forked from CMS/memberPlumbing
89 lines
2.4 KiB
Python
Executable File
89 lines
2.4 KiB
Python
Executable File
#!/usr/bin/env python3
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import datetime
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import itertools
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import re
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import numpy as np
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import pandas as pd
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import requests
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from lxml import etree
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from common import doors
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from hid.DoorController import ROOT, E
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def getStrings(door):
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"""Parses out the message strings from source."""
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r = requests.get('https://' + door.ip + '/html/en_EN/en_EN.js',
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auth=requests.auth.HTTPDigestAuth(door.username,
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door.password),
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verify=False)
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regex = re.compile(r'([0-9]+)="([^"]*)')
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strings = [regex.search(s) for s in r.text.split(';')
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if s.startswith('localeStrings.eventDetails')]
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print({int(g.group(1)): g.group(2) for g in strings})
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def getMessages(door):
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events = None
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recordCount = 0
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moreRecords = True
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while moreRecords:
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res = door.doXMLRequest(ROOT(
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E.EventMessages({
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"action": "LR",
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"recordCount": str(1000 - recordCount),
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"recordOffset": str(recordCount),
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})))
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if events is None:
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events = res[0]
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else:
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for event in res[0]:
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events.append(event)
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recordCount += int(res[0].get('recordCount'))
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moreRecords = res[0].get('moreRecords') == 'true'
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print(recordCount, moreRecords)
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etree.dump(events, pretty_print=True)
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return events
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# def stats(events):
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# eventsByDay = {k: list(v) for k, v in
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# itertools.groupby(sorted(events, key=get_day), key=get_day)}
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# print({k: len(v) for k, v in eventsByDay.items()})
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# #print([get_day(e) for e in events])
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def main():
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for door in doors.values():
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getMessages(door)
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if __name__ == '__main__':
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main()
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events = getMessages(doors["Studio Space"])
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# stats(events)
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df = pd.DataFrame([dict(e.attrib) for e in events])
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idx = pd.to_datetime(df['timestamp'], format='%Y-%m-%dT%H:%M:%S')
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df = df.set_index(pd.DatetimeIndex(idx.values)).drop('timestamp', axis=1)
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print()
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print(df[df.eventType == '2020'].dropna(axis=1, how='all').head())
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entriesPerDay = df[df.eventType == '2020'] \
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.dropna(axis=1, how='all') \
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.resample('1D') \
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.count()['eventType']
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entriesPerDay.index = entriesPerDay.index.map(lambda t: t.strftime('%Y-%m-%d'))
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print(df.groupby(by=['forename', 'surname']).size().sort_values())
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entriesPerDay.plot(kind='bar')
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