def run(path, days, notPacked):
f = open(path, "rb")
f.seek(0, 2)
now = datetime.date.today()
#day->size
stats = {}
th = prev_txn(f)
bool = True
while bool:
ts = TimeStamp(th.tid)
then = datetime.date(int(ts.year()), int(ts.month()), int(ts.day()))
delta = timedelta(days=int(days))
if( not(now - then < delta)):
bool = False
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
for i in iterator:
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
try:
stats[ot] = stats[ot] + 1
except KeyError:
stats[ot] = 1
f.close()
for (o,n) in sorted(stats.items(), key=lambda (k,v): v, reverse=True):
print "%6d: %s" % (n,o)
def run(path, days, notPacked):
f = open(path, "rb")
f.seek(0, 2)
now = datetime.date.today()
#day->size
stats = {}
th = prev_txn(f)
bool = True
while bool:
ts = TimeStamp(th.tid)
then = datetime.date(int(ts.year()), int(ts.month()), int(ts.day()))
delta = timedelta(days=int(days))
if( not(now - then < delta)):
bool = False
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
for i in iterator:
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
try:
stats[ot] = stats[ot] + 1
except KeyError:
stats[ot] = 1
f.close()
for (o,n) in sorted(stats.items(), key=lambda (k,v): v, reverse=True):
print "%6d: %s" % (n,o)
def run(path, tid):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
while (str(TimeStamp(th.tid)) != tid):
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
header = TxnHeader(f, th._pos)
for i in iterator:
if (str(TimeStamp(i.tid)) == tid):
print "\nTRANSACTION: ", TimeStamp(
i.tid), i.user, i.description, pretty_size(header.length), "\n"
header = header.next_txn()
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
print " - ", ot, pretty_size(len(o.data))
ob = cPickle.loads(o.data)
# Not sure why some objects are stored as tuple (object, ())
if type(ob) == tuple and len(ob) == 2:
ob = ob[0]
if hasattr(ob, "__dict__"):
for i in ob.__dict__.items():
if str(i[0]) == "__doc__":
print "\t('__doc__',", i[1], ")"
elif not callable(i[1]):
print "\t", i
else:
print "can't extract:" + str(ob)
break
f.close()
def run(path, tid):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
while (str(TimeStamp(th.tid)) != tid):
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
header = TxnHeader(f,th._pos)
for i in iterator:
if(str(TimeStamp(i.tid)) == tid):
print "\nTRANSACTION: ", TimeStamp(i.tid), i.user, i.description, pretty_size(header.length),"\n"
header = header.next_txn()
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
print " - ", ot, pretty_size(len(o.data))
ob = cPickle.loads(o.data)
# Not sure why some objects are stored as tuple (object, ())
if type(ob) == tuple and len(ob) == 2:
ob = ob[0]
if hasattr(ob, "__dict__"):
for i in ob.__dict__.items():
if str(i[0]) == "__doc__":
print "\t('__doc__',", i[1],")"
elif not callable(i[1]):
print "\t",i
else:
print "can't extract:" + str(ob)
break
f.close()
def run(path, ntxn, orderTransactions):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
for i in range(ntxn - 1):
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
header = TxnHeader(f, th._pos)
transactions = []
for i in iterator:
transactions.append({
"tid": TimeStamp(i.tid),
"user": i.user,
"desc": i.description,
"len": header.length,
"objs": None
})
header = header.next_txn()
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
if ot in object_types:
size, count = object_types[ot]
object_types[ot] = (size + len(o.data), count + 1)
else:
object_types[ot] = (len(o.data), 1)
keys = object_types.keys()
transactions[-1]["objs"] = object_types
f.close()
if orderTransactions:
transactions = sorted(transactions,
key=lambda (d): d["len"],
reverse=True)
for tr in transactions:
print "\n\nTRANSACTION: ", tr["tid"], tr["user"], tr[
"desc"], pretty_size(tr["len"])
object_types = tr["objs"]
keys = object_types.keys()
for k in sorted(keys, key=lambda (k): object_types[k][0],
reverse=True):
# count, class, size (aggregate)
print " - ", object_types[k][1], k, pretty_size(object_types[k][0])
def main(path, ntxn):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
i = ntxn
while th and i > 0:
hash = sha1(th.get_raw_data()).digest()
l = len(str(th.get_timestamp())) + 1
th.read_meta()
print "%s: hash=%s" % (th.get_timestamp(), binascii.hexlify(hash))
print("user=%r description=%r length=%d offset=%d" %
(th.user, th.descr, th.length, th.get_data_offset()))
print
th = th.prev_txn()
i -= 1
def main(path, ntxn):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
i = ntxn
while th and i > 0:
hash = sha1(th.get_raw_data()).digest()
l = len(str(th.get_timestamp())) + 1
th.read_meta()
print "%s: hash=%s" % (th.get_timestamp(),
binascii.hexlify(hash))
print ("user=%r description=%r length=%d offset=%d"
% (th.user, th.descr, th.length, th.get_data_offset()))
print
th = th.prev_txn()
i -= 1
def run(path, ntxn, orderTransactions):
f = open(path, "rb")
f.seek(0, 2)
th = prev_txn(f)
for i in range(ntxn - 1):
th = th.prev_txn()
reader = Reader()
iterator = FileIterator(path, pos=th._pos)
header = TxnHeader(f, th._pos)
transactions = []
for i in iterator:
transactions.append(
{"tid": TimeStamp(i.tid), "user": i.user, "desc": i.description, "len": header.length, "objs": None}
)
header = header.next_txn()
object_types = {}
for o in i:
ot = reader.getIdentity(o.data)
if ot in object_types:
size, count = object_types[ot]
object_types[ot] = (size + len(o.data), count + 1)
else:
object_types[ot] = (len(o.data), 1)
keys = object_types.keys()
transactions[-1]["objs"] = object_types
f.close()
if orderTransactions:
transactions = sorted(transactions, key=lambda (d): d["len"], reverse=True)
for tr in transactions:
print "\n\nTRANSACTION: ", tr["tid"], tr["user"], tr["desc"], pretty_size(tr["len"])
object_types = tr["objs"]
keys = object_types.keys()
for k in sorted(keys, key=lambda (k): object_types[k][0], reverse=True):
# count, class, size (aggregate)
print " - ", object_types[k][1], k, pretty_size(object_types[k][0])
def run(path, days, notPacked):
f = open(path, "rb")
f.seek(0, 2)
size = os.path.getsize(path)
now = datetime.date.today()
notPackedDays = []
for day in range(notPacked):
notPackedDays.append(str(now - timedelta(days=day + 1)))
# day->size
stats = {}
th = prev_txn(f)
bool = True
while bool:
ts = TimeStamp(th.tid)
then = datetime.date(int(ts.year()), int(ts.month()), int(ts.day()))
delta = timedelta(days=int(days))
if now - then < delta:
dateT = strftime("%Y-%m-%d", [int(ts.year()), int(ts.month()), int(ts.day()), 1, 1, 1, 1, 1, 1])
try:
stats[dateT] = stats[dateT] + th.length
except KeyError:
stats[dateT] = th.length
else:
bool = False
th = th.prev_txn()
f.close()
total = 0
totalPacked = 0
daysPacked = 0
for (d, s) in sorted(stats.items(), key=lambda (k, v): v, reverse=True):
print d, "size:", pretty_size(s),
date = str(d)
if date in notPackedDays or date == str(now):
print "(not yet packed)"
else:
totalPacked = totalPacked + s
daysPacked = daysPacked + 1
print
total = total + s
if int(totalPacked):
average = totalPacked / int(daysPacked)
else:
average = 0
print "\n-- ALREADY PACKED DAYS--"
print "The amount of data added in", daysPacked, "days is", pretty_size(totalPacked)
print "Average", pretty_size(average), "per day"
print "Following this trend, the size of the database will be:"
print "\t", pretty_size(average * 365 + size), " in 1 year"
print "\t", pretty_size(average * 365 * 2 + size), " in 2 years"
print "\t", pretty_size(average * 365 * 10 + size), " in 10 years"
print "\n-- ALL DAYS --"
print "The amount of data added in", days, "days is", pretty_size(total)
if int(total):
print "Average", pretty_size(total / int(days)), "per day"
else:
print "Average 0bytes per day"
def run(path, days, notPacked):
f = open(path, "rb")
f.seek(0, 2)
size = os.path.getsize(path)
now = datetime.date.today()
notPackedDays = []
for day in range(notPacked):
notPackedDays.append(str(now - timedelta(days=day + 1)))
#day->size
stats = {}
th = prev_txn(f)
bool = True
while bool:
ts = TimeStamp(th.tid)
then = datetime.date(int(ts.year()), int(ts.month()), int(ts.day()))
delta = timedelta(days=int(days))
if (now - then < delta):
dateT = strftime("%Y-%m-%d", [
int(ts.year()),
int(ts.month()),
int(ts.day()), 1, 1, 1, 1, 1, 1
])
try:
stats[dateT] = stats[dateT] + th.length
except KeyError:
stats[dateT] = th.length
else:
bool = False
th = th.prev_txn()
f.close()
total = 0
totalPacked = 0
daysPacked = 0
for (d, s) in sorted(stats.items(), key=lambda (k, v): v, reverse=True):
print d, "size:", pretty_size(s),
date = str(d)
if (date in notPackedDays or date == str(now)):
print "(not yet packed)"
else:
totalPacked = totalPacked + s
daysPacked = daysPacked + 1
print
total = total + s
if int(totalPacked):
average = totalPacked / int(daysPacked)
else:
average = 0
print "\n-- ALREADY PACKED DAYS--"
print "The amount of data added in", daysPacked, "days is", pretty_size(
totalPacked)
print "Average", pretty_size(average), "per day"
print "Following this trend, the size of the database will be:"
print "\t", pretty_size(average * 365 + size), " in 1 year"
print "\t", pretty_size(average * 365 * 2 + size), " in 2 years"
print "\t", pretty_size(average * 365 * 10 + size), " in 10 years"
print "\n-- ALL DAYS --"
print "The amount of data added in", days, "days is", pretty_size(total)
if int(total):
print "Average", pretty_size(total / int(days)), "per day"
else:
print "Average 0bytes per day"