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google-labs-jules[bot]andmaghdam 5c24d2d72d test: add error path test for live trading get_data
- Add check for `mt5.copy_rates_from_pos` returning `None` in `live_trading/multi_bar.py:82`
- Add test in `tests/test_multi_bar.py` verifying that when `mt5.copy_rates_from_pos` returns `None`, the function returns `None` and an error is logged.

Co-authored-by: maghdam <63883156+maghdam@users.noreply.github.com>
2026-03-11 18:33:09 +00:00
4 changed files with 27 additions and 67 deletions
+3
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@@ -82,6 +82,9 @@ class TradingApp:
Fetch 'n' bars of historical data for the given symbol and timeframe.
"""
rates = mt5.copy_rates_from_pos(symbol, timeframe, 0, n)
if rates is None:
log_and_print(f"Could not retrieve data for {symbol}", is_error=True)
return None
rates_frame = pd.DataFrame(rates)
rates_frame['time'] = pd.to_datetime(rates_frame['time'], unit='s')
rates_frame.set_index('time', inplace=True)
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-67
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@@ -1,67 +0,0 @@
import pandas as pd
import numpy as np
import pytest
from features.labeling_schemes import create_labels_multi_bar
def test_create_labels_multi_bar():
"""
Test create_labels_multi_bar correctly assigns labels based on future returns.
"""
# Create a simple dummy dataframe
# We want future returns over horizon=2 to be:
# index 0: (10.5 / 10.0) - 1 = 0.05 (should be +1, since >= 0.05 is not met if threshold=0.06, wait let's use exact)
df = pd.DataFrame({
"close": [100.0, 100.0, 105.0, 95.0, 100.0, 100.0]
})
# Let's set horizon=2, threshold=0.04
# future returns for horizon=2:
# i=0: (105.0 - 100.0)/100.0 = 0.05 => >= 0.04 => 1
# i=1: (95.0 - 100.0)/100.0 = -0.05 => <= -0.04 => -1
# i=2: (100.0 - 105.0)/105.0 = -0.0476 => <= -0.04 => -1
# i=3: (100.0 - 95.0)/95.0 = 0.0526 => >= 0.04 => 1
# i=4: NaN
# i=5: NaN
labeled_df = create_labels_multi_bar(df, horizon=2, threshold=0.04)
# Check that df wasn't modified in place
assert "multi_bar_label" not in df.columns
# Ensure correct columns exist in result
assert "future_return_h" in labeled_df.columns
assert "multi_bar_label" in labeled_df.columns
# Since the original drops NaN, it should have 4 rows
assert len(labeled_df) == 4
# Check calculated future returns roughly match expected
expected_returns = [0.05, -0.05, -0.047619047619047616, 0.052631578947368474]
np.testing.assert_allclose(labeled_df["future_return_h"].values, expected_returns, rtol=1e-5)
# Check assigned labels
expected_labels = [1, -1, -1, 1]
np.testing.assert_array_equal(labeled_df["multi_bar_label"].values, expected_labels)
def test_create_labels_multi_bar_neutral():
"""
Test create_labels_multi_bar handles neutral labels correctly (returns inside threshold).
"""
df = pd.DataFrame({
"close": [100.0, 101.0, 102.0, 99.0, 100.0]
})
# Let's set horizon=1, threshold=0.02
# future returns for horizon=1:
# i=0: (101 - 100)/100 = 0.01 (neutral -> 0)
# i=1: (102 - 101)/101 = 0.0099 (neutral -> 0)
# i=2: (99 - 102)/102 = -0.0294 (down -> -1)
# i=3: (100 - 99)/99 = 0.0101 (neutral -> 0)
labeled_df = create_labels_multi_bar(df, horizon=1, threshold=0.02)
assert len(labeled_df) == 4
expected_labels = [0, 0, -1, 0]
np.testing.assert_array_equal(labeled_df["multi_bar_label"].values, expected_labels)
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@@ -0,0 +1,24 @@
import sys
from unittest.mock import MagicMock
# Mock out MetaTrader5 before importing our module
sys.modules['MetaTrader5'] = MagicMock()
import unittest
from unittest.mock import patch
import pandas as pd
from live_trading.multi_bar import TradingApp, log_and_print
class TestTradingApp(unittest.TestCase):
def setUp(self):
self.app = TradingApp(symbol="EURUSD", lot_size=0.01, magic_number=123456)
@patch("live_trading.multi_bar.mt5.copy_rates_from_pos")
@patch("live_trading.multi_bar.log_and_print")
def test_get_data_returns_none(self, mock_log, mock_copy_rates):
mock_copy_rates.return_value = None
# Test what happens when mt5.copy_rates_from_pos returns None
result = self.app.get_data("EURUSD", 100, 16408)
self.assertIsNone(result)
mock_log.assert_called_once_with("Could not retrieve data for EURUSD", is_error=True)