2019-05-29 01:30:57 +02:00
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import datetime
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import time
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2018-09-24 09:21:02 +02:00
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from collections import defaultdict
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2017-11-06 10:42:51 +01:00
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2017-11-27 16:28:27 +01:00
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ONE_DAY = 60*60*24
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2017-11-27 09:47:55 +01:00
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def getZrange(serv_redis_db, keyCateg, date, topNum, endSubkey=""):
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date_str = getDateStrFormat(date)
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keyname = "{}:{}{}".format(keyCateg, date_str, endSubkey)
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data = serv_redis_db.zrange(keyname, 0, topNum-1, desc=True, withscores=True)
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data = [ [record[0].decode('utf8'), record[1]] for record in data ]
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return data
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2017-12-01 15:39:17 +01:00
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def noSpaceLower(text):
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return text.lower().replace(' ', '_')
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2017-11-29 16:09:39 +01:00
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def push_to_redis_zset(serv_redis_db, mainKey, toAdd, endSubkey="", count=1):
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now = datetime.datetime.now()
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2017-12-01 15:39:17 +01:00
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today_str = getDateStrFormat(now)
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2017-11-29 16:09:39 +01:00
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keyname = "{}:{}{}".format(mainKey, today_str, endSubkey)
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serv_redis_db.zincrby(keyname, toAdd, count)
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2017-11-06 10:42:51 +01:00
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def getMonthSpan(date):
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ds = datetime.datetime(date.year, date.month, 1)
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dyear = 1 if ds.month+1 > 12 else 0
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dmonth = -12 if ds.month+1 > 12 else 0
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de = datetime.datetime(ds.year + dyear, ds.month+1 + dmonth, 1)
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delta = de - ds
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to_return = []
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for i in range(delta.days):
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to_return.append(ds + datetime.timedelta(days=i))
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return to_return
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2017-11-10 09:28:59 +01:00
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def getXPrevDaysSpan(date, days):
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de = date
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ds = de - datetime.timedelta(days=days)
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delta = de - ds
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to_return = []
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for i in range(delta.days+1):
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to_return.append(de - datetime.timedelta(days=i))
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return to_return
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2017-11-15 09:36:44 +01:00
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def getXPrevHoursSpan(date, hours):
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de = date
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de = de.replace(minute=0, second=0, microsecond=0)
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ds = de - datetime.timedelta(hours=hours)
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delta = de - ds
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to_return = []
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for i in range(0, int(delta.total_seconds()/3600)+1):
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to_return.append(de - datetime.timedelta(hours=i))
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return to_return
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2017-11-21 11:59:07 +01:00
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def getHoursSpanOfDate(date, adaptToFitCurrentTime=True, daySpanned=6):
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ds = date
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ds = ds.replace(hour=0, minute=0, second=0, microsecond=0)
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to_return = []
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now = datetime.datetime.now()
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for i in range(0, 24):
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the_date = ds + datetime.timedelta(hours=i)
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if the_date > now or the_date < now - datetime.timedelta(days=daySpanned): # avoid going outside
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continue
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to_return.append(the_date)
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return to_return
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2017-11-06 10:42:51 +01:00
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def getDateStrFormat(date):
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return str(date.year)+str(date.month).zfill(2)+str(date.day).zfill(2)
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2017-11-10 11:15:31 +01:00
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2017-11-17 11:47:20 +01:00
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def getDateHoursStrFormat(date):
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return getDateStrFormat(date)+str(date.hour)
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2017-11-10 11:15:31 +01:00
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def getTimestamp(date):
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2017-11-15 09:36:44 +01:00
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return int(time.mktime(date.timetuple()))
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2018-09-24 09:21:02 +02:00
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def sortByTrendingScore(toSort, topNum=5):
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scoredLabels = defaultdict(float)
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numDay = len(toSort)
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baseDecay = 1.0
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2018-09-24 10:26:15 +02:00
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decayRate = lambda x: baseDecay*((numDay-x**2)/numDay)
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2018-09-24 09:21:02 +02:00
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for i, arr in enumerate(toSort):
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timestamp = arr[0]
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dailyData = arr[1]
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for item in dailyData:
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label = item[0]
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occ = item[1]
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scoredLabels[label] += occ*decayRate(i)
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topList = [[l, s] for l, s in scoredLabels.items()]
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topList.sort(key=lambda x: x[1], reverse=True)
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topSet = [ l for l, v in topList[:topNum]]
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# now that we have the top, filter out poor scored elements
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topArray = []
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for arr in toSort:
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timestamp = arr[0]
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dailyData = arr[1]
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topDailyArray = list(filter(lambda item: (item[0] in topSet), dailyData))
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dailyCombi = [timestamp, topDailyArray]
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topArray.append(dailyCombi)
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return topArray
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