7 Commits
Author SHA1 Message Date
yeuimu 740bd803a9 fix: EVRI 面单 OCR 单号入库前去掉 '-'
CI / test (pull_request) Successful in 36s
2026-10-29 09:41:53 +00:00
yeuimu f87662ba4b fix: order/goods 限速收紧至峰值<3次/秒(340ms+0~160ms随机间隔)
CI / test (pull_request) Successful in 1m8s
2026-10-23 11:06:49 +00:00
yeuimu eb97ee1647 fix: RIIN order/goods 全局限速(并发20→5+150ms间隔,峰值≤6.7QPS);暂停 recent-sync/verify 调度(分销侧反馈调用量过大) 2026-10-23 10:57:46 +00:00
rom 1a13075926 fix(ci): 锁定 Python 3.12,避免 uv 选 3.15 触发全量源码编译
CI / test (pull_request) Successful in 3m40s
2026-10-21 17:45:56 +08:00
rom 019cbadd1e feat: 新增 shop-dim-sync flow 并注册每 5 分钟调度
CI / test (pull_request) Canceled after 5m33s
2026-10-21 16:55:31 +08:00
yeuimu 2321e8ae9f Merge branch 'inkreach/ocr-pl': OCR 新增支持波兰(PL) 2026-10-15 03:14:40 +00:00
yeuimu e5175a0504 fix: 写库重试 3→5 次、退避拉长至 1/3/7/15/30s
CI / test (pull_request) Successful in 4m30s
sceptical-finch(riin-recent-sync 10-10 16:04)失败复盘:17track 物流回写
(宿主机本地进程,不走 advisory 锁)与 sync 写库在 panel 触发器链
(panel.orders/dims/dims_daily)上交叉持锁,冲突窗口持续约 3 分钟,
原 3 次重试(1/3/7s)全部耗尽。加深重试使其可跨过分钟级外部冲突窗口。
2026-10-10 09:08:01 +00:00
6 changed files with 187 additions and 4 deletions
+1
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@@ -0,0 +1 @@
3.12
+8 -1
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@@ -29,13 +29,20 @@ _OCR_FIELD_MAP = [
]
# 单号不需要 "-" 的承运商(Evri 单号两段式带 "-",下游查询用无 "-" 形式)
_DASH_STRIP_COURIERS = {"EVRI"}
def _result_to_fields(r) -> dict[str, str | None]:
if not r.ok:
err = (r.error or "").lower()
if "reject" in err or "not a recognized layout" in err:
return {"ocrLayout": "UNSUPPORTED"}
return {"ocrLayout": "ERROR"}
return {col: (getattr(r, attr) or "") for attr, col in _OCR_FIELD_MAP}
fields = {col: (getattr(r, attr) or "") for attr, col in _OCR_FIELD_MAP}
if (r.courier or "").strip().upper() in _DASH_STRIP_COURIERS:
fields["ocrTracking"] = fields["ocrTracking"].replace("-", "")
return fields
def _has_running_peer() -> bool:
+144
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@@ -0,0 +1,144 @@
# -*- coding: utf-8 -*-
"""shop_dim 同步 flow:teable(源) -> 本地 smt 库(目标)。
最小包装自 sync_shop_dim.py,对应 shop-dim-sync,每 5 分钟调度一次。
源: PostgreSQL @ table.inkreach.cc:10432 db=teable schema=bsehWCxpH6HoHUdkjUd
物理表 tblUF7OrBxeRKUyWBc2 (teable 里名为 "shop_dim" 的表)
目标: PostgreSQL @ 192.168.124.92:5432 db=smt public.shop_dim
本地直接跑: python flows/platform_order/sync_shop_dim.py
"""
import time
from typing import Any
import psycopg2
from prefect import flow
SRC = dict(host="table.inkreach.cc", port=10432, dbname="teable",
user="read_only_role_bsehWCxpH6HoHUdkjUd",
password="ygBuh8Au5J-PjuNQASos0", connect_timeout=25)
SRC_TABLE = '"bsehWCxpH6HoHUdkjUd"."tblUF7OrBxeRKUyWBc2"'
DST = dict(host="192.168.124.92", port=5432, dbname="smt",
user="postgres", password="Inkreach123456.", connect_timeout=15)
COL_MAP = [
("Guo_Jia", "country"),
("Dian_Pu_Ming_Cheng", "shop_name"),
("DBDian_Pu_Ming", "db_store_name"),
("Ping_Tai", "platform"),
("Lei_Xing", "shop_type"),
("Deng_Ji", "tier"),
("Fu_Ze_Ren", "owner"),
("Pin_Lei", "category"),
("Xia_Dian_Shi_Jian", "opened_at"),
("Mu_Biao_Jian_Shu", "sep_target_qty"),
]
def log_msg(msg):
print(msg)
def connect(cfg, tries=5):
last = None
for i in range(tries):
try:
return psycopg2.connect(**cfg)
except Exception as e:
last = e
log_msg(f" 连接重试 {i+1}/{tries}: {e}")
time.sleep(3)
raise ConnectionError(f"连接失败: {last}")
def norm(v, col):
if v is None:
return None
if col == "opened_at":
return v.date() if hasattr(v, "date") else v
if col == "sep_target_qty":
try:
return int(round(float(v)))
except Exception:
return None
s = str(v).strip()
return s if s != "" else None
@flow(name="shop-dim-sync", log_prints=True)
def shop_dim_sync(dry_run: bool = False, prune: bool = True) -> dict[str, Any]:
log_msg(f"[1/4] 读取源表 {SRC_TABLE} ...")
sc = connect(SRC)
scur = sc.cursor()
sel = ", ".join('"%s"' % c for c, _ in COL_MAP)
scur.execute("SELECT %s FROM %s" % (sel, SRC_TABLE))
raw = scur.fetchall()
scur.close(); sc.close()
src_rows = [
dict(zip([d for _, d in COL_MAP], [norm(v, c) for v, (_, c) in zip(row, COL_MAP)]))
for row in raw
]
log_msg(f" 源记录: {len(src_rows)} 行")
log_msg("[2/4] 连接目标 smt.shop_dim ...")
dc = connect(DST)
dcur = dc.cursor()
dcur.execute("SELECT country, db_store_name FROM shop_dim WHERE db_store_name IS NOT NULL")
existing = {(r[0], r[1]) for r in dcur.fetchall()}
log_msg(f" 目标现有: {len(existing)} 个 (country, db_store_name)")
src_keys = {(r["country"], r["db_store_name"]) for r in src_rows}
to_update = src_keys & existing
to_insert = src_keys - existing
to_delete = existing - src_keys
log_msg(f"[3/4] 计划: 更新 {len(to_update)} | 新增 {len(to_insert)} | 待删 {len(to_delete)}")
if dry_run:
log_msg("[dry-run] 不执行写入。")
if to_delete:
log_msg(" 待删示例: " + str(list(to_delete)[:10]))
dcur.close(); dc.close()
return {"sourceRows": len(src_rows), "dryRun": True}
cols = [d for _, d in COL_MAP]
upd = 0
ins = 0
for r in src_rows:
vals = [r[c] for c in cols]
if (r["country"], r["db_store_name"]) in existing:
set_clause = ", ".join(f"{c}=%s" for c in cols)
dcur.execute(
f"UPDATE shop_dim SET {set_clause} WHERE country=%s AND db_store_name=%s",
vals + [r["country"], r["db_store_name"]])
upd += dcur.rowcount
else:
ph = ", ".join(["%s"] * len(cols))
dcur.execute(f"INSERT INTO shop_dim ({', '.join(cols)}) VALUES ({ph})", vals)
ins += dcur.rowcount
dele = 0
if prune and to_delete:
for country, dbn in to_delete:
dcur.execute("DELETE FROM shop_dim WHERE country=%s AND db_store_name=%s", (country, dbn))
dele += dcur.rowcount
dc.commit()
log_msg(f"[4/4] 完成: 更新 {upd} | 新增 {ins} | 删除 {dele}")
dcur.execute("SELECT COUNT(*) FROM shop_dim WHERE db_store_name IS NOT NULL")
total = dcur.fetchone()[0]
log_msg(f" 目标现有总数: {total}")
dcur.close(); dc.close()
return {
"sourceRows": len(src_rows),
"updated": upd,
"inserted": ins,
"deleted": dele,
"total": total,
}
if __name__ == "__main__":
shop_dim_sync.serve(name="shop-dim-sync", cron="*/5 * * * *")
+22 -1
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@@ -8,6 +8,8 @@
from __future__ import annotations
import json
import random
import threading
import time
from datetime import datetime, timedelta, timezone
from typing import Any, Callable, TypeVar
@@ -21,7 +23,9 @@ from flows.shared.mappers import map_sds_channel_type
T = TypeVar("T")
GOODS_CONCURRENCY = 20
GOODS_CONCURRENCY = 5
GOODS_MIN_INTERVAL_MS = 340 # 相邻两次 order/goods 调用全局最小间隔(峰值 < 3 次/秒)
GOODS_MAX_JITTER_MS = 160 # 在最小间隔上叠加的随机抖动上限,实际间隔 340~500ms 随机
PAGE_DELAY_MS = 500
MAX_RETRIES = 3
RETRY_DELAY_MS = 3000
@@ -144,8 +148,25 @@ def fetch_sds_all_pages(client: SdsMngClient, params: dict[str, Any]) -> list[An
# ---------- RIIN 商品 ----------
# 全局限速:RIIN 分销侧反馈 distribution/order/goods 逐单调用对其服务器压力过大,
# 所有线程共享节拍,相邻两次调用间隔 = GOODS_MIN_INTERVAL_MS + 随机抖动(340~500ms,峰值 < 3 次/秒)。
_goods_pace_lock = threading.Lock()
_goods_last_call_at = 0.0
def _pace_goods_call() -> None:
global _goods_last_call_at
with _goods_pace_lock:
interval = (GOODS_MIN_INTERVAL_MS + random.uniform(0, GOODS_MAX_JITTER_MS)) / 1000
wait = _goods_last_call_at + interval - time.monotonic()
if wait > 0:
time.sleep(wait)
_goods_last_call_at = time.monotonic()
def fetch_goods_for_order(client: RiinDisClient, order_id: str) -> list[Any]:
try:
_pace_goods_call()
resp = client.get_order_goods(order_id)
return list(resp.data)
except Exception as err: # noqa: BLE001
+3 -2
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@@ -25,8 +25,9 @@ LOOKUP_BATCH = 10000
# 单锁无环,写事务之间从结构上不可能死锁。1768851058 = "inkr" 的 ASCII 整数表示。
DB_WRITE_LOCK_KEY = 1768851058
LOCK_TIMEOUT = "15s" # 等锁超时 → LockNotAvailable → 交给重试兜底
WRITE_RETRIES = 3 # 死锁/等锁超时的整事务重试次数
WRITE_RETRY_BACKOFF = [1, 3, 7] # 重试退避(秒)
WRITE_RETRIES = 5 # 死锁/等锁超时的整事务重试次数(外部写者如 17track
# 物流回写不走 advisory 锁,冲突窗口可达分钟级,重试需够深)
WRITE_RETRY_BACKOFF = [1, 3, 7, 15, 30] # 重试退避(秒;末位预留,最后一次失败直接抛出)
WRITE_RETRYABLE_ERRORS = (pg_errors.DeadlockDetected, pg_errors.LockNotAvailable)
+9
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@@ -21,6 +21,7 @@ deployments:
schedules:
- cron: 30 * * * *
timezone: Asia/Shanghai
active: false # 暂停:每小时重拉近7天全部订单商品,对 RIIN distribution/order/goods 调用量过大(增量/刷新未完结/日报核验已覆盖)
work_pool:
name: inkreach-pool
- name: riin-refresh-pending
@@ -39,6 +40,7 @@ deployments:
schedules:
- cron: 0 6 * * *
timezone: Asia/Shanghai
active: false # 暂停:与 daily-report 18:30 的核验子流程重复,保留日报一处即可
work_pool:
name: inkreach-pool
- name: sds-order-sync
@@ -108,6 +110,13 @@ deployments:
timezone: Asia/Shanghai
work_pool:
name: inkreach-pool
- name: shop-dim-sync
entrypoint: flows/platform_order/sync_shop_dim.py:shop_dim_sync
schedules:
- cron: '*/5 * * * *'
timezone: Asia/Shanghai
work_pool:
name: inkreach-pool
- name: label-ocr
entrypoint: flows/label_ocr.py:label_ocr
schedules: