def fastmsgpack_object_hook(ob):
typ = ob.get('typ')
if typ is None:
return ob
if typ == 'nat':
return pd.NaT
if typ == 'block_manager':
df = pd_msgpack_object_hook(ob)
for block in df._data.blocks:
values = block.values
if not values.flags.writeable:
if sys.getrefcount(_final_base(values)) == 2:
# Compatibility shim until this is fixed in pandas
# See: https://github.com/pydata/pandas/pull/12359
# Mark that we own the memory for this block.
# We know that we own it because the only 2 references
# for the base object are the values of this block and
# TOS because we are passing this object to a function.
values.flags.writeable = True
else:
# If we cannot 'safely' make the bytes object mutable
# then just copy the data.
block.values = values.copy()
return df
return pd_msgpack_object_hook(ob)
def fastmsgpack_object_hook(ob):
typ = ob.get('typ')
if typ is None:
return ob
if typ == 'nat':
return pd.NaT
if typ == 'block_manager':
df = pd_msgpack_object_hook(ob)
for block in df._data.blocks:
values = block.values
if not values.flags.writeable:
if sys.getrefcount(_final_base(values)) == 2:
# Compatibility shim until this is fixed in pandas
# See: https://github.com/pydata/pandas/pull/12359
# Mark that we own the memory for this block.
# We know that we own it because the only 2 references
# for the base object are the values of this block and
# TOS because we are passing this object to a function.
values.flags.writeable = True
else:
# If we cannot 'safely' make the bytes object mutable
# then just copy the data.
block.values = values.copy()
return df
return pd_msgpack_object_hook(ob)