def dictionary():
# Création de dictionnaire en chargeant le jeu de données (dataset) (.txt)
for i in xrange(len(line_dataset) - 1):
# xrange() Génèration des nombres à la demande
# range() pré-calcule tous les nombres et les enregistre en mémoire, ce qui provoque l'erreur.
if not re.match(r'([\d]+)', line_dataset[i]):
line_temp = i
for i in xrange(line_temp + 1, len(line_dataset) - 1):
list_source_destination.append(
(int(line_dataset[i].strip().split(" ")[0]),
int(line_dataset[i].strip().split(" ")[1]),
float(line_dataset[i].strip().split(" ")[2])))
list_keys.append(int(line_dataset[i].strip().split(" ")[0]))
def mul(n1, n2):
n1.reverse()
n2.reverse()
n3 = []
print(n1, n2)
for i0 in xrange(len(n1) + len(n2)):
n3.append(0)
for i1 in xrange(len(n1)):
for i2 in xrange(len(n2)):
n3[i1 + i2] += n1[i1] * n2[i2]
for i3 in xrange(len(n3)):
if (n3[i3] > 9):
n3[i3 + 1] += n3[i3] / 10
n3[i3] = n3[i3] % 10
n3.reverse()
return n3
def dijAlgo(lists_sources_lists):
for k in xrange(len(list_keys)):
for unit in list_source_destination:
if unit[0] == k:
lists_sources_lists.append((unit[1], unit[2]))
else:
pass
if len(lists_sources_lists) != 0:
graph_dijkstra[k] = lists_sources_lists
lists_sources_lists = []
def genTestData(es):
eventnamelst = [
'Acceleration',
'Deceleration',
'Sharp_Turn',
'LDWS',
'OverSpeed',
'OverEngine',
'Panic',
'Gsensor',
'Vloss_1',
'Vloss_2',
'Vloss_3',
'Vloss_4',
'Vloss_5',
'Vloss_6',
'Vloss_7',
'Vloss_8',
'SSD_Error',
'SD_Error',
'System_Error',
'ACC_ON',
'ACC_OFF',
'Alarm_1',
'Alarm_2',
'Alarm_3',
'Alarm_4',
'Alarm_5',
'Alarm_6',
'Alarm_7',
'Alarm_8',
'USER_DOWNLOAD',
]
eventlen = len(eventnamelst) - 1
carlen = 10
index_name = "es_event"
utctime, strtime = __getEpochtimeDay(2021, 5, 1)
logging.info(f"utctime={utctime}")
for i in xrange(0, 10000):
randev = random.randint(0, eventlen)
randcar = random.randint(0, carlen)
randyear = random.randint(2020, 2022)
randmonth = random.randint(1, 12)
randday = random.randint(1, 28)
utctime, strtime = __getEpochtimeDay(randyear, randmonth, randday)
testdata = {
"date": utctime,
"hdate": strtime,
"car_uid": f"car{randcar:06d}",
"event_name": f"{eventnamelst[randev]}",
"interval": "month",
"desc": f"desc-{utctime}"
}
es.index(index=index_name, body=testdata)
def execute(self, function, *args, **kwargs):
# step 1
for x in xrange(LOOPS):
self.call(function, *args, **kwargs)
del x
gc.collect()
rss1 = self.get_mem()
# step 2
for x in xrange(LOOPS):
self.call(function, *args, **kwargs)
del x
gc.collect()
rss2 = self.get_mem()
# comparison
difference = rss2 - rss1
if difference > TOLERANCE:
# This doesn't necessarily mean we have a leak yet.
# At this point we assume that after having called the
# function so many times the memory usage is stabilized
# and if there are no leaks it should not increase any
# more.
# Let's keep calling fun for 3 more seconds and fail if
# we notice any difference.
stop_at = time.time() + 3
while 1:
self.call(function, *args, **kwargs)
if time.time() >= stop_at:
break
del stop_at
gc.collect()
rss3 = self.get_mem()
difference = rss3 - rss2
if rss3 > rss2:
self.fail("rss2=%s, rss3=%s, difference=%s" \
% (rss2, rss3, difference))
def get_files_by_file_size(dirname, reverse=False):
""" Return list of file paths in directory sorted by file size """
# Get list of files
filepaths = []
for basename in os.listdir(dirname):
filename = os.path.join(dirname, basename)
if os.path.isfile(filename):
filepaths.append(filename)
# Re-populate list with filename, size tuples
for i in xrange(len(filepaths)):
filepaths[i] = (filepaths[i], os.path.getsize(filepaths[i]))
# Sort list by file size
# If reverse=True sort from largest to smallest
# If reverse=False sort from smallest to largest
filepaths.sort(key=lambda filename: filename[1], reverse=reverse)
# Re-populate list with just filenames
for i in xrange(len(filepaths)):
filepaths[i] = filepaths[i][0]
return filepaths
def dataset_with_dict():
# Variable locale pour l'ensemble de données (dataset)
f = open('metro_paris.txt', 'r') # Ouverture de fichier
stations_with_dictinary = []
my_stations_with_dict = {}
for unit in f.readlines()[1:]:
if unit.strip(
) != '[Edges]': #Tant que la ligne représente un nom d'une station
stations_with_dictinary.append(unit[5:])
else:
break
for i in xrange(len(
stations_with_dictinary)): # Convertir la liste en dictionnaire
my_stations_with_dict[i] = stations_with_dictinary[i]
return my_stations_with_dict
def call_many_times():
for x in xrange(LOOPS - 1):
self.call(function, *args, **kwargs)
del x
gc.collect()
return self.get_mem()
def call_many_times():
for x in xrange(LOOPS - 1):
self.call(function, *args, **kwargs)
del x
gc.collect()
return self.get_mem()
def cpu_affinity_get(self):
from_bitmask = lambda x: [i for i in xrange(64) if (1 << i) & x]
bitmask = cext.proc_cpu_affinity_get(self.pid)
return from_bitmask(bitmask)
def cpu_affinity_get(self):
from_bitmask = lambda x: [i for i in xrange(64) if (1 << i) & x]
bitmask = cext.proc_cpu_affinity_get(self.pid)
return from_bitmask(bitmask)
def call_many_times():
for x in xrange(loops):
self._call(fun, *args, **kwargs)
del x
gc.collect()
def get_process_cpu_affinity(self):
from_bitmask = lambda x: [i for i in xrange(64) if (1 << i) & x]
bitmask = _psutil_linux.get_process_cpu_affinity(self.pid)
return from_bitmask(bitmask)
def get_process_cpu_affinity(self):
from_bitmask = lambda x: [i for i in xrange(64) if (1 << i) & x]
bitmask = _psutil_mswindows.get_process_cpu_affinity(self.pid)
return from_bitmask(bitmask)
def call_many_times():
for x in xrange(loops):
self._call(fun, *args, **kwargs)
del x
gc.collect()
randyear = random.randint(2020, 2022)
randmonth = random.randint(1, 12)
randday = random.randint(1, 28)
utctime, strtime = __getEpochtimeDay(randyear, randmonth, randday)
testdata = {
"date": utctime,
"hdate": strtime,
"car_uid": f"car{randcar:06d}",
"event_name": f"{eventnamelst[randev]}",
"interval": "month",
"desc": f"desc-{utctime}"
}
es.index(index=index_name, body=testdata)
def unit_test():
for i in xrange(0, 12):
randmonth = random.randint(1, 12)
randday = random.randint(1, 28)
print(f"month={randmonth} randday={randday}")
if __name__ == "__main__":
es = Elasticsearch(hosts="192.168.83.129", port=9200)
for i in xrange(0, 100):
genTestData(es)
sleep(500 / 1000)
# unit_test()
def unit_test():
for i in xrange(0, 12):
randmonth = random.randint(1, 12)
randday = random.randint(1, 28)
print(f"month={randmonth} randday={randday}")
