def getSavedList( self, user, clients ):
"""
@summary : Returns the checksum of the files contained in the saved list.
"""
self.savedFileList = {}
statsPaths = StatsPaths()
statsPaths.setPaths()
directory = statsPaths.STATSDATA + "fileAccessVersions/"
combinedName = ""
for client in clients:
combinedName = combinedName + client
fileName = combinedName + "_" + user
try :
self.savedFileList = CpickleWrapper.load( directory + fileName )
if self.savedFileLis == None :
self.savedFileList = {}
except: # if file does not exist
pass
return self.savedFileList
def loadAccessFile(self):
"""
@summary: Loads the accessFile into the accessDictionary.
"""
self.accessDictionary = CpickleWrapper.load( self.accessFile )
def getSavedList(self, user, clients):
"""
@summary : Returns the checksum of the files contained in the saved list.
"""
self.savedFileList = {}
statsPaths = StatsPaths()
statsPaths.setPaths()
directory = statsPaths.STATSDATA + "fileAccessVersions/"
combinedName = ""
for client in clients:
combinedName = combinedName + client
fileName = combinedName + "_" + user
try:
self.savedFileList = CpickleWrapper.load(directory + fileName)
if self.savedFileLis == None:
self.savedFileList = {}
except: # if file does not exist
pass
return self.savedFileList
def loadAccessFile(self):
"""
@summary: Loads the accessFile into the accessDictionary.
"""
self.accessDictionary = CpickleWrapper.load(self.accessFile)
def printPickle(pickle, outputFile=""):
"""
Print content of a pickle file containing a FileStatscollector
instance on the desired output.
Default output is the console screen.
File can be specified to make reading easier.
"""
if outputFile != "":
fileHandle = open(outputFile, 'w')
old_stdout = sys.stdout
sys.stdout = fileHandle
statsCollection = CpickleWrapper.load(pickle)
print _("Pickle used : %s") % pickle
print _("\n\nFiles used : %s") % statsCollection.files
print _("Starting date: %s") % statsCollection.startTime
print _("Interval: %s") % statsCollection.interval
print _("End time : %s") % statsCollection.endTime
print _("nbEntries : %s") % statsCollection.nbEntries
for j in range(statsCollection.nbEntries):
print _("\nEntry's interval : %s - %s ") % (
statsCollection.fileEntries[j].startTime,
statsCollection.fileEntries[j].endTime)
print _("Files : ")
print statsCollection.fileEntries[j].files
print _("Products : ")
print statsCollection.fileEntries[j].values.productTypes
print _("Values :")
print statsCollection.fileEntries[j].values.dictionary
print _("Means :")
print statsCollection.fileEntries[j].means
print _("Medians")
print statsCollection.fileEntries[j].medians
print _("Minimums")
print statsCollection.fileEntries[j].minimums
print _("Maximums")
print statsCollection.fileEntries[j].maximums
print _("Time where max occured :")
print statsCollection.fileEntries[j].timesWhereMaxOccured
print _("Total")
print statsCollection.fileEntries[j].totals
print _("Files over maximum latency")
print statsCollection.fileEntries[j].filesOverMaxLatency
if outputFile != "":
fileHandle.close()
sys.stdout = old_stdout #resets standard output
def mergePicklesFromDifferentHours( logger = None , startTime = "2006-07-31 13:00:00",\
endTime = "2006-07-31 19:00:00", client = "satnet",\
machine = "pdsPM", fileType = "tx" ):
"""
@summary : This method merges entire hourly pickles files together.
@None : This does not support merging part of the data of pickles.
"""
if logger != None :
logger.debug( _("Call to mergeHourlyPickles received.") )
logging = True
else:
logging = False
pickles = []
entries = {}
width = StatsDateLib.getSecondsSinceEpoch( endTime ) - StatsDateLib.getSecondsSinceEpoch( startTime )
startTime = StatsDateLib.getIsoWithRoundedHours( startTime )
seperators = [startTime]
seperators.extend( StatsDateLib.getSeparatorsWithStartTime( startTime = startTime , width=width, interval=60*StatsDateLib.MINUTE )[:-1])
for seperator in seperators :
pickles.append( StatsPickler.buildThisHoursFileName( client = client, offset = 0, currentTime = seperator, machine = machine, fileType = fileType ) )
startingNumberOfEntries = 0
#print "prior to loading and merging pickles : %s " %( StatsDateLib.getIsoFromEpoch( time.time() ) )
for pickle in pickles :
if os.path.isfile( pickle ) :
tempCollection = CpickleWrapper.load( pickle )
if tempCollection != None :
for i in xrange( len( tempCollection.fileEntries ) ):
entries[startingNumberOfEntries + i] = tempCollection.fileEntries[i]
startingNumberOfEntries = startingNumberOfEntries + len( tempCollection.fileEntries )
else:
sys.exit()
else:
emptyEntries = PickleMerging.fillWithEmptyEntries( nbEmptyEntries = 60, entries = {} )
for i in xrange( 60 ):
entries[i + startingNumberOfEntries ] = emptyEntries [i]
startingNumberOfEntries = startingNumberOfEntries + 60
#print "after the loading and merging og pickles : %s " %( StatsDateLib.getIsoFromEpoch( time.time() ) )
statsCollection = FileStatsCollector( startTime = startTime , endTime = endTime, interval = StatsDateLib.MINUTE, totalWidth = width, fileEntries = entries,fileType= fileType, logger = logger, logging = logging )
return statsCollection
def printPickle( pickle, outputFile = "" ):
"""
Print content of a pickle file containing a FileStatscollector
instance on the desired output.
Default output is the console screen.
File can be specified to make reading easier.
"""
if outputFile != "":
fileHandle = open( outputFile , 'w' )
old_stdout = sys.stdout
sys.stdout = fileHandle
statsCollection = CpickleWrapper.load( pickle )
print _("Pickle used : %s" )%pickle
print _("\n\nFiles used : %s" ) %statsCollection.files
print _("Starting date: %s" ) % statsCollection.startTime
print _("Interval: %s" ) %statsCollection.interval
print _("End time : %s" ) %statsCollection.endTime
print _("nbEntries : %s" ) %statsCollection.nbEntries
for j in range( statsCollection.nbEntries ):
print _("\nEntry's interval : %s - %s " ) %( statsCollection.fileEntries[j].startTime, statsCollection.fileEntries[j].endTime )
print _("Files : " )
print statsCollection.fileEntries[j].files
print _("Products : " )
print statsCollection.fileEntries[j].values.productTypes
print _("Values :" )
print statsCollection.fileEntries[j].values.dictionary
print _("Means :" )
print statsCollection.fileEntries[j].means
print _("Medians" )
print statsCollection.fileEntries[j].medians
print _("Minimums" )
print statsCollection.fileEntries[j].minimums
print _("Maximums" )
print statsCollection.fileEntries[j].maximums
print _("Time where max occured :" )
print statsCollection.fileEntries[j].timesWhereMaxOccured
print _("Total" )
print statsCollection.fileEntries[j].totals
print _("Files over maximum latency" )
print statsCollection.fileEntries[j].filesOverMaxLatency
if outputFile != "":
fileHandle.close()
sys.stdout = old_stdout #resets standard output
def changeInUpdateFrenquencyFoundDuringTimespan( self, startTime, endTime ):
"""
@summary : Searchs whether or not there was a change during the specified timespan.
@param statTime : Start time in the iso format of the time span to survey.
@param endTime : End time in the iso format of the time span to survey/
@return : True or false whether there was a change or not, plus the original
frequency and the new frequency.
"""
changeWasMade = False
paths = StatsPaths()
paths.setPaths()
updatesDoneDuringTimespan = self.__getAutomaticUpdatesDoneDuringTimeSpan( startTime, endTime )
updatesDoneDuringTimespan.sort()
if updatesDoneDuringTimespan != []:
fileName = paths.STATSTEMPAUTUPDTLOGS + str(updatesDoneDuringTimespan[0]).replace( " ", "_" )
originalUpdateFrequency = CpickleWrapper.load(fileName)
newUpdateFrequency = originalUpdateFrequency
for update in updatesDoneDuringTimespan:
fileName = paths.STATSTEMPAUTUPDTLOGS + str(update).replace( " ", "_" )
newUpdateFrequency = CpickleWrapper.load(fileName)
if newUpdateFrequency != originalUpdateFrequency:
changeWasMade = True
break
return changeWasMade, originalUpdateFrequency, newUpdateFrequency
def getMachineParametersFromPreviousCall() :
"""
@summary: Gets the machine parameters that are
saved in data/previousMachineParameters.
@return: Returns the saved machine parameters.
"""
paths = StatsPaths()
paths.setPaths()
previousMachineParams = None
if os.path.isfile( paths.STATSPREVIOUSMACHINEPARAMS ):
previousMachineParams = CpickleWrapper.load( paths.STATSPREVIOUSMACHINEPARAMS )
return previousMachineParams
def previousUpdateFrequency(self):
"""
@summary : Finds and returns the frequency
of the previous update.
@return : The freqency of the previous update.
"""
paths = StatsPaths()
paths.setPaths()
lastUpdate = self.getTimeOfLastUpdateInLogs()
fileName = paths.STATSTEMPAUTUPDTLOGS + str(lastUpdate).replace( " ", "_" )
lastUpdateFrequency = CpickleWrapper.load(fileName)
return lastUpdateFrequency
def getMachineParametersFromPreviousCall():
"""
@summary: Gets the machine parameters that are
saved in data/previousMachineParameters.
@return: Returns the saved machine parameters.
"""
paths = StatsPaths()
paths.setPaths()
previousMachineParams = None
if os.path.isfile(paths.STATSPREVIOUSMACHINEPARAMS):
previousMachineParams = CpickleWrapper.load(
paths.STATSPREVIOUSMACHINEPARAMS)
return previousMachineParams
def mergePicklesFromSameHour( logger = None , pickleNames = None, mergedPickleName = "",\
clientName = "" , combinedMachineName = "", currentTime = "",\
fileType = "tx" ):
"""
@summary: This methods receives a list of filenames referring to pickled FileStatsEntries.
After the merger pickles get saved since they might be reused somewhere else.
@precondition: Pickle should be of the same timespan and bucket width.
If not no merging will occur.
"""
if logger != None :
logger.debug( _("Call to mergePickles received.") )
logging = True
else:
logging = False
entryList = []
for pickle in pickleNames:#for every pickle we eneed to merge
if os.path.isfile( pickle ):
entryList.append( CpickleWrapper.load( pickle ) )
else:#Use empty entry if there is no existing pickle of that name
endTime = StatsDateLib.getIsoFromEpoch( StatsDateLib.getSecondsSinceEpoch( currentTime ) + StatsDateLib.HOUR )
entryList.append( FileStatsCollector( startTime = currentTime, endTime = endTime,logger =logger, logging =logging ) )
if logger != None :
logger.warning( _("Pickle named %s did not exist. Empty entry was used instead.") %pickle )
#start off with a carbon copy of first pickle in list.
newFSC = FileStatsCollector( files = entryList[0].files , statsTypes = entryList[0].statsTypes, startTime = entryList[0].startTime,\
endTime = entryList[0].endTime, interval=entryList[0].interval, totalWidth = entryList[0].totalWidth,\
firstFilledEntry = entryList[0].firstFilledEntry, lastFilledEntry = entryList[0].lastFilledEntry,\
maxLatency = entryList[0].maxLatency, fileEntries = entryList[0].fileEntries,logger = logger,\
logging = logging )
if PickleMerging.entryListIsValid( entryList ) == True :
for i in range ( 1 , len( entryList ) ): #add other entries
for file in entryList[i].files :
if file not in newFSC.files :
newFSC.files.append( file )
for j in range( len( newFSC.fileEntries ) ) : # add all entries
newFSC.fileEntries[j].values.productTypes.extend( entryList[i].fileEntries[j].values.productTypes )
newFSC.fileEntries[j].files.extend( entryList[i].fileEntries[j].files )
newFSC.fileEntries[j].times.extend( entryList[i].fileEntries[j].times )
newFSC.fileEntries[j].nbFiles = newFSC.fileEntries[j].nbFiles + ( newFSC.fileEntries[ j ].nbFiles)
for type in newFSC.statsTypes :
newFSC.fileEntries[j].values.dictionary[type].extend( entryList[i].fileEntries[j].values.dictionary[type] )
newFSC.fileEntries[j].values.rows = newFSC.fileEntries[j].values.rows + entryList[i].fileEntries[j].values.rows
newFSC = newFSC.setMinMaxMeanMedians( startingBucket = 0 , finishingBucket = newFSC.nbEntries -1 )
else:#Did not merge pickles named. Pickle list was not valid."
if logger != None :
logger.warning( _("Did not merge pickles named : %s. Pickle list was not valid.") %pickleNames )
logger.warning( _("Filled with empty entries instead.") %pickleNames )
newFSC.fileEntries = PickleMerging.fillWithEmptyEntries( nbEmptyEntries = 60 , entries = {} )
#prevents us from having ro remerge file later on.
temp = newFSC.logger
del newFSC.logger
CpickleWrapper.save( newFSC, mergedPickleName )
try:
os.chmod( mergedPickleName, 0777 )
except:
pass
#print "saved :%s" %mergedPickleName
newFSC.logger = temp
return newFSC
def mergePicklesFromSameHour( logger = None , pickleNames = None, mergedPickleName = "",\
clientName = "" , combinedMachineName = "", currentTime = "",\
fileType = "tx" ):
"""
@summary: This methods receives a list of filenames referring to pickled FileStatsEntries.
After the merger pickles get saved since they might be reused somewhere else.
@precondition: Pickle should be of the same timespan and bucket width.
If not no merging will occur.
"""
if logger != None:
logger.debug(_("Call to mergePickles received."))
logging = True
else:
logging = False
entryList = []
for pickle in pickleNames: #for every pickle we eneed to merge
if os.path.isfile(pickle):
entryList.append(CpickleWrapper.load(pickle))
else: #Use empty entry if there is no existing pickle of that name
endTime = StatsDateLib.getIsoFromEpoch(
StatsDateLib.getSecondsSinceEpoch(currentTime) +
StatsDateLib.HOUR)
entryList.append(
FileStatsCollector(startTime=currentTime,
endTime=endTime,
logger=logger,
logging=logging))
if logger != None:
logger.warning(
_("Pickle named %s did not exist. Empty entry was used instead."
) % pickle)
#start off with a carbon copy of first pickle in list.
newFSC = FileStatsCollector( files = entryList[0].files , statsTypes = entryList[0].statsTypes, startTime = entryList[0].startTime,\
endTime = entryList[0].endTime, interval=entryList[0].interval, totalWidth = entryList[0].totalWidth,\
firstFilledEntry = entryList[0].firstFilledEntry, lastFilledEntry = entryList[0].lastFilledEntry,\
maxLatency = entryList[0].maxLatency, fileEntries = entryList[0].fileEntries,logger = logger,\
logging = logging )
if PickleMerging.entryListIsValid(entryList) == True:
for i in range(1, len(entryList)): #add other entries
for file in entryList[i].files:
if file not in newFSC.files:
newFSC.files.append(file)
for j in range(len(newFSC.fileEntries)): # add all entries
newFSC.fileEntries[j].values.productTypes.extend(
entryList[i].fileEntries[j].values.productTypes)
newFSC.fileEntries[j].files.extend(
entryList[i].fileEntries[j].files)
newFSC.fileEntries[j].times.extend(
entryList[i].fileEntries[j].times)
newFSC.fileEntries[j].nbFiles = newFSC.fileEntries[
j].nbFiles + (newFSC.fileEntries[j].nbFiles)
for type in newFSC.statsTypes:
newFSC.fileEntries[j].values.dictionary[type].extend(
entryList[i].fileEntries[j].values.dictionary[type]
)
newFSC.fileEntries[j].values.rows = newFSC.fileEntries[
j].values.rows + entryList[i].fileEntries[j].values.rows
newFSC = newFSC.setMinMaxMeanMedians(
startingBucket=0, finishingBucket=newFSC.nbEntries - 1)
else: #Did not merge pickles named. Pickle list was not valid."
if logger != None:
logger.warning(
_("Did not merge pickles named : %s. Pickle list was not valid."
) % pickleNames)
logger.warning(
_("Filled with empty entries instead.") % pickleNames)
newFSC.fileEntries = PickleMerging.fillWithEmptyEntries(
nbEmptyEntries=60, entries={})
#prevents us from having ro remerge file later on.
temp = newFSC.logger
del newFSC.logger
CpickleWrapper.save(newFSC, mergedPickleName)
try:
os.chmod(mergedPickleName, 0777)
except:
pass
#print "saved :%s" %mergedPickleName
newFSC.logger = temp
return newFSC
def mergePicklesFromDifferentHours( logger = None , startTime = "2006-07-31 13:00:00",\
endTime = "2006-07-31 19:00:00", client = "satnet",\
machine = "pdsPM", fileType = "tx" ):
"""
@summary : This method merges entire hourly pickles files together.
@None : This does not support merging part of the data of pickles.
"""
if logger != None:
logger.debug(_("Call to mergeHourlyPickles received."))
logging = True
else:
logging = False
pickles = []
entries = {}
width = StatsDateLib.getSecondsSinceEpoch(
endTime) - StatsDateLib.getSecondsSinceEpoch(startTime)
startTime = StatsDateLib.getIsoWithRoundedHours(startTime)
seperators = [startTime]
seperators.extend(
StatsDateLib.getSeparatorsWithStartTime(startTime=startTime,
width=width,
interval=60 *
StatsDateLib.MINUTE)[:-1])
for seperator in seperators:
pickles.append(
StatsPickler.buildThisHoursFileName(client=client,
offset=0,
currentTime=seperator,
machine=machine,
fileType=fileType))
startingNumberOfEntries = 0
#print "prior to loading and merging pickles : %s " %( StatsDateLib.getIsoFromEpoch( time.time() ) )
for pickle in pickles:
if os.path.isfile(pickle):
tempCollection = CpickleWrapper.load(pickle)
if tempCollection != None:
for i in xrange(len(tempCollection.fileEntries)):
entries[startingNumberOfEntries +
i] = tempCollection.fileEntries[i]
startingNumberOfEntries = startingNumberOfEntries + len(
tempCollection.fileEntries)
else:
sys.exit()
else:
emptyEntries = PickleMerging.fillWithEmptyEntries(
nbEmptyEntries=60, entries={})
for i in xrange(60):
entries[i + startingNumberOfEntries] = emptyEntries[i]
startingNumberOfEntries = startingNumberOfEntries + 60
#print "after the loading and merging og pickles : %s " %( StatsDateLib.getIsoFromEpoch( time.time() ) )
statsCollection = FileStatsCollector(startTime=startTime,
endTime=endTime,
interval=StatsDateLib.MINUTE,
totalWidth=width,
fileEntries=entries,
fileType=fileType,
logger=logger,
logging=logging)
return statsCollection
