import dataclasses
from decimal import Decimal
import datetime
import logging
from collections.abc import Iterator, Mapping

from frozendict import frozendict

from personal_data.data import DeduplicateMode, Scraper

from .. import secrets

logger = logging.getLogger(__name__)

HA_ROOT = secrets.HOME_ASSISTANT_ROOT
HA_LLAK= secrets.HOME_ASSISTANT_LLAK

@dataclasses.dataclass(frozen=True)
class HomeAssistantScaleWeight(Scraper):
    dataset_name = 'health_weight'
    deduplicate_mode = DeduplicateMode.BY_ALL_COLUMNS
    deduplicate_ignore_columns = []

    def scrape(self) -> Iterator[Mapping[str, object]]:
        headers = {
                'Authorization': 'Bearer '+HA_LLAK,
                'Content-Type': 'application/json',
        }
        end_time = datetime.datetime.now()
        start_time = end_time - datetime.timedelta(days = 90)
        url = '{}/api/history/period/{}'.format(HA_ROOT, start_time)
        print(url)
        params = {
                'filter_entity_id': 'sensor.bathroom_scale_mass',
                'end_time': end_time,
        }
        response = self.session.get(url, params = params, headers = headers)
        response.raise_for_status()

        data = response.json()

        state_range_for_consideration = (Decimal(30), Decimal(300))

        for d in data[0]:
            if d['state'] == 'unavailable':
                continue
            state = Decimal(d['state'])
            if state_range_for_consideration[0] <= state <= state_range_for_consideration[1]:
                yield {
                        'weight.sample_time': datetime.datetime.fromisoformat(d['last_updated']),
                        'weight.kg': state,
                }