Store dates when predictions were madeHEADmaster

2 files changed, 6 insertions, 2 deletions

diff --git a/waterspout_radar/_radar.py b/waterspout_radar/_radar.py
index 380c70b..336edd5 100644
--- a/waterspout_radar/_radar.py
+++ b/waterspout_radar/_radar.py
@@ -16,6 +16,7 @@ _L = point_forecast.Level
 @dataclasses.dataclass
 class Prediction:
 	time: datetime.datetime
+	made: datetime.datetime
 	latitude: float
 	longitude: float
 	temperature_difference: pint.Quantity
@@ -27,6 +28,7 @@ class Prediction:
 	def json(self):
 		return {
 			"time": self.time.isoformat(),
+			"made": self.made.isoformat(),
 			"latitude": self.latitude,
 			"longitude": self.longitude,
 			"dt": self.temperature_difference.m_as("kelvin"),
@@ -40,6 +42,7 @@ class Prediction:
 	def from_json(cls, json):
 		return cls(
 			datetime.datetime.fromisoformat(json["time"]),
+			datetime.datetime.fromisoformat(json["made"]),
 			json["latitude"],
 			json["longitude"],
 			json["dt"] * metunits.units.kelvin,
@@ -53,6 +56,7 @@ class Prediction:
 def calculate(config) -> typing.List[Prediction]:
 	units = metunits.units
 	windy = Windy(units)
+	now = datetime.datetime.now()
 
 	def _calculate(latitude, longitude):
 		forecasts = windy.point_forecast(
@@ -79,7 +83,7 @@ def calculate(config) -> typing.List[Prediction]:
 			wind = [cast.at("wind_u", _L.H850), cast.at("wind_v", _L.H850)]
 			wind = np.array([x.m_as("kts") for x in wind])
 			wind = np.linalg.norm(wind) * units.kts
-			yield Prediction(cast.timestamp, latitude, longitude, dt, ccd, wind, clouds, swi)
+			yield Prediction(cast.timestamp, now, latitude, longitude, dt, ccd, wind, clouds, swi)
 
 	predictions = []
 	locator = geocoders.Nominatim(user_agent="waterspout-radar")
diff --git a/waterspout_radar/web.py b/waterspout_radar/web.py
index f43d2c0..332c533 100644
--- a/waterspout_radar/web.py
+++ b/waterspout_radar/web.py
@@ -8,5 +8,5 @@ config = _config.load(_config.effective_pathname())
 
 @app.route("/")
 def predictions():
-	predictions = sorted(_storage.Storage(config.db), key=lambda x: (x.time, x.swi))
+	predictions = sorted(_storage.Storage(config.db), key=lambda x: (x.time, x.made))
 	return flask.render_template("predictions.html", predictions=predictions)