53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
import dataclasses
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from decimal import Decimal
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import datetime
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import logging
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from collections.abc import Iterator, Mapping
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from frozendict import frozendict
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from personal_data.data import DeduplicateMode, Scraper
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from .. import secrets
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logger = logging.getLogger(__name__)
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HA_ROOT = secrets.HOME_ASSISTANT_ROOT
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HA_LLAK= secrets.HOME_ASSISTANT_LLAK
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@dataclasses.dataclass(frozen=True)
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class HomeAssistantScaleWeight(Scraper):
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dataset_name = 'health_weight'
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deduplicate_mode = DeduplicateMode.BY_ALL_COLUMNS
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deduplicate_ignore_columns = []
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def scrape(self) -> Iterator[Mapping[str, object]]:
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headers = {
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'Authorization': 'Bearer '+HA_LLAK,
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'Content-Type': 'application/json',
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}
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end_time = datetime.datetime.now()
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start_time = end_time - datetime.timedelta(days = 90)
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url = '{}/api/history/period/{}'.format(HA_ROOT, start_time)
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print(url)
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params = {
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'filter_entity_id': 'sensor.bathroom_scale_mass',
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'end_time': end_time,
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}
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response = self.session.get(url, params = params, headers = headers)
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response.raise_for_status()
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data = response.json()
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state_range_for_consideration = (Decimal(30), Decimal(300))
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for d in data[0]:
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if d['state'] == 'unavailable':
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continue
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state = Decimal(d['state'])
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if state_range_for_consideration[0] <= state <= state_range_for_consideration[1]:
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yield {
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'weight.sample_time': datetime.datetime.fromisoformat(d['last_updated']),
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'weight.kg': state,
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}
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