File size: 11,412 Bytes
680c684 31ad0ef 19a8231 31ad0ef 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 680c684 19a8231 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 | # TANZG 量价分析引擎 - 数据库模块
import json
import math
import os
import re
import sqlite3
from contextlib import contextmanager
# 默认仍使用本地 SQLite;配置 DATABASE_URL 或 PG* 环境变量后自动切换 PostgreSQL。
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
DB_PATH = os.getenv("SQLITE_PATH") or os.getenv("DB_PATH") or os.path.join(BASE_DIR, "history.db")
DATABASE_URL = os.getenv("DATABASE_URL") or os.getenv("POSTGRES_URL") or os.getenv("POSTGRES_DSN")
USE_POSTGRES = bool(
DATABASE_URL
or os.getenv("PGHOST")
or os.getenv("POSTGRES_HOST")
)
def _to_native(obj):
"""递归将 numpy / pandas 类型转换为 Python 原生类型,兼容 PostgreSQL 写入。"""
try:
import numpy as np
if isinstance(obj, np.floating):
val = float(obj)
return None if (math.isnan(val) or math.isinf(val)) else val
if isinstance(obj, np.integer):
return int(obj)
if isinstance(obj, np.bool_):
return bool(obj)
if isinstance(obj, np.ndarray):
return _to_native(obj.tolist())
except ImportError:
pass
try:
import pandas as pd
if obj is pd.NA:
return None
if hasattr(pd, "isna") and not isinstance(obj, (dict, list, tuple, str, bytes)):
try:
if pd.isna(obj):
return None
except Exception:
pass
except Exception:
pass
if isinstance(obj, dict):
return {k: _to_native(v) for k, v in obj.items()}
if isinstance(obj, (list, tuple)):
return [_to_native(x) for x in obj]
if isinstance(obj, float) and (math.isnan(obj) or math.isinf(obj)):
return None
return obj
def _pg_connect():
import psycopg2
if DATABASE_URL:
return psycopg2.connect(DATABASE_URL)
return psycopg2.connect(
host=os.getenv("PGHOST") or os.getenv("POSTGRES_HOST", "localhost"),
port=int(os.getenv("PGPORT") or os.getenv("POSTGRES_PORT", "5432")),
dbname=os.getenv("PGDATABASE") or os.getenv("POSTGRES_DB", "tanzg"),
user=os.getenv("PGUSER") or os.getenv("POSTGRES_USER", "postgres"),
password=os.getenv("PGPASSWORD") or os.getenv("POSTGRES_PASSWORD", ""),
)
@contextmanager
def _connect():
if USE_POSTGRES:
conn = _pg_connect()
else:
db_dir = os.path.dirname(DB_PATH)
if db_dir:
os.makedirs(db_dir, exist_ok=True)
conn = sqlite3.connect(DB_PATH)
conn.row_factory = sqlite3.Row
try:
yield conn
conn.commit()
finally:
conn.close()
def _convert_sql(sql):
"""将项目里 SQLite 风格 SQL 转为 PostgreSQL 兼容 SQL。"""
if not USE_POSTGRES:
return sql
converted = sql
converted = converted.replace("INTEGER PRIMARY KEY AUTOINCREMENT", "SERIAL PRIMARY KEY")
converted = converted.replace("?", "%s")
return converted
def _execute(conn, sql, params=None):
cur = conn.cursor()
cur.execute(_convert_sql(sql), tuple(_to_native(params or ())))
return cur
def _fetchall_dict(cur):
rows = cur.fetchall()
if not rows:
return []
if not USE_POSTGRES:
return [dict(r) for r in rows]
cols = [d[0] for d in cur.description]
return [dict(zip(cols, r)) for r in rows]
def _fetchone_dict(cur):
row = cur.fetchone()
if not row:
return None
if not USE_POSTGRES:
return dict(row)
cols = [d[0] for d in cur.description]
return dict(zip(cols, row))
def _insert_returning_id(conn, sql, params=None):
if USE_POSTGRES:
sql = sql.rstrip().rstrip(";") + " RETURNING id"
cur = _execute(conn, sql, params)
return cur.fetchone()[0]
cur = _execute(conn, sql, params)
return cur.lastrowid
def init_db():
with _connect() as conn:
_execute(conn, """
CREATE TABLE IF NOT EXISTS analysis_history (
id INTEGER PRIMARY KEY AUTOINCREMENT,
ts_code TEXT NOT NULL,
name TEXT,
created_at TEXT,
latest_close REAL,
pct_change REAL,
ma5 REAL,
ma10 REAL,
ma20 REAL,
boll_upper REAL,
boll_mid REAL,
boll_lower REAL,
boll_pct REAL,
vol_ratio REAL,
high_volume_days TEXT,
trigger_rules TEXT,
signal TEXT,
signal_emoji TEXT,
summary TEXT,
kline_10d TEXT,
raw_data TEXT
)
""")
def init_watchlist_db():
with _connect() as conn:
_execute(conn, """
CREATE TABLE IF NOT EXISTS watchlist (
id INTEGER PRIMARY KEY AUTOINCREMENT,
ts_code TEXT NOT NULL UNIQUE,
name TEXT,
position INTEGER DEFAULT 0,
created_at TEXT DEFAULT CURRENT_TIMESTAMP
)
""")
def init_recommendations_db():
with _connect() as conn:
_execute(conn, """
CREATE TABLE IF NOT EXISTS recommendations (
id INTEGER PRIMARY KEY AUTOINCREMENT,
created_at TEXT,
sentiment TEXT,
sentiment_label TEXT,
hot_sectors TEXT,
stocks TEXT,
raw_report TEXT
)
""")
def get_watchlist():
with _connect() as conn:
cur = _execute(conn, "SELECT id, ts_code, name, position FROM watchlist ORDER BY position ASC, id ASC")
return _fetchall_dict(cur)
def add_to_watchlist(ts_code, name):
with _connect() as conn:
cur = _execute(conn, "SELECT COALESCE(MAX(position), -1) + 1 FROM watchlist")
next_pos = cur.fetchone()[0]
_execute(conn, "INSERT INTO watchlist (ts_code, name, position) VALUES (?, ?, ?)", (ts_code, name, next_pos))
return True
def remove_from_watchlist(ts_code):
with _connect() as conn:
_execute(conn, "DELETE FROM watchlist WHERE ts_code = ?", (ts_code,))
return True
def update_watchlist_order(stocks):
with _connect() as conn:
_execute(conn, "DELETE FROM watchlist")
for idx, stock in enumerate(stocks):
_execute(conn, "INSERT INTO watchlist (ts_code, name, position) VALUES (?, ?, ?)", (stock['code'], stock.get('name', ''), idx))
return True
def move_watchlist_item(ts_code, direction):
with _connect() as conn:
cur = _execute(conn, "SELECT id, ts_code, position FROM watchlist ORDER BY position ASC")
items = _fetchall_dict(cur)
if not items:
return False, "关注列表为空"
target_idx = next((i for i, item in enumerate(items) if item['ts_code'] == ts_code), -1)
if target_idx == -1:
return False, "未找到该股票"
if direction == 'up':
if target_idx == 0:
return False, "已在最上方"
swap_idx = target_idx - 1
else:
if target_idx == len(items) - 1:
return False, "已在最下方"
swap_idx = target_idx + 1
items[target_idx], items[swap_idx] = items[swap_idx], items[target_idx]
for idx, item in enumerate(items):
_execute(conn, "UPDATE watchlist SET position = ? WHERE id = ?", (idx, item['id']))
return True, "移动成功"
def watchlist_exists(ts_code):
with _connect() as conn:
cur = _execute(conn, "SELECT COUNT(*) FROM watchlist WHERE ts_code = ?", (ts_code,))
return cur.fetchone()[0] > 0
def save_report(report: dict) -> int:
report = _to_native(report)
with _connect() as conn:
return _insert_returning_id(conn, """
INSERT INTO analysis_history
(ts_code, name, created_at, latest_close, pct_change,
ma5, ma10, ma20, boll_upper, boll_mid, boll_lower, boll_pct,
vol_ratio, high_volume_days, trigger_rules, signal, signal_emoji,
summary, kline_10d, raw_data)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""", (
report.get("ts_code"),
report.get("name"),
report.get("created_at"),
report.get("latest_close"),
report.get("pct_change"),
report.get("ma5"),
report.get("ma10"),
report.get("ma20"),
report.get("boll_upper"),
report.get("boll_mid"),
report.get("boll_lower"),
report.get("boll_pct"),
report.get("vol_ratio"),
json.dumps(_to_native(report.get("high_volume_days", [])), ensure_ascii=False),
json.dumps(_to_native(report.get("trigger_rules", {})), ensure_ascii=False),
report.get("signal"),
report.get("signal_emoji"),
report.get("summary"),
json.dumps(_to_native(report.get("kline_10d", [])), ensure_ascii=False),
json.dumps(_to_native(report.get("raw_data", [])), ensure_ascii=False),
))
def get_history(limit=50, ts_code=None, start_date=None, end_date=None):
with _connect() as conn:
where = []
params = []
if ts_code:
where.append("ts_code = ?")
params.append(ts_code)
if start_date:
where.append("created_at >= ?")
params.append(start_date)
if end_date:
where.append("created_at <= ?")
params.append(end_date)
sql = "SELECT * FROM analysis_history"
if where:
sql += " WHERE " + " AND ".join(where)
sql += " ORDER BY created_at DESC LIMIT ?"
params.append(int(limit))
cur = _execute(conn, sql, params)
return _fetchall_dict(cur)
def get_history_by_id(report_id: int):
with _connect() as conn:
cur = _execute(conn, "SELECT * FROM analysis_history WHERE id = ?", (report_id,))
return _fetchone_dict(cur)
def delete_history(report_id: int):
with _connect() as conn:
_execute(conn, "DELETE FROM analysis_history WHERE id = ?", (report_id,))
def save_recommendation(rec: dict) -> int:
rec = _to_native(rec)
with _connect() as conn:
return _insert_returning_id(conn, """
INSERT INTO recommendations
(created_at, sentiment, sentiment_label, hot_sectors, stocks, raw_report)
VALUES (?, ?, ?, ?, ?, ?)
""", (
rec.get("created_at"),
rec.get("sentiment", "中性"),
rec.get("sentiment_label", "中性"),
json.dumps(_to_native(rec.get("hot_sectors", [])), ensure_ascii=False),
json.dumps(_to_native(rec.get("stocks", [])), ensure_ascii=False),
rec.get("raw_report", ""),
))
def get_recommendation_history(limit=20):
with _connect() as conn:
cur = _execute(conn, "SELECT * FROM recommendations ORDER BY created_at DESC LIMIT ?", (int(limit),))
return _fetchall_dict(cur)
def get_recommendation_by_id(rid: int):
with _connect() as conn:
cur = _execute(conn, "SELECT * FROM recommendations WHERE id = ?", (rid,))
return _fetchone_dict(cur)
init_db()
init_recommendations_db()
init_watchlist_db()
|