tests: Update orderflow tests

freqtrade/data/converter/orderflow.py

@@ -4,14 +4,12 @@ Functions to convert orderflow data from public_trades
 
 import logging
 import time
-from collections import OrderedDict
 from datetime import datetime
 
 import numpy as np
 import pandas as pd
 
 from freqtrade.constants import DEFAULT_ORDERFLOW_COLUMNS, Config
-from freqtrade.enums import RunMode
 from freqtrade.exceptions import DependencyException
 
 

freqtrade/strategy/interface.py

@@ -5,7 +5,6 @@ This module defines the interface to apply for strategies
 
 import logging
 from abc import ABC, abstractmethod
-from collections import OrderedDict
 from datetime import datetime, timedelta, timezone
 from math import isinf, isnan
 

tests/data/test_converter_orderflow.py

@@ -1,5 +1,3 @@
-from collections import OrderedDict
-
 import numpy as np
 import pandas as pd
 import pytest
@@ -105,7 +103,7 @@ def test_public_trades_mock_populate_dataframe_with_trades__check_orderflow(
         },
     }
     # Apply the function to populate the data frame with order flow data
-    df, _ = populate_dataframe_with_trades(OrderedDict(), config, dataframe, trades)
+    df, _ = populate_dataframe_with_trades(None, config, dataframe, trades)
     # Extract results from the first row of the DataFrame
     results = df.iloc[0]
     t = results["trades"]
@@ -246,7 +244,7 @@ def test_public_trades_trades_mock_populate_dataframe_with_trades__check_trades(
     }
 
     # Populate the DataFrame with trades and order flow data
-    df, _ = populate_dataframe_with_trades(OrderedDict(), config, dataframe, trades)
+    df, _ = populate_dataframe_with_trades(None, config, dataframe, trades)
 
     # --- DataFrame and Trade Data Validation ---
 
@@ -404,9 +402,7 @@ def test_public_trades_config_max_trades(
         },
     }
 
-    df, _ = populate_dataframe_with_trades(
-        OrderedDict(), default_conf | orderflow_config, dataframe, trades
-    )
+    df, _ = populate_dataframe_with_trades(None, default_conf | orderflow_config, dataframe, trades)
     assert df.delta.count() == 1