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Refactor code for improved readability and consistency

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- Cleaned up whitespace and formatting in various files including http.py, language.py, logger.py, safe_exec.py, and SQL migration scripts.
- Consolidated import statements and removed unnecessary blank lines.
- Updated logging configuration for better clarity.
- Enhanced the safe execution code with improved error handling and logging.
- Removed commented-out code and unnecessary variables in backfill_zero_trades.py and other scripts.
- Added a pyproject.toml for Ruff and Vulture configuration.
- Introduced requirements-dev.txt for development dependencies.
- Removed commented-out stock entries in init.sql for cleaner migration scripts.
This commit is contained in:
dienakdz
2026-04-09 14:30:51 +07:00
parent 103055b3df
commit 87f2845483
157 changed files with 19026 additions and 17773 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend_api_python/app/routes/dashboard.py
+50 -33
View File
@@ -13,13 +13,13 @@ from __future__ import annotations
import json
import time
from typing import Any, Dict, List, Tuple
from typing import Any, Dict, List
from flask import Blueprint, jsonify, request, g
from flask import Blueprint, g, jsonify, request
from app.utils.auth import login_required
from app.utils.db import get_db_connection
from app.utils.logger import get_logger
from app.utils.auth import login_required
logger = get_logger(__name__)
@@ -44,7 +44,7 @@ def _format_datetime(dt: Any) -> Any:
"""Convert datetime object to ISO format string for JSON serialization."""
if dt is None:
return None
if hasattr(dt, 'isoformat'):
if hasattr(dt, "isoformat"):
return dt.isoformat()
return dt
@@ -96,7 +96,9 @@ def _calc_unrealized_pnl(side: str, entry_price: float, current_price: float, si
return 0.0
def _calc_pnl_percent(entry_price: float, size: float, pnl: float, leverage: float = 1.0, market_type: str = "spot") -> float:
def _calc_pnl_percent(
entry_price: float, size: float, pnl: float, leverage: float = 1.0, market_type: str = "spot"
) -> float:
try:
denom = float(entry_price or 0.0) * float(size or 0.0)
if denom <= 0:
@@ -189,7 +191,7 @@ def _compute_performance_stats(trades: List[Dict[str, Any]], initial_capital: fl
# Calculate drawdown percentage: drawdown / peak_equity * 100
# If peak_equity is 0 or very small, use a fallback calculation
if peak_equity > 0:
max_drawdown_pct = (max_drawdown / peak_equity * 100)
max_drawdown_pct = max_drawdown / peak_equity * 100
elif initial_capital > 0:
# Fallback: use initial capital as baseline
max_drawdown_pct = (max_drawdown / initial_capital * 100) if initial_capital > 0 else 0.0
@@ -202,10 +204,10 @@ def _compute_performance_stats(trades: List[Dict[str, Any]], initial_capital: fl
cumulative.append(acc)
peak_profit = max(cumulative) if cumulative else 0.0
if peak_profit > 0:
max_drawdown_pct = (max_drawdown / peak_profit * 100)
max_drawdown_pct = max_drawdown / peak_profit * 100
else:
max_drawdown_pct = 0.0
# Cap drawdown percentage at reasonable maximum (e.g., 10000%) to avoid display issues
if max_drawdown_pct > 10000:
max_drawdown_pct = 10000.0
@@ -277,16 +279,18 @@ def _compute_strategy_stats(trades: List[Dict[str, Any]], strategies: List[Dict[
total_pnl = sum(_safe_float(t.get("profit"), 0.0) for t in strades)
roi = (total_pnl / capital * 100) if capital > 0 else 0.0
result.append({
"strategy_id": sid,
"strategy_name": sid_to_name.get(sid, f"Strategy_{sid}"),
"total_trades": stats["total_trades"],
"win_rate": stats["win_rate"],
"profit_factor": stats["profit_factor"],
"total_pnl": round(total_pnl, 2),
"roi": round(roi, 2),
"max_drawdown": stats["max_drawdown"],
})
result.append(
{
"strategy_id": sid,
"strategy_name": sid_to_name.get(sid, f"Strategy_{sid}"),
"total_trades": stats["total_trades"],
"win_rate": stats["win_rate"],
"profit_factor": stats["profit_factor"],
"total_pnl": round(total_pnl, 2),
"roi": round(roi, 2),
"max_drawdown": stats["max_drawdown"],
}
)
# Sort by total PnL descending
result.sort(key=lambda x: x.get("total_pnl", 0), reverse=True)
@@ -301,7 +305,7 @@ def summary():
"""
try:
user_id = g.user_id
# Strategy counts (filtered by user_id)
with get_db_connection() as db:
cur = db.cursor()
@@ -311,7 +315,7 @@ def summary():
FROM qd_strategies_trading
WHERE user_id = ?
""",
(user_id,)
(user_id,),
)
strategies = cur.fetchall() or []
cur.close()
@@ -347,7 +351,7 @@ def summary():
WHERE p.user_id = ?
ORDER BY p.updated_at DESC
""",
(user_id,)
(user_id,),
)
rows = cur.fetchall() or []
cur.close()
@@ -397,17 +401,17 @@ def summary():
ORDER BY t.created_at DESC
LIMIT 500
""",
(user_id,)
(user_id,),
)
recent_trades_raw = cur.fetchall() or []
cur.close()
# Convert datetime to timestamp for frontend compatibility
recent_trades = []
for t in recent_trades_raw:
trade = dict(t)
if trade.get('created_at') and hasattr(trade['created_at'], 'timestamp'):
trade['created_at'] = int(trade['created_at'].timestamp())
if trade.get("created_at") and hasattr(trade["created_at"], "timestamp"):
trade["created_at"] = int(trade["created_at"].timestamp())
recent_trades.append(trade)
# Total equity/pnl (best-effort) - calculate before performance stats for drawdown calculation
@@ -487,7 +491,7 @@ def summary():
# Calendar data: organized by month for monthly calendar view
# Format: { "2024-01": { "days": { "01": 123.45, "02": -50.0, ... }, "total": 500.0 }, ... }
import calendar as cal_module
from datetime import datetime, timedelta
from datetime import datetime
calendar_data: Dict[str, Dict[str, Any]] = {}
for d, p in day_to_profit.items():
@@ -524,10 +528,7 @@ def summary():
calendar_months = []
for month_key in sorted(calendar_data.keys(), reverse=True):
data = calendar_data[month_key]
calendar_months.append({
"month_key": month_key,
**data
})
calendar_months.append({"month_key": month_key, **data})
return jsonify(
{
@@ -612,16 +613,32 @@ def pending_orders():
# Frontend expects these keys:
# - filled_amount, filled_price, error_message
filled_amount = float(r.get("filled") or 0.0)
filled_price = float(r.get("avg_price") or 0.0) if float(r.get("avg_price") or 0.0) > 0 else float(r.get("price") or 0.0)
filled_price = (
float(r.get("avg_price") or 0.0)
if float(r.get("avg_price") or 0.0) > 0
else float(r.get("price") or 0.0)
)
# Derive exchange_id + notify channels without leaking secrets to frontend.
ex_cfg = _safe_json_loads(r.get("strategy_exchange_config"), {}) or {}
notify_cfg = _safe_json_loads(r.get("strategy_notification_config"), {}) or {}
exchange_id = (r.get("exchange_id") or ex_cfg.get("exchange_id") or ex_cfg.get("exchangeId") or "").strip().lower()
exchange_id = (
(r.get("exchange_id") or ex_cfg.get("exchange_id") or ex_cfg.get("exchangeId") or "").strip().lower()
)
notify_channels = _as_list((notify_cfg or {}).get("channels"))
if not notify_channels:
notify_channels = ["browser"]
market_type = (r.get("market_type") or r.get("strategy_market_type") or ex_cfg.get("market_type") or ex_cfg.get("marketType") or "").strip().lower()
market_type = (
(
r.get("market_type")
or r.get("strategy_market_type")
or ex_cfg.get("market_type")
or ex_cfg.get("marketType")
or ""
)
.strip()
.lower()
)
market_category = str(r.get("strategy_market_category") or "").strip().lower()
execution_mode = str(r.get("strategy_execution_mode") or r.get("execution_mode") or "").strip().lower()