LEGSTECH Optimizer
7a3e13a734
Full optimization system for LEGSTECH_EA_V2: - Flask + SocketIO live dashboard (dark premium UI) - MT5 process control (auto-kill, clean launch, retry) - HTML report parser (UTF-16 LE, 597 trades, metrics) - Pre-run validation and actionable error messages - Analysis engines: Reversal, TimePerfomance, EntryExit, EquityCurve - Composite scoring (Calmar-primary) - Mutation engine with knowledge_base.yaml - Validation gate: IS + Walk-Forward - Reports folder with HTML/CSV per run - Double-click launcher batch file
339 lines
13 KiB
Python
339 lines
13 KiB
Python
"""
|
|
mt5/report_parser.py
|
|
Parses the MT5 strategy tester HTML report (production format: pure HTML tables).
|
|
Extracts RunMetrics and paired in/out deal trades.
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import re
|
|
from datetime import datetime
|
|
from pathlib import Path
|
|
from typing import Optional
|
|
|
|
from lxml import html as lhtml
|
|
from loguru import logger
|
|
|
|
from data.models import RunMetrics, Trade
|
|
|
|
|
|
# ── Helpers ───────────────────────────────────────────────────────────────────
|
|
|
|
def _clean(s: str) -> str:
|
|
"""Remove HTML entity remnants, spaces, currency symbols."""
|
|
if not s:
|
|
return ""
|
|
# MT5 uses non-breaking spaces (0xa0) and regular spaces
|
|
s = s.replace("\xa0", "").replace(",", "").replace(" ", "").strip()
|
|
return s
|
|
|
|
|
|
def _parse_float(s: str) -> float:
|
|
s = _clean(s)
|
|
# Remove everything except digits, dot, minus
|
|
s = re.sub(r"[^\d.\-]", "", s)
|
|
try:
|
|
return float(s)
|
|
except (ValueError, TypeError):
|
|
return 0.0
|
|
|
|
|
|
def _parse_int(s: str) -> int:
|
|
s = _clean(s)
|
|
s = re.sub(r"[^\d\-]", "", s.split("(")[0])
|
|
try:
|
|
return int(s)
|
|
except (ValueError, TypeError):
|
|
return 0
|
|
|
|
|
|
def _parse_dt(s: str) -> Optional[datetime]:
|
|
s = (s or "").strip()
|
|
for fmt in ("%Y.%m.%d %H:%M:%S", "%Y.%m.%d %H:%M", "%Y.%m.%d"):
|
|
try:
|
|
return datetime.strptime(s, fmt)
|
|
except ValueError:
|
|
continue
|
|
return None
|
|
|
|
|
|
def _cell_text(td) -> str:
|
|
"""Get all inner text from an lxml element, stripping tags."""
|
|
return "".join(td.itertext()).strip()
|
|
|
|
|
|
# ── Main Parser ───────────────────────────────────────────────────────────────
|
|
|
|
class ReportParser:
|
|
"""
|
|
Parses the MT5 HTML strategy tester report.
|
|
|
|
Report format (confirmed from live MT5 output):
|
|
- Summary metrics: <td>Label:</td><td><b>Value</b></td> pairs
|
|
- Deals table: Time | Deal | Symbol | Type | Direction | Volume |
|
|
Price | Order | Commission | Swap | Profit | Balance | Comment
|
|
Direction='in' → position open (entry deal)
|
|
Direction='out' → position close (exit deal, has Profit value)
|
|
"""
|
|
|
|
def parse(
|
|
self, xml_path: Optional[str], html_path: Optional[str]
|
|
) -> tuple[Optional[RunMetrics], list[Trade]]:
|
|
"""
|
|
Parse the MT5 HTML report. xml_path is ignored (MT5 command-line
|
|
runs produce .htm, not .xml). Falls back gracefully if html is missing.
|
|
"""
|
|
path = None
|
|
if html_path and Path(html_path).exists():
|
|
path = Path(html_path)
|
|
elif xml_path and Path(xml_path).exists():
|
|
path = Path(xml_path)
|
|
|
|
if path is None:
|
|
logger.error("No report file available to parse.")
|
|
return None, []
|
|
|
|
logger.debug(f"Parsing report: {path}")
|
|
try:
|
|
raw = path.read_bytes()
|
|
# MT5 HTML reports are UTF-16 LE (BOM: ff fe) — detect and decode
|
|
if raw[:2] == b'\xff\xfe':
|
|
# Pass raw bytes; lxml's HTML parser handles UTF-16 correctly
|
|
tree = lhtml.document_fromstring(raw)
|
|
else:
|
|
# Regular UTF-8 or latin-1
|
|
try:
|
|
content = raw.decode("utf-8")
|
|
except UnicodeDecodeError:
|
|
content = raw.decode("windows-1252", errors="replace")
|
|
tree = lhtml.document_fromstring(content.encode("utf-8"))
|
|
except Exception as e:
|
|
logger.error(f"Failed to parse HTML: {e}")
|
|
return None, []
|
|
|
|
summary = self._extract_summary(tree)
|
|
deals = self._extract_deals(tree)
|
|
trades = self._pair_deals(deals)
|
|
|
|
if not summary:
|
|
logger.warning("No summary data found in MT5 HTML report.")
|
|
return None, trades
|
|
|
|
metrics = self._build_metrics(summary)
|
|
logger.info(f"Parsed: {metrics.total_trades} trades, PF={metrics.profit_factor:.3f}")
|
|
return metrics, trades
|
|
|
|
# ── Summary ───────────────────────────────────────────────────────────────
|
|
|
|
def _extract_summary(self, tree) -> dict[str, str]:
|
|
"""
|
|
Extract label→value pairs from the stats tables.
|
|
MT5 pattern: <td ...>Label:</td> <td ...><b>Value</b></td>
|
|
The label and value are adjacent siblings in the same <tr>.
|
|
"""
|
|
result: dict[str, str] = {}
|
|
for tr in tree.iter("tr"):
|
|
tds = list(tr.findall(".//td"))
|
|
if len(tds) < 2:
|
|
continue
|
|
for i in range(len(tds) - 1):
|
|
label = _cell_text(tds[i]).rstrip(":")
|
|
val = _cell_text(tds[i + 1])
|
|
if label and val and len(label) < 60:
|
|
result[label] = val
|
|
logger.debug(f"Summary fields: {len(result)}")
|
|
return result
|
|
|
|
# ── Deals ─────────────────────────────────────────────────────────────────
|
|
|
|
def _extract_deals(self, tree) -> list[dict]:
|
|
"""
|
|
Find the Deals table and parse every row.
|
|
Columns: Time|Deal|Symbol|Type|Direction|Volume|Price|Order|Commission|Swap|Profit|Balance|Comment
|
|
"""
|
|
# Find the <th> that contains "Deals" text
|
|
deals_header = None
|
|
for th in tree.iter("th"):
|
|
if "Deals" in (_cell_text(th) or ""):
|
|
deals_header = th
|
|
break
|
|
|
|
if deals_header is None:
|
|
logger.warning("Deals table not found in report.")
|
|
return []
|
|
|
|
# Walk up to find the table element
|
|
table = deals_header
|
|
while table is not None and table.tag != "table":
|
|
table = table.getparent()
|
|
if table is None:
|
|
return []
|
|
|
|
rows = table.findall(".//tr")
|
|
# Skip header rows (first 2 rows: table title + column headers)
|
|
data_rows = []
|
|
header_seen = 0
|
|
for row in rows:
|
|
ths = row.findall(".//th")
|
|
tds = row.findall(".//td")
|
|
if ths:
|
|
header_seen += 1
|
|
continue
|
|
if not tds:
|
|
continue
|
|
data_rows.append(tds)
|
|
|
|
deals = []
|
|
for tds in data_rows:
|
|
texts = [_cell_text(td) for td in tds]
|
|
if len(texts) < 13:
|
|
continue
|
|
# Cols: 0=Time 1=Deal 2=Symbol 3=Type 4=Direction 5=Volume
|
|
# 6=Price 7=Order 8=Commission 9=Swap 10=Profit 11=Balance 12=Comment
|
|
deal_type = texts[3].lower()
|
|
if "balance" in deal_type or "credit" in deal_type:
|
|
continue # skip balance entries at start
|
|
|
|
deals.append({
|
|
"time": texts[0],
|
|
"deal": _parse_int(texts[1]),
|
|
"symbol": texts[2],
|
|
"type": deal_type, # buy / sell
|
|
"direction": texts[4].lower(), # in / out
|
|
"volume": _parse_float(texts[5]),
|
|
"price": _parse_float(texts[6]),
|
|
"order": _parse_int(texts[7]),
|
|
"commission": _parse_float(texts[8]),
|
|
"swap": _parse_float(texts[9]),
|
|
"profit": _parse_float(texts[10]),
|
|
"balance": _parse_float(texts[11]),
|
|
"comment": texts[12] if len(texts) > 12 else "",
|
|
})
|
|
|
|
logger.debug(f"Raw deals extracted: {len(deals)}")
|
|
return deals
|
|
|
|
# ── Pairing in→out ────────────────────────────────────────────────────────
|
|
|
|
def _pair_deals(self, deals: list[dict]) -> list[Trade]:
|
|
"""
|
|
Pair 'in' (open) and 'out' (close) deals to form complete trades.
|
|
MT5 reports alternate: in-deal → out-deal for each closed position.
|
|
"""
|
|
trades: list[Trade] = []
|
|
pending: Optional[dict] = None # the last 'in' deal
|
|
|
|
for d in deals:
|
|
if d["direction"] == "in":
|
|
pending = d
|
|
elif d["direction"] == "out" and pending is not None:
|
|
open_dt = _parse_dt(pending["time"])
|
|
close_dt = _parse_dt(d["time"])
|
|
if not open_dt or not close_dt:
|
|
pending = None
|
|
continue
|
|
|
|
direction = pending["type"] # buy / sell
|
|
open_price = pending["price"]
|
|
close_price = d["price"]
|
|
net_money = d["profit"]
|
|
lot_size = d["volume"]
|
|
commission = d["commission"] + pending["commission"]
|
|
swap = d["swap"] + pending["swap"]
|
|
duration_m = max(0, int((close_dt - open_dt).total_seconds() / 60))
|
|
|
|
# Net pips (XAUUSD: price moves in dollars, 1 pip = 0.1)
|
|
price_diff = (close_price - open_price) * (1 if direction == "buy" else -1)
|
|
net_pips = round(price_diff / 0.1, 2) if price_diff != 0 else 0.0
|
|
|
|
trades.append(Trade(
|
|
ticket = d["deal"],
|
|
open_time = open_dt,
|
|
close_time = close_dt,
|
|
direction = direction,
|
|
open_price = open_price,
|
|
close_price = close_price,
|
|
lot_size = lot_size,
|
|
net_pips = net_pips,
|
|
net_money = net_money,
|
|
duration_minutes = duration_m,
|
|
commission = commission,
|
|
swap = swap,
|
|
sl = 0.0, # not in deals table
|
|
tp = 0.0,
|
|
))
|
|
pending = None
|
|
# if direction is empty/"" skip it
|
|
|
|
logger.info(f"Paired {len(trades)} complete trades from deals.")
|
|
return trades
|
|
|
|
# ── Metrics ───────────────────────────────────────────────────────────────
|
|
|
|
def _build_metrics(self, raw: dict[str, str]) -> RunMetrics:
|
|
"""Build RunMetrics from the extracted label→value dictionary."""
|
|
|
|
def get(*keys) -> str:
|
|
for k in keys:
|
|
v = raw.get(k, "")
|
|
if v:
|
|
return v
|
|
return "0"
|
|
|
|
net_profit = _parse_float(get("Total Net Profit", "Net Profit", "Balance"))
|
|
gross_profit = _parse_float(get("Gross Profit"))
|
|
gross_loss = _parse_float(get("Gross Loss"))
|
|
profit_factor = _parse_float(get("Profit Factor"))
|
|
# Total Deals = number of deal rows; Total Trades = positions
|
|
total_trades = _parse_int(get("Total Trades", "Total Deals"))
|
|
win_trades = _parse_int(get("Profit Trades", "Profit Trades (% of total)",
|
|
"Profit Deals"))
|
|
|
|
# Drawdown: "2 160.22 (19.25%)"
|
|
dd_str = get("Equity Drawdown Maximal", "Equity Drawdown Relative",
|
|
"Balance Drawdown Maximal")
|
|
max_dd_abs = _parse_float(dd_str.split("(")[0])
|
|
pct_match = re.search(r"([\d.]+)%", dd_str)
|
|
max_dd_pct = float(pct_match.group(1)) / 100 if pct_match else 0.0
|
|
|
|
initial_dep = _parse_float(get("Initial Deposit", "Deposit"))
|
|
if initial_dep <= 0:
|
|
initial_dep = 10_000.0
|
|
|
|
sharpe = _parse_float(get("Sharpe Ratio", "Sharp Ratio"))
|
|
recovery_factor = _parse_float(get("Recovery Factor"))
|
|
expected_payoff = _parse_float(get("Expected Payoff"))
|
|
|
|
# Compute max_dd_pct if only absolute was found
|
|
if max_dd_pct == 0.0 and max_dd_abs > 0:
|
|
total_equity = initial_dep + net_profit
|
|
max_dd_pct = max_dd_abs / max(1, total_equity)
|
|
|
|
# Calmar = annualised return / max drawdown
|
|
# Use simple ratio since we don't know exact test duration
|
|
calmar = 0.0
|
|
if max_dd_pct > 0:
|
|
annual_return = net_profit / initial_dep
|
|
calmar = round(annual_return / max_dd_pct, 4)
|
|
|
|
win_rate = win_trades / total_trades if total_trades > 0 else 0.0
|
|
loss_trades = max(0, total_trades - win_trades)
|
|
avg_win = gross_profit / win_trades if win_trades > 0 else 0.0
|
|
avg_loss = gross_loss / loss_trades if loss_trades > 0 else 0.0
|
|
|
|
return RunMetrics(
|
|
run_id = "__placeholder__",
|
|
net_profit = net_profit,
|
|
profit_factor = profit_factor,
|
|
max_drawdown_abs= max_dd_abs,
|
|
max_drawdown_pct= max_dd_pct,
|
|
calmar_ratio = calmar,
|
|
sharpe_ratio = sharpe,
|
|
total_trades = total_trades,
|
|
win_rate = win_rate,
|
|
avg_win = avg_win,
|
|
avg_loss = avg_loss,
|
|
recovery_factor = recovery_factor,
|
|
largest_loss = _parse_float(get("Largest loss trade")),
|
|
expected_payoff = expected_payoff,
|
|
)
|