from datetime import datetime
from pathlib import Path
from functools import lru_cache
import logging
from datetime import timedelta, datetime, date
from typing import List, Dict, Iterator, NamedTuple
import json

from collections import OrderedDict as odict

from kython import cproperty


fromts = datetime.fromtimestamp

def get_logger():
    return logging.getLogger('emfit-provider')

def hhmm(minutes):
    return '{:02d}:{:02d}'.format(*divmod(minutes, 60))

PATH = Path("/L/backups/emfit")

EXCLUDED = [
    '***REMOVED***', # pretty weird, detected sleep and HR (!) during the day when I was at work
    '***REMOVED***',

    '***REMOVED***', # some weird sleep during the day?
]

AWAKE = 4

class Emfit:
    def __init__(self, sid: str, jj):
        self.sid = sid
        self.jj = jj

    def __hash__(self):
        return hash(self.sid)

    @property
    def hrv_morning(self):
        return self.jj['hrv_rmssd_morning']

    @property
    def hrv_evening(self):
        return self.jj['hrv_rmssd_evening']

    # ok, I guess that's reasonable way of defining sleep date
    @property
    def date(self):
        return self.end.date()

    """
    Bed time, not necessarily sleep
    """
    @property
    def start(self):
        return fromts(self.jj['time_start'])

    """
    Bed time, not necessarily sleep
    """
    @property
    def end(self):
        return fromts(self.jj['time_end'])

    @property
    def epochs(self):
        return self.jj['sleep_epoch_datapoints']

    @property
    def epoch_series(self):
        tss = []
        eps = []
        for [ts, e] in self.epochs:
            tss.append(ts)
            eps.append(e)
        return tss, eps

    # TODO are these utc?? should be visible on big plot
    @cproperty
    def sleep_start(self) -> datetime:
        for [ts, e] in self.epochs:
            if e == AWAKE:
                continue
            return fromts(ts)
        raise RuntimeError

    @cproperty
    def sleep_end(self) -> datetime:
        for [ts, e] in reversed(self.epochs):
            if e == AWAKE:
                continue
            return fromts(ts)
        raise RuntimeError
# 'sleep_epoch_datapoints'
# [[timestamp, number]]

    @cproperty
    def time_in_bed(self):
        return int((self.sleep_end - self.sleep_start).total_seconds()) // 60

    # so it's actual sleep, without awake
    # ok, so I need time_asleep
    @property
    def sleep_minutes_emfit(self):
        return self.jj['sleep_duration'] // 60

    @property
    def hrv_lf(self):
        return self.jj['hrv_lf']

    @property
    def hrv_hf(self):
        return self.jj['hrv_hf']

    @property
    def recovery(self):
        return self.hrv_morning - self.hrv_evening

    @property
    def summary(self):
        return f"""in bed for {hhmm(self.time_in_bed)}
emfit time: {hhmm(self.sleep_minutes_emfit)}; covered: {self.sleep_hr_coverage:.0f}
hrv morning: {self.hrv_morning:.0f}
hrv evening: {self.hrv_evening:.0f}
avg hr: {self.measured_hr_avg:.0f}
recovery: {self.recovery:3.0f}
{self.hrv_lf}/{self.hrv_hf}"""

    @property
    def strip_awakes(self):
        ff = None
        ll = None
        for i, [ts, e] in enumerate(self.epochs):
            if e != AWAKE:
                ff = i
                break
        for i in range(len(self.epochs) - 1, -1, -1):
            [ts, e] = self.epochs[i]
            if e != AWAKE:
                ll = i
                break
        return self.epochs[ff: ll]


    # # TODO epochs with implicit sleeps? not sure... e.g. night wakeups.
    # # I guess I could input intervals/correct data/exclude days manually?
    # @property
    # def pulse_percentage(self):

    #     # TODO pulse intervals are 4 seconds?
    #     # TODO ok, how to compute that?...
    #     # TODO cut ff start and end?
    #     # TODO remove awakes from both sides
    #     sp = self.strip_awakes
    #     present = {ep[0] for ep in sp}
    #     start = min(present)
    #     end = max(present)
    #     # TODO get start and end in one go?

    #     for p in self.iter_points():
    #         p.ts 


    #     INT = 30

    #     missing = 0
    #     total = 0
    #     for tt in range(start, end + INT, INT):
    #         total += 1
    #         if tt not in present:
    #             missing += 1
    #     # TODO get hr instead!
    #     import ipdb; ipdb.set_trace() 
    #     return missing


    #     st = st[0][0]
    #     INT = 30
    #     for [ts, e] in sp:
    #         if e == AWAKE:
    #             continue
    #         return fromts(ts)
    #     raise RuntimeError
    #     pass

    def __str__(self) -> str:
        return f"from {self.sleep_start} to {self.sleep_end}"

# measured_datapoints
# [[timestamp, pulse, breath?, ??? hrv?]] # every 4 seconds?

    def iter_points(self):
        for ll in self.jj['measured_datapoints']:
            [ts, pulse, br, activity] = ll
            # TODO what the fuck is whaat?? It can't be HRV, it's about 500 ms on average
            # act in csv.. so it must be activity? wonder how is it measured.
            # but I guess makes sense. yeah,  "measured_activity_avg": 595, about that
            # makes even more sense given tossturn datapoints only have timestamp
            yield ts, pulse

    @property
    def sleep_hr(self):
        tss = []
        res = []
        for ts, pulse in self.iter_points():
            if self.sleep_start < fromts(ts) < self.sleep_end:
                tss.append(ts)
                res.append(pulse)
        return tss, res

    @property
    def sleep_hr_series(self):
        return self.sleep_hr

    @property
    def hrv(self):
        tss = []
        res = []
        for ll in self.jj['hrv_rmssd_datapoints']:
            [ts, rmssd, _, _, almost_always_zero, _] = ll
            # timestamp,rmssd,tp,lfn,hfn,r_hrv
            # TP is total_power??
            # erm. looks like there is a discrepancy between csv and json data.
            # right, so web is using api v 1. what if i use v1??
            # definitely a discrepancy between v1 and v4. have no idea how to resolve it :(
            # also if one of them is indeed tp value, it must have been rounded.
            # TODO what is the meaning of the rest???
            # they don't look like HR data.
            tss.append(ts)
            res.append(rmssd)
        return tss, res

    @property
    def measured_hr_avg(self):
        return self.jj["measured_hr_avg"]

    @cproperty
    def sleep_hr_coverage(self):
        tss, hrs = self.sleep_hr
        covered = len([h for h in hrs if h is not None])
        expected = len(hrs)
        return covered / expected * 100


import functools

@functools.lru_cache(1000) # TODO hmm. should I configure it dynamically???
def get_emfit(sid: str, f: Path) -> Emfit:
    return Emfit(sid=sid, jj=json.loads(f.read_text()))


def iter_datas() -> Iterator[Emfit]:
    for f in PATH.glob('*.json'):
        sid = f.stem
        if sid in EXCLUDED:
            continue

        yield get_emfit(sid, f)


def get_datas() -> List[Emfit]:
    return list(sorted(iter_datas(), key=lambda e: e.start))
# TODO move away old entries if there is a diff??

from kython import timed
from kython import group_by_key

@timed
def by_night() -> Dict[date, Emfit]:
    logger = get_logger()
    res: Dict[date, Emfit] = odict()
    # TODO shit. I need some sort of interrupted sleep detection?
    for dd, sleeps in group_by_key(get_datas(), key=lambda s: s.date).items():
        if len(sleeps) > 1:
            logger.warning("multiple sleeps per night, not handled yet: %s", sleeps)
            continue
        [s] = sleeps
        res[s.date] = s
    return res



def test():
    for d in get_datas():
        assert len(d.epochs) > 0