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- # -*- coding: utf-8 -*-
- """
- SQLite 存储层
- - stores 门店主数据
- - metrics 指标明细(按 门店 × 周期 × 日期 × 粒度 唯一)
- - batches 导入批次
- - thresholds 考核指标阈值(单行 JSON)
- - settings 杂项键值
- 日粒度数据按月聚合,聚合口径统一在这里,前端不重复算。
- """
- import json
- import os
- import re
- import sqlite3
- from datetime import datetime
- import rules
- BASE = os.path.dirname(os.path.abspath(__file__))
- DATA_DIR = os.path.join(os.path.dirname(BASE), "data")
- DB_PATH = os.path.join(DATA_DIR, "app.db")
- INBOX = os.path.join(DATA_DIR, "inbox")
- PROCESSED = os.path.join(DATA_DIR, "processed")
- SCHEMA = """
- CREATE TABLE IF NOT EXISTS stores (
- id TEXT PRIMARY KEY,
- name TEXT NOT NULL,
- city TEXT,
- status TEXT DEFAULT 'active',
- first_seen TEXT,
- last_seen TEXT
- );
- CREATE TABLE IF NOT EXISTS metrics (
- store_id TEXT NOT NULL,
- period TEXT NOT NULL, -- YYYY-MM(月)或 截至日 YYYY-MM-DD(快照)
- date TEXT NOT NULL DEFAULT '',-- YYYY-MM-DD;月汇总行留空
- granularity TEXT NOT NULL, -- daily | period | snapshot
- window_start TEXT DEFAULT '', -- 快照:统计窗口开始日
- window_end TEXT DEFAULT '', -- 快照:统计窗口结束日(= 数据截至日)
- visit INTEGER DEFAULT 0,
- deal INTEGER DEFAULT 0,
- deal_refund INTEGER DEFAULT 0,
- intend_deal INTEGER DEFAULT 0,
- used_amount REAL DEFAULT 0,
- used_coupons INTEGER DEFAULT 0,
- intend_refund INTEGER DEFAULT 0,
- videos INTEGER DEFAULT 0,
- video_views INTEGER DEFAULT 0,
- score REAL,
- reviews_new INTEGER DEFAULT 0,
- good_new INTEGER DEFAULT 0,
- bad_new INTEGER DEFAULT 0,
- reviews_total INTEGER DEFAULT 0,
- good_total INTEGER DEFAULT 0,
- bad_total INTEGER DEFAULT 0,
- reply_rate REAL,
- complaint_rate REAL,
- return_rate REAL,
- lit INTEGER DEFAULT 0,
- lit_posts INTEGER DEFAULT 0,
- favs INTEGER DEFAULT 0,
- rank_note TEXT,
- batch_id INTEGER,
- PRIMARY KEY (store_id, period, date, granularity)
- );
- CREATE INDEX IF NOT EXISTS idx_metrics_period ON metrics(period, granularity);
- CREATE TABLE IF NOT EXISTS batches (
- id INTEGER PRIMARY KEY AUTOINCREMENT,
- filename TEXT,
- rows_read INTEGER,
- rows_written INTEGER,
- new_stores INTEGER,
- period TEXT,
- date_from TEXT,
- date_to TEXT,
- created_at TEXT,
- note TEXT,
- file_path TEXT -- 原始文件在 data/processed 下的文件名
- );
- CREATE TABLE IF NOT EXISTS users (
- id INTEGER PRIMARY KEY AUTOINCREMENT,
- username TEXT UNIQUE NOT NULL,
- pass_hash TEXT NOT NULL,
- salt TEXT NOT NULL,
- role TEXT NOT NULL DEFAULT 'viewer',
- display_name TEXT DEFAULT '',
- active INTEGER DEFAULT 1,
- must_change INTEGER DEFAULT 0,
- created_at TEXT,
- last_login TEXT
- );
- CREATE TABLE IF NOT EXISTS sessions (
- token_hash TEXT PRIMARY KEY,
- user_id INTEGER NOT NULL,
- created_at TEXT,
- expires_at TEXT,
- ip TEXT DEFAULT ''
- );
- CREATE TABLE IF NOT EXISTS thresholds (
- id INTEGER PRIMARY KEY CHECK (id = 1),
- data TEXT NOT NULL,
- updated_at TEXT
- );
- CREATE TABLE IF NOT EXISTS settings (
- key TEXT PRIMARY KEY,
- value TEXT
- );
- """
- METRIC_FIELDS = ["visit", "deal", "deal_refund", "intend_deal", "used_amount",
- "used_coupons", "intend_refund", "videos", "video_views", "score",
- "reviews_new", "good_new", "bad_new", "reviews_total", "good_total",
- "bad_total", "reply_rate", "complaint_rate", "return_rate",
- "lit", "lit_posts", "favs", "rank_note"]
- def connect():
- os.makedirs(DATA_DIR, exist_ok=True)
- os.makedirs(INBOX, exist_ok=True)
- os.makedirs(PROCESSED, exist_ok=True)
- conn = sqlite3.connect(DB_PATH, timeout=15)
- conn.row_factory = sqlite3.Row
- conn.execute("PRAGMA journal_mode=WAL")
- return conn
- def _migrate(conn):
- """老库补齐新增列(SQLite 的 ADD COLUMN 不会报错重复)"""
- cols = {r[1] for r in conn.execute("PRAGMA table_info(metrics)")}
- for c in ("window_start", "window_end"):
- if c not in cols:
- conn.execute("ALTER TABLE metrics ADD COLUMN %s TEXT DEFAULT ''" % c)
- bcols = {r[1] for r in conn.execute("PRAGMA table_info(batches)")}
- if "file_path" not in bcols:
- conn.execute("ALTER TABLE batches ADD COLUMN file_path TEXT")
- def backfill_batch_files(conn):
- """老批次补上「原始文件」路径:用 created_at 的时间戳去匹配 processed 里的文件名前缀"""
- try:
- rows = conn.execute("SELECT id, created_at FROM batches "
- "WHERE file_path IS NULL OR file_path=''").fetchall()
- if not rows or not os.path.isdir(PROCESSED):
- return
- idx = {}
- for f in os.listdir(PROCESSED):
- m = re.match(r"^(\d{8}_\d{6})_", f)
- if m:
- idx[m.group(1)] = f
- for r in rows:
- try:
- stamp = datetime.fromisoformat(r["created_at"]).strftime("%Y%m%d_%H%M%S")
- except (TypeError, ValueError):
- continue
- f = idx.get(stamp)
- if f:
- conn.execute("UPDATE batches SET file_path=? WHERE id=?", (f, r["id"]))
- except Exception:
- pass
- def init_db():
- conn = connect()
- with conn:
- conn.executescript(SCHEMA)
- _migrate(conn)
- backfill_batch_files(conn)
- cur = conn.execute("SELECT id FROM thresholds WHERE id=1")
- if not cur.fetchone():
- conn.execute("INSERT INTO thresholds(id, data, updated_at) VALUES (1, ?, ?)",
- (json.dumps(rules.DEFAULT_THRESHOLDS, ensure_ascii=False),
- datetime.now().isoformat(timespec="seconds")))
- conn.close()
- def get_thresholds():
- """读取阈值;库里没有的新键(v2 新增门槛)用默认值补全,老库不用迁移"""
- conn = connect()
- row = conn.execute("SELECT data FROM thresholds WHERE id=1").fetchone()
- conn.close()
- T = dict(rules.DEFAULT_THRESHOLDS)
- if row:
- try:
- T.update(json.loads(row["data"]))
- except Exception:
- pass
- return T
- def set_thresholds(T):
- conn = connect()
- with conn:
- conn.execute("UPDATE thresholds SET data=?, updated_at=? WHERE id=1",
- (json.dumps(T, ensure_ascii=False),
- datetime.now().isoformat(timespec="seconds")))
- conn.close()
- def reset_thresholds():
- set_thresholds(dict(rules.DEFAULT_THRESHOLDS))
- return dict(rules.DEFAULT_THRESHOLDS)
- def get_setting(key, default=None):
- conn = connect()
- row = conn.execute("SELECT value FROM settings WHERE key=?", (key,)).fetchone()
- conn.close()
- return row["value"] if row else default
- def set_setting(key, value):
- conn = connect()
- with conn:
- conn.execute("INSERT INTO settings(key, value) VALUES(?,?) "
- "ON CONFLICT(key) DO UPDATE SET value=excluded.value", (key, str(value)))
- conn.close()
- # ---- 文案模板(settings 表单行 JSON,key='texts')----
- def get_texts():
- """
- 读取文案。库里存的是整份模板,升级后旧存档会盖住新默认值,所以按规则迁移:
- 存档值 == v1 默认值 → 用户没改过,用新默认值
- 存档值 != v1 默认值 → 用户自定义过,保留
- """
- conn = connect()
- row = conn.execute("SELECT value FROM settings WHERE key='texts'").fetchone()
- conn.close()
- merged = dict(rules.DEFAULT_TEXTS)
- if row:
- try:
- stored = json.loads(row["value"])
- except Exception:
- stored = {}
- for k, v in stored.items():
- if k not in rules.DEFAULT_TEXTS:
- continue # 已废弃的旧键直接丢弃
- if rules.V1_TEXTS.get(k) == v:
- continue # 与 v1 默认一致 = 没自定义过
- merged[k] = v
- return merged
- def set_texts(X):
- """只存「与默认值不同」的键,默认值以后再改也能自动生效"""
- diff = {k: v for k, v in X.items()
- if k in rules.DEFAULT_TEXTS and v != rules.DEFAULT_TEXTS[k]}
- conn = connect()
- with conn:
- conn.execute(
- "INSERT INTO settings(key, value) VALUES('texts', ?) "
- "ON CONFLICT(key) DO UPDATE SET value=excluded.value",
- (json.dumps(diff, ensure_ascii=False),))
- conn.close()
- def reset_texts():
- set_texts(dict(rules.DEFAULT_TEXTS))
- return dict(rules.DEFAULT_TEXTS)
- def _pick_granularity(conn, period):
- """
- 快照(近30天滚动窗口)优先级最高:一个 period 只有一份快照行/店。
- 同一周期两种粒度都存在时的取舍:
- 日数据覆盖 >= 15 天才用日粒度(避免刚导 1 天日报就把整月视图切成残缺的日聚合);
- 否则用月汇总行。
- """
- has_snap = conn.execute("SELECT 1 FROM metrics WHERE period=? AND granularity='snapshot' LIMIT 1",
- (period,)).fetchone()
- if has_snap:
- return "snapshot"
- has_daily = conn.execute("SELECT 1 FROM metrics WHERE period=? AND granularity='daily' LIMIT 1",
- (period,)).fetchone()
- has_month = conn.execute("SELECT 1 FROM metrics WHERE period=? AND granularity='period' LIMIT 1",
- (period,)).fetchone()
- if has_daily and has_month:
- n = conn.execute("SELECT COUNT(DISTINCT date) c FROM metrics WHERE period=? "
- "AND granularity='daily' AND date<>''", (period,)).fetchone()["c"]
- return "daily" if n >= 15 else "period"
- return "daily" if has_daily else "period"
- def get_periods():
- """
- 返回周期列表。三种粒度:
- 快照 snapshot —— 近 N 天滚动窗口,period 记「截至日」,带 window_start/end
- daily —— 当月按日导入
- period —— 月汇总
- """
- conn = connect()
- rows = conn.execute("""
- SELECT period, granularity, COUNT(DISTINCT store_id) AS stores, COUNT(DISTINCT date) AS days
- FROM metrics GROUP BY period, granularity
- """).fetchall()
- plans = {}
- for r in rows:
- plans.setdefault(r["period"], {})[r["granularity"]] = r
- out = []
- for p, gs in plans.items():
- g = _pick_granularity(conn, p)
- r = gs.get(g) or next(iter(gs.values()))
- item = {"period": p, "stores": r["stores"], "granularity": g,
- "days": r["days"] if g == "daily" else 0}
- if g == "snapshot":
- w = conn.execute("SELECT window_start, window_end FROM metrics "
- "WHERE period=? AND granularity='snapshot' LIMIT 1", (p,)).fetchone()
- ws, we = (w["window_start"] or "", w["window_end"] or "") if w else ("", "")
- d = _days_between(ws, we)
- item.update({"window_start": ws, "window_end": we, "as_of": we or p,
- "days": d or 30,
- "label": "近%d天 · 截至 %s" % (d or 30, (we or p)[5:])})
- item["sort_key"] = (item.get("as_of") or (p + "-01"))
- out.append(item)
- conn.close()
- return sorted(out, key=lambda x: x["sort_key"], reverse=True)
- def latest_period():
- ps = get_periods()
- return ps[0]["period"] if ps else None
- def _days_between(a, b):
- """两个 YYYY-MM-DD 之间的天数(含首尾)"""
- try:
- from datetime import date
- d1 = date.fromisoformat(a)
- d2 = date.fromisoformat(b)
- return (d2 - d1).days + 1
- except Exception:
- return 0
- def _weighted(items, weight_key, value_key):
- """加权平均:权重为 None/0 时退化为简单平均"""
- num = den = 0.0
- simple = []
- for it in items:
- v = it.get(value_key)
- if v is None:
- continue
- w = it.get(weight_key) or 0
- num += v * w
- den += w
- simple.append(v)
- if den > 0:
- return num / den
- return (sum(simple) / len(simple)) if simple else None
- def aggregate_period(period):
- """
- 按月聚合。日粒度优先;没有日粒度就用月汇总行。
- 返回每店一条,含派生指标 hx_rate / cp_rate / cp_src。
- """
- conn = connect()
- g = _pick_granularity(conn, period)
- rows = conn.execute("""
- SELECT m.*, s.name, s.city FROM metrics m JOIN stores s ON s.id = m.store_id
- WHERE m.period=? AND m.granularity=?
- ORDER BY m.store_id, m.date
- """, (period, g)).fetchall()
- conn.close()
- grouped = {}
- for r in rows:
- grouped.setdefault(r["store_id"], []).append(dict(r))
- out = []
- for sid, items in grouped.items():
- latest = max(items, key=lambda x: (x["date"] or ""))
- total = {k: 0 for k in ("visit", "intend_deal", "used_coupons", "used_amount",
- "deal", "deal_refund", "videos", "video_views", "reviews_new",
- "bad_new", "reviews_total", "bad_total", "favs", "lit")}
- for it in items:
- for k in total:
- total[k] += (it.get(k) or 0)
- score = None
- rank_note = ""
- for it in sorted(items, key=lambda x: x["date"] or ""):
- if it.get("score") is not None:
- score = it["score"] # 取最近一次有值(含 0 分未开分)的评分
- v = (it.get("rank_note") or "").strip()
- if v and v not in ("-", "无"):
- rank_note = v # 取最近一次有内容的上榜信息
- # 核销率分母 = 门店页成交券数(2026-11-01 用户确定口径)
- hx_rate = rules.diff_rate(total["used_coupons"], total["deal"])
- cp_rate, cp_src, _cp_small = rules.bad_rate(
- total["reviews_new"], total["bad_new"], total["reviews_total"], total["bad_total"])
- out.append({
- "id": sid,
- "name": latest["name"],
- "city": latest["city"] or "",
- "visit": total["visit"],
- "deal": total["deal"],
- "deal_refund": total["deal_refund"],
- "intend_deal": total["intend_deal"],
- "used_coupons": total["used_coupons"],
- "used_amount": round(total["used_amount"], 2),
- "score": score,
- "hx_rate": hx_rate,
- "cp_rate": cp_rate,
- "cp_src": cp_src,
- # 评价明细:差评率口径与样本量判定需要原始计数
- "reviews_new": total["reviews_new"],
- "bad_new": total["bad_new"],
- "reviews_total": total["reviews_total"],
- "bad_total": total["bad_total"],
- "lit": total["lit"],
- "rank_note": rank_note,
- "return_rate": _weighted(items, "deal", "return_rate"),
- "complaint_rate": _weighted(items, "deal", "complaint_rate"),
- "reply_rate": _weighted(items, "reviews_new", "reply_rate"),
- "videos": total["videos"],
- "video_views": total["video_views"],
- "favs": total["favs"],
- "days": (_days_between(items[0].get("window_start") or "",
- items[0].get("window_end") or "")
- if g == "snapshot"
- else len({it["date"] for it in items if it["date"]})),
- "window_start": items[0].get("window_start") or "",
- "window_end": items[0].get("window_end") or "",
- })
- return out
- def upsert_store(conn, sid, name, city, today):
- cur = conn.execute("SELECT id FROM stores WHERE id=?", (sid,))
- if cur.fetchone():
- conn.execute("UPDATE stores SET name=?, city=?, last_seen=? WHERE id=?",
- (name, city, today, sid))
- return False
- conn.execute("INSERT INTO stores(id, name, city, first_seen, last_seen) VALUES (?,?,?,?,?)",
- (sid, name, city, today, today))
- return True
- def insert_metric(conn, row, batch_id):
- cols = ", ".join(METRIC_FIELDS)
- qs = ", ".join(["?"] * len(METRIC_FIELDS))
- vals = [row.get(k) for k in METRIC_FIELDS]
- conn.execute(
- "INSERT OR REPLACE INTO metrics(store_id, period, date, granularity, window_start, window_end, "
- "%s, batch_id) VALUES (?,?,?,?,?,?,%s,?)" % (cols, qs),
- [row["store_id"], row["period"], row.get("date", ""), row["granularity"],
- row.get("window_start", ""), row.get("window_end", "")] + vals + [batch_id])
- def record_batch(conn, info):
- cur = conn.execute(
- "INSERT INTO batches(filename, rows_read, rows_written, new_stores, period, date_from, date_to, "
- "created_at, note, file_path) VALUES (?,?,?,?,?,?,?,?,?,?)",
- (info.get("filename"), info.get("rows_read"), info.get("rows_written"),
- info.get("new_stores"), info.get("period"), info.get("date_from"),
- info.get("date_to"), datetime.now().isoformat(timespec="seconds"), info.get("note"),
- info.get("file_path")))
- return cur.lastrowid
- # ---------------------------------------------------------------- 账号
- def user_count():
- conn = connect()
- n = conn.execute("SELECT COUNT(*) FROM users").fetchone()[0]
- conn.close()
- return n
- def get_user_by_name(username):
- conn = connect()
- r = conn.execute("SELECT * FROM users WHERE username=?", (username,)).fetchone()
- conn.close()
- return dict(r) if r else None
- def get_user(uid):
- conn = connect()
- r = conn.execute("SELECT * FROM users WHERE id=?", (uid,)).fetchone()
- conn.close()
- return dict(r) if r else None
- def list_users():
- conn = connect()
- rows = [dict(r) for r in conn.execute(
- "SELECT id, username, role, display_name, active, must_change, created_at, last_login "
- "FROM users ORDER BY CASE role WHEN 'admin' THEN 0 WHEN 'editor' THEN 1 ELSE 2 END, id")]
- conn.close()
- return rows
- def create_user(username, password, role, display_name=""):
- import auth
- h, salt = auth.hash_password(password)
- conn = connect()
- try:
- cur = conn.execute(
- "INSERT INTO users(username, pass_hash, salt, role, display_name, active, must_change, created_at) "
- "VALUES (?,?,?,?,?,1,0,?)",
- (username, h, salt, role, display_name or username,
- datetime.now().isoformat(timespec="seconds")))
- conn.commit()
- return cur.lastrowid
- finally:
- conn.close()
- def update_user(uid, role=None, display_name=None, active=None):
- sets, vals = [], []
- if role is not None:
- sets.append("role=?"); vals.append(role)
- if display_name is not None:
- sets.append("display_name=?"); vals.append(display_name)
- if active is not None:
- sets.append("active=?"); vals.append(1 if active else 0)
- if not sets:
- return
- vals.append(uid)
- conn = connect()
- conn.execute("UPDATE users SET %s WHERE id=?" % ",".join(sets), vals)
- conn.commit()
- conn.close()
- def set_password(uid, password, must_change=0):
- import auth
- h, salt = auth.hash_password(password)
- conn = connect()
- conn.execute("UPDATE users SET pass_hash=?, salt=?, must_change=? WHERE id=?",
- (h, salt, 1 if must_change else 0, uid))
- conn.commit()
- conn.close()
- def delete_user(uid):
- conn = connect()
- conn.execute("DELETE FROM sessions WHERE user_id=?", (uid,))
- conn.execute("DELETE FROM users WHERE id=?", (uid,))
- conn.commit()
- conn.close()
- def admin_count():
- conn = connect()
- n = conn.execute("SELECT COUNT(*) FROM users WHERE role='admin' AND active=1").fetchone()[0]
- conn.close()
- return n
- def touch_login(uid):
- conn = connect()
- conn.execute("UPDATE users SET last_login=? WHERE id=?",
- (datetime.now().isoformat(timespec="seconds"), uid))
- conn.commit()
- conn.close()
- # ---------------------------------------------------------------- 会话
- def create_session(token_hash, user_id, expires_at, ip=""):
- conn = connect()
- conn.execute("DELETE FROM sessions WHERE expires_at < ?",
- (datetime.now().isoformat(timespec="seconds"),))
- conn.execute("INSERT INTO sessions(token_hash, user_id, created_at, expires_at, ip) VALUES (?,?,?,?,?)",
- (token_hash, user_id, datetime.now().isoformat(timespec="seconds"), expires_at, ip))
- conn.commit()
- conn.close()
- def get_session(token_hash):
- """返回 (user_dict, expires_at) 或 (None, None)"""
- conn = connect()
- r = conn.execute("SELECT * FROM sessions WHERE token_hash=?", (token_hash,)).fetchone()
- if not r:
- conn.close()
- return None, None
- if (r["expires_at"] or "") < datetime.now().isoformat(timespec="seconds"):
- conn.execute("DELETE FROM sessions WHERE token_hash=?", (token_hash,))
- conn.commit()
- conn.close()
- return None, None
- u = conn.execute("SELECT * FROM users WHERE id=?", (r["user_id"],)).fetchone()
- conn.close()
- if not u or not u["active"]:
- return None, None
- return dict(u), r["expires_at"]
- def delete_session(token_hash):
- conn = connect()
- conn.execute("DELETE FROM sessions WHERE token_hash=?", (token_hash,))
- conn.commit()
- conn.close()
- def delete_user_sessions(uid):
- conn = connect()
- conn.execute("DELETE FROM sessions WHERE user_id=?", (uid,))
- conn.commit()
- conn.close()
- def get_batch(batch_id):
- conn = connect()
- r = conn.execute("SELECT * FROM batches WHERE id=?", (batch_id,)).fetchone()
- conn.close()
- return dict(r) if r else None
- def latest_batch_with_file(period=None):
- """找某个周期(或全局最新)里带原始文件的批次"""
- conn = connect()
- sql = ("SELECT * FROM batches WHERE file_path IS NOT NULL AND file_path<>''")
- args = []
- if period:
- sql += " AND period=?"
- args.append(period)
- sql += " ORDER BY id DESC LIMIT 1"
- r = conn.execute(sql, args).fetchone()
- if not r and period:
- r = conn.execute("SELECT * FROM batches WHERE file_path IS NOT NULL AND file_path<>'' "
- "ORDER BY id DESC LIMIT 1").fetchone()
- conn.close()
- return dict(r) if r else None
- def import_history(limit=20):
- conn = connect()
- rows = conn.execute("SELECT * FROM batches ORDER BY id DESC LIMIT ?", (limit,)).fetchall()
- conn.close()
- return [dict(r) for r in rows]
- def stats():
- conn = connect()
- n_stores = conn.execute("SELECT COUNT(*) c FROM stores").fetchone()["c"]
- n_metrics = conn.execute("SELECT COUNT(*) c FROM metrics").fetchone()["c"]
- n_batches = conn.execute("SELECT COUNT(*) c FROM batches").fetchone()["c"]
- conn.close()
- return {"stores": n_stores, "metrics": n_metrics, "batches": n_batches}
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