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17 Commits
feat/kvsto
...
feat/hyper
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f1e831a7b8 |
@@ -274,19 +274,20 @@ A backtesting result will look like that:
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| XRP/BTC | 35 | 0.66 | 22.96 | 0.00114897 | 11.48 | 3:49:00 | 12 0 23 34.3 |
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| ZEC/BTC | 22 | -0.46 | -10.18 | -0.00050971 | -5.09 | 2:22:00 | 7 0 15 31.8 |
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| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 |
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========================================================= EXIT REASON STATS ==========================================================
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| Exit Reason | Exits | Wins | Draws | Losses |
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|:-------------------|--------:|------:|-------:|--------:|
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| trailing_stop_loss | 205 | 150 | 0 | 55 |
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| stop_loss | 166 | 0 | 0 | 166 |
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| exit_signal | 56 | 36 | 0 | 20 |
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| force_exit | 2 | 0 | 0 | 2 |
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====================================================== LEFT OPEN TRADES REPORT ======================================================
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| Pair | Entries | Avg Profit % | Cum Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Win Draw Loss Win% |
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|:---------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
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| ADA/BTC | 1 | 0.89 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 0 0 100 |
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| LTC/BTC | 1 | 0.68 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 0 0 100 |
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| TOTAL | 2 | 0.78 | 1.57 | 0.00007855 | 0.78 | 4:00:00 | 2 0 0 100 |
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==================== EXIT REASON STATS ====================
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| Exit Reason | Exits | Wins | Draws | Losses |
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|:-------------------|--------:|------:|-------:|--------:|
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| trailing_stop_loss | 205 | 150 | 0 | 55 |
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| stop_loss | 166 | 0 | 0 | 166 |
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| exit_signal | 56 | 36 | 0 | 20 |
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| force_exit | 2 | 0 | 0 | 2 |
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================== SUMMARY METRICS ==================
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| Metric | Value |
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|-----------------------------+---------------------|
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|
@@ -1291,7 +1291,7 @@ class FreqaiDataKitchen:
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return dataframe
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def use_strategy_to_populate_indicators(
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def use_strategy_to_populate_indicators( # noqa: C901
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self,
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strategy: IStrategy,
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corr_dataframes: dict = {},
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@@ -1362,12 +1362,12 @@ class FreqaiDataKitchen:
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dataframe = self.populate_features(dataframe.copy(), corr_pair, strategy,
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corr_dataframes, base_dataframes, True)
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if self.live:
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dataframe = strategy.set_freqai_targets(dataframe.copy(), metadata=metadata)
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dataframe = self.remove_special_chars_from_feature_names(dataframe)
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self.get_unique_classes_from_labels(dataframe)
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dataframe = self.remove_special_chars_from_feature_names(dataframe)
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if self.config.get('reduce_df_footprint', False):
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dataframe = reduce_dataframe_footprint(dataframe)
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@@ -306,7 +306,7 @@ class IFreqaiModel(ABC):
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if check_features:
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self.dd.load_metadata(dk)
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dataframe_dummy_features = self.dk.use_strategy_to_populate_indicators(
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strategy, prediction_dataframe=dataframe.tail(1), pair=metadata["pair"]
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strategy, prediction_dataframe=dataframe.tail(1), pair=pair
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)
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dk.find_features(dataframe_dummy_features)
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self.check_if_feature_list_matches_strategy(dk)
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@@ -316,7 +316,7 @@ class IFreqaiModel(ABC):
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else:
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if populate_indicators:
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dataframe = self.dk.use_strategy_to_populate_indicators(
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strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
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strategy, prediction_dataframe=dataframe, pair=pair
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)
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populate_indicators = False
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@@ -332,6 +332,10 @@ class IFreqaiModel(ABC):
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dataframe_train = dk.slice_dataframe(tr_train, dataframe_base_train)
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dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe_base_backtest)
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dataframe_train = dk.remove_special_chars_from_feature_names(dataframe_train)
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dataframe_backtest = dk.remove_special_chars_from_feature_names(dataframe_backtest)
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dk.get_unique_classes_from_labels(dataframe_train)
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if not self.model_exists(dk):
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dk.find_features(dataframe_train)
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dk.find_labels(dataframe_train)
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@@ -1,24 +1,11 @@
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import logging
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import sys
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from logging import Formatter
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from logging.handlers import BufferingHandler, RotatingFileHandler, SysLogHandler
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from logging.handlers import RotatingFileHandler, SysLogHandler
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from freqtrade.constants import Config
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from freqtrade.exceptions import OperationalException
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class FTBufferingHandler(BufferingHandler):
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def flush(self):
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"""
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Override Flush behaviour - we keep half of the configured capacity
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otherwise, we have moments with "empty" logs.
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"""
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self.acquire()
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try:
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# Keep half of the records in buffer.
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self.buffer = self.buffer[-int(self.capacity / 2):]
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finally:
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self.release()
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from freqtrade.loggers.buffering_handler import FTBufferingHandler
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from freqtrade.loggers.std_err_stream_handler import FTStdErrStreamHandler
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logger = logging.getLogger(__name__)
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@@ -69,7 +56,7 @@ def setup_logging_pre() -> None:
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logging.basicConfig(
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level=logging.INFO,
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format=LOGFORMAT,
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handlers=[logging.StreamHandler(sys.stderr), bufferHandler]
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handlers=[FTStdErrStreamHandler(), bufferHandler]
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)
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15
freqtrade/loggers/buffering_handler.py
Normal file
15
freqtrade/loggers/buffering_handler.py
Normal file
@@ -0,0 +1,15 @@
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from logging.handlers import BufferingHandler
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class FTBufferingHandler(BufferingHandler):
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def flush(self):
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"""
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Override Flush behaviour - we keep half of the configured capacity
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otherwise, we have moments with "empty" logs.
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"""
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self.acquire()
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try:
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# Keep half of the records in buffer.
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self.buffer = self.buffer[-int(self.capacity / 2):]
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finally:
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self.release()
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26
freqtrade/loggers/std_err_stream_handler.py
Normal file
26
freqtrade/loggers/std_err_stream_handler.py
Normal file
@@ -0,0 +1,26 @@
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import sys
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from logging import Handler
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class FTStdErrStreamHandler(Handler):
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def flush(self):
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"""
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Override Flush behaviour - we keep half of the configured capacity
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otherwise, we have moments with "empty" logs.
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"""
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self.acquire()
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try:
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sys.stderr.flush()
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finally:
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self.release()
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def emit(self, record):
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try:
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msg = self.format(record)
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# Don't keep a reference to stderr - this can be problematic with progressbars.
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sys.stderr.write(msg + '\n')
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self.flush()
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except RecursionError:
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raise
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except Exception:
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self.handleError(record)
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@@ -13,13 +13,13 @@ from math import ceil
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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import progressbar
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import rapidjson
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from colorama import Fore, Style
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from colorama import init as colorama_init
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from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
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from joblib.externals import cloudpickle
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from pandas import DataFrame
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from rich.progress import (BarColumn, MofNCompleteColumn, Progress, TaskProgressColumn, TextColumn,
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TimeElapsedColumn, TimeRemainingColumn)
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from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN, Config
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from freqtrade.data.converter import trim_dataframes
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@@ -44,8 +44,6 @@ with warnings.catch_warnings():
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from skopt import Optimizer
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from skopt.space import Dimension
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progressbar.streams.wrap_stderr()
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progressbar.streams.wrap_stdout()
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logger = logging.getLogger(__name__)
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@@ -520,29 +518,6 @@ class Hyperopt:
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else:
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return self.opt.ask(n_points=n_points), [False for _ in range(n_points)]
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def get_progressbar_widgets(self):
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if self.print_colorized:
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widgets = [
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' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
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' (', progressbar.Percentage(), ')] ',
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progressbar.Bar(marker=progressbar.AnimatedMarker(
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fill='\N{FULL BLOCK}',
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fill_wrap=Fore.GREEN + '{}' + Fore.RESET,
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marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL,
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)),
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' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
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]
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else:
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widgets = [
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' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
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' (', progressbar.Percentage(), ')] ',
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progressbar.Bar(marker=progressbar.AnimatedMarker(
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fill='\N{FULL BLOCK}',
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)),
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' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
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]
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return widgets
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def evaluate_result(self, val: Dict[str, Any], current: int, is_random: bool):
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"""
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Evaluate results returned from generate_optimizer
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@@ -602,11 +577,19 @@ class Hyperopt:
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logger.info(f'Effective number of parallel workers used: {jobs}')
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# Define progressbar
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widgets = self.get_progressbar_widgets()
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with progressbar.ProgressBar(
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max_value=self.total_epochs, redirect_stdout=False, redirect_stderr=False,
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widgets=widgets
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with Progress(
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TextColumn("[progress.description]{task.description}"),
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BarColumn(bar_width=None),
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MofNCompleteColumn(),
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TaskProgressColumn(),
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"•",
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TimeElapsedColumn(),
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"•",
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TimeRemainingColumn(),
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expand=True,
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) as pbar:
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task = pbar.add_task("Epochs", total=self.total_epochs)
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start = 0
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if self.analyze_per_epoch:
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@@ -616,7 +599,7 @@ class Hyperopt:
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f_val0 = self.generate_optimizer(asked[0])
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self.opt.tell(asked, [f_val0['loss']])
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self.evaluate_result(f_val0, 1, is_random[0])
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pbar.update(1)
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pbar.update(task, advance=1)
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start += 1
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evals = ceil((self.total_epochs - start) / jobs)
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@@ -630,14 +613,12 @@ class Hyperopt:
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f_val = self.run_optimizer_parallel(parallel, asked)
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self.opt.tell(asked, [v['loss'] for v in f_val])
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# Calculate progressbar outputs
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for j, val in enumerate(f_val):
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# Use human-friendly indexes here (starting from 1)
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current = i * jobs + j + 1 + start
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self.evaluate_result(val, current, is_random[j])
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pbar.update(current)
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pbar.update(task, advance=1)
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except KeyboardInterrupt:
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print('User interrupted..')
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|
@@ -865,6 +865,11 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
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print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
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print(table)
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table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
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if isinstance(table, str) and len(table) > 0:
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print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
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print(table)
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if (results.get('results_per_enter_tag') is not None
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or results.get('results_per_buy_tag') is not None):
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# results_per_buy_tag is deprecated and should be removed 2 versions after short golive.
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@@ -884,11 +889,6 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
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print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
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print(table)
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table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
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if isinstance(table, str) and len(table) > 0:
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print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
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print(table)
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for period in backtest_breakdown:
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days_breakdown_stats = generate_periodic_breakdown_stats(
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trade_list=results['trades'], period=period)
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@@ -917,11 +917,11 @@ def show_backtest_results(config: Config, backtest_stats: Dict):
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strategy, results, stake_currency,
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config.get('backtest_breakdown', []))
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if len(backtest_stats['strategy']) > 1:
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if len(backtest_stats['strategy']) > 0:
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# Print Strategy summary table
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table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
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print(f"{results['backtest_start']} -> {results['backtest_end']} |"
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print(f"Backtested {results['backtest_start']} -> {results['backtest_end']} |"
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f" Max open trades : {results['max_open_trades']}")
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print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
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print(table)
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|
@@ -6,4 +6,3 @@ scipy==1.10.1
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scikit-learn==1.1.3
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scikit-optimize==0.9.0
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filelock==3.10.6
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progressbar2==4.2.0
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|
@@ -20,6 +20,7 @@ jinja2==3.1.2
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tables==3.8.0
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blosc==1.11.1
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joblib==1.2.0
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rich==13.3.3
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pyarrow==11.0.0; platform_machine != 'armv7l'
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# find first, C search in arrays
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|
2
setup.py
2
setup.py
@@ -8,7 +8,6 @@ hyperopt = [
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'scikit-learn',
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'scikit-optimize>=0.7.0',
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'filelock',
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'progressbar2',
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]
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freqai = [
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@@ -82,6 +81,7 @@ setup(
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'numpy',
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'pandas',
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'joblib>=1.2.0',
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'rich',
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'pyarrow; platform_machine != "armv7l"',
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'fastapi',
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'pydantic>=1.8.0',
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|
@@ -119,6 +119,7 @@ def make_unfiltered_dataframe(mocker, freqai_conf):
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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freqai.dk.live = True
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freqai.dk.pair = "ADA/BTC"
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data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)
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@@ -152,6 +153,7 @@ def make_data_dictionary(mocker, freqai_conf):
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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freqai.dk.live = True
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freqai.dk.pair = "ADA/BTC"
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data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
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freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)
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|
@@ -19,6 +19,7 @@ def test_update_historic_data(mocker, freqai_conf):
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
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freqai.dk.live = True
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timerange = TimeRange.parse_timerange("20180110-20180114")
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freqai.dd.load_all_pair_histories(timerange, freqai.dk)
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@@ -41,6 +42,7 @@ def test_load_all_pairs_histories(mocker, freqai_conf):
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freqai = strategy.freqai
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freqai.live = True
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freqai.dk = FreqaiDataKitchen(freqai_conf)
|
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freqai.dk.live = True
|
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timerange = TimeRange.parse_timerange("20180110-20180114")
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freqai.dd.load_all_pair_histories(timerange, freqai.dk)
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|
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@@ -60,6 +62,7 @@ def test_get_base_and_corr_dataframes(mocker, freqai_conf):
|
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freqai = strategy.freqai
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freqai.live = True
|
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freqai.dk = FreqaiDataKitchen(freqai_conf)
|
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freqai.dk.live = True
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timerange = TimeRange.parse_timerange("20180110-20180114")
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freqai.dd.load_all_pair_histories(timerange, freqai.dk)
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sub_timerange = TimeRange.parse_timerange("20180111-20180114")
|
||||
@@ -87,6 +90,7 @@ def test_use_strategy_to_populate_indicators(mocker, freqai_conf):
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freqai = strategy.freqai
|
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freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180114")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
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sub_timerange = TimeRange.parse_timerange("20180111-20180114")
|
||||
@@ -103,8 +107,9 @@ def test_get_timerange_from_live_historic_predictions(mocker, freqai_conf):
|
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exchange = get_patched_exchange(mocker, freqai_conf)
|
||||
strategy.dp = DataProvider(freqai_conf, exchange)
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.live = False
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = False
|
||||
timerange = TimeRange.parse_timerange("20180126-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
sub_timerange = TimeRange.parse_timerange("20180128-20180130")
|
||||
|
@@ -180,6 +180,7 @@ def test_get_full_model_path(mocker, freqai_conf, model):
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
|
@@ -87,6 +87,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
|
||||
freqai.live = True
|
||||
freqai.can_short = can_short
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
freqai.dk.set_paths('ADA/BTC', 10000)
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
@@ -135,6 +136,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
@@ -178,6 +180,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
@@ -371,6 +374,9 @@ def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
|
||||
sub_timerange = TimeRange.parse_timerange("20180129-20180130")
|
||||
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
|
||||
df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
|
||||
df = strategy.set_freqai_targets(df.copy(), metadata={"pair": "LTC/BTC"})
|
||||
df = freqai.dk.remove_special_chars_from_feature_names(df)
|
||||
freqai.dk.get_unique_classes_from_labels(df)
|
||||
freqai.dk.pair = "ADA/BTC"
|
||||
freqai.dk.full_df = df.fillna(0)
|
||||
freqai.dk.full_df
|
||||
@@ -394,6 +400,7 @@ def test_principal_component_analysis(mocker, freqai_conf):
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
@@ -425,10 +432,12 @@ def test_plot_feature_importance(mocker, freqai_conf):
|
||||
freqai = strategy.freqai
|
||||
freqai.live = True
|
||||
freqai.dk = FreqaiDataKitchen(freqai_conf)
|
||||
freqai.dk.live = True
|
||||
timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
|
||||
|
||||
freqai.dd.pair_dict = MagicMock()
|
||||
freqai.dd.pair_dict = {"ADA/BTC": {"model_filename": "fake_name",
|
||||
"trained_timestamp": 1, "data_path": "", "extras": {}}}
|
||||
|
||||
data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
|
||||
new_timerange = TimeRange.parse_timerange("20180120-20180130")
|
||||
|
@@ -23,7 +23,8 @@ from freqtrade.configuration.load_config import (load_config_file, load_file, lo
|
||||
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL, ENV_VAR_PREFIX
|
||||
from freqtrade.enums import RunMode
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.loggers import FTBufferingHandler, _set_loggers, setup_logging, setup_logging_pre
|
||||
from freqtrade.loggers import (FTBufferingHandler, FTStdErrStreamHandler, _set_loggers,
|
||||
setup_logging, setup_logging_pre)
|
||||
from tests.conftest import (CURRENT_TEST_STRATEGY, log_has, log_has_re,
|
||||
patched_configuration_load_config_file)
|
||||
|
||||
@@ -658,7 +659,7 @@ def test_set_loggers_syslog():
|
||||
setup_logging(config)
|
||||
assert len(logger.handlers) == 3
|
||||
assert [x for x in logger.handlers if type(x) == logging.handlers.SysLogHandler]
|
||||
assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
|
||||
assert [x for x in logger.handlers if type(x) == FTStdErrStreamHandler]
|
||||
assert [x for x in logger.handlers if type(x) == FTBufferingHandler]
|
||||
# setting up logging again should NOT cause the loggers to be added a second time.
|
||||
setup_logging(config)
|
||||
@@ -681,7 +682,7 @@ def test_set_loggers_Filehandler(tmpdir):
|
||||
setup_logging(config)
|
||||
assert len(logger.handlers) == 3
|
||||
assert [x for x in logger.handlers if type(x) == logging.handlers.RotatingFileHandler]
|
||||
assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
|
||||
assert [x for x in logger.handlers if type(x) == FTStdErrStreamHandler]
|
||||
assert [x for x in logger.handlers if type(x) == FTBufferingHandler]
|
||||
# setting up logging again should NOT cause the loggers to be added a second time.
|
||||
setup_logging(config)
|
||||
@@ -706,7 +707,7 @@ def test_set_loggers_journald(mocker):
|
||||
setup_logging(config)
|
||||
assert len(logger.handlers) == 3
|
||||
assert [x for x in logger.handlers if type(x).__name__ == "JournaldLogHandler"]
|
||||
assert [x for x in logger.handlers if type(x) == logging.StreamHandler]
|
||||
assert [x for x in logger.handlers if type(x) == FTStdErrStreamHandler]
|
||||
# reset handlers to not break pytest
|
||||
logger.handlers = orig_handlers
|
||||
|
||||
|
Reference in New Issue
Block a user