471 lines
21 KiB
Python
471 lines
21 KiB
Python
# ruff: noqa: E501 - compact SQL fixtures intentionally mirror the legacy schema.
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from __future__ import annotations
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import base64
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import hashlib
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import json
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import sqlite3
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from cryptography.fernet import Fernet
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from backend.features.market.events import apply_event_revisions
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from backend.features.screener.catalog import strategy_by_id
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from backend.security.passwords import PasswordHasher
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from tools.legacy_migration import LegacyMigrator
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def _legacy_database(path, key: str) -> None:
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salt = b"0123456789abcdef"
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digest = hashlib.scrypt(
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b"Password123", salt=salt, n=2**14, r=8, p=1, dklen=32
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)
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encoded_salt = base64.urlsafe_b64encode(salt).decode()
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encoded_hash = base64.urlsafe_b64encode(digest).decode()
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fernet = Fernet(key.encode())
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credentials = {
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"tushare_token": "secret-tushare",
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"ifind_refresh_token": "secret-refresh",
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"member_daily_limit": 61,
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"llm_models": [{
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"id": "main", "name": "Primary", "base_url": "https://model.invalid/v1",
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"model": "model-a", "api_key": "secret-model",
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}],
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"primary_model_id": "main",
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}
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with sqlite3.connect(path) as connection:
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connection.executescript(
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"""
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CREATE TABLE users (id INTEGER PRIMARY KEY,username TEXT,password_salt TEXT,
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password_hash TEXT,created_at TEXT,updated_at TEXT,role TEXT,llm_mode TEXT,
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membership_status TEXT,membership_plan TEXT,membership_starts_at TEXT,
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membership_expires_at TEXT);
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CREATE TABLE user_birth_profiles
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(user_id INTEGER PRIMARY KEY,encrypted_payload TEXT,updated_at TEXT);
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CREATE TABLE llm_usage (id INTEGER PRIMARY KEY,user_id INTEGER,feature TEXT,
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source TEXT,model TEXT,status TEXT,latency_ms INTEGER,created_at TEXT,
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role TEXT,prompt_version TEXT,error_code TEXT,input_tokens INTEGER,output_tokens INTEGER);
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CREATE TABLE system_settings
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(setting_key TEXT PRIMARY KEY,encrypted_payload TEXT,updated_at TEXT);
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CREATE TABLE stock_master (ts_code TEXT PRIMARY KEY,code TEXT,name TEXT,
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industry TEXT,market TEXT,list_date TEXT,updated_at TEXT);
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CREATE TABLE daily_bars (trade_date TEXT,ts_code TEXT,open REAL,high REAL,
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low REAL,close REAL,pct_chg REAL,vol REAL,amount REAL);
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CREATE TABLE dashboard_snapshots
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(trade_date TEXT PRIMARY KEY,source TEXT,payload TEXT,record_count INTEGER,updated_at TEXT);
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CREATE TABLE watchlist (user_id INTEGER,code TEXT,name TEXT,sector TEXT,color TEXT,
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created_at TEXT,updated_at TEXT,remark TEXT);
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CREATE TABLE review_notes (id INTEGER PRIMARY KEY,code TEXT,stock_name TEXT,
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trade_date TEXT,content TEXT,plan TEXT,created_at TEXT,updated_at TEXT,
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user_id INTEGER,summary TEXT);
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CREATE TABLE trade_entries (id INTEGER PRIMARY KEY,user_id INTEGER,trade_date TEXT,
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code TEXT,name TEXT,action TEXT,price REAL,quantity INTEGER,position_pct REAL,
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pnl_amount REAL,pnl_pct REAL,thesis TEXT,execution TEXT,emotion TEXT,tags TEXT,
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created_at TEXT,updated_at TEXT);
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CREATE TABLE alerts (id INTEGER PRIMARY KEY,user_id INTEGER,kind TEXT,title TEXT,
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content TEXT,available_date TEXT,code TEXT,dedupe_key TEXT,is_read INTEGER,
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created_at TEXT,updated_at TEXT,read_at TEXT);
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CREATE TABLE assistant_messages (id INTEGER PRIMARY KEY,user_id INTEGER,role TEXT,
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content TEXT,context_date TEXT,created_at TEXT);
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CREATE TABLE mentor_preferences (user_id INTEGER,mentor_id TEXT,pinned INTEGER,
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sort_order INTEGER,updated_at TEXT);
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CREATE TABLE mentor_messages (id INTEGER PRIMARY KEY,user_id INTEGER,mentor_id TEXT,
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trade_date TEXT,role TEXT,content TEXT,meta TEXT,created_at TEXT);
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CREATE TABLE heaven_readings (id INTEGER PRIMARY KEY,user_id INTEGER,mode TEXT,
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context_date TEXT,subject TEXT,subject_detail TEXT,answer TEXT,
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context_snapshot TEXT,dedupe_key TEXT,created_at TEXT);
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CREATE TABLE screener_runs (id INTEGER PRIMARY KEY,trade_date TEXT,regime TEXT,
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strategy_name TEXT,formula TEXT,result TEXT,created_at TEXT,user_id INTEGER,mode TEXT);
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CREATE TABLE screener_strategies (id INTEGER PRIMARY KEY,name TEXT,description TEXT,
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regimes TEXT,formula TEXT,builtin INTEGER,created_at TEXT,updated_at TEXT,user_id INTEGER);
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CREATE TABLE strategy_tracks (id INTEGER PRIMARY KEY,user_id INTEGER,run_id INTEGER,
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selection_date TEXT,strategy_name TEXT,ts_code TEXT,code TEXT,name TEXT,sector TEXT,
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entry_price REAL,created_at TEXT,updated_at TEXT);
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CREATE TABLE data_snapshots (kind TEXT,cache_key TEXT,source TEXT,payload TEXT,
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updated_at TEXT,PRIMARY KEY(kind,cache_key));
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CREATE TABLE reason_overrides (trade_date TEXT,code TEXT,reason TEXT,
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updated_at TEXT,PRIMARY KEY(trade_date,code));
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CREATE TABLE seat_aliases (seat_name TEXT PRIMARY KEY,alias TEXT,updated_at TEXT);
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"""
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)
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now = "2026-07-29T16:00:00+08:00"
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connection.execute(
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"INSERT INTO users VALUES (8,'leefer',?,?,?,?,'admin','auto','active','永久',?,NULL)",
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(encoded_salt, encoded_hash, now, now, now),
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)
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profile = fernet.encrypt(
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b'{"birth_datetime":"1990-03-08T08:30:00","gender":"male"}'
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).decode()
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connection.execute("INSERT INTO user_birth_profiles VALUES (8,?,?)", (profile, now))
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connection.execute(
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"INSERT INTO llm_usage VALUES (1,8,'mentor','model','','success',3,?,'','','',0,0)",
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(now,),
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)
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encrypted = fernet.encrypt(json.dumps(credentials).encode()).decode()
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connection.execute("INSERT INTO system_settings VALUES ('credentials',?,?)", (encrypted, now))
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connection.execute(
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"INSERT INTO stock_master VALUES ('000001.SZ','000001','平安银行','银行','主板','19910403',?)",
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(now,),
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)
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connection.execute(
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"INSERT INTO daily_bars VALUES ('20260729','000001.SZ',10,11,9,10.5,5,100,1000)"
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)
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dashboard = json.dumps(
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{
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"meta": {
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"requested_date": "2026-07-30",
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"trade_date": "2026-07-29",
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"previous_trade_date": "2026-07-28",
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},
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"overview": {
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"up_count": 1,
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"down_count": 0,
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"flat_count": 0,
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"limit_up_count": 1,
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"limit_down_count": 0,
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"broken_count": 0,
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"amount_billion": 12.5,
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"seal_rate": 100,
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"sentiment_score": 64,
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"sentiment_label": "情绪偏强",
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"sentiment_phase": "修复",
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"sentiment_direction": "升温",
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"sentiment_components": {
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"breadth": {"label": "市场宽度", "score": 100, "weight": 20}
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},
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"sentiment_engine_version": 2,
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},
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"limits": [
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{
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"ts_code": "000001.SZ",
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"code": "000001",
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"name": "Ping An Bank",
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"reason": "legacy",
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"amount_billion": 1.25,
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"seal_amount_million": 20,
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}
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],
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"broken": [],
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"down_limits": [],
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}
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)
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connection.execute(
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"INSERT INTO dashboard_snapshots VALUES ('20260730','tushare',?,1,?)",
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(dashboard, now),
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)
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connection.execute(
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"INSERT INTO watchlist VALUES (8,'000001','平安银行','银行','red',?,?, '长期')",
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(now, now),
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)
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connection.execute(
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"INSERT INTO review_notes VALUES (1,'000001','平安银行','20260729','复盘','计划',?,?,8,'总结')",
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(now, now),
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)
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connection.execute(
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"INSERT INTO trade_entries VALUES (1,8,'20260729','000001','平安银行','buy',10,100,20,NULL,NULL,'逻辑','执行','calm','[]',?,?)",
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(now, now),
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)
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connection.execute(
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"INSERT INTO alerts VALUES (1,8,'manual','提醒','','20260730','','a',0,?,?,NULL)",
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(now, now),
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)
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connection.execute("INSERT INTO assistant_messages VALUES (1,8,'user','问题','20260729',?)", (now,))
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connection.execute("INSERT INTO mentor_preferences VALUES (8,'mentor',1,1,?)", (now,))
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connection.execute(
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"INSERT INTO mentor_messages VALUES (1,8,'mentor','20260729','user','问题','',?)", (now,)
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)
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connection.execute(
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"INSERT INTO heaven_readings VALUES (1,8,'fortune','20260729','','','结果','{}','d',?)", (now,)
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)
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result = json.dumps({"candidates": [{"identifier": "000001.SZ", "close": 10.5}]})
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connection.execute(
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"INSERT INTO screener_runs VALUES (1,'20260729','','策略','{}',?, ?,8,'curated')",
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(result, now),
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)
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connection.execute(
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"INSERT INTO screener_runs VALUES (2,'20260729','','退潮防守观察','{}',?, ?,8,'smart')",
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(result, now),
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)
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connection.execute(
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"INSERT INTO screener_runs VALUES (3,'20260729','','退潮防守观察','{}',?, ?,NULL,'smart')",
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(result, now),
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)
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multi_factor = strategy_by_id("curated-25")
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assert multi_factor is not None
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connection.execute(
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"INSERT INTO screener_runs VALUES (4,'20260729','','多因子综合打分(IC动态加权)',?, ?, ?,NULL,'curated')",
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(json.dumps(multi_factor["formula"]), result, now),
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)
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connection.execute(
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"INSERT INTO screener_strategies VALUES (1,'自定义','','[]','{}',0,?,?,8)",
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(now, now),
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)
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connection.execute(
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"INSERT INTO screener_strategies VALUES (2,'legacy builtin','','[]','{}',1,?,?,NULL)",
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(now, now),
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)
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connection.execute(
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"INSERT INTO strategy_tracks VALUES (1,8,1,'20260729','策略','000001.SZ','000001','平安银行','银行',10.5,?,?)",
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(now, now),
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)
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connection.execute(
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"INSERT INTO strategy_tracks VALUES (2,8,2,'20260729','退潮防守观察','000001.SZ','000001','平安银行','银行',10.5,?,?)",
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(now, now),
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)
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connection.execute(
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"INSERT INTO data_snapshots VALUES ('popularity_v1','20260729','legacy','{}',?)", (now,)
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)
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connection.execute(
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"INSERT INTO reason_overrides VALUES ('20260729','000001','admin reason',?)",
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(now,),
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)
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connection.execute(
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"INSERT INTO seat_aliases VALUES ('seat-a','trader-a',?)", (now,)
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)
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snapshots = {
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"ifind_event_enrichment_v1": (
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"20260729",
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{
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"trade_date": "20260729",
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"generated_at": now,
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"limits": {
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"000001": {
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"reason": "ifind reason",
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"first_time": "09:31:03",
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"last_time": "14:52:01",
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"open_times": 1,
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}
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},
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"broken": {},
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"down_limits": {},
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},
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),
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"rotation_sector_members_v1": (
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"20260729:Bank",
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{
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"meta": {"sector_code": "801780.SI"},
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"rows": [
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{
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"ts_code": "000001.SZ",
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"code": "000001",
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"name": "Ping An Bank",
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"quoted": True,
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}
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],
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},
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),
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"theme_directory_v1": (
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"ths",
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{"items": [{"ts_code": "885001.TI", "name": "Theme A"}]},
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),
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"theme_library_v1": (
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"20260729",
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{
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"meta": {"updated_at": now},
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"summary": {"theme_count": 1},
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"items": [{"code": "885001.TI", "name": "Theme A"}],
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},
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),
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"theme_detail_v1": (
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"20260729:885001.TI",
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{
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"meta": {"updated_at": now},
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"theme": {"code": "885001.TI", "name": "Theme A"},
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"series": [
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{
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"trade_date": "20260728",
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"open": 10,
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"high": 11,
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"low": 9,
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"close": 10,
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"volume": 100,
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},
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{
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"trade_date": "20260729",
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"open": 10,
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"high": 12,
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"low": 10,
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"close": 11,
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"volume": 120,
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},
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],
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"members": [
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{
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"ts_code": "000001.SZ",
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"code": "000001",
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"name": "Ping An Bank",
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"price": 10.5,
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"change": 5,
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"amount_billion": 1.2,
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"has_quote": True,
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}
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],
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"summary": {"member_count": 1},
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},
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),
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"hot_money_profiles_v1": (
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"directory",
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{
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"profiles": [
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{
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"name": "trader-a",
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"description": "profile",
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"organizations": ["seat-a"],
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}
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]
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},
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),
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"dragon_tiger": (
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"20260729",
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{
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"meta": {"updated_at": now},
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"rows": [
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{
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"ts_code": "000001.SZ",
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"name": "Ping An Bank",
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"change": 5,
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"reason": "listed",
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"institutions": [
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{
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"seat_name": "seat-a",
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"buy_million": 2,
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"sell_million": 1,
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"net_buy_million": 1,
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}
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],
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}
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],
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},
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),
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"hot_money_detail_v3": (
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"20260729",
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{
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"meta": {"updated_at": now},
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"traders": [
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{
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"name": "trader-a",
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"operations": [
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{
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"ts_code": "000001.SZ",
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"name": "Ping An Bank",
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"change": 5,
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"seat_name": "seat-a",
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"buy_million": 2,
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"sell_million": 1,
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"net_buy_million": 1,
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"reason": "listed",
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}
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],
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}
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],
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},
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),
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}
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connection.executemany(
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"INSERT INTO data_snapshots VALUES (?,?, 'legacy',?,?)",
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[
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(kind, cache_key, json.dumps(payload), now)
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for kind, (cache_key, payload) in snapshots.items()
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],
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)
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def test_legacy_migration_is_idempotent_and_preserves_login(tmp_path) -> None:
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source = tmp_path / "legacy.db"
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target = tmp_path / "next.db"
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key = Fernet.generate_key().decode()
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_legacy_database(source, key)
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first = LegacyMigrator(source, target, key).run()
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second = LegacyMigrator(source, target, key).run()
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assert first["integrity"] == second["integrity"] == "ok"
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assert first["unmapped_tables"] == []
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assert first["unmapped_snapshot_kinds"] == []
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assert first["source_tables"]["reason_overrides"] == 1
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assert first["intentionally_skipped_rows"]["screener_strategies_builtin"]["count"] == 1
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assert "market_event_revisions" in first["target_counts"]
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rendered = json.dumps(first)
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assert "secret-tushare" not in rendered
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assert "secret-model" not in rendered
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with sqlite3.connect(target) as connection:
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connection.row_factory = sqlite3.Row
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password = connection.execute("SELECT password_hash FROM users WHERE id=8").fetchone()[0]
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assert PasswordHasher().verify("Password123", password)
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assert connection.execute("SELECT count(*) FROM watchlist_entries").fetchone()[0] == 1
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profile_payload = json.loads(
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Fernet(key.encode()).decrypt(
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connection.execute(
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"SELECT encrypted_payload FROM birth_profiles WHERE user_id=8"
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).fetchone()[0].encode()
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)
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)
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assert profile_payload == {
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"birth_date": "1990-03-08",
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"birth_time": "08:30",
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"gender": "male",
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}
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assert connection.execute("SELECT count(*) FROM screener_runs").fetchone()[0] == 3
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stage_run = connection.execute(
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"""SELECT id,owner_user_id,strategy_id,strategy_version FROM screener_runs
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WHERE mode='stage'"""
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).fetchone()
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assert dict(stage_run) == {
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"id": 3,
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"owner_user_id": None,
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"strategy_id": "stage-06",
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"strategy_version": 1,
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}
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renamed = connection.execute(
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"""SELECT strategy_id,strategy_name FROM screener_runs
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WHERE strategy_id='curated-25'"""
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).fetchone()
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assert dict(renamed) == {
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"strategy_id": "curated-25",
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"strategy_name": "动态多因子（基础版）",
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}
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assert connection.execute("SELECT count(*) FROM strategy_tracks").fetchone()[0] == 2
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assert connection.execute(
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"SELECT run_id FROM strategy_tracks WHERE id=2"
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).fetchone()[0] == 3
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assert connection.execute("SELECT daily_llm_limit FROM memberships").fetchone()[0] == 61
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assert connection.execute("SELECT count(*) FROM seat_aliases").fetchone()[0] == 1
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assert connection.execute(
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"SELECT count(*) FROM sector_member_snapshots"
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).fetchone()[0] == 1
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assert connection.execute(
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"SELECT count(*) FROM chart_series WHERE entity_type='theme'"
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).fetchone()[0] == 1
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summary = json.loads(
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connection.execute(
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"SELECT payload_json FROM market_summaries WHERE trade_date='2026-07-29'"
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).fetchone()[0]
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)
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assert summary["limits"][0]["identifier"] == "000001.SZ"
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assert summary["trade_date"] == "2026-07-29"
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assert summary["overview"]["limit_up"] == 1
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assert summary["overview"]["amount"] == 1_250_000_000
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assert summary["limits"][0]["amount"] == 125_000_000
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assert summary["limits"][0]["seal_amount"] == 20_000_000
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assert summary["sentiment"]["score"] == 64
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assert summary["sentiment"]["phase"] == "修复"
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assert summary["sentiment"]["components"][0]["key"] == "breadth"
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all_revisions = tuple(
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connection.execute(
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"""SELECT * FROM market_event_revisions WHERE trade_date='2026-07-29'
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ORDER BY priority DESC,id DESC"""
|
|
).fetchall()
|
|
)
|
|
assert len(all_revisions) == 2
|
|
revisions = all_revisions[:1]
|
|
revised = apply_event_revisions(summary, revisions)
|
|
assert revised["limits"][0]["reason"] == "admin reason"
|
|
raw_dragon = json.loads(
|
|
connection.execute(
|
|
"""SELECT payload_json FROM market_insight_snapshots
|
|
WHERE kind='dragon-list' AND trade_date='2026-07-29'"""
|
|
).fetchone()[0]
|
|
)
|
|
assert raw_dragon["profiles"][0]["desc"] == "profile"
|
|
assert raw_dragon["official"][0]["hm_name"] == "trader-a"
|