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