def transformer(old_data):
row = {}
for k, v in old_data.items():
if k == "id":
continue
d = msgpackext_dumps(converters[k](v))
row[k + "_"] = d
return row
def transformer(old_data):
arr = old_data["return_result"]
if arr is None:
pass
elif old_data["driver"] == "gradient":
arr = np.array(arr, dtype=float).reshape(-1, 3)
elif old_data["driver"] == "hessian":
arr = np.array(arr, dtype=float)
arr.shape = (-1, int(arr.shape[0]**0.5))
return {"return_result_": msgpackext_dumps(arr)}
def transformer(old_data):
extras = old_data["extras"]
extras.pop("_qcfractal_tags", None) # cleanup old tags
return {"extras_": msgpackext_dumps(extras)}
def transformer(old_data):
spec = old_data["extra"]
return {"extra_": msgpackext_dumps(spec)}
def process_bind_param(self, value, dialect):
if value is None:
return value
else:
return msgpackext_dumps(value)
def process_bind_param(self, value, dialect):
return msgpackext_dumps(value)
