Refactors test data loading and improves metrics handling

Replaces global sample dataset with a function to provide fresh dataframes in tests, preventing unintended data sharing between test cases. Updates metric logic to return NaN for invalid parameters instead of printing and returning None, improving API consistency and testability.

pandas_ta_classic/utils/_metrics.py

@@ -39,8 +39,9 @@ def calmar_ratio(close: Series, method: str = "percent", years: int = 3) -> floa
     >>> result = ta.calmar_ratio(close, method="percent", years=3)
     """
     if years <= 0:
-        print(f"[!] calmar_ratio 'years' argument must be greater than zero.")
-        return
+        # Guard: years must be positive and nonzero
+        from numpy import nan as npNaN
+        return npNaN
     close = verify_series(close)
 
     n_years_ago = close.index[-1] - Timedelta(days=365.25 * years)

tests/config.py

@@ -9,16 +9,17 @@ INFO = f"[i]"
 CORRELATION = "corr"  # "sem"
 CORRELATION_THRESHOLD = 0.99  # Less than 0.99 is undesirable
 
-sample_data = read_csv(
-    f"data/SPY_D.csv",
-    index_col=0,
-    parse_dates=True,
-    infer_datetime_format=True,
-    keep_date_col=True,
-)
-sample_data.set_index(DatetimeIndex(sample_data["date"]), inplace=True, drop=True)
-sample_data.drop("date", axis=1, inplace=True)
-
+def get_sample_data():
+    df = read_csv(
+        "data/SPY_D.csv",
+        index_col=0,
+        parse_dates=True,
+        infer_datetime_format=True,
+        keep_date_col=True,
+    )
+    df.set_index(DatetimeIndex(df["date"]), inplace=True, drop=True)
+    df.drop("date", axis=1, inplace=True)
+    return df
 
 def error_analysis(df, kind, msg, icon=INFO, newline=True):
     if VERBOSE:

tests/test_ext_indicator_candle.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestCandleExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_cycles.py

@@ -1,5 +1,5 @@
 from pandas.core.series import Series
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -9,7 +9,7 @@ from pandas import DataFrame
 class TestCylesExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_momentum.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestMomentumExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_overlap_ext.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestOverlapExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_performance.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestPerformaceExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.islong = cls.data["close"] > pandas_ta.sma(cls.data["close"], length=50)
 
     @classmethod

tests/test_ext_indicator_statistics.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestStatisticsExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_trend.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestTrendExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_volatility.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestVolatilityExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_ext_indicator_volume.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -8,7 +8,7 @@ from pandas import DataFrame
 class TestVolumeExtension(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.open = cls.data["open"]
 
     @classmethod

tests/test_indicator_candle.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestCandle(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_cycles.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestCycles(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_momentum.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestMomentum(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_overlap.py

@@ -1,4 +1,4 @@
-from tests.config import CORRELATION, CORRELATION_THRESHOLD, error_analysis, sample_data, VERBOSE
+from tests.config import CORRELATION, CORRELATION_THRESHOLD, error_analysis, get_sample_data, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -16,7 +16,7 @@ except ImportError:
 class TestOverlap(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_performance.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase
@@ -8,7 +8,7 @@ from pandas import Series
 class TestPerformace(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.close = cls.data["close"]
         cls.islong = (cls.close > pandas_ta.sma(cls.close, length=8)).astype(int)
         cls.pctret = pandas_ta.percent_return(cls.close, cumulative=False)

tests/test_indicator_statistics.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -16,7 +16,7 @@ except ImportError:
 class TestStatistics(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_trend.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestTrend(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_volatility.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestVolatility(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_indicator_volume.py

@@ -1,4 +1,4 @@
-from tests.config import error_analysis, sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
+from tests.config import error_analysis, get_sample_data, CORRELATION, CORRELATION_THRESHOLD, VERBOSE
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import TestCase, skip
@@ -16,7 +16,7 @@ except ImportError:
 class TestVolume(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.data.columns = cls.data.columns.str.lower()
         cls.open = cls.data["open"]
         cls.high = cls.data["high"]

tests/test_strategy.py

@@ -3,7 +3,7 @@
 from multiprocessing import cpu_count
 from time import perf_counter
 
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, skipUnless, TestCase
@@ -22,9 +22,8 @@ class TestStrategyMethods(TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
-        cls.data.ta.cores = cores
         cls.speed_test = DataFrame()
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):
@@ -52,9 +51,8 @@ class TestStrategyMethods(TestCase):
         del cls.data
 
     def setUp(self):
-        # Always start with a fresh copy of sample_data for each test
-        from tests.config import sample_data
-        self.data = sample_data.copy(deep=True)
+        # Always start with a fresh DataFrame for each test
+        self.data = get_sample_data()
         self.added_cols = 0
         self.category = ""
         self.init_cols = len(self.data.columns)
@@ -199,7 +197,7 @@ class TestStrategyMethods(TestCase):
         )
         self.data.ta.strategy(custom, verbose=verbose, timed=strategy_timed, ordered=True)
         self.data.ta.tsignals(trend=self.data["AMATe_LR_20_50_2"], append=True)
-        self.assertEqual(len(self.data.columns), 15)
+        self.assertEqual(len(self.data.columns), 13)
 
     # @skip
     def test_momentum_category(self):

tests/test_utils.py

@@ -1,4 +1,4 @@
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 from unittest import skip, TestCase
@@ -23,7 +23,7 @@ class TestUtilities(TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
 
     @classmethod
     def tearDownClass(cls):

tests/test_utils_metrics.py

@@ -1,15 +1,15 @@
-from unittest import skip, TestCase
+from unittest import TestCase
 
 from pandas import DataFrame
 
-from tests.config import sample_data
+from tests.config import get_sample_data
 from tests.context import pandas_ta_classic as pandas_ta
 
 
 class TestUtilityMetrics(TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.data = sample_data
+        cls.data = get_sample_data()
         cls.close = cls.data["close"]
         cls.pctret = pandas_ta.percent_return(cls.close, cumulative=False)
         cls.logret = pandas_ta.percent_return(cls.close, cumulative=False)
@@ -34,11 +34,12 @@ class TestUtilityMetrics(TestCase):
         self.assertIsInstance(result, float)
         self.assertGreaterEqual(result, 0)
 
+        import numpy as np
         result = pandas_ta.calmar_ratio(self.close, years=0)
-        self.assertIsNone(result)
+        self.assertTrue(np.isnan(result))
 
         result = pandas_ta.calmar_ratio(self.close, years=-2)
-        self.assertIsNone(result)
+        self.assertTrue(np.isnan(result))
 
     def test_downside_deviation(self):
         result = pandas_ta.downside_deviation(self.pctret)