def testUpdateDocument(self):
''' Function updates/increments a specific hour.minute in a document. '''
# Get connection to mongo
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# New timeseries object with data
ts = timeSeries()
ts.importData(self.kw, blockPrecision=24)
success = ts.insertBlankDoc()
self.assertEquals(success, 1)
# Update/increment a specific hour.minute
ts.updateCount()
# Run a query for this item
outDocs = dbh.timeseries.find({'data.12.1':1})
for doc in outDocs:
print doc
self.assertEquals(doc['mgrs'], '38SND4595706622')
# Close the connection
mdb.close(c, dbh)
def MongoLookup(self):
''' Fn checks whether a timeseries document already exists for this period. '''
# Get connection to mongo
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# New timeseries object with data
ts = timeSeries()
ts.importData(self.kw, blockPrecision=1)
# Check the count - should be 0 before the doc gets inserted
count = ts.mongoLookup()
self.assertEquals(count, 0)
# Build and insert a new mongo formatted document
success = ts.insertBlankDoc()
# Count should be 1 now that the document has been inserted
count = ts.mongoLookup()
self.assertEquals(count, 1)
# Clean up, remove he content and close the connection
#dbh.timeseries.remove()
mdb.close(c, dbh)
def testBuildFullArrayFlat(self):
'''Build a full FLATTENED array from a cursor result'''
st = datetime.datetime.utcnow()
# A keyword that went in yesterday creates a timeseries yesterday
nowDt = datetime.datetime(year=2011,month=1,day=12,hour=11,minute=1,second=1)
oneDay= datetime.timedelta(days=1)
# Get a db handle
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# Build a keyword
kword = kw(keyword='keyword1', timeStamp=nowDt-oneDay, lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# New timeseries object
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# Insert 2ND DOC IN THE COLLECTION
kword.timeStamp = nowDt
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
nowDate = nowDt.replace(hour=0,minute=0,second=0,microsecond=0)
# Last 1 weeks worth of documents
resultSet = bl.getResultsPerCell(dbh, '38SND4595706622', 'keyword1', nowDate, 168)
# Close the connection
mdb.close(c, dbh)
# Inputs
period = datetime.timedelta(days=7)
dates, data = bl.buildFullArray(resultSet, nowDate, period, 1)
firstDay = dates[0]
lastDay = dates[-1]
self.assertEquals(data.shape[0], 11520)
self.assertEquals(firstDay, nowDate - period)
self.assertEquals(lastDay, nowDate)
def testGetAllCountForOneCell(self):
''' Gets a count for a single cell'''
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
tweetTime = datetime.datetime(2011,1,2,12,5,15)
oldTweetTime = tweetTime - datetime.timedelta(seconds=11*60)
# Build a keyword to represent the basekine
kword = kw(keyword='keyword1', timeStamp=oldTweetTime, lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# New timeseries object
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# Build a keyword
kword = kw(keyword='keyword1', timeStamp=tweetTime, lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# New timeseries object
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# ALL DOCUMENTS
mgrs = '38SND4595706622'
keyword = 'keyword1'
# This indate represents when the baseline was run (12:10) minus the interest period (10 minutes)
inDate = datetime.datetime(2011,1,2,12,0,0)
results = bl.getResultsPerCell(dbh, collection='timeseries', mgrs=mgrs, keyword=keyword, inDate=inDate)
self.assertEqual(len(results), 1)
def testBuildFullArray(self):
'''Build a full array from a cursor result'''
# Get a db handle
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# Build a keyword
kword = kw(keyword='keyword1', timeStamp=datetime.datetime(2011,1,2,12,1,1), lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1', tweetID=346664, userID=4444, source='twitter')
# New timeseries object
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# Insert the doc now that its been modified
kword.timeStamp = datetime.datetime(2011,1,1,12,1,1)
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# Last 1 weeks worth of documents
resultSet = bl.getResultsPerCell(dbh, '38SND4595706622', 'keyword1', datetime.datetime(2011,1,2), 168)
# Inputs
inDate = datetime.datetime(2011, 1, 2, 0, 0)
period = datetime.timedelta(days=7)
flat = None
dates, data = bl.buildFullArray(resultSet, inDate, period, flat)
self.assertEquals(len(dates), 8)
self.assertEquals(len(data), 8)
# Close the connection
mdb.close(c, dbh)
def testImportData(self):
''' Check import of keyword object.'''
# New timeseries object
ts = timeSeries()
# Import the data
ts.importData(self.kw)
print 'start',ts.start
self.assertEquals(ts.start, datetime.datetime(2011,1,2,0,0,0))
self.assertEquals(ts.source, 'twitter')
self.assertEquals(ts.period, datetime.timedelta(hours=24))
self.assertEquals(ts.mgrs, '38SND4595706622')
# Close the connection
ts.c.disconnect()
def testGetAllCountForOneCellLookback(self):
''' Gets a count for a single cell'''
tweetTime = datetime.datetime(2011,1,2,12,5,15)
oldTweetTime = tweetTime - datetime.timedelta(seconds=15*60)
baselineTime = datetime.datetime(2011,1,2,12,0,0)
# Get a db handle
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# Build a keyword
kword = kw(keyword='keyword1', timeStamp=tweetTime, lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# New timeseries object
ts = timeSeries()
ts.importData(kword)
success = ts.insertBlankDoc()
# Last 2 documents
lookback = 24
mgrs = '38SND4595706622'
qKeyword = 'keyword1'
res = bl.getResultsPerCell(dbh,
collection='timeseries',
mgrs=mgrs,
keyword=qKeyword,
inDate=baselineTime,
lookback=lookback)
print res
results = []
for doc in res:
print doc
results.append(doc)
self.assertEqual(len(results), 1)
# Close the connection
mdb.close(c, dbh)
def InsertBlankDoc(self):
''' Checks the successful inserting of a mongo document '''
# Get connection to mongo
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True) # Set up collections
# New timeseries object with data
ts = timeSeries()
ts.importData(self.kw, blockPrecision=1)
# Build and insert a new mongo formatted document
success = ts.insertBlankDoc()
self.assertEquals(success, 1)
# Clean up and drop it
#dbh.timeseries.remove()
# Close the connection
mdb.close(c, dbh)
def testGetStart(self):
''' Checks getting the start dt '''
# A days worth of hour
#times = list(datetime.datetime(2011,1,1, i, random.randint(0,59)) for i in range(0,24,4))
inTime = datetime.datetime(2011,1,1,7)
blockPrecisions = [
[1, datetime.datetime(2011,1,1,7)],
[4, datetime.datetime(2011,1,1,4)],
[6, datetime.datetime(2011,1,1,6)],
[12, datetime.datetime(2011,1,1,0)],
[24, datetime.datetime(2011,1,1,0)]
]
# Test the input block precision against the output dt
for bp in blockPrecisions:
ts = timeSeries()
start = ts.getStart(timeStamp=inTime, blockPrecision=bp[0])
self.assertEquals(start, bp[1])
# Disconnect
ts.c.disconnect()
def testProcessBaselineLast30Days(self):
''' Checks accurate population of an array for 30 day all '''
# Connect and get handle
c, dbh = mdb.getHandle()
dbh = mdb.setupCollections(dbh, dropCollections=True)
# Set up some times to work with
tweetTime = datetime.datetime.utcnow()
thisMinute = tweetTime.replace(second=0,microsecond=0)
today = tweetTime.replace(hour=0, minute=0, second=0, microsecond=0)
# Thirty days ago - at the start of the day
lastMonthTweet = tweetTime - datetime.timedelta(days=30)
# Build a keyword object
testKywd = kw(keyword='keyword1',
timeStamp=lastMonthTweet,
lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# Insert a new timeseries object for the tweet 30 days ago
ts = timeSeries()
ts.importData(testKywd)
success = ts.insertBlankDoc()
ts.updateCount()
# Create a keyword object for the current tweet
testKywd2 = kw(keyword='keyword1',
timeStamp=lastMonthTweet + datetime.timedelta(hours=1),
lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# Insert the current keyword - NOTE HOW THIS IS AFTER THE BASELINE BUILD
ts2 = timeSeries()
ts2.importData(testKywd2)
success = ts2.insertBlankDoc()
ts2.updateCount()
# Create a keyword object for the current tweet
testKywd3 = testKywd
testKywd3.timeStamp = tweetTime
# Instantiate the baseline object/class
base = bl.baseline(kywd=testKywd3, cellBuildPeriod=600)
if base.needUpdate == True:
if not base.lastBaselined():
doc = base.buildDoc()
bl.insertBaselineDoc(dbh, doc)
# Insert the current keyword - NOTE HOW THIS IS AFTER THE BASELINE BUILD
ts3 = timeSeries()
ts3.importData(testKywd3)
success = ts3.insertBlankDoc()
ts3.updateCount()
tweetTimeMinus2Days = tweetTime - datetime.timedelta(days=2)
# Create a new keyword object to test the daily slicing
testKywd5 = kw(keyword='keyword1',
timeStamp=tweetTimeMinus2Days,
lat=34.4, lon=45.5,
text='this text contained the hashtag #keyword1',
tweetID=346664, userID=4444, source='twitter')
# Insert the current keyword - NOTE HOW THIS IS AFTER THE BASELINE BUILD
ts5 = timeSeries()
ts5.importData(testKywd5)
success = ts5.insertBlankDoc()
ts5.updateCount()
# Process Baseline
base.processBaseline()
# Get back the 30 day array
arr = base.test30DayArray
# Calculate what the array length should be
soFarToday = (thisMinute - today).seconds/60.0
# The start of the array datetime
lastMonthDay = lastMonthTweet.replace(hour=0, minute=0, second=0, microsecond=0)
# The number of days between today and the start of the array (then in minutes)
dateDiff = (today - lastMonthDay)
minsDiff = dateDiff.days*1440 + dateDiff.seconds/60.0
total = minsDiff + soFarToday
# Confirm its the right length
self.assertEqual(total, len(arr))
# Get the minutes for the first 2 keywords (the third shouldn't be there)
kwd1Min = int((testKywd.timeStamp - lastMonthDay).seconds/60)
kwd2Min = int((testKywd2.timeStamp - lastMonthDay).seconds/60)
kwd1Test = [arr[kwd1Min-1], arr[kwd1Min], arr[kwd1Min+1]]
kwd2Test = [arr[kwd2Min-1], arr[kwd2Min], arr[kwd2Min+1]]
for j in arr:
if arr[j] > 0:
print j, arr[j]
self.assertEquals(kwd1Test, [0,1,0])
self.assertEquals(kwd2Test, [0,1,0])
# 30 DAY TIME SLICE CHECK
arr = base.test30DaySliced
# weekly
testSliced = int(30/7) * 6 * 60
self.assertEquals(testSliced, len(arr))
arr7Day = base.test7DayArray
test7DayAll = (thisMinute - today).seconds/60.0 + 1440*7
self.assertEquals(len(arr7Day), int(test7DayAll))
arr30Hrs = base.test30hrArray
test30Hours = 30*60
self.assertEquals(len(arr30Hrs), int(test30Hours))
# Close the connection
mdb.close(c, dbh)
