From 4628f7d6ac3b3ab45d2b623b4b574da9adf5b4c1 Mon Sep 17 00:00:00 2001
From: xgboosted <1528712+xgboosted@users.noreply.github.com>
Date: Wed, 8 Jul 2026 19:23:59 +1000
Subject: [PATCH] test(metrics): align optimal_leverage test with float
 contract

optimal_leverage returns float instead of int(...) and raises
ValueError on zero-variance input; the old test pinned the int
truncation. Adds finiteness asserts and the zero-std raise path.
---
 tests/test_utils_metrics.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/tests/test_utils_metrics.py b/tests/test_utils_metrics.py
index 216aa29..5167e4e 100644
--- a/tests/test_utils_metrics.py
+++ b/tests/test_utils_metrics.py
@@ -1,6 +1,7 @@
+import math
 from unittest import TestCase
 
-from pandas import DataFrame
+from pandas import DataFrame, Series
 
 from tests.config import get_sample_data
 import pandas_ta_classic as pandas_ta
@@ -94,17 +95,20 @@ class TestUtilityMetrics(TestCase):
 
     def test_optimal_leverage(self):
         result = pandas_ta.optimal_leverage(self.close)
-        self.assertIsInstance(result, int)
+        self.assertIsInstance(result, float)
+        self.assertTrue(math.isfinite(result))
         result = pandas_ta.optimal_leverage(self.close, log=True)
-        self.assertIsInstance(result, int)
+        self.assertIsInstance(result, float)
+        self.assertTrue(math.isfinite(result))
+        constant = Series([100.0] * 60)
+        with self.assertRaises(ValueError):
+            pandas_ta.optimal_leverage(constant)
 
     def test_pure_profit_score(self):
         result = pandas_ta.pure_profit_score(self.close)
         self.assertGreaterEqual(result, 0)
 
     def test_sharpe_ratio(self):
-        import math
-
         result = pandas_ta.sharpe_ratio(self.close)
         self.assertIsInstance(result, float)
         self.assertGreaterEqual(result, 0)