d95e5102c6
Bug: a .set file saved out of MT5's "save settings" button (rather than "save optimization") contains bare \`Inp...=value\` lines with no \`|min|max|step\` metadata. The parser previously marked every such param as type="fixed", and /api/ea_params filters fixed params out, so the user saw "No optimizable parameters found in .set file" and could not start a run with that EA. Reproduces with LEGSTECH_EA_V4 in this user's setup. Fix: - SetParser.parse() now takes an auto_infer_ranges flag (default True). When a line has no '|' separator, the parser falls back to a heuristic range based on the param's name + value: * `*Pips`, `*Period`, `*Lookback`, `*Spread`, `*Trades` → integer ±50% / ±150% * `*Percent`, `*Pct`, `*Risk`, `*Buffer`, `*Multiplier`, `*Ratio` → float ±50% / ×2 * `RRRatio` → 0.5–2.5x with 0.25 step * `Score` → 0.5–1.5x with 0.05 step * `Lot*` → ±50% with 0.01 step * `Hour*` / `Session*` → 0–23 * Pure 0/1 with `Use*`/`Enable*`/`Allow*` prefix → bool * `true`/`false` literals → bool * Generic numeric fallback → ±50% with type-appropriate step - Added timeframe enum names (htf/mtf/ltf/_tf/timeframe) and debug/log flags to _FORCE_FIXED_PATTERNS so MT5 internal constants like InpHTF=16388 don't get incorrectly inferred as scalars. Verified on LEGSTECH_EA_V4 (raw saved-settings format): 64/71 params now optimizable (was 0); regression-checked LEGSTECH_EA_V2 still returns 42 params from its existing optimization metadata.
407 lines
15 KiB
Python
407 lines
15 KiB
Python
"""
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ea/set_parser.py
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Parse any MT5 .set file into a ParameterSchema.
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Handles both .set formats:
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value|min|max|step (single pipe — most common)
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value||min||max||step||Y/N (double pipe — some MT5 builds)
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Fixed detection:
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min == max → type="fixed" (e.g. InpMagicNumber=202402|202402|202402|1)
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min == 0 AND max == 0 → type="fixed" (zeroed range = "don't optimize")
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No range at all → type="fixed"
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Type detection (non-fixed only):
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min==0, max==1, step==1 → bool
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"." in step string → float
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max - min <= 8, step==1 → enum (small discrete integer set)
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otherwise → int
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"""
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from __future__ import annotations
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import re
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from pathlib import Path
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from typing import Any, Optional
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from loguru import logger
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from ea.schema import ParameterDef, ParameterSchema
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# ── Tester section keys to skip (not EA inputs) ───────────────────────────────
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_TESTER_KEYS = {
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"expert", "symbol", "period", "optimization", "model",
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"fromdate", "todate", "forwardmode", "report", "replacereport",
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"shutdownterminal", "deposit", "currency", "leverage",
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"optimizationmode", "forwarddate", "optimizationiterations",
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}
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# EA params that should always be fixed even if they have a range
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# Includes magic numbers, debug/UI flags, and MT5 timeframe enum constants
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# (HTF/MTF/LTF values like 16388 are PERIOD_H1/etc — not optimizable scalars).
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_FORCE_FIXED_PATTERNS = [
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"testermode", "testeri", "testerinit", "showpanel",
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"magicnumber", "magic",
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"htf", "mtf", "ltf", # higher/medium/lower timeframe enums
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"_tf", "timeframe",
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"comment", "label", "prefix",
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"verbose", "debug", "log",
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]
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class SetParser:
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"""
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Parses a MT5 .set file into a ParameterSchema.
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Usage:
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parser = SetParser()
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schema = parser.parse(
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path=Path("C:/MT5 Set files/LEGSTECH_EA_V2.set"),
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ea_name="LEGSTECH_EA_V2",
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default_optimize=False, # user chooses via UI
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)
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"""
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def parse(
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self,
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path: Path,
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ea_name: str,
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default_optimize: bool = False,
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force_optimize: Optional[set[str]] = None,
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force_fixed: Optional[set[str]] = None,
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auto_infer_ranges: bool = True,
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) -> ParameterSchema:
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"""
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Parse a .set file and return a ParameterSchema.
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Args:
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path: Path to the .set file.
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ea_name: Display name for the EA.
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default_optimize: Whether to mark all optimizable params as optimize=True by default.
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If False (default), the user selects via UI.
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force_optimize: Set of param names that are always optimize=True regardless.
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force_fixed: Set of param names that are always type="fixed".
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"""
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force_optimize = force_optimize or set()
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force_fixed = force_fixed or set()
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path = Path(path)
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if not path.exists():
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raise FileNotFoundError(f".set file not found: {path}")
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try:
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text = path.read_text(encoding="utf-16")
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except UnicodeError:
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text = path.read_text(encoding="utf-8", errors="replace")
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parameters: dict[str, ParameterDef] = {}
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current_section = ""
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for raw_line in text.splitlines():
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line = raw_line.strip()
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if not line or line.startswith(";"):
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continue
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# Section header
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if line.startswith("[") and line.endswith("]"):
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current_section = line[1:-1].lower()
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continue
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# Skip lines without "="
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if "=" not in line:
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continue
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name, _, rest = line.partition("=")
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name = name.strip()
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rest = rest.strip()
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# Skip tester-section metadata keys
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if name.lower() in _TESTER_KEYS:
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continue
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# Parse the value + optional range
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param = self._parse_param(name, rest)
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if param is None:
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logger.debug(f"SetParser: skipped unrecognised line: {line!r}")
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continue
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# If the file had no optimization metadata (just `Name=value`),
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# heuristically infer a reasonable range so the user can still
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# optimize. Triggered for raw MT5 "saved settings" .set files.
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if auto_infer_ranges and param.type == "fixed" and "|" not in rest:
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inferred = self._infer_range_from_value(name, rest)
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if inferred is not None:
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param = inferred
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# Apply force-fixed overrides
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if name in force_fixed or self._is_force_fixed(name):
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param.type = "fixed"
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param.optimize = False
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elif name in force_optimize:
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param.optimize = True
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elif default_optimize and param.type != "fixed":
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param.optimize = True
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parameters[name] = param
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if not parameters:
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raise ValueError(f"No EA input parameters found in .set file: {path}")
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schema = ParameterSchema(ea_name=ea_name, source_set=path, parameters=parameters)
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logger.info(f"SetParser: parsed {schema.summary()} from {path.name}")
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return schema
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# ── Internal ─────────────────────────────────────────────────────────────
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def _parse_param(self, name: str, rest: str) -> Optional[ParameterDef]:
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"""
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Parse a single parameter line.
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rest is everything after the first "=" on the line.
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"""
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# Normalise: double-pipe "||" → single "|"
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rest = re.sub(r"\|\|", "|", rest)
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# Strip trailing Y/N optimize flag if present
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yn_match = re.search(r"\|([YN])$", rest, re.IGNORECASE)
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if yn_match:
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rest = rest[:yn_match.start()]
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parts = [p.strip() for p in rest.split("|")]
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if len(parts) == 1:
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# No range info → fixed
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value = self._cast_value(parts[0])
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return ParameterDef(
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name=name, default=value, type="fixed",
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min=None, max=None, step=None, optimize=False,
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)
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if len(parts) < 4:
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# Incomplete range — treat as fixed
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value = self._cast_value(parts[0])
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return ParameterDef(
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name=name, default=value, type="fixed",
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min=None, max=None, step=None, optimize=False,
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)
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raw_val, raw_min, raw_max, raw_step = parts[0], parts[1], parts[2], parts[3]
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try:
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default_f = float(raw_val)
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min_f = float(raw_min)
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max_f = float(raw_max)
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step_f = float(raw_step)
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except ValueError:
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value = self._cast_value(raw_val)
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return ParameterDef(
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name=name, default=value, type="fixed",
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min=None, max=None, step=None, optimize=False,
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)
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# Fixed detection
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is_fixed = (
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abs(min_f - max_f) < 1e-9 # min == max
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or (abs(min_f) < 1e-9 and abs(max_f) < 1e-9) # both zero (zeroed range)
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)
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if is_fixed:
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return ParameterDef(
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name=name,
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default=self._typed_default(raw_val, raw_step),
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type="fixed",
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min=min_f, max=max_f, step=step_f,
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optimize=False,
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)
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# Type detection
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ptype = self._detect_type(min_f, max_f, step_f, raw_step, raw_val)
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default = self._typed_cast(ptype, default_f, raw_val)
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return ParameterDef(
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name=name,
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default=default,
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type=ptype,
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min=min_f,
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max=max_f,
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step=step_f,
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optimize=False, # user sets this via UI; can be overridden by caller
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)
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@staticmethod
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def _detect_type(min_f: float, max_f: float, step_f: float,
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raw_step: str, raw_val: str) -> str:
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"""Infer parameter type from its range."""
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# Bool: exactly 0–1 with step 1
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if abs(min_f) < 1e-9 and abs(max_f - 1.0) < 1e-9 and abs(step_f - 1.0) < 1e-9:
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return "bool"
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# Float: step has decimal component
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if "." in raw_step and not raw_step.endswith(".0") and float(raw_step) % 1 != 0:
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return "float"
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# Also float if default value has meaningful decimal
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if "." in raw_val and float(raw_val) % 1 != 0:
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return "float"
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# Enum: small integer set (≤ 8 distinct values, step 1)
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n_values = int(round((max_f - min_f) / step_f)) + 1 if step_f > 0 else 1
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if abs(step_f - 1.0) < 1e-9 and n_values <= 8:
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return "enum"
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return "int"
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@staticmethod
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def _typed_cast(ptype: str, value_f: float, raw: str) -> Any:
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if ptype == "bool":
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return value_f != 0 or raw.lower() in ("true", "1")
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if ptype == "int":
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return int(round(value_f))
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if ptype == "enum":
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return int(round(value_f))
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return value_f # float
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@staticmethod
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def _typed_default(raw: str, raw_step: str) -> Any:
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"""Cast a fixed-param value without range context."""
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lower = raw.lower()
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if lower in ("true", "false"):
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return lower == "true"
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try:
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f = float(raw)
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# Return int if it's a whole number and step is integer-like
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if "." not in raw_step or raw_step.endswith(".0"):
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if f == int(f):
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return int(f)
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return f
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except ValueError:
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return raw
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@staticmethod
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def _cast_value(raw: str) -> Any:
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lower = raw.lower()
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if lower in ("true", "false"):
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return lower == "true"
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try:
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f = float(raw)
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return int(f) if f == int(f) and "." not in raw else f
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except ValueError:
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return raw
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@staticmethod
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def _is_force_fixed(name: str) -> bool:
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"""Return True for params that are always fixed regardless of their range."""
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lower = name.lower()
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return any(pat in lower for pat in _FORCE_FIXED_PATTERNS)
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# ── Range inference for "saved settings" .set files ──────────────────────
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def _infer_range_from_value(self, name: str, raw: str) -> Optional[ParameterDef]:
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"""
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Heuristic range inference for .set files that contain bare `Name=value`
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lines (no `|min|max|step` metadata). Common with files saved out of MT5
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directly rather than exported as an optimization preset.
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Returns None to leave the param as fixed (e.g. magic numbers, strings).
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"""
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lower = name.lower()
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# Force-fixed by name pattern → keep fixed
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if self._is_force_fixed(name):
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return None
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# Bool: explicit true/false, or value 0/1 + name implies a toggle
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if raw.lower() in ("true", "false"):
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default_b = raw.lower() == "true"
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return ParameterDef(
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name=name, type="bool", default=default_b,
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min=0.0, max=1.0, step=1.0, optimize=False,
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)
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try:
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v = float(raw)
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except ValueError:
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return None # non-numeric (e.g. enum string) → leave fixed
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is_int_value = ("." not in raw) and v == int(v)
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toggle_names = ("use", "enable", "allow", "show", "is_", "include", "with")
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looks_toggle = any(lower.startswith(p) for p in toggle_names) and v in (0, 1)
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if looks_toggle:
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return ParameterDef(
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name=name, type="bool", default=bool(int(v)),
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min=0.0, max=1.0, step=1.0, optimize=False,
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)
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if v == 0:
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# Can't ±% a zero meaningfully — give a small fixed nudge
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if is_int_value:
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return ParameterDef(name=name, type="int", default=0,
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min=0.0, max=10.0, step=1.0, optimize=False)
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return ParameterDef(name=name, type="float", default=0.0,
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min=0.0, max=1.0, step=0.05, optimize=False)
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# Pattern-based ranges by name suffix / keyword
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# (lower-bound, upper-bound multipliers, step, force_int)
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patterns = [
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("pips", 0.5, 2.0, None, True),
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("period", 0.5, 2.0, 1.0, True),
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("lookback", 0.5, 2.0, 1.0, True),
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("multiplier", 0.5, 2.0, None, False),
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("ratio", 0.5, 2.0, None, False),
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("rrratio", 0.5, 2.5, 0.25, False),
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("percent", 0.5, 2.0, None, False),
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("pct", 0.5, 2.0, None, False),
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("risk", 0.5, 2.0, None, False),
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("buffer", 0.5, 2.0, None, False),
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("threshold", 0.5, 2.0, None, False),
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("score", 0.5, 1.5, 0.05, False),
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("size", 0.5, 2.0, None, False),
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("lot", 0.5, 2.0, 0.01, False),
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("spread", 0.5, 2.0, 1.0, True),
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("trades", 0.5, 2.5, 1.0, True),
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("hour", 0.0, 23.0, 1.0, True),
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("session", 0.0, 23.0, 1.0, True),
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]
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match = None
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for kw, *_ in patterns:
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if kw in lower:
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match = next(p for p in patterns if p[0] == kw)
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break
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if match:
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_, lo_mul, hi_mul, step_override, force_int = match
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lo = abs(v) * lo_mul
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hi = abs(v) * hi_mul
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if v < 0:
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lo, hi = -hi, -lo
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# Special-case hour ranges (absolute, not %-of-value)
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if match[0] in ("hour", "session"):
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lo, hi = 0.0, 23.0
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else:
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# Generic fallback: ±50% of value
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lo = abs(v) * 0.5
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hi = abs(v) * 2.0
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if v < 0:
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lo, hi = -hi, -lo
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step_override = None
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force_int = is_int_value
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# Choose step
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if step_override is not None:
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step = step_override
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elif force_int:
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span = hi - lo
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step = max(1.0, round(span / 10.0))
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else:
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span = hi - lo
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step = round(span / 10.0, 4)
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if step <= 0:
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step = 0.01
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ptype = "int" if force_int else "float"
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default = int(round(v)) if force_int else v
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return ParameterDef(
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name=name, type=ptype, default=default,
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min=round(lo, 4), max=round(hi, 4), step=step,
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optimize=False,
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)
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