justin
f3f0bf2a77
Vehicle data is now DATA, not code. PIDs/scaling/DTCs/presets live in profiles/*.json; the app loads them at runtime, so it works across vehicles and others can contribute profiles (open source). Core: - obdcore/formula.py: safe AST evaluator for scaling formulas (A/B/... byte vars, Torque/FORScan convention). Only arithmetic/bitwise + min/max/abs/ round/int/float; names/attrs/arbitrary calls rejected at load -> a community profile CANNOT execute code. - obdcore/profile.py: load/save/list profiles; compiles each formula into a decode callable. registry.py now profile-backed (PidRegistry/DtcDatabase take a Profile); hardcoded Ford table removed. - store.py: clear()/snapshot()/export_csv() for capture management. Profiles: - profiles/ford-6.0-powerstroke.json (27 PIDs, verified formulas, DTCs) - profiles/generic-obd2.json (standard SAE Mode-01 base, any vehicle) - profiles/README.md (schema + formula language + contributing) GUI: - Menu bar: File (new/record/export/replay capture, quit), Profile (switch/ load/import/reload/edit-JSON/export, live profile list), View (Graph/Table views, gauges P2, toggle PID dock, normalize, light/dark theme), Help (about/confidence legend/profile info). - PID browser + presets rebuild on profile switch; added Table view; raw-JSON profile editor dialog (validates schema+formulas before saving). Tests: profiles load+compile, formula sandbox rejects hostile input, decoders still match real truck bytes, crank/derived/dead-PID/replay -- all pass. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016yT89n4zR4qbrySoSiEyZs
73 lines
2.2 KiB
Python
73 lines
2.2 KiB
Python
"""PID + DTC data model and registry, backed by a vehicle Profile.
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The actual PID numbers, scaling formulas, and DTC meanings live in JSON
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vehicle profiles under profiles/ (data, not code) so the app is vehicle-
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agnostic and others can contribute profiles. This module is the in-memory
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model + lookups; profile.py loads/saves the JSON.
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"""
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from dataclasses import dataclass, field
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from typing import Callable, Tuple
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@dataclass
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class Pid:
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key: str
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name: str
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mode: str = "22" # "01" | "22" | "atrv" | "derived"
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pid: str = "" # hex: "1446" (m22) or "0C" (m01)
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nbytes: int = 2
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formula: str = "" # scaling expr in A/B/... (raw) or dep keys (derived)
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decode: Callable = None # built from formula by profile loader
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unit: str = ""
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group: str = "misc" # fuel | ficm | air | engine | driveline | power | misc
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vmin: float = 0.0
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vmax: float = 100.0
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confidence: str = "verified" # verified | doc | tentative
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round: int = None # display rounding (None=raw float, 0=int)
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deps: Tuple[str, ...] = ()
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notes: str = ""
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@dataclass
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class Dtc:
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code: str
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desc: str
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system: str = "powertrain"
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no_start: bool = False
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causes: str = ""
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class PidRegistry:
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"""In-memory PID set + presets for the active vehicle profile."""
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def __init__(self, profile):
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self.profile = profile
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self._by_key = {p.key: p for p in profile.pids}
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self.presets = dict(profile.presets)
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def get(self, key):
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return self._by_key.get(key)
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def all(self):
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return list(self._by_key.values())
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def group(self, g):
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return [p for p in self._by_key.values() if p.group == g]
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def preset(self, name):
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return [self._by_key[k] for k in self.presets.get(name, []) if k in self._by_key]
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def preset_names(self):
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return list(self.presets.keys())
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class DtcDatabase:
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def __init__(self, profile):
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self._db = {d.code: d for d in profile.dtcs}
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def get(self, code):
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return self._db.get(code) or Dtc(code, "(unknown - look up this code)")
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def all(self):
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return list(self._db.values())
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