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fix lock bug, update docstring

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This commit is contained in:
robcaulk
2022-08-14 20:24:29 +02:00
parent 464d99808f
commit ad846cdb76
3 changed files with 27 additions and 24 deletions
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29
freqtrade/freqai/freqai_interface.py
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@@ -12,7 +12,7 @@ import numpy as np
import pandas as pd
from numpy.typing import NDArray
from pandas import DataFrame
from threading import Lock
from freqtrade.configuration import TimeRange
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
@@ -52,7 +52,7 @@ class IFreqaiModel(ABC):
Beta testing and bug reporting:
@bloodhunter4rc, Salah Lamkadem @ikonx, @ken11o2, @longyu, @paranoidandy, @smidelis, @smarm
Juha Nykänen @suikula, Wagner Costa @wagnercosta
Juha Nykänen @suikula, Wagner Costa @wagnercosta, Johan Vlugt @Jooopieeert
"""
def __init__(self, config: Dict[str, Any]) -> None:
@@ -81,6 +81,7 @@ class IFreqaiModel(ABC):
self.total_pairs = len(self.config.get("exchange", {}).get("pair_whitelist"))
self.last_trade_database_summary: DataFrame = {}
self.current_trade_database_summary: DataFrame = {}
self.analysis_lock = Lock()
def assert_config(self, config: Dict[str, Any]) -> None:
@@ -114,10 +115,10 @@ class IFreqaiModel(ABC):
elif not self.follow_mode:
self.dk = FreqaiDataKitchen(self.config, self.live, metadata["pair"])
logger.info(f"Training {len(self.dk.training_timeranges)} timeranges")
dataframe = self.dk.use_strategy_to_populate_indicators(
strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
)
with self.analysis_lock:
dataframe = self.dk.use_strategy_to_populate_indicators(
strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
)
dk = self.start_backtesting(dataframe, metadata, self.dk)
dataframe = dk.remove_features_from_df(dk.return_dataframe)
@@ -289,9 +290,10 @@ class IFreqaiModel(ABC):
# load the model and associated data into the data kitchen
self.model = self.dd.load_data(metadata["pair"], dk)
dataframe = self.dk.use_strategy_to_populate_indicators(
strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
)
with self.analysis_lock:
dataframe = self.dk.use_strategy_to_populate_indicators(
strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
)
if not self.model:
logger.warning(
@@ -485,9 +487,10 @@ class IFreqaiModel(ABC):
data_load_timerange, pair, dk
)
unfiltered_dataframe = dk.use_strategy_to_populate_indicators(
strategy, corr_dataframes, base_dataframes, pair
)
with self.analysis_lock:
unfiltered_dataframe = dk.use_strategy_to_populate_indicators(
strategy, corr_dataframes, base_dataframes, pair
)
unfiltered_dataframe = dk.slice_dataframe(new_trained_timerange, unfiltered_dataframe)
@@ -500,7 +503,7 @@ class IFreqaiModel(ABC):
dk.set_new_model_names(pair, new_trained_timerange)
self.dd.pair_dict[pair]["first"] = False
if self.dd.pair_dict[pair]["priority"] == 1 and self.scanning:
with dk.analysis_lock:
with self.analysis_lock:
self.dd.pair_to_end_of_training_queue(pair)
self.dd.save_data(model, pair, dk)