Fbo Status

FBO 发货台账全局状态

综合读 ledger/shipment_ledger_*.json (每次 run 一份), 按日期/集群/SKU 聚合展示 shipped 和 skipped, 补 pending 总数.

触发场景

• "看一下 FBO 总体发货状态"
• "过去一周发了多少件"
• "所有 SKU 目前 shipped/pending 数"
• "哪个集群发得最多"
• "看看 ledger"
• "有没有新的 skipped"

路径

• 台账目录: /Users/mac/Documents/ozns/丝绸生活/海外仓发货表/2026-04-23海外仓发货/ledger/
• 文件: shipment_ledger_<YYYYMMDD_HHMMSS>.json, pending_summary.json

查看工具

没有独立 CLI, 用 bash + python 一段脚本即可. 标准用法:

1. 所有 run 的发货总览 (最常用)

cd /Users/mac/Documents/ozns/丝绸生活/海外仓发货表/2026-04-23海外仓发货
python3 <<'EOF'
import json, glob
from collections import defaultdict
files = sorted(glob.glob("ledger/shipment_ledger_*.json"))
print(f"=== {len(files)} runs in ledger/ ===\n")
total_ship = total_skip = 0
by_cluster_ship = defaultdict(int); by_cluster_skip = defaultdict(int)
by_sku_ship = defaultdict(int);     by_sku_skip = defaultdict(int)
for f in files:
    d = json.load(open(f))
    run_at = d.get("run_at","")
    ship_n = sum(sum(it.get("quantity",0) for it in s.get("items",[])) for s in d.get("shipped",[]))
    skip_n = sum(s.get("quantity",0) for s in d.get("skipped",[]))
    orders = len(d.get("shipped",[]))
    print(f"{run_at[:19]:20}  orders={orders:3}  shipped={ship_n:6}件  skipped={skip_n:6}件  ({f.split('/')[-1]})")
    total_ship += ship_n; total_skip += skip_n
    for s in d.get("shipped",[]):
        for it in s.get("items",[]):
            for c in (s.get("cluster_names") or [s.get("cluster")]):
                if c: by_cluster_ship[c] += it.get("quantity",0)
            by_sku_ship[it.get("offer_id","")] += it.get("quantity",0)
    for s in d.get("skipped",[]):
        by_cluster_skip[s.get("cluster","")] += s.get("quantity",0)
        by_sku_skip[s.get("offer_id","")] += s.get("quantity",0)
print(f"\n=== 汇总: shipped={total_ship} 件, skipped={total_skip} 件 (含重复, 看 pending 去重) ===")
print("\n按集群 shipped:")
for c,n in sorted(by_cluster_ship.items(), key=lambda x:-x[1]):
    print(f"  {c:40} {n:6} 件 (skipped={by_cluster_skip.get(c,0)})")
print("\n按 SKU shipped:")
for k,n in sorted(by_sku_ship.items(), key=lambda x:-x[1]):
    print(f"  {k:40} {n:6} 件 (skipped={by_sku_skip.get(k,0)})")
EOF

2. 看最新 run 的明细

python3 <<'EOF'
import json, glob
f = sorted(glob.glob("ledger/shipment_ledger_*.json"))[-1]
d = json.load(open(f))
print(f"=== {f.split('/')[-1]} ===")
print(f"run_at: {d.get('run_at')}  account: {d.get('account')}")
print(f"shipped: {len(d.get('shipped',[]))} orders")
for s in d.get("shipped",[]):
    cl = s.get("cluster_names") or [s.get("cluster")]
    print(f"  order={s.get('order_id')}  supply={s.get('supply_id')}  cluster={cl}  mode={s.get('mode')}")
    for it in s.get("items",[]):
        print(f"    {it.get('offer_id'):30}  ×{it.get('quantity'):5}  boxes={it.get('boxes')}")
print(f"\nskipped: {len(d.get('skipped',[]))} 条")
for s in d.get("skipped",[]):
    print(f"  {s.get('cluster'):25} {s.get('offer_id'):30} ×{s.get('quantity'):5}  {s.get('reason_code','')}")
EOF

3. 看 pending 当前总数 (跨 run 去重后)

python3 list_pending.py
# 或分组:
python3 list_pending.py --by-cluster
python3 list_pending.py --by-sku
python3 list_pending.py --by-reason

(list_pending.py 内部自动消解 — 后续 run 发成功的会从 pending 里移除)

4. 查某个 order_id 的历史记录

python3 <<'EOF'
import json, glob, sys
ORDER = 100532100   # 改这里
for f in sorted(glob.glob("ledger/shipment_ledger_*.json")):
    d = json.load(open(f))
    for s in d.get("shipped",[]):
        if s.get("order_id") == ORDER:
            print(f"--- {f.split('/')[-1]} / run_at={d.get('run_at')} ---")
            print(json.dumps(s, ensure_ascii=False, indent=2))
EOF

5. 哪些 SKU 在哪个集群发最多

python3 <<'EOF'
import json, glob
from collections import defaultdict
grid = defaultdict(lambda: defaultdict(int))
for f in glob.glob("ledger/shipment_ledger_*.json"):
    d = json.load(open(f))
    for s in d.get("shipped",[]):
        cl = s.get("cluster_names") or [s.get("cluster")]
        for it in s.get("items",[]):
            for c in cl:
                if c: grid[it.get("offer_id","")][c] += it.get("quantity",0)
for sku, by in grid.items():
    print(f"\n[{sku}]")
    for c,n in sorted(by.items(), key=lambda x:-x[1]):
        print(f"  {c:40} {n:6} 件")
EOF

字段速查 (shipped 条)

{
  "order_id": 100532100,
  "mode": "CROSSDOCK" | "MULTI_CLUSTER",
  "supply_id": 2000050076860,
  "cluster_kws": ["Новосибирск"],
  "cluster_names": ["Новосибирск"],
  "macrolocal_cluster_ids": ["4067"],
  "drop_off": {"id": 22190776129000, "name": "МО_ЩЕРБИНКА_ХАБ"},
  "storage_warehouse": {"id": 18044341087000, "name": "НОВОСИБИРСК_РФЦ_НОВЫЙ"},
  "timeslot": {"from": "...", "to": "..."},
  "state": "DATA_FILLING",
  "items": [{"offer_id":"...","sku":...,"barcode":"...","quantity":600,"boxes":2,"cargo_ids":[...]}],
  "pdf_path": "/app/labels/supply_2000050076860.pdf",
  "pdf_file_url": "https://...s3...",
  "timestamp": "..."
}

字段速查 (skipped 条)

{
  "cluster": "Новосибирск",
  "cluster_kw": "Новосибирск",
  "macrolocal_cluster_id": "4067",
  "offer_id": "Q_MeiGongDao-HeiSe-Free",
  "sku": 3214793665,
  "barcode": "...",
  "quantity": 1800,
  "reason": "...",
  "reason_code": "MATRIX_DROPPED_FROM_SUPPLY" | "NO_AVAILABLE_WAREHOUSE" | "DRAFT_OR_SUPPLY_FAILED",
  "related_order_id": 100532100,
  "related_supply_id": 2000050076860,
  "timestamp": "..."
}

常见问题

Q1: 总 shipped 件数 vs Ozon 后台数对不上

ledger 是"本机发起的 run"维度. Ozon 后台还含:

• 手工在 UI 建的 supply
• 旧脚本 demo.py / writeShiploaction.py 发的 (没台账)
• 被取消的 (ledger 有 shipped 但 UI 可能 cancelled 了) 去 Ozon seller.ozon.ru 「供货单」里按 date 筛选再对.

Q2: pending_summary.json 和 list_pending.py 输出不一致

pending_summary.json 是 create_fbo_plan.py 写的快照, list_pending.py 是动态重算. 以后者为准 (能反映最新 run 的自动消解).

Q3: 想删某个 ledger 文件

可以直接 rm ledger/shipment_ledger_xxx.json, 不会影响已发的 Ozon 单. pending 会重新去重计算 (相应的 skipped 记录会被去掉).

Q4: 备份

整个 ledger/ 目录用 tar 压一下备份即可, 纯 JSON 文本无副作用. 恢复用 tar -xf 回来, list_pending.py 自动读.

build_shipment_overview.py — 计划 vs 已发对照表 (2026-04-25 起首选)

聚合 4181 plans (cap_total) + Ozon /supply-order/list+get+bundle (active) 出 Excel, 直观看每集群每 SKU 计划/已发/差额.

python3 build_shipment_overview.py --exclude-before 2026-04-23T00:00:00Z

输出列: 集群 | offer_id | 计划件数 | 已发件数 | 差额 | 状态 | 关联 supply_id

新加状态 (2026-04-25, per-SKU 算法配合):

• 改派抵扣已完成 — 本 cluster cap > active 但全 SKU 总 active ≥ cap_total (远东 600 → Москва 抵扣)
• 无计划-意外发货 (改派目标) — 本 cluster planned=0 但 active>0 (Москва 接了远东改派)
• 缺 X 件 — 还没发齐
• 已发齐 — cluster 单独够数

跟 list_pending 共用 per-SKU 算法 (cap_total / active_total); supply-order/list 必传 sort_by:1 (reference_shipment_overview_script.md).

同步本 skill 的 .py 文件

bash /Users/mac/.claude/skills/sync_fbo_scripts.sh

相关 skill

• /fbo-retry — pending 清单 + 重试
• /fbo-plan — 新一轮发货 run
• memory reference_shipment_ledger.md — ledger schema + pending 去重规则完整说明
• memory reference_shipment_overview_script.md — build_shipment_overview.py 详解