adelorenzo
/
stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge branch 'develop' of https://github.com/freqtrade/freqtrade into max-open-trades

This commit is contained in:
Antonio Della Fortuna 2023-01-07 11:11:59 +01:00
parent f2fa476dc6 349d67f582
commit 8c3ac56bc5
10 changed files with 39 additions and 105 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
freqtrade/data/entryexitanalysis.py
View File

@ -52,7 +52,7 @@ def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_cand
return analysed_trades_dict
def _analyze_candles_and_indicators(pair, trades, signal_candles):
def _analyze_candles_and_indicators(pair, trades: pd.DataFrame, signal_candles: pd.DataFrame):
buyf = signal_candles
if len(buyf) > 0:
@ -120,7 +120,7 @@ def _do_group_table_output(bigdf, glist):
else:
agg_mask = {'profit_abs': ['count', 'sum', 'median', 'mean'],
'profit_ratio': ['sum', 'median', 'mean']}
'profit_ratio': ['median', 'mean', 'sum']}
agg_cols = ['num_buys', 'profit_abs_sum', 'profit_abs_median',
'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct',
'total_profit_pct']

4
freqtrade/data/metrics.py
View File

@ -197,7 +197,7 @@ def calculate_cagr(days_passed: int, starting_balance: float, final_balance: flo
def calculate_expectancy(trades: pd.DataFrame) -> float:
"""
Calculate expectancy
:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
:param trades: DataFrame containing trades (requires columns close_date and profit_abs)
:return: expectancy
"""
if len(trades) == 0:
@ -239,7 +239,7 @@ def calculate_sortino(trades: pd.DataFrame, min_date: datetime, max_date: dateti
down_stdev = np.std(trades.loc[trades['profit_abs'] < 0, 'profit_abs'] / starting_balance)
if down_stdev != 0:
if down_stdev != 0 and not np.isnan(down_stdev):
sortino_ratio = expected_returns_mean / down_stdev * np.sqrt(365)
else:
# Define high (negative) sortino ratio to be clear that this is NOT optimal.

4
freqtrade/exchange/binance.py
View File

@ -11,7 +11,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
from freqtrade.exchange import Exchange
from freqtrade.exchange.common import retrier
from freqtrade.exchange.types import Tickers
from freqtrade.exchange.types import OHLCVResponse, Tickers
from freqtrade.misc import deep_merge_dicts, json_load
@ -112,7 +112,7 @@ class Binance(Exchange):
since_ms: int, candle_type: CandleType,
is_new_pair: bool = False, raise_: bool = False,
until_ms: Optional[int] = None
) -> Tuple[str, str, str, List]:
) -> OHLCVResponse:
"""
Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
Does not work for other exchanges, which don't return the earliest data when called with "0"

43
freqtrade/exchange/exchange.py
View File

@ -36,7 +36,7 @@ from freqtrade.exchange.exchange_utils import (CcxtModuleType, amount_to_contrac
price_to_precision, timeframe_to_minutes,
timeframe_to_msecs, timeframe_to_next_date,
timeframe_to_prev_date, timeframe_to_seconds)
from freqtrade.exchange.types import Ticker, Tickers
from freqtrade.exchange.types import OHLCVResponse, Ticker, Tickers
from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json,
safe_value_fallback2)
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@ -1813,32 +1813,18 @@ class Exchange:
:param candle_type: '', mark, index, premiumIndex, or funding_rate
:return: List with candle (OHLCV) data
"""
pair, _, _, data = self.loop.run_until_complete(
pair, _, _, data, _ = self.loop.run_until_complete(
self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
since_ms=since_ms, until_ms=until_ms,
is_new_pair=is_new_pair, candle_type=candle_type))
logger.info(f"Downloaded data for {pair} with length {len(data)}.")
return data
def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
since_ms: int, candle_type: CandleType) -> DataFrame:
"""
Minimal wrapper around get_historic_ohlcv - converting the result into a dataframe
:param pair: Pair to download
:param timeframe: Timeframe to get data for
:param since_ms: Timestamp in milliseconds to get history from
:param candle_type: Any of the enum CandleType (must match trading mode!)
:return: OHLCV DataFrame
"""
ticks = self.get_historic_ohlcv(pair, timeframe, since_ms=since_ms, candle_type=candle_type)
return ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, candle_type: CandleType,
is_new_pair: bool = False, raise_: bool = False,
until_ms: Optional[int] = None
) -> Tuple[str, str, str, List]:
) -> OHLCVResponse:
"""
Download historic ohlcv
:param is_new_pair: used by binance subclass to allow "fast" new pair downloading
@ -1869,15 +1855,16 @@ class Exchange:
continue
else:
# Deconstruct tuple if it's not an exception
p, _, c, new_data = res
p, _, c, new_data, _ = res
if p == pair and c == candle_type:
data.extend(new_data)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
return pair, timeframe, candle_type, data
return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType,
since_ms: Optional[int], cache: bool) -> Coroutine:
def _build_coroutine(
self, pair: str, timeframe: str, candle_type: CandleType,
since_ms: Optional[int], cache: bool) -> Coroutine[Any, Any, OHLCVResponse]:
not_all_data = cache and self.required_candle_call_count > 1
if cache and (pair, timeframe, candle_type) in self._klines:
candle_limit = self.ohlcv_candle_limit(timeframe, candle_type)
@ -1914,7 +1901,7 @@ class Exchange:
"""
Build Coroutines to execute as part of refresh_latest_ohlcv
"""
input_coroutines = []
input_coroutines: List[Coroutine[Any, Any, OHLCVResponse]] = []
cached_pairs = []
for pair, timeframe, candle_type in set(pair_list):
if (timeframe not in self.timeframes
@ -1978,7 +1965,6 @@ class Exchange:
:return: Dict of [{(pair, timeframe): Dataframe}]
"""
logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list))
drop_incomplete = self._ohlcv_partial_candle if drop_incomplete is None else drop_incomplete
# Gather coroutines to run
input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache)
@ -1996,8 +1982,9 @@ class Exchange:
if isinstance(res, Exception):
logger.warning(f"Async code raised an exception: {repr(res)}")
continue
# Deconstruct tuple (has 4 elements)
pair, timeframe, c_type, ticks = res
# Deconstruct tuple (has 5 elements)
pair, timeframe, c_type, ticks, drop_hint = res
drop_incomplete = drop_hint if drop_incomplete is None else drop_incomplete
ohlcv_df = self._process_ohlcv_df(
pair, timeframe, c_type, ticks, cache, drop_incomplete)
@ -2025,7 +2012,7 @@ class Exchange:
timeframe: str,
candle_type: CandleType,
since_ms: Optional[int] = None,
) -> Tuple[str, str, str, List]:
) -> OHLCVResponse:
"""
Asynchronously get candle history data using fetch_ohlcv
:param candle_type: '', mark, index, premiumIndex, or funding_rate
@ -2065,9 +2052,9 @@ class Exchange:
data = sorted(data, key=lambda x: x[0])
except IndexError:
logger.exception("Error loading %s. Result was %s.", pair, data)
return pair, timeframe, candle_type, []
return pair, timeframe, candle_type, [], self._ohlcv_partial_candle
logger.debug("Done fetching pair %s, interval %s ...", pair, timeframe)
return pair, timeframe, candle_type, data
return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
except ccxt.NotSupported as e:
raise OperationalException(

7
freqtrade/exchange/types.py
View File

@ -1,4 +1,6 @@
from typing import Dict, Optional, TypedDict
from typing import Dict, List, Optional, Tuple, TypedDict
from freqtrade.enums import CandleType
class Ticker(TypedDict):
@ -14,3 +16,6 @@ class Ticker(TypedDict):
Tickers = Dict[str, Ticker]
# pair, timeframe, candleType, OHLCV, drop last?,
OHLCVResponse = Tuple[str, str, CandleType, List, bool]

1
freqtrade/optimize/backtesting.py
View File

@ -1178,6 +1178,7 @@ class Backtesting:
open_trade_count_start = self.backtest_loop(
row, pair, current_time, end_date, max_open_trades,
open_trade_count_start)
continue
detail_data.loc[:, 'enter_long'] = row[LONG_IDX]
detail_data.loc[:, 'exit_long'] = row[ELONG_IDX]
detail_data.loc[:, 'enter_short'] = row[SHORT_IDX]

5
freqtrade/templates/FreqaiExampleStrategy.py
View File

@ -28,7 +28,7 @@ class FreqaiExampleStrategy(IStrategy):
plot_config = {
"main_plot": {},
"subplots": {
"prediction": {"prediction": {"color": "blue"}},
"&-s_close": {"prediction": {"color": "blue"}},
"do_predict": {
"do_predict": {"color": "brown"},
},
@ -140,7 +140,8 @@ class FreqaiExampleStrategy(IStrategy):
# If user wishes to use multiple targets, they can add more by
# appending more columns with '&'. User should keep in mind that multi targets
# requires a multioutput prediction model such as
# templates/CatboostPredictionMultiModel.py,
# freqai/prediction_models/CatboostRegressorMultiTarget.py,
# freqtrade trade --freqaimodel CatboostRegressorMultiTarget
# df["&-s_range"] = (
# df["close"]

6
tests/commands/test_commands.py
View File

@ -746,9 +746,7 @@ def test_download_data_no_exchange(mocker, caplog):
start_download_data(pargs)
def test_download_data_no_pairs(mocker, caplog):
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
def test_download_data_no_pairs(mocker):
mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
@ -770,8 +768,6 @@ def test_download_data_no_pairs(mocker, caplog):
def test_download_data_all_pairs(mocker, markets):
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
dl_mock = mocker.patch('freqtrade.commands.data_commands.refresh_backtest_ohlcv_data',
MagicMock(return_value=["ETH/BTC", "XRP/BTC"]))
patch_exchange(mocker)

4
tests/exchange/test_binance.py
View File

@ -557,7 +557,7 @@ async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, c
exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
pair = 'ETH/BTC'
respair, restf, restype, res = await exchange._async_get_historic_ohlcv(
respair, restf, restype, res, _ = await exchange._async_get_historic_ohlcv(
pair, "5m", 1500000000000, is_new_pair=False, candle_type=candle_type)
assert respair == pair
assert restf == '5m'
@ -566,7 +566,7 @@ async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog, c
assert exchange._api_async.fetch_ohlcv.call_count > 400
# assert res == ohlcv
exchange._api_async.fetch_ohlcv.reset_mock()
_, _, _, res = await exchange._async_get_historic_ohlcv(
_, _, _, res, _ = await exchange._async_get_historic_ohlcv(
pair, "5m", 1500000000000, is_new_pair=True, candle_type=candle_type)
# Called twice - one "init" call - and one to get the actual data.

66
tests/exchange/test_exchange.py
View File

@ -1955,7 +1955,7 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_
pair = 'ETH/BTC'
async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
return pair, timeframe, candle_type, ohlcv
return pair, timeframe, candle_type, ohlcv, True
exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
# one_call calculation * 1.8 should do 2 calls
@ -1988,62 +1988,6 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_
assert log_has_re(r"Async code raised an exception: .*", caplog)
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize('candle_type', ['mark', ''])
def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name, candle_type):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
ohlcv = [
[
arrow.utcnow().int_timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
],
[
arrow.utcnow().shift(minutes=5).int_timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
],
[
arrow.utcnow().shift(minutes=10).int_timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
pair = 'ETH/BTC'
async def mock_candle_hist(pair, timeframe, candle_type, since_ms):
return pair, timeframe, candle_type, ohlcv
exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
# one_call calculation * 1.8 should do 2 calls
since = 5 * 60 * exchange.ohlcv_candle_limit('5m', CandleType.SPOT) * 1.8
ret = exchange.get_historic_ohlcv_as_df(
pair,
"5m",
int((arrow.utcnow().int_timestamp - since) * 1000),
candle_type=candle_type
)
assert exchange._async_get_candle_history.call_count == 2
# Returns twice the above OHLCV data
assert len(ret) == 2
assert isinstance(ret, DataFrame)
assert 'date' in ret.columns
assert 'open' in ret.columns
assert 'close' in ret.columns
assert 'high' in ret.columns
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize('candle_type', [CandleType.MARK, CandleType.SPOT])
@ -2063,7 +2007,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
pair = 'ETH/USDT'
respair, restf, _, res = await exchange._async_get_historic_ohlcv(
respair, restf, _, res, _ = await exchange._async_get_historic_ohlcv(
pair, "5m", 1500000000000, candle_type=candle_type, is_new_pair=False)
assert respair == pair
assert restf == '5m'
@ -2074,7 +2018,7 @@ async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_
exchange._api_async.fetch_ohlcv.reset_mock()
end_ts = 1_500_500_000_000
start_ts = 1_500_000_000_000
respair, restf, _, res = await exchange._async_get_historic_ohlcv(
respair, restf, _, res, _ = await exchange._async_get_historic_ohlcv(
pair, "5m", since_ms=start_ts, candle_type=candle_type, is_new_pair=False,
until_ms=end_ts
)
@ -2306,7 +2250,7 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
pair = 'ETH/BTC'
res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
assert type(res) is tuple
assert len(res) == 4
assert len(res) == 5
assert res[0] == pair
assert res[1] == "5m"
assert res[2] == CandleType.SPOT
@ -2393,7 +2337,7 @@ async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
pair = 'ETH/BTC'
res = await exchange._async_get_candle_history(pair, "5m", CandleType.SPOT)
assert type(res) is tuple
assert len(res) == 4
assert len(res) == 5
assert res[0] == pair
assert res[1] == "5m"
assert res[2] == CandleType.SPOT