stable/freqtrade/rpc/api_server/ws/serializer.py
2022-08-29 15:48:29 -06:00

66 lines
1.6 KiB
Python

import json
import logging
from abc import ABC, abstractmethod
import msgpack
import orjson
from freqtrade.rpc.api_server.ws.proxy import WebSocketProxy
logger = logging.getLogger(__name__)
class WebSocketSerializer(ABC):
def __init__(self, websocket: WebSocketProxy):
self._websocket: WebSocketProxy = websocket
@abstractmethod
def _serialize(self, data):
raise NotImplementedError()
@abstractmethod
def _deserialize(self, data):
raise NotImplementedError()
async def send(self, data: bytes):
await self._websocket.send(self._serialize(data))
async def recv(self) -> bytes:
data = await self._websocket.recv()
return self._deserialize(data)
async def close(self, code: int = 1000):
await self._websocket.close(code)
# Going to explore using MsgPack as the serialization,
# as that might be the best method for sending pandas
# dataframes over the wire
class JSONWebSocketSerializer(WebSocketSerializer):
def _serialize(self, data):
return json.dumps(data)
def _deserialize(self, data):
return json.loads(data)
class ORJSONWebSocketSerializer(WebSocketSerializer):
ORJSON_OPTIONS = orjson.OPT_NAIVE_UTC | orjson.OPT_SERIALIZE_NUMPY
def _serialize(self, data):
return orjson.dumps(data, option=self.ORJSON_OPTIONS)
def _deserialize(self, data):
return orjson.loads(data)
class MsgPackWebSocketSerializer(WebSocketSerializer):
def _serialize(self, data):
return msgpack.packb(data, use_bin_type=True)
def _deserialize(self, data):
return msgpack.unpackb(data, raw=False)