def test_serialize_and_deserialize_order_book_deltas_grouped(self):
kw = {
"instrument_id": "AUD/USD.SIM",
"ts_event": 0,
"ts_init": 0,
"book_type": "L2_MBP",
}
deltas = [
{
"action": "ADD",
"order_side": "SELL",
"order_price": 0.9901,
"order_size": 327.25,
"order_id": "1",
},
{
"action": "CLEAR",
"order_side": None,
"order_price": None,
"order_size": None,
"order_id": None,
},
{
"action": "ADD",
"order_side": "SELL",
"order_price": 0.98039,
"order_size": 27.91,
"order_id": "2",
},
{
"action": "ADD",
"order_side": "SELL",
"order_price": 0.97087,
"order_size": 14.43,
"order_id": "3",
},
]
deltas = OrderBookDeltas(
instrument_id=TestStubs.audusd_id(),
book_type=BookType.L2_MBP,
deltas=[OrderBookDelta.from_dict({
**kw,
**d
}) for d in deltas],
ts_event=0,
ts_init=0,
)
serialized = ParquetSerializer.serialize(deltas)
[deserialized] = ParquetSerializer.deserialize(cls=OrderBookDeltas,
chunk=serialized)
# Assert
assert deserialized == deltas
write_objects(catalog=self.catalog, chunk=[deserialized])
assert [d.action for d in deserialized.deltas] == [
BookAction.ADD,
BookAction.CLEAR,
BookAction.ADD,
BookAction.ADD,
]
def frame_to_nautilus(df: pd.DataFrame, cls: type) -> List[Any]:
return ParquetSerializer.deserialize(cls=cls, chunk=df.to_dict("records"))