',
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'POZ-DXPW-1668-PDD',
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'AH-YS-0584-TMGJ',
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'POZ-JHY-7022',
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'SEDATE-YMT-1682-PDD',
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}
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# 以下无产品资料商品固定归属成品，不按20号仓库自动归为包材。
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FORCE_FINISHED_PRODUCTS = {
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'POZ-WPH-0137',
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'（AVA-YS-3252)',
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'（UO-AJS-3362)',
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'(WPK-CBZT-9707)',
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'【UOUONE】LHJ0385',
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}
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FORCE_FINISHED_PRODUCTS_SQL = ', '.join(
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"'%s'" % code.replace("'", "''") for code in sorted(FORCE_FINISHED_PRODUCTS)
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)
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def resolve_cost_price(product_code, inventory_price):
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"""解析产品成本价：命中特殊规则的用单独指定的正确成本价，否则用库存表成本价。"""
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if product_code in SPECIAL_COST_PRICES:
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return SPECIAL_COST_PRICES[product_code]
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return inventory_price
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def _get_latest_inv_date():
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"""获取最新库存数据日期"""
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latest = query("SELECT MAX(data_date) AS d FROM inventory_detail")[0]['d']
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if hasattr(latest, 'strftime'):
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return latest.strftime('%Y-%m-%d')
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return str(latest)[:10]
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def _compute_product_inventory():
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"""计算每个产品的最新库存（排除15号仓库）"""
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latest_str = _get_latest_inv_date()
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rows = query("""
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SELECT product_code, SUM(available_qty) AS total_qty
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FROM inventory_detail
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WHERE data_date = %s AND warehouse_code != '15'
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AND NOT (product_code IN ('POZ-03033', 'POZ-DXPW-1668-PDD', 'AH-YS-0584-TMGJ', 'POZ-JHY-7022', 'SEDATE-YMT-1682-PDD')
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AND LPAD(warehouse_code, 2, '0') = '20')
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GROUP BY product_code
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""", (latest_str,))
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inv_map = {}
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for r in rows:
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inv_map[r['product_code']] = int(r['total_qty']) if r['total_qty'] else 0
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return inv_map
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def _compute_raw_inventory_15():
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"""计算每个产品的最新加工厂库存（仅15号仓库）"""
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latest_str = _get_latest_inv_date()
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rows = query(
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"SELECT product_code, SUM(available_qty) AS total_qty "
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"FROM inventory_detail "
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"WHERE data_date = %s AND warehouse_code = '15' "
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"GROUP BY product_code",
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(latest_str,))
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inv15_map = {}
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for r in rows:
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inv15_map[r['product_code']] = int(r['total_qty']) if r['total_qty'] else 0
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return inv15_map
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# 缓存版获取最新加工厂库存
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inv15_cache = RefreshableCache(maxsize=1)
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register_cache(inv15_cache)
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@inv15_cache.wrap
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def compute_product_inventory_15():
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"""缓存版加工厂库存计算（支持跨 worker 主动刷新）"""
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return _compute_raw_inventory_15()
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def compute_product_inventory_by_property(property_keyword):
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"""根据仓库属性标签计算每个产品的库存（如云仓、外仓）"""
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wh_codes = query(
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"SELECT warehouse_code FROM warehouses WHERE FIND_IN_SET(%s, warehouse_property) > 0",
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(property_keyword,)
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)
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# 仓库管理和库存明细的编号格式可能不同（例如管理表为035、明细为35）。
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# 对纯数字仓号按数值匹配，其他编号仍按原字符串精确匹配。
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numeric_codes = set()
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text_codes = set()
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for row in wh_codes:
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code = str(row.get('warehouse_code') or '').strip()
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if not code:
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continue
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if code.isdigit():
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numeric_codes.add(int(code))
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else:
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text_codes.add(code)
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if not numeric_codes and not text_codes:
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return {}
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latest_str = _get_latest_inv_date()
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match_clauses = []
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params = [latest_str]
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if numeric_codes:
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placeholders = ','.join(['%s'] * len(numeric_codes))
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match_clauses.append(
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"warehouse_code REGEXP '^[0-9]+$' "
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f"AND CAST(warehouse_code AS UNSIGNED) IN ({placeholders})"
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)
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params.extend(sorted(numeric_codes))
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if text_codes:
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placeholders = ','.join(['%s'] * len(text_codes))
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match_clauses.append(f"warehouse_code IN ({placeholders})")
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params.extend(sorted(text_codes))
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rows = query(f"""
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SELECT product_code, SUM(available_qty) AS total_qty
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FROM inventory_detail
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WHERE data_date = %s AND ({' OR '.join(match_clauses)})
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GROUP BY product_code
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""", tuple(params))
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inv_map = {}
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for r in rows:
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inv_map[r['product_code']] = int(r['total_qty']) if r['total_qty'] else 0
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return inv_map
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# 缓存版云仓库存
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_cloud_inv_cache = RefreshableCache(maxsize=1)
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register_cache(_cloud_inv_cache)
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@_cloud_inv_cache.wrap
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def compute_cloud_inventory_cached():
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"""缓存版云仓库存计算（支持跨 worker 主动刷新）"""
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return compute_product_inventory_by_property('云仓')
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# 缓存版外仓库存
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_ext_inv_cache = RefreshableCache(maxsize=1)
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register_cache(_ext_inv_cache)
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@_ext_inv_cache.wrap
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def compute_external_inventory_cached():
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"""缓存版外仓库存计算（支持跨 worker 主动刷新）"""
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return compute_product_inventory_by_property('外仓')
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def compute_product_in_transit():
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"""计算每个产品的最新生产在途、采购在途（所有仓库合计）"""
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latest_str = _get_latest_inv_date()
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rows = query(
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"SELECT product_code, SUM(production_in_transit) AS prod_in_transit, "
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"SUM(purchase_in_transit) AS purch_in_transit "
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"FROM inventory_detail "
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"WHERE data_date = %s "
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"GROUP BY product_code",
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(latest_str,))
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transit_map = {}
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for r in rows:
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transit_map[r['product_code']] = {
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'生产在途': int(r['prod_in_transit']) if r['prod_in_transit'] else 0,
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'采购在途': int(r['purch_in_transit']) if r['purch_in_transit'] else 0,
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}
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return transit_map
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# 缓存版在途库存
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_transit_cache = RefreshableCache(maxsize=1)
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register_cache(_transit_cache)
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@_transit_cache.wrap
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def compute_product_in_transit_cached():
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"""缓存版在途库存计算（支持跨 worker 主动刷新）"""
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return compute_product_in_transit()
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def _determine_trend(avg_3, avg_7, avg_14):
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"""根据3/7/14天销量均值判断销售趋势（共10种）"""
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a3, a7, a14 = float(avg_3), float(avg_7), float(avg_14)
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# 全部为0 → 近期无销售
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if a3 == 0 and a7 == 0 and a14 == 0:
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return '近期无销售'
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# 防止除零
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base_7 = a7 if a7 != 0 else 1
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base_14 = a14 if a14 != 0 else 1
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# 计算比值
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ratio_3_7 = a3 / base_7
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ratio_7_14 = a7 / base_14
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diff_3_7 = abs(a3 - a7)
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diff_7_14 = abs(a7 - a14)
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# 应用趋势规则
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if a3 > a7 and 0.95 <= ratio_7_14 <= 1.05:
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return '开始上升'
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if a3 < a7 and 0.95 <= ratio_7_14 <= 1.05:
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return '开始下跌'
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if diff_3_7 <= 20 and diff_7_14 <= 20:
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return '平稳趋势'
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if 0.95 <= ratio_3_7 <= 1.05 and a7 > a14:
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return '上升趋稳'
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if 0.95 <= ratio_3_7 <= 1.05 and a7 < a14:
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return '下跌趋稳'
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if a3 > a7 and a7 > a14:
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return '持续上升'
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if a3 < a7 and a7 > a14:
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return '急跌'
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if a3 < a7 and a7 < a14:
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return '持续下跌'
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if a3 > a7 and a7 < a14:
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return '急增'
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return '平稳趋势'
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def _determine_trend_cached(avg_3, avg_7, avg_14):
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"""趋势判断（带缓存）"""
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return _determine_trend(avg_3, avg_7, avg_14)
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# 主库存计算缓存
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inv_cache = RefreshableCache(maxsize=1)
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register_cache(inv_cache)
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@inv_cache.wrap
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def compute_product_inventory_cached():
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"""缓存版库存计算（支持跨 worker 主动刷新）"""
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return _compute_product_inventory()
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def compute_inventory_cost_summary(latest_date=None):
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"""按系统数据概览口径计算当前库存成本汇总（与 /api/dashboard/stats 一致）。
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规则：
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- 成本价：命中 SPECIAL_COST_PRICES 的商品用单独指定的正确成本价，其余用库存表成本价
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- 成本价与库存数量使用同一个核对日期（latest_date，默认最新库存日期）
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- 排除内料（编码含 -NL 或名称含"内料"）
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- 成品/包材分类：有产品资料的按 product_type；无资料按仓库 20 号=包材、其他=成品
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- 20号仓库特定商品（EXCLUDE_WAREHOUSE_20_PRODUCTS）不统计
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- 生产在途按成品BOM中"内料"项的库存成本价计算；采购在途按成品成本价计算
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返回 dict：total_cost / finished_cost / packaging_cost / 各分项 / latest_date
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"""
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if not latest_date:
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latest_date = _get_latest_inv_date()
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# 成本价（同一核对日期）
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_latest_cost = query("""
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SELECT product_code, ANY_VALUE(cost_price) AS pr
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FROM inventory_detail WHERE data_date = %s GROUP BY product_code
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""", (latest_date,))
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_cost_map = {r['product_code']: resolve_cost_price(r['product_code'], float(r['pr']) if r['pr'] else 0) for r in _latest_cost}
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# 成品/包材分类汇总
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_inventory_rows = query("""
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SELECT id.product_code,
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SUM(CASE WHEN
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(p.product_type IN ('成品', '清库存', '现货', '赠品') AND p.deleted_at IS NULL)
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OR (p.product_code IS NULL AND (LPAD(id.warehouse_code, 2, '0') != '20'
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OR id.product_code IN ('POZ-WPH-0137', '（AVA-YS-3252)', '（UO-AJS-3362)', '(WPK-CBZT-9707)', '【UOUONE】LHJ0385')))
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THEN id.available_qty ELSE 0 END) AS finished_available_qty,
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SUM(CASE WHEN
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(p.product_type IN ('成品', '清库存', '现货', '赠品') AND p.deleted_at IS NULL)
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OR (p.product_code IS NULL AND (LPAD(id.warehouse_code, 2, '0') != '20'
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OR id.product_code IN ('POZ-WPH-0137', '（AVA-YS-3252)', '（UO-AJS-3362)', '(WPK-CBZT-9707)', '【UOUONE】LHJ0385')))
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THEN id.production_in_transit ELSE 0 END) AS finished_production_in_transit,
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SUM(CASE WHEN
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(p.product_type IN ('成品', '清库存', '现货', '赠品') AND p.deleted_at IS NULL)
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OR (p.product_code IS NULL AND (LPAD(id.warehouse_code, 2, '0') != '20'
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OR id.product_code IN ('POZ-WPH-0137', '（AVA-YS-3252)', '（UO-AJS-3362)', '(WPK-CBZT-9707)', '【UOUONE】LHJ0385')))
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THEN id.purchase_in_transit ELSE 0 END) AS finished_purchase_in_transit,
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SUM(CASE WHEN
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(p.product_type = '包材' AND p.product_name NOT LIKE %s AND p.deleted_at IS NULL)
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OR (p.product_code IS NULL AND LPAD(id.warehouse_code, 2, '0') = '20'
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AND id.product_code NOT IN ('POZ-WPH-0137', '（AVA-YS-3252)', '（UO-AJS-3362)', '(WPK-CBZT-9707)', '【UOUONE】LHJ0385'))
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THEN id.available_qty ELSE 0 END) AS packaging_available_qty,
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SUM(CASE WHEN
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(p.product_type = '包材' AND p.product_name NOT LIKE %s AND p.deleted_at IS NULL)
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OR (p.product_code IS NULL AND LPAD(id.warehouse_code, 2, '0') = '20'
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AND id.product_code NOT IN ('POZ-WPH-0137', '（AVA-YS-3252)', '（UO-AJS-3362)', '(WPK-CBZT-9707)', '【UOUONE】LHJ0385'))
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THEN id.purchase_in_transit ELSE 0 END) AS packaging_purchase_in_transit
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FROM inventory_detail id
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LEFT JOIN products p ON id.product_code = p.product_code
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WHERE id.data_date = %s
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AND id.product_code NOT LIKE %s
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AND id.product_name NOT LIKE %s
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AND NOT (id.product_code IN ('POZ-03033', 'POZ-DXPW-1668-PDD', 'AH-YS-0584-TMGJ', 'POZ-JHY-7022', 'SEDATE-YMT-1682-PDD')
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AND LPAD(id.warehouse_code, 2, '0') = '20')
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GROUP BY id.product_code
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""", ('%内料%', '%内料%', latest_date, '%-NL%', '%内料%'))
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# BOM 内料成本价（生产在途成本用）
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_inner_cost_rows = query("""
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SELECT b.product_code, b.material_code,
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COALESCE(mi.cost_price, m.cost_price, 0) AS inner_cost
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FROM bom b
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LEFT JOIN (
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SELECT product_code, ANY_VALUE(cost_price) AS cost_price
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FROM inventory_detail WHERE data_date = %s GROUP BY product_code
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) mi ON mi.product_code = b.material_code
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LEFT JOIN products m ON m.product_code = b.material_code
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WHERE (b.material_name LIKE %s OR b.material_code LIKE %s)
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""", (latest_date, '%内料%', '%-NL'))
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_inner_cost_map = {
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r['product_code']: resolve_cost_price(r['material_code'], float(r['inner_cost'] or 0)) if r['material_code'] else 0
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for r in _inner_cost_rows
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}
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finished_inventory_cost = finished_production_transit_cost = finished_purchase_transit_cost = 0.0
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packaging_inventory_cost = packaging_purchase_transit_cost = 0.0
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for r in _inventory_rows:
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price = _cost_map.get(r['product_code'], 0)
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finished_inventory_cost += float(r['finished_available_qty'] or 0) * price
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finished_production_transit_cost += float(r['finished_production_in_transit'] or 0) * _inner_cost_map.get(r['product_code'], 0)
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finished_purchase_transit_cost += float(r['finished_purchase_in_transit'] or 0) * price
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packaging_inventory_cost += float(r['packaging_available_qty'] or 0) * price
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packaging_purchase_transit_cost += float(r['packaging_purchase_in_transit'] or 0) * price
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finished_inventory_cost = round(finished_inventory_cost, 2)
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finished_production_transit_cost = round(finished_production_transit_cost, 2)
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finished_purchase_transit_cost = round(finished_purchase_transit_cost, 2)
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packaging_inventory_cost = round(packaging_inventory_cost, 2)
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packaging_purchase_transit_cost = round(packaging_purchase_transit_cost, 2)
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finished_cost = round(finished_inventory_cost + finished_production_transit_cost + finished_purchase_transit_cost, 2)
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packaging_cost = round(packaging_inventory_cost + packaging_purchase_transit_cost, 2)
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total_cost = round(finished_cost + packaging_cost, 2)
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return {
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'latest_date': latest_date,
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'total_cost': total_cost,
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'finished_cost': finished_cost,
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'packaging_cost': packaging_cost,
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'finished_inventory_cost': finished_inventory_cost,
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'finished_production_transit_cost': finished_production_transit_cost,
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'finished_purchase_transit_cost': finished_purchase_transit_cost,
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'packaging_inventory_cost': packaging_inventory_cost,
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'packaging_purchase_transit_cost': packaging_purchase_transit_cost,
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}
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