#!/usr/bin/env python3
import datetime
import itertools
import re

import numpy as np
import pandas as pd

import requests
from lxml import etree

from common import doors
from hid.DoorController import ROOT, E


def getStrings(door):
    """Parses out the message strings from source."""
    r = requests.get('https://' + door.ip + '/html/en_EN/en_EN.js',
                     auth=requests.auth.HTTPDigestAuth(door.username,
                                                       door.password),
                     verify=False)
    regex = re.compile(r'([0-9]+)="([^"]*)')
    strings = [regex.search(s) for s in r.text.split(';')
               if s.startswith('localeStrings.eventDetails')]
    print({int(g.group(1)): g.group(2) for g in strings})

def getMessages(door):
    events = None
    recordCount = 0
    moreRecords = True

    while moreRecords:
        res = door.doXMLRequest(ROOT(
            E.EventMessages({
                "action": "LR",
                "recordCount": str(1000 - recordCount),
                "recordOffset": str(recordCount),
            })))
        if events is None:
            events = res[0]
        else:
            for event in res[0]:
                events.append(event)

        recordCount += int(res[0].get('recordCount'))
        moreRecords = res[0].get('moreRecords') == 'true'

        print(recordCount, moreRecords)

    etree.dump(events, pretty_print=True)

    return events

# def stats(events):
#     eventsByDay = {k: list(v) for k, v in
#                    itertools.groupby(sorted(events, key=get_day), key=get_day)}

#     print({k: len(v) for k, v in eventsByDay.items()})

#     #print([get_day(e) for e in events])

def main():
    for door in doors.values():
        getMessages(door)

if __name__ == '__main__':
    main()

events = getMessages(doors["Studio Space"])

# stats(events)

df = pd.DataFrame([dict(e.attrib) for e in events])
idx = pd.to_datetime(df['timestamp'], format='%Y-%m-%dT%H:%M:%S')
df = df.set_index(pd.DatetimeIndex(idx.values)).drop('timestamp', axis=1)
print()
print(df[df.eventType == '2020'].dropna(axis=1, how='all').head())

entriesPerDay = df[df.eventType == '2020'] \
    .dropna(axis=1, how='all') \
    .resample('1D') \
    .count()['eventType']

entriesPerDay.index = entriesPerDay.index.map(lambda t: t.strftime('%Y-%m-%d'))

print(df.groupby(by=['forename', 'surname']).size().sort_values())

entriesPerDay.plot(kind='bar')