def deserialize_object(buffers, g=None):
"""reconstruct an object serialized by serialize_object from data buffers.
Parameters
----------
bufs : list of buffers/bytes
g : globals to be used when uncanning
Returns
-------
(newobj, bufs) : unpacked object, and the list of remaining unused buffers.
"""
bufs = list(buffers)
pobj = buffer_to_bytes_py2(bufs.pop(0))
canned = pickle.loads(pobj)
if istype(canned, sequence_types) and len(canned) < MAX_ITEMS:
for c in canned:
_restore_buffers(c, bufs)
newobj = uncan_sequence(canned, g)
elif istype(canned, dict) and len(canned) < MAX_ITEMS:
newobj = {}
for k in sorted(canned):
c = canned[k]
_restore_buffers(c, bufs)
newobj[k] = uncan(c, g)
else:
_restore_buffers(canned, bufs)
newobj = uncan(canned, g)
return newobj, bufs
def deserialize_object(buffers, g=None):
"""reconstruct an object serialized by serialize_object from data buffers.
Parameters
----------
bufs : list of buffers/bytes
g : globals to be used when uncanning
Returns
-------
(newobj, bufs) : unpacked object, and the list of remaining unused buffers.
"""
bufs = list(buffers)
pobj = buffer_to_bytes_py2(bufs.pop(0))
canned = pickle.loads(pobj)
if istype(canned, sequence_types) and len(canned) < MAX_ITEMS:
for c in canned:
_restore_buffers(c, bufs)
newobj = uncan_sequence(canned, g)
elif istype(canned, dict) and len(canned) < MAX_ITEMS:
newobj = {}
for k in sorted(canned):
c = canned[k]
_restore_buffers(c, bufs)
newobj[k] = uncan(c, g)
else:
_restore_buffers(canned, bufs)
newobj = uncan(canned, g)
return newobj, bufs
def set_unique_id_int(data: Series, autoname_bolean_col: bool = True, return_map: bool = False) -> Series:
"""
Mengambil `Series` dengan nilai membernya menjadi id unik int.
:param data: pandas.Series.
:param return_map: `True` maka fungsi ini akan me-return map uniqeId-nya dari `unique_id_int` juga.
:param autoname_bolean_col: `True` -> jika kolom tipe `object` dengan nilai id hanya 2, maka nama kolom tersebut
akan diubah menjadi nilai yang memiliki nilai 1.
:return: pandas.Series dengan membernya id unik int.
"""
#print("afhaiuhgphagha")
if istype(data, DataFrame):
raise TypeError("`data` merupakan `DataFrame` yang dapat menyebabkan error karena tiap elemen iterasi "
"mengembalikan `Series`.")
ids = unique_id_int(data)
if autoname_bolean_col and len(ids.keys()) == 2:
data = data.copy()
new = None
for k in ids:
if ids[k] == 1:
new = k
break
if new is not None:
data.name = new
# noinspection PyTypeChecker
res = data.apply(lambda x: ids[x])
if not return_map:
return res
else:
return res, ids
def serialize_object(obj,
buffer_threshold=MAX_BYTES,
item_threshold=MAX_ITEMS):
"""Serialize an object into a list of sendable buffers.
Parameters
----------
obj : object
The object to be serialized
buffer_threshold : int
The threshold (in bytes) for pulling out data buffers
to avoid pickling them.
item_threshold : int
The maximum number of items over which canning will iterate.
Containers (lists, dicts) larger than this will be pickled without
introspection.
Returns
-------
[bufs] : list of buffers representing the serialized object.
"""
buffers = []
if istype(obj, sequence_types) and len(obj) < item_threshold:
cobj = can_sequence(obj)
for c in cobj:
buffers.extend(_extract_buffers(c, buffer_threshold))
elif istype(obj, dict) and len(obj) < item_threshold:
cobj = {}
for k in sorted(obj):
c = can(obj[k])
buffers.extend(_extract_buffers(c, buffer_threshold))
cobj[k] = c
else:
cobj = can(obj)
buffers.extend(_extract_buffers(cobj, buffer_threshold))
buffers.insert(0, pickle.dumps(cobj, PICKLE_PROTOCOL))
return buffers
def serialize_object(obj, buffer_threshold=MAX_BYTES, item_threshold=MAX_ITEMS):
"""Serialize an object into a list of sendable buffers.
Parameters
----------
obj : object
The object to be serialized
buffer_threshold : int
The threshold (in bytes) for pulling out data buffers
to avoid pickling them.
item_threshold : int
The maximum number of items over which canning will iterate.
Containers (lists, dicts) larger than this will be pickled without
introspection.
Returns
-------
[bufs] : list of buffers representing the serialized object.
"""
buffers = []
if istype(obj, sequence_types) and len(obj) < item_threshold:
cobj = can_sequence(obj)
for c in cobj:
buffers.extend(_extract_buffers(c, buffer_threshold))
elif istype(obj, dict) and len(obj) < item_threshold:
cobj = {}
for k in sorted(obj):
c = can(obj[k])
buffers.extend(_extract_buffers(c, buffer_threshold))
cobj[k] = c
else:
cobj = can(obj)
buffers.extend(_extract_buffers(cobj, buffer_threshold))
buffers.insert(0, pickle.dumps(cobj, PICKLE_PROTOCOL))
return buffers
