WIP: improve events retrieval and add some statistics

events.py

@@ -1,16 +1,23 @@
 #!/usr/bin/env python3
-from collections import defaultdict
+import datetime
-from lxml import etree
+import itertools
-import os
 import re
-import requests
 
-from common import *
+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),
+                     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(';')
@@ -18,46 +25,39 @@ def getStrings(door):
     print({int(g.group(1)): g.group(2) for g in strings})
 
 def getMessages(door):
-    # get parameters for messages to get?
+    events = None
-    # honestly not really sure why this is required, their API is confusing
+    recordCount = 0
-    parXMLIn = E_plain.VertXMessage(
+    moreRecords = True
-        E.EventMessages({"action": "LR"}))
-    parXMLOut = door.doXMLRequest(parXMLIn)
-    etree.dump(parXMLOut)
 
-    if os.path.exists("logs/" + door.name + ".xml"):
+    while moreRecords:
-        # read last log
+        res = door.doXMLRequest(ROOT(
-        tree = etree.ElementTree(file="logs/" + door.name + ".xml")
+            E.EventMessages({
-        root = tree.getroot()
+                "action": "LR",
-        recordCount = int(parXMLOut[0].attrib["historyRecordMarker"]) - \
+                "recordCount": str(1000 - recordCount),
-                      int(root[0][0].attrib["recordMarker"])
+                "recordOffset": str(recordCount),
+            })))
+        if events is None:
+            events = res[0]
         else:
-        # first run for this door
+            for event in res[0]:
-        root = None
+                events.append(event)
-        recordCount = 1000
 
-    if recordCount == 0:
+        recordCount += int(res[0].get('recordCount'))
-        print("No records to get!")
+        moreRecords = res[0].get('moreRecords') == 'true'
-        return
-    print("Getting", recordCount, "records")
-    # get the actual messages
-    eventsXMLIn = E_plain.VertXMessage(
-        E.EventMessages({"action": "LR",
-                         "recordCount": str(recordCount),
-                         "historyRecordMarker": parXMLOut[0].attrib["historyRecordMarker"],
-                         "historyTimestamp": parXMLOut[0].attrib["historyTimestamp"]}))
-    eventsXMLOut = door.doXMLRequest(eventsXMLIn)
-    #TODO: handle modeRecords=true
 
-    for index, event in enumerate(eventsXMLOut[0]):
+        print(recordCount, moreRecords)
-        event.attrib["recordMarker"] = str(int(parXMLOut[0].attrib["historyRecordMarker"]) - index)
 
-    if root is None:
+    etree.dump(events, pretty_print=True)
-        tree = etree.ElementTree(eventsXMLOut)
+
-    else:
+    return events
-        for event in reversed(eventsXMLOut[0]):
+
-            root[0].insert(0, event)
+# def stats(events):
-    tree.write("logs/" + doorName + ".xml")
+#     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():
@@ -65,3 +65,24 @@ def main():
 
 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')