258 lines
9.5 KiB
Python
258 lines
9.5 KiB
Python
"""
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[[https://bluemaestro.com/products/product-details/bluetooth-environmental-monitor-and-logger][Bluemaestro]] temperature/humidity/pressure monitor
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"""
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# todo most of it belongs to DAL... but considering so few people use it I didn't bother for now
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import re
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import sqlite3
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from abc import abstractmethod
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from dataclasses import dataclass
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from datetime import datetime, timedelta
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from pathlib import Path
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from typing import Iterable, Optional, Protocol, Sequence, Set
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import pytz
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from my.core import (
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Paths,
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Res,
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Stats,
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get_files,
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make_logger,
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stat,
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unwrap,
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)
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from my.core.cachew import mcachew
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from my.core.pandas import DataFrameT, as_dataframe
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from my.core.sqlite import sqlite_connect_immutable
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class config(Protocol):
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@property
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@abstractmethod
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def export_path(self) -> Paths:
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raise NotImplementedError
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@property
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def tz(self) -> pytz.BaseTzInfo:
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# fixme: later, rely on the timezone provider
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# NOTE: the timezone should be set with respect to the export date!!!
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return pytz.timezone('Europe/London')
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# TODO when I change tz, check the diff
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def make_config() -> config:
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from my.config import bluemaestro as user_config
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class combined_config(user_config, config): ...
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return combined_config()
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logger = make_logger(__name__)
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def inputs() -> Sequence[Path]:
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cfg = make_config()
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return get_files(cfg.export_path)
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Celsius = float
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Percent = float
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mBar = float
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@dataclass
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class Measurement:
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dt: datetime # todo aware/naive
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temp: Celsius
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humidity: Percent
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pressure: mBar
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dewpoint: Celsius
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def is_bad_table(name: str) -> bool:
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# todo hmm would be nice to have a hook that can patch any module up to
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delegate = getattr(config, 'is_bad_table', None)
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return False if delegate is None else delegate(name)
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@mcachew(depends_on=inputs)
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def measurements() -> Iterable[Res[Measurement]]:
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cfg = make_config()
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tz = cfg.tz
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# todo ideally this would be via arguments... but needs to be lazy
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paths = inputs()
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total = len(paths)
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width = len(str(total))
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last: Optional[datetime] = None
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# tables are immutable, so can save on processing..
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processed_tables: Set[str] = set()
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for idx, path in enumerate(paths):
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logger.info(f'processing [{idx:>{width}}/{total:>{width}}] {path}')
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tot = 0
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new = 0
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# todo assert increasing timestamp?
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with sqlite_connect_immutable(path) as db:
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db_dt: Optional[datetime] = None
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try:
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datas = db.execute(
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f'SELECT "{path.name}" as name, Time, Temperature, Humidity, Pressure, Dewpoint FROM data ORDER BY log_index'
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)
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oldfmt = True
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[(db_dts,)] = db.execute('SELECT last_download FROM info')
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if db_dts == 'N/A':
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# ??? happens for 20180923-20180928
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continue
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if db_dts.endswith(':'):
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db_dts += '00' # wtf.. happens on some day
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db_dt = tz.localize(datetime.strptime(db_dts, '%Y-%m-%d %H:%M:%S'))
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except sqlite3.OperationalError:
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# Right, this looks really bad.
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# The device doesn't have internal time & what it does is:
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# 1. every X seconds, record a datapoint, store it in the internal memory
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# 2. on sync, take the phone's datetime ('now') and then ASSIGN the timestamps to the collected data
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# as now, now - X, now - 2X, etc
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#
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# that basically means that for example, hourly timestamps are completely useless? because their error is about 1h
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# yep, confirmed on some historic exports. seriously, what the fuck???
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#
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# The device _does_ have an internal clock, but it's basically set to 0 every time you update settings
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# So, e.g. if, say, at 17:15 you set the interval to 3600, the 'real' timestamps would be
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# 17:15, 18:15, 19:15, etc
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# But depending on when you export, you might get
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# 17:35, 18:35, 19:35; or 17:55, 18:55, 19:55, etc
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# basically all you guaranteed is that the 'correct' interval is within the frequency
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# it doesn't seem to keep the reference time in the database
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#
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# UPD: fucking hell, so you can set the reference date in the settings (calcReferenceUnix field in meta db)
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# but it's not set by default.
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log_tables = [c[0] for c in db.execute('SELECT name FROM sqlite_sequence WHERE name LIKE "%_log"')]
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log_tables = [t for t in log_tables if t not in processed_tables]
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processed_tables |= set(log_tables)
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# todo use later?
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frequencies = [list(db.execute(f'SELECT interval from {t.replace("_log", "_meta")}'))[0][0] for t in log_tables] # noqa: RUF015
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# todo could just filter out the older datapoints?? dunno.
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# eh. a bit horrible, but seems the easiest way to do it?
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# note: for some reason everything in the new table multiplied by 10
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query = ' UNION '.join(
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f'SELECT "{t}" AS name, unix, tempReadings / 10.0, humiReadings / 10.0, pressReadings / 10.0, dewpReadings / 10.0 FROM {t}'
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for t in log_tables
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)
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if len(log_tables) > 0: # ugh. otherwise end up with syntax error..
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query = f'SELECT * FROM ({query}) ORDER BY name, unix'
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datas = db.execute(query)
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oldfmt = False
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db_dt = None
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for (name, tsc, temp, hum, pres, dewp) in datas:
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if is_bad_table(name):
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continue
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# note: bluemaestro keeps local datetime
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if oldfmt:
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tss = tsc.replace('Juli', 'Jul').replace('Aug.', 'Aug')
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dt = datetime.strptime(tss, '%Y-%b-%d %H:%M')
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dt = tz.localize(dt)
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assert db_dt is not None
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else:
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# todo cache?
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m = re.search(r'_(\d+)_', name)
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assert m is not None
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export_ts = int(m.group(1))
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db_dt = datetime.fromtimestamp(export_ts / 1000, tz=tz)
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dt = datetime.fromtimestamp(tsc / 1000, tz=tz)
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## sanity checks (todo make defensive/configurable?)
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# not sure how that happens.. but basically they'd better be excluded
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lower = timedelta(days=6000 / 24) # ugh some time ago I only did it once in an hour.. in theory can detect from meta?
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upper = timedelta(days=10) # kinda arbitrary
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if not (db_dt - lower < dt < db_dt + timedelta(days=10)):
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# todo could be more defenive??
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yield RuntimeError('timestamp too far out', path, name, db_dt, dt)
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continue
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# err.. sometimes my values are just interleaved with these for no apparent reason???
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if (temp, hum, pres, dewp) == (-144.1, 100.0, 1152.5, -144.1):
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yield RuntimeError('the weird sensor bug')
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continue
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assert -60 <= temp <= 60, (path, dt, temp)
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##
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tot += 1
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if last is not None and last >= dt:
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continue
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# todo for performance, pass 'last' to sqlite instead?
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last = dt
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new += 1
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p = Measurement(
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dt=dt,
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temp=temp,
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pressure=pres,
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humidity=hum,
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dewpoint=dewp,
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)
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yield p
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logger.debug(f'{path}: new {new}/{tot}')
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# logger.info('total items: %d', len(merged))
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# for k, v in merged.items():
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# # TODO shit. quite a few of them have varying values... how is that freaking possible????
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# # most of them are within 0.5 degree though... so just ignore?
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# if isinstance(v, set) and len(v) > 1:
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# print(k, v)
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# for k, v in merged.items():
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# yield Point(dt=k, temp=v) # meh?
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def stats() -> Stats:
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return stat(measurements)
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def dataframe() -> DataFrameT:
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"""
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%matplotlib gtk
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from my.bluemaestro import dataframe
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dataframe().plot()
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"""
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df = as_dataframe(measurements(), schema=Measurement)
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# todo not sure how it would handle mixed timezones??
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# todo hmm, not sure about setting the index
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return df.set_index('dt')
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def fill_influxdb() -> None:
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from my.core import influxdb
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influxdb.fill(measurements(), measurement=__name__)
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def check() -> None:
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temps = list(measurements())
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latest = temps[:-2]
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prev = unwrap(latest[-2]).dt
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last = unwrap(latest[-1]).dt
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# todo stat should expose a dataclass?
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# TODO ugh. might need to warn about points past 'now'??
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# the default shouldn't allow points in the future...
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#
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# TODO also needs to be filtered out on processing, should be rejected on the basis of export date?
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POINTS_STORED = 6000 # on device?
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FREQ_SEC = 60
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SECS_STORED = POINTS_STORED * FREQ_SEC
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HOURS_STORED = POINTS_STORED / (60 * 60 / FREQ_SEC) # around 4 days
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NOW = datetime.now()
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assert NOW - last < timedelta(hours=HOURS_STORED / 2), f'old backup! {last}'
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assert last - prev < timedelta(minutes=3), f'bad interval! {last - prev}'
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single = (last - prev).seconds
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