from influxdb_client import InfluxDBClient, Point, WritePrecision
from datetime import datetime
import datetime as dt
import pandas as pd

class DataBaseInflux:
    def __init__(self, url: str, token: str, org: str, bucket: str):
        self.url = url
        self.token = token
        self.org = org
        self.bucket = bucket
        self.client = InfluxDBClient(url=self.url, token=self.token, org=self.org)
        self.write_api = self.client.write_api()

    def store_data(self, device_name: str, data: dict):
        measurement = device_name # Fest auf "messungen" gesetzt

        point = Point(measurement)

        # Alle Key/Value-Paare als Fields speichern
        for key, value in data.items():
            point = point.field(key, value)

        # Zeitstempel automatisch auf jetzt setzen
        point = point.time(datetime.utcnow(), WritePrecision.NS)

        # Punkt in InfluxDB schreiben
        self.write_api.write(bucket=self.bucket, org=self.org, record=point)

    def store_forecasts(self, forecast_name: str, data: pd.Series):

        measurement = forecast_name
        run_tag = dt.datetime.now(dt.timezone.utc).replace(second=0, microsecond=0).isoformat(timespec="minutes")

        pts = []

        series = pd.to_numeric(data, errors="coerce").dropna()

        for ts, val in series.items():
            pts.append(
                Point(measurement)
                .tag("run", run_tag)
                .field("value", float(val))
                .time(ts.to_pydatetime(), WritePrecision.S)
            )

        self.write_api.write(bucket=self.bucket, org=self.org, record=pts)