IQ.Pilot Release Commit @ 83fbdd3

iqpilot/selfdrive/car/card.py

@@ -270,10 +270,14 @@ class Car:
     return tuple(attr for attr in ("gasfactor", "windfactor") if hasattr(self.CI.CC, attr))
 
   def _stored_learned_factors(self) -> dict:
-    try:
+    # JSON-typed params come back already parsed from params_pyx; only the pure-python fallback
-      stored = json.loads(self.params.get("IQLongLearnedFactors") or b"{}")
+    # returns raw bytes
-    except ValueError:
+    stored = self.params.get("IQLongLearnedFactors")
-      stored = {}
+    if isinstance(stored, bytes | str):
+      try:
+        stored = json.loads(stored)
+      except ValueError:
+        stored = None
     return stored if isinstance(stored, dict) else {}
 
   def _seed_learned_factors(self):
@@ -292,14 +296,19 @@ class Car:
       return
     stored = self._stored_learned_factors()
     stored[str(self.CP.carFingerprint)] = {attr: float(getattr(self.CI.CC, attr)) for attr in attrs}
-    self.params.put_nonblocking("IQLongLearnedFactors", json.dumps(stored))
+    # JSON-typed params take the dict itself; params_pyx serializes and rejects pre-dumped strings
+    self.params.put_nonblocking("IQLongLearnedFactors", stored)
 
   def state_publish(self, CS: car.CarState, CS_IQ: custom.IQCarState, RD: structs.RadarDataT | None):
     """carState and carParams publish loop"""
 
-    # persist live-learned longitudinal factors so they survive across drives
+    # persist live-learned longitudinal factors so they survive across drives; card authors the
+    # car's CAN stream, so a persistence failure must never take it down mid-drive
     if self.sm.frame > 0 and self.sm.frame % int(60. / DT_CTRL) == 0:
-      self._save_learned_factors()
+      try:
+        self._save_learned_factors()
+      except Exception:
+        cloudlog.exception("failed to persist learned longitudinal factors")
 
     # carParams - logged every 50 seconds (> 1 per segment)
     if self.sm.frame % int(50. / DT_CTRL) == 0:

iqpilot/selfdrive/car/tests/test_learned_factor_persistence.py

@@ -55,7 +55,7 @@ class TestLearnedFactorPersistence:
 
     other.CI.CC.gasfactor = 0.5
     other._save_learned_factors()
-    stored = json.loads(other.params.values["IQLongLearnedFactors"])
+    stored = other.params.values["IQLongLearnedFactors"]
     assert stored["HONDA_CRV_6G"]["gasfactor"] == 2.0
     assert stored["HONDA_CIVIC_BOSCH"]["gasfactor"] == 0.5
 
@@ -80,3 +80,40 @@ class TestLearnedFactorPersistence:
     car._seed_learned_factors()
     car._save_learned_factors()
     assert "IQLongLearnedFactors" not in car.params.values
+
+
+class TestLearnedFactorRealParams:
+  """Round-trips through the actual params store so the pyx JSON type marshaling is exercised:
+  JSON params take dicts on put and come back parsed on get."""
+
+  def make_real_car(self, tmp_path, controller):
+    from iqpilot.common.params import Params
+    car = object.__new__(Car)
+    car.params = Params(str(tmp_path))
+    car.CI = SimpleNamespace(CC=controller)
+    car.CP = SimpleNamespace(carFingerprint="HONDA_CIVIC_2022")
+    return car
+
+  def test_save_then_seed_through_real_params(self, tmp_path):
+    import time
+    car = self.make_real_car(tmp_path, HondaLikeController())
+    car.CI.CC.gasfactor = 1.31
+    car.CI.CC.windfactor = 0.88
+    car._save_learned_factors()
+    time.sleep(0.3)
+
+    fresh = self.make_real_car(tmp_path, HondaLikeController())
+    fresh._seed_learned_factors()
+    assert fresh.CI.CC.gasfactor == 1.31
+    assert fresh.CI.CC.windfactor == 0.88
+
+  def test_repeated_saves_through_real_params(self, tmp_path):
+    import time
+    car = self.make_real_car(tmp_path, HondaLikeController())
+    for value in (1.1, 1.2, 1.3):
+      car.CI.CC.gasfactor = value
+      car._save_learned_factors()
+      time.sleep(0.3)
+    fresh = self.make_real_car(tmp_path, HondaLikeController())
+    fresh._seed_learned_factors()
+    assert fresh.CI.CC.gasfactor == 1.3