def trains(self):
station_codes = [i.station_code for i in self.api.stations.all.values() if i == self]
if not self.api.timestamp:
data = self.api.get_json(build_url(Service.rail_predictions, "GetPrediction/%s" % ",".join(station_codes)), nocache=True)["Trains"]
return [MetrorailTrainPrediction(
self.api.lines[i["Line"]],
self.api.stations[i["DestinationCode"]],
self,
i["Min"],
i["Car"],
int(i["Group"])
) for i in data if (
i["DestinationCode"] is not None and
MetrorailLines._line_valid(i["Line"]) and
i["Car"] is not None
)]
else:
data = list(HistoricalTrainPosition.select().where(HistoricalTrainPosition.timestamp == self.api.timestamp, HistoricalTrainPosition.next_station << station_codes))
return [MetrorailTrainPrediction(
self.api.lines[prediction.line_code],
self.api.stations[prediction.dest_station],
self,
str(prediction.time),
str(prediction.cars),
prediction.trackgroup
) for prediction in data]
def all_trains(self):
if not self.api.timestamp:
data = self.api.get_json(build_url(Service.rail_predictions, "GetPrediction/All"), nocache=True)["Trains"]
result = {}
for prediction in data:
if prediction["LocationCode"] is None or prediction["DestinationCode"] is None or prediction["Car"] is None:
continue
if self.api.stations[prediction["LocationCode"]] not in result:
result[self.api.stations[prediction["LocationCode"]]] = []
result[self.api.stations[prediction["LocationCode"]]].append(
MetrorailTrainPrediction(
self.api.lines[prediction["Line"]],
self.api.stations[prediction["DestinationCode"]],
self.api.stations[prediction["LocationCode"]],
prediction["Min"],
prediction["Car"],
prediction["Group"]
)
)
all_stations = self.api.stations.all
for station in all_stations:
st = all_stations[station]
if st not in result:
result[st] = []
return result
else:
data = list(HistoricalTrainPosition.select().where(HistoricalTrainPosition.timestamp == self.api.timestamp))
predictions = [MetrorailTrainPrediction(
self.api.lines[prediction.line_code],
self.api.stations[prediction.dest_station],
self.api.stations[prediction.next_station],
str(prediction.time),
str(prediction.cars),
prediction.trackgroup
) for prediction in data]
d = {}
for p in predictions:
if p.station not in d: d[p.station] = []
d[p.station].append(p)
return d
from models import HistoricalTrainPosition
pos = list(HistoricalTrainPosition.select())
dels = []
for p in pos:
if p.timestamp.microsecond == 0:
dels.append(p.id)
print(HistoricalTrainPosition.delete().where(HistoricalTrainPosition.id << dels).execute())
