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Merge pull request #7842 from wizrds/feat/refactor-emc

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Change to broadcasting single candles in Producer/Consumer
This commit is contained in:
Matthias 2022-12-15 19:47:29 +01:00 committed by GitHub
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10 changed files with 345 additions and 58 deletions
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1
freqtrade/constants.py
View File

@ -61,6 +61,7 @@ USERPATH_FREQAIMODELS = 'freqaimodels'
TELEGRAM_SETTING_OPTIONS = ['on', 'off', 'silent']
WEBHOOK_FORMAT_OPTIONS = ['form', 'json', 'raw']
FULL_DATAFRAME_THRESHOLD = 100
ENV_VAR_PREFIX = 'FREQTRADE__'

89
freqtrade/data/dataprovider.py
View File

@ -9,14 +9,16 @@ from collections import deque
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame
from pandas import DataFrame, to_timedelta
from freqtrade.configuration import TimeRange
from freqtrade.constants import Config, ListPairsWithTimeframes, PairWithTimeframe
from freqtrade.constants import (FULL_DATAFRAME_THRESHOLD, Config, ListPairsWithTimeframes,
PairWithTimeframe)
from freqtrade.data.history import load_pair_history
from freqtrade.enums import CandleType, RPCMessageType, RunMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.exchange import Exchange, timeframe_to_seconds
from freqtrade.misc import append_candles_to_dataframe
from freqtrade.rpc import RPCManager
from freqtrade.util import PeriodicCache
@ -120,7 +122,7 @@ class DataProvider:
'type': RPCMessageType.ANALYZED_DF,
'data': {
'key': pair_key,
'df': dataframe,
'df': dataframe.tail(1),
'la': datetime.now(timezone.utc)
}
}
@ -131,7 +133,7 @@ class DataProvider:
'data': pair_key,
})
def _add_external_df(
def _replace_external_df(
self,
pair: str,
dataframe: DataFrame,
@ -157,6 +159,85 @@ class DataProvider:
self.__producer_pairs_df[producer_name][pair_key] = (dataframe, _last_analyzed)
logger.debug(f"External DataFrame for {pair_key} from {producer_name} added.")
def _add_external_df(
self,
pair: str,
dataframe: DataFrame,
last_analyzed: datetime,
timeframe: str,
candle_type: CandleType,
producer_name: str = "default"
) -> Tuple[bool, int]:
"""
Append a candle to the existing external dataframe. The incoming dataframe
must have at least 1 candle.
:param pair: pair to get the data for
:param timeframe: Timeframe to get data for
:param candle_type: Any of the enum CandleType (must match trading mode!)
:returns: False if the candle could not be appended, or the int number of missing candles.
"""
pair_key = (pair, timeframe, candle_type)
if dataframe.empty:
# The incoming dataframe must have at least 1 candle
return (False, 0)
if len(dataframe) >= FULL_DATAFRAME_THRESHOLD:
# This is likely a full dataframe
# Add the dataframe to the dataprovider
self._replace_external_df(
pair,
dataframe,
last_analyzed=last_analyzed,
timeframe=timeframe,
candle_type=candle_type,
producer_name=producer_name
)
return (True, 0)
if (producer_name not in self.__producer_pairs_df
or pair_key not in self.__producer_pairs_df[producer_name]):
# We don't have data from this producer yet,
# or we don't have data for this pair_key
# return False and 1000 for the full df
return (False, 1000)
existing_df, _ = self.__producer_pairs_df[producer_name][pair_key]
# CHECK FOR MISSING CANDLES
timeframe_delta = to_timedelta(timeframe) # Convert the timeframe to a timedelta for pandas
local_last = existing_df.iloc[-1]['date'] # We want the last date from our copy
incoming_first = dataframe.iloc[0]['date'] # We want the first date from the incoming
# Remove existing candles that are newer than the incoming first candle
existing_df1 = existing_df[existing_df['date'] < incoming_first]
candle_difference = (incoming_first - local_last) / timeframe_delta
# If the difference divided by the timeframe is 1, then this
# is the candle we want and the incoming data isn't missing any.
# If the candle_difference is more than 1, that means
# we missed some candles between our data and the incoming
# so return False and candle_difference.
if candle_difference > 1:
return (False, candle_difference)
if existing_df1.empty:
appended_df = dataframe
else:
appended_df = append_candles_to_dataframe(existing_df1, dataframe)
# Everything is good, we appended
self._replace_external_df(
pair,
appended_df,
last_analyzed=last_analyzed,
timeframe=timeframe,
candle_type=candle_type,
producer_name=producer_name
)
return (True, 0)
def get_producer_df(
self,
pair: str,

18
freqtrade/misc.py
View File

@ -301,3 +301,21 @@ def remove_entry_exit_signals(dataframe: pd.DataFrame):
dataframe[SignalTagType.EXIT_TAG.value] = None
return dataframe
def append_candles_to_dataframe(left: pd.DataFrame, right: pd.DataFrame) -> pd.DataFrame:
"""
Append the `right` dataframe to the `left` dataframe
:param left: The full dataframe you want appended to
:param right: The new dataframe containing the data you want appended
:returns: The dataframe with the right data in it
"""
if left.iloc[-1]['date'] != right.iloc[-1]['date']:
left = pd.concat([left, right])
# Only keep the last 1500 candles in memory
left = left[-1500:] if len(left) > 1500 else left
left.reset_index(drop=True, inplace=True)
return left

3
freqtrade/rpc/api_server/api_ws.py
View File

@ -91,9 +91,10 @@ async def _process_consumer_request(
elif type == RPCRequestType.ANALYZED_DF:
# Limit the amount of candles per dataframe to 'limit' or 1500
limit = min(data.get('limit', 1500), 1500) if data else None
pair = data.get('pair', None) if data else None
# For every pair in the generator, send a separate message
for message in rpc._ws_request_analyzed_df(limit):
for message in rpc._ws_request_analyzed_df(limit, pair):
# Format response
response = WSAnalyzedDFMessage(data=message)
await channel.send(response.dict(exclude_none=True))

7
freqtrade/rpc/api_server/ws/channel.py
View File

@ -27,7 +27,8 @@ class WebSocketChannel:
self,
websocket: WebSocketType,
channel_id: Optional[str] = None,
serializer_cls: Type[WebSocketSerializer] = HybridJSONWebSocketSerializer
serializer_cls: Type[WebSocketSerializer] = HybridJSONWebSocketSerializer,
send_throttle: float = 0.01
):
self.channel_id = channel_id if channel_id else uuid4().hex[:8]
self._websocket = WebSocketProxy(websocket)
@ -41,6 +42,7 @@ class WebSocketChannel:
self._send_times: Deque[float] = deque([], maxlen=10)
# High limit defaults to 3 to start
self._send_high_limit = 3
self._send_throttle = send_throttle
# The subscribed message types
self._subscriptions: List[str] = []
@ -106,7 +108,8 @@ class WebSocketChannel:
# Explicitly give control back to event loop as
# websockets.send does not
await asyncio.sleep(0.01)
# Also throttles how fast we send
await asyncio.sleep(self._send_throttle)
async def recv(self):
"""

2
freqtrade/rpc/api_server/ws_schemas.py
View File

@ -47,7 +47,7 @@ class WSWhitelistRequest(WSRequestSchema):
class WSAnalyzedDFRequest(WSRequestSchema):
type: RPCRequestType = RPCRequestType.ANALYZED_DF
data: Dict[str, Any] = {"limit": 1500}
data: Dict[str, Any] = {"limit": 1500, "pair": None}
# ------------------------------ MESSAGE SCHEMAS ----------------------------

114
freqtrade/rpc/external_message_consumer.py
View File

@ -8,15 +8,17 @@ import asyncio
import logging
import socket
from threading import Thread
from typing import TYPE_CHECKING, Any, Callable, Dict, List, TypedDict
from typing import TYPE_CHECKING, Any, Callable, Dict, List, TypedDict, Union
import websockets
from pydantic import ValidationError
from freqtrade.constants import FULL_DATAFRAME_THRESHOLD
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import RPCMessageType
from freqtrade.misc import remove_entry_exit_signals
from freqtrade.rpc.api_server.ws import WebSocketChannel
from freqtrade.rpc.api_server.ws.channel import WebSocketChannel, create_channel
from freqtrade.rpc.api_server.ws.message_stream import MessageStream
from freqtrade.rpc.api_server.ws_schemas import (WSAnalyzedDFMessage, WSAnalyzedDFRequest,
WSMessageSchema, WSRequestSchema,
WSSubscribeRequest, WSWhitelistMessage,
@ -38,6 +40,10 @@ class Producer(TypedDict):
logger = logging.getLogger(__name__)
def schema_to_dict(schema: Union[WSMessageSchema, WSRequestSchema]):
return schema.dict(exclude_none=True)
class ExternalMessageConsumer:
"""
The main controller class for consuming external messages from
@ -92,6 +98,8 @@ class ExternalMessageConsumer:
RPCMessageType.ANALYZED_DF: self._consume_analyzed_df_message,
}
self._channel_streams: Dict[str, MessageStream] = {}
self.start()
def start(self):
@ -118,6 +126,8 @@ class ExternalMessageConsumer:
logger.info("Stopping ExternalMessageConsumer")
self._running = False
self._channel_streams = {}
if self._sub_tasks:
# Cancel sub tasks
for task in self._sub_tasks:
@ -175,7 +185,6 @@ class ExternalMessageConsumer:
:param producer: Dictionary containing producer info
:param lock: An asyncio Lock
"""
channel = None
while self._running:
try:
host, port = producer['host'], producer['port']
@ -190,19 +199,21 @@ class ExternalMessageConsumer:
max_size=self.message_size_limit,
ping_interval=None
) as ws:
channel = WebSocketChannel(ws, channel_id=name)
async with create_channel(
ws,
channel_id=name,
send_throttle=0.5
) as channel:
logger.info(f"Producer connection success - {channel}")
# Create the message stream for this channel
self._channel_streams[name] = MessageStream()
# Now request the initial data from this Producer
for request in self._initial_requests:
await channel.send(
request.dict(exclude_none=True)
# Run the channel tasks while connected
await channel.run_channel_tasks(
self._receive_messages(channel, producer, lock),
self._send_requests(channel, self._channel_streams[name])
)
# Now receive data, if none is within the time limit, ping
await self._receive_messages(channel, producer, lock)
except (websockets.exceptions.InvalidURI, ValueError) as e:
logger.error(f"{ws_url} is an invalid WebSocket URL - {e}")
break
@ -229,11 +240,19 @@ class ExternalMessageConsumer:
# An unforseen error has occurred, log and continue
logger.error("Unexpected error has occurred:")
logger.exception(e)
await asyncio.sleep(self.sleep_time)
continue
finally:
if channel:
await channel.close()
async def _send_requests(self, channel: WebSocketChannel, channel_stream: MessageStream):
# Send the initial requests
for init_request in self._initial_requests:
await channel.send(schema_to_dict(init_request))
# Now send any subsequent requests published to
# this channel's stream
async for request, _ in channel_stream:
logger.debug(f"Sending request to channel - {channel} - {request}")
await channel.send(request)
async def _receive_messages(
self,
@ -270,19 +289,31 @@ class ExternalMessageConsumer:
latency = (await asyncio.wait_for(pong, timeout=self.ping_timeout) * 1000)
logger.info(f"Connection to {channel} still alive, latency: {latency}ms")
continue
except (websockets.exceptions.ConnectionClosed):
# Just eat the error and continue reconnecting
logger.warning(f"Disconnection in {channel} - retrying in {self.sleep_time}s")
await asyncio.sleep(self.sleep_time)
break
except Exception as e:
# Just eat the error and continue reconnecting
logger.warning(f"Ping error {channel} - {e} - retrying in {self.sleep_time}s")
logger.debug(e, exc_info=e)
await asyncio.sleep(self.sleep_time)
raise
break
def send_producer_request(
self,
producer_name: str,
request: Union[WSRequestSchema, Dict[str, Any]]
):
"""
Publish a message to the producer's message stream to be
sent by the channel task.
:param producer_name: The name of the producer to publish the message to
:param request: The request to send to the producer
"""
if isinstance(request, WSRequestSchema):
request = schema_to_dict(request)
if channel_stream := self._channel_streams.get(producer_name):
channel_stream.publish(request)
def handle_producer_message(self, producer: Producer, message: Dict[str, Any]):
"""
@ -336,16 +367,45 @@ class ExternalMessageConsumer:
pair, timeframe, candle_type = key
if df.empty:
logger.debug(f"Received Empty Dataframe for {key}")
return
# If set, remove the Entry and Exit signals from the Producer
if self._emc_config.get('remove_entry_exit_signals', False):
df = remove_entry_exit_signals(df)
# Add the dataframe to the dataprovider
self._dp._add_external_df(pair, df,
logger.debug(f"Received {len(df)} candle(s) for {key}")
did_append, n_missing = self._dp._add_external_df(
pair,
df,
last_analyzed=la,
timeframe=timeframe,
candle_type=candle_type,
producer_name=producer_name)
producer_name=producer_name
)
if not did_append:
# We want an overlap in candles incase some data has changed
n_missing += 1
# Set to None for all candles if we missed a full df's worth of candles
n_missing = n_missing if n_missing < FULL_DATAFRAME_THRESHOLD else 1500
logger.warning(f"Holes in data or no existing df, requesting {n_missing} candles "
f"for {key} from `{producer_name}`")
self.send_producer_request(
producer_name,
WSAnalyzedDFRequest(
data={
"limit": n_missing,
"pair": pair
}
)
)
return
logger.debug(
f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`")
f"Consumed message from `{producer_name}` "
f"of type `RPCMessageType.ANALYZED_DF` for {key}")

39
freqtrade/rpc/rpc.py
View File

@ -1062,15 +1062,26 @@ class RPC:
return self._convert_dataframe_to_dict(self._freqtrade.config['strategy'],
pair, timeframe, _data, last_analyzed)
def __rpc_analysed_dataframe_raw(self, pair: str, timeframe: str,
limit: Optional[int]) -> Tuple[DataFrame, datetime]:
""" Get the dataframe and last analyze from the dataprovider """
def __rpc_analysed_dataframe_raw(
self,
pair: str,
timeframe: str,
limit: Optional[int]
) -> Tuple[DataFrame, datetime]:
"""
Get the dataframe and last analyze from the dataprovider
:param pair: The pair to get
:param timeframe: The timeframe of data to get
:param limit: The amount of candles in the dataframe
"""
_data, last_analyzed = self._freqtrade.dataprovider.get_analyzed_dataframe(
pair, timeframe)
_data = _data.copy()
if limit:
_data = _data.iloc[-limit:]
return _data, last_analyzed
def _ws_all_analysed_dataframes(
@ -1078,7 +1089,16 @@ class RPC:
pairlist: List[str],
limit: Optional[int]
) -> Generator[Dict[str, Any], None, None]:
""" Get the analysed dataframes of each pair in the pairlist """
"""
Get the analysed dataframes of each pair in the pairlist.
If specified, only return the most recent `limit` candles for
each dataframe.
:param pairlist: A list of pairs to get
:param limit: If an integer, limits the size of dataframe
If a list of string date times, only returns those candles
:returns: A generator of dictionaries with the key, dataframe, and last analyzed timestamp
"""
timeframe = self._freqtrade.config['timeframe']
candle_type = self._freqtrade.config.get('candle_type_def', CandleType.SPOT)
@ -1091,10 +1111,15 @@ class RPC:
"la": last_analyzed
}
def _ws_request_analyzed_df(self, limit: Optional[int]):
def _ws_request_analyzed_df(
self,
limit: Optional[int] = None,
pair: Optional[str] = None
):
""" Historical Analyzed Dataframes for WebSocket """
whitelist = self._freqtrade.active_pair_whitelist
return self._ws_all_analysed_dataframes(whitelist, limit)
pairlist = [pair] if pair else self._freqtrade.active_pair_whitelist
return self._ws_all_analysed_dataframes(pairlist, limit)
def _ws_request_whitelist(self):
""" Whitelist data for WebSocket """

85
tests/data/test_dataprovider.py
View File

@ -2,13 +2,13 @@ from datetime import datetime, timezone
from unittest.mock import MagicMock
import pytest
from pandas import DataFrame
from pandas import DataFrame, Timestamp
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import CandleType, RunMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.plugins.pairlistmanager import PairListManager
from tests.conftest import get_patched_exchange
from tests.conftest import generate_test_data, get_patched_exchange
@pytest.mark.parametrize('candle_type', [
@ -161,9 +161,9 @@ def test_producer_pairs(mocker, default_conf, ohlcv_history):
assert dataprovider.get_producer_pairs("bad") == []
def test_get_producer_df(mocker, default_conf, ohlcv_history):
def test_get_producer_df(mocker, default_conf):
dataprovider = DataProvider(default_conf, None)
ohlcv_history = generate_test_data('5m', 150)
pair = 'BTC/USDT'
timeframe = default_conf['timeframe']
candle_type = CandleType.SPOT
@ -412,3 +412,80 @@ def test_dp_send_msg(default_conf):
dp = DataProvider(default_conf, None)
dp.send_msg(msg, always_send=True)
assert msg not in dp._msg_queue
def test_dp__add_external_df(default_conf_usdt):
timeframe = '1h'
default_conf_usdt["timeframe"] = timeframe
dp = DataProvider(default_conf_usdt, None)
df = generate_test_data(timeframe, 24, '2022-01-01 00:00:00+00:00')
last_analyzed = datetime.now(timezone.utc)
res = dp._add_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
# Why 1000 ??
assert res[1] == 1000
# Hard add dataframe
dp._replace_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
# BTC is not stored yet
res = dp._add_external_df('BTC/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
df_res, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
assert len(df_res) == 24
# Add the same dataframe again - dataframe size shall not change.
res = dp._add_external_df('ETH/USDT', df, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
assert len(df) == 24
# Add a new day.
df2 = generate_test_data(timeframe, 24, '2022-01-02 00:00:00+00:00')
res = dp._add_external_df('ETH/USDT', df2, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
assert len(df) == 48
# Add a dataframe with a 12 hour offset - so 12 candles are overlapping, and 12 valid.
df3 = generate_test_data(timeframe, 24, '2022-01-02 12:00:00+00:00')
res = dp._add_external_df('ETH/USDT', df3, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is True
assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
# New length = 48 + 12 (since we have a 12 hour offset).
assert len(df) == 60
assert df.iloc[-1]['date'] == df3.iloc[-1]['date']
assert df.iloc[-1]['date'] == Timestamp('2022-01-03 11:00:00+00:00')
# Generate 1 new candle
df4 = generate_test_data(timeframe, 1, '2022-01-03 12:00:00+00:00')
res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
# assert res[0] is True
# assert res[1] == 0
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
# New length = 61 + 1
assert len(df) == 61
assert df.iloc[-2]['date'] == Timestamp('2022-01-03 11:00:00+00:00')
assert df.iloc[-1]['date'] == Timestamp('2022-01-03 12:00:00+00:00')
# Gap in the data ...
df4 = generate_test_data(timeframe, 1, '2022-01-05 00:00:00+00:00')
res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
assert res[1] == 36
df, _ = dp.get_producer_df('ETH/USDT', timeframe, CandleType.SPOT)
# New length = 61 + 1
assert len(df) == 61
# Empty dataframe
df4 = generate_test_data(timeframe, 0, '2022-01-05 00:00:00+00:00')
res = dp._add_external_df('ETH/USDT', df4, last_analyzed, timeframe, CandleType.SPOT)
assert res[0] is False
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
assert res[1] == 0

37
tests/rpc/test_rpc_emc.py
View File

@ -83,6 +83,7 @@ def test_emc_init(patched_emc):
def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
test_producer = {"name": "test", "url": "ws://test", "ws_token": "test"}
producer_name = test_producer['name']
invalid_msg = r"Invalid message .+"
caplog.set_level(logging.DEBUG)
@ -94,7 +95,7 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
assert log_has(
f"Consumed message from `{producer_name}` of type `RPCMessageType.WHITELIST`", caplog)
# Test handle analyzed_df message
# Test handle analyzed_df single candle message
df_message = {
"type": "analyzed_df",
"data": {
@ -106,8 +107,7 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
patched_emc.handle_producer_message(test_producer, df_message)
assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog)
assert log_has(
f"Consumed message from `{producer_name}` of type `RPCMessageType.ANALYZED_DF`", caplog)
assert log_has_re(r"Holes in data or no existing df,.+", caplog)
# Test unhandled message
unhandled_message = {"type": "status", "data": "RUNNING"}
@ -120,7 +120,8 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
malformed_message = {"type": "whitelist", "data": {"pair": "BTC/USDT"}}
patched_emc.handle_producer_message(test_producer, malformed_message)
assert log_has_re(r"Invalid message .+", caplog)
assert log_has_re(invalid_msg, caplog)
caplog.clear()
malformed_message = {
"type": "analyzed_df",
@ -133,13 +134,30 @@ def test_emc_handle_producer_message(patched_emc, caplog, ohlcv_history):
patched_emc.handle_producer_message(test_producer, malformed_message)
assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog)
assert log_has_re(r"Invalid message .+", caplog)
assert log_has_re(invalid_msg, caplog)
caplog.clear()
# Empty dataframe
malformed_message = {
"type": "analyzed_df",
"data": {
"key": ("BTC/USDT", "5m", "spot"),
"df": ohlcv_history.loc[ohlcv_history['open'] < 0],
"la": datetime.now(timezone.utc)
}
}
patched_emc.handle_producer_message(test_producer, malformed_message)
assert log_has(f"Received message of type `analyzed_df` from `{producer_name}`", caplog)
assert not log_has_re(invalid_msg, caplog)
assert log_has_re(r"Received Empty Dataframe for.+", caplog)
caplog.clear()
malformed_message = {"some": "stuff"}
patched_emc.handle_producer_message(test_producer, malformed_message)
assert log_has_re(r"Invalid message .+", caplog)
assert log_has_re(invalid_msg, caplog)
caplog.clear()
caplog.clear()
malformed_message = {"type": "whitelist", "data": None}
@ -183,7 +201,7 @@ async def test_emc_create_connection_success(default_conf, caplog, mocker):
async with websockets.serve(eat, _TEST_WS_HOST, _TEST_WS_PORT):
await emc._create_connection(test_producer, lock)
assert log_has_re(r"Producer connection success.+", caplog)
assert log_has_re(r"Connected to channel.+", caplog)
finally:
emc.shutdown()
@ -212,7 +230,8 @@ async def test_emc_create_connection_invalid_url(default_conf, caplog, mocker, h
dp = DataProvider(default_conf, None, None, None)
# Handle start explicitly to avoid messing with threading in tests
mocker.patch("freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start",)
mocker.patch("freqtrade.rpc.external_message_consumer.ExternalMessageConsumer.start")
mocker.patch("freqtrade.rpc.api_server.ws.channel.create_channel")
emc = ExternalMessageConsumer(default_conf, dp)
try:
@ -390,6 +409,8 @@ async def test_emc_receive_messages_timeout(default_conf, caplog, mocker):
try:
change_running(emc)
loop.call_soon(functools.partial(change_running, emc=emc))
with pytest.raises(asyncio.TimeoutError):
await emc._receive_messages(TestChannel(), test_producer, lock)
assert log_has_re(r"Ping error.+", caplog)