def save_dictionary(data, filename):
"""Save dictionary in a single file .spydata file"""
filename = osp.abspath(filename)
old_cwd = getcwd_or_home()
os.chdir(osp.dirname(filename))
error_message = None
# Copy dictionary before modifying to fix #6689
try:
data = copy.deepcopy(data)
except NotImplementedError:
try:
data = copy.copy(data)
except Exception:
data = data
try:
saved_arrays = {}
if load_array is not None:
# Saving numpy arrays with np.save
arr_fname = osp.splitext(filename)[0]
for name in list(data.keys()):
if isinstance(data[name], np.ndarray) and data[name].size > 0:
# Saving arrays at data root
fname = __save_array(data[name], arr_fname,
len(saved_arrays))
saved_arrays[(name, None)] = osp.basename(fname)
data.pop(name)
elif isinstance(data[name], (list, dict)):
# Saving arrays nested in lists or dictionaries
if isinstance(data[name], list):
iterator = enumerate(data[name])
else:
iterator = iter(list(data[name].items()))
to_remove = []
for index, value in iterator:
if isinstance(value, np.ndarray) and value.size > 0:
fname = __save_array(value, arr_fname,
len(saved_arrays))
saved_arrays[(name, index)] = osp.basename(fname)
to_remove.append(index)
for index in sorted(to_remove, reverse=True):
data[name].pop(index)
if saved_arrays:
data['__saved_arrays__'] = saved_arrays
pickle_filename = osp.splitext(filename)[0] + '.pickle'
with open(pickle_filename, 'w+b') as fdesc:
pickle.dump(data, fdesc, 2)
tar = tarfile.open(filename, "w")
for fname in [pickle_filename
] + [fn for fn in list(saved_arrays.values())]:
tar.add(osp.basename(fname))
os.remove(fname)
tar.close()
if saved_arrays:
data.pop('__saved_arrays__')
except (RuntimeError, pickle.PicklingError, TypeError) as error:
error_message = to_text_string(error)
os.chdir(old_cwd)
return error_message
def save_dictionary(data, filename):
"""Save dictionary in a single file .spydata file"""
filename = osp.abspath(filename)
old_cwd = getcwd_or_home()
os.chdir(osp.dirname(filename))
error_message = None
try:
saved_arrays = {}
if load_array is not None:
# Saving numpy arrays with np.save
arr_fname = osp.splitext(filename)[0]
for name in list(data.keys()):
if isinstance(data[name], np.ndarray) and data[name].size > 0:
# Saving arrays at data root
fname = __save_array(data[name], arr_fname,
len(saved_arrays))
saved_arrays[(name, None)] = osp.basename(fname)
data.pop(name)
elif isinstance(data[name], (list, dict)):
# Saving arrays nested in lists or dictionaries
if isinstance(data[name], list):
iterator = enumerate(data[name])
else:
iterator = iter(list(data[name].items()))
to_remove = []
for index, value in iterator:
if isinstance(value, np.ndarray) and value.size > 0:
fname = __save_array(value, arr_fname,
len(saved_arrays))
saved_arrays[(name, index)] = osp.basename(fname)
to_remove.append(index)
for index in sorted(to_remove, reverse=True):
data[name].pop(index)
if saved_arrays:
data['__saved_arrays__'] = saved_arrays
pickle_filename = osp.splitext(filename)[0]+'.pickle'
with open(pickle_filename, 'wb') as fdesc:
pickle.dump(data, fdesc, 2)
tar = tarfile.open(filename, "w")
for fname in [pickle_filename]+[fn for fn in list(saved_arrays.values())]:
tar.add(osp.basename(fname))
os.remove(fname)
tar.close()
if saved_arrays:
data.pop('__saved_arrays__')
except (RuntimeError, pickle.PicklingError, TypeError) as error:
error_message = to_text_string(error)
os.chdir(old_cwd)
return error_message
def save(self):
while len(self.rdata) > self.max_entries:
self.rdata.pop(-1)
pickle.dump([self.VERSION] + self.rdata, open(self.DATAPATH, 'wb'), 2)
def save(self):
while len(self.rdata) > self.max_entries:
self.rdata.pop(-1)
pickle.dump([self.VERSION]+self.rdata, open(self.DATAPATH, 'wb'), 2)
