Merge pull request #11681 from JamesLinxun/develop

skip trade-related columns
This commit is contained in:
Matthias
2025-04-30 17:59:54 +02:00
committed by GitHub
3 changed files with 20 additions and 16 deletions

View File

@@ -71,6 +71,19 @@ DEFAULT_DATAFRAME_COLUMNS = ["date", "open", "high", "low", "close", "volume"]
# it has wide consequences for stored trades files
DEFAULT_TRADES_COLUMNS = ["timestamp", "id", "type", "side", "price", "amount", "cost"]
DEFAULT_ORDERFLOW_COLUMNS = ["level", "bid", "ask", "delta"]
ORDERFLOW_ADDED_COLUMNS = [
"trades",
"orderflow",
"imbalances",
"stacked_imbalances_bid",
"stacked_imbalances_ask",
"max_delta",
"min_delta",
"bid",
"ask",
"delta",
"total_trades",
]
TRADES_DTYPES = {
"timestamp": "int64",
"id": "str",

View File

@@ -9,26 +9,12 @@ from datetime import datetime
import numpy as np
import pandas as pd
from freqtrade.constants import DEFAULT_ORDERFLOW_COLUMNS, Config
from freqtrade.constants import DEFAULT_ORDERFLOW_COLUMNS, ORDERFLOW_ADDED_COLUMNS, Config
from freqtrade.exceptions import DependencyException
logger = logging.getLogger(__name__)
ORDERFLOW_ADDED_COLUMNS = [
"trades",
"orderflow",
"imbalances",
"stacked_imbalances_bid",
"stacked_imbalances_ask",
"max_delta",
"min_delta",
"bid",
"ask",
"delta",
"total_trades",
]
def _init_dataframe_with_trades_columns(dataframe: pd.DataFrame):
"""

View File

@@ -16,7 +16,7 @@ from pandas import DataFrame
from sklearn.model_selection import train_test_split
from freqtrade.configuration import TimeRange
from freqtrade.constants import DOCS_LINK, Config
from freqtrade.constants import DOCS_LINK, ORDERFLOW_ADDED_COLUMNS, Config
from freqtrade.data.converter import reduce_dataframe_footprint
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_seconds
@@ -709,6 +709,11 @@ class FreqaiDataKitchen:
skip_columns = [
(f"{s}_{suffix}") for s in ["date", "open", "high", "low", "close", "volume"]
]
for s in ORDERFLOW_ADDED_COLUMNS:
if s in dataframe.columns and f"{s}_{suffix}" in dataframe.columns:
skip_columns.append(f"{s}_{suffix}")
dataframe = dataframe.drop(columns=skip_columns)
return dataframe