From 86583268dde59548e2acc6f3dee408457dd6d86d Mon Sep 17 00:00:00 2001
From: Gregory Morse <gregory.morse@live.com>
Date: Thu, 9 Apr 2026 11:42:03 +0200
Subject: [PATCH] fix: validate accuracy is a positive even integer upfront
 (closes #25)

calc_support_resistance and get_extrema now raise a clear ValueError with a
descriptive message when accuracy is not a positive even integer, instead of
letting findiff raise a cryptic traceback deep in the call stack.
The root cause of the original reports (default accuracy=1) was already fixed
by changing the default to accuracy=2.
---
 CHANGELOG.md          |  8 ++++++++
 setup.py              |  2 +-
 tests/test_trendln.py | 21 +++++++++++++++++++++
 trendln/__init__.py   |  4 ++++
 4 files changed, 34 insertions(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9df58e9..33d92a6 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,14 @@
 Change Log
 ===========
 
+0.1.13
+-------
+- Added upfront validation of the ``accuracy`` parameter in
+  ``calc_support_resistance`` and ``get_extrema``: raises a clear
+  ``ValueError('accuracy must be a positive even integer')`` instead of a
+  cryptic findiff traceback when an odd or non-integer value is supplied;
+  the default remains ``accuracy=2`` (closes #25)
+
 0.1.12
 -------
 - `calc_support_resistance` and `get_extrema` now accept string names for their
diff --git a/setup.py b/setup.py
index 4a24b65..4a01807 100644
--- a/setup.py
+++ b/setup.py
@@ -30,7 +30,7 @@
 
 setup(
     name='trendln',
-    version="0.1.12",
+    version="0.1.13",
     description='Support and Resistance Trend lines Calculator for Financial Analysis',
     long_description=long_description,
     long_description_content_type='text/markdown',
diff --git a/tests/test_trendln.py b/tests/test_trendln.py
index 43ccafb..43757e3 100644
--- a/tests/test_trendln.py
+++ b/tests/test_trendln.py
@@ -279,6 +279,27 @@ def test_tuple_both_none_raises(self):
         with pytest.raises(ValueError):
             calc_support_resistance((None, None))
 
+    def test_accuracy_must_be_int(self):
+        with pytest.raises(ValueError, match='accuracy'):
+            calc_support_resistance(DATA_SIMPLE, accuracy=2.0)
+
+    def test_accuracy_must_be_positive(self):
+        with pytest.raises(ValueError, match='accuracy'):
+            calc_support_resistance(DATA_SIMPLE, accuracy=0)
+
+    def test_accuracy_must_be_even(self):
+        with pytest.raises(ValueError, match='accuracy'):
+            calc_support_resistance(DATA_SIMPLE, accuracy=1)
+
+    def test_accuracy_odd_raises_on_get_extrema(self):
+        with pytest.raises(ValueError, match='accuracy'):
+            get_extrema(DATA_SIMPLE, accuracy=3)
+
+    def test_accuracy_even_values_accepted(self):
+        # 2, 4, 6, 8 should all be accepted without error
+        for acc in (2, 4, 6, 8):
+            calc_support_resistance(DATA_SIMPLE, accuracy=acc)
+
 
 # ---------------------------------------------------------------------------
 # String aliases for method / extmethod constants (issue #14)
diff --git a/trendln/__init__.py b/trendln/__init__.py
index 13350f7..2cc9c12 100644
--- a/trendln/__init__.py
+++ b/trendln/__init__.py
@@ -516,6 +516,8 @@ def _resolve(explicit, default_key):
 
 def get_extrema(h, extmethod=METHOD_NUMDIFF, accuracy=2):
     extmethod = _resolve_name(extmethod, _EXTMETHOD_NAMES, 'extmethod')
+    if not type(accuracy) is int or accuracy <= 0 or accuracy % 2 != 0:
+        raise ValueError('accuracy must be a positive even integer (e.g. 2, 4, 6, 8)')
     #h must be single dimensional array-like object e.g. List, np.ndarray, pd.Series
     if type(h) is tuple and len(h) == 2 and (h[0] is None or check_num_alike(h[0])) and (h[1] is None or check_num_alike(h[1])) and (not h[0] is None or not h[1] is None):
         hmin, hmax = h[0], h[1]
@@ -591,6 +593,8 @@ def calc_support_resistance(h, extmethod = METHOD_NUMDIFF, method=METHOD_NSQURED
         raise ValueError('house_prob_iter must be of type int')
     if not type(sortError) is bool:
         raise ValueError('sortError must be True of False')
+    if not type(accuracy) is int or accuracy <= 0 or accuracy % 2 != 0:
+        raise ValueError('accuracy must be a positive even integer (e.g. 2, 4, 6, 8)')
     #h = hist.Close.tolist()
     if type(h) is tuple and len(h) == 2 and (h[0] is None or check_num_alike(h[0])) and (h[1] is None or check_num_alike(h[1])) and (not h[0] is None or not h[1] is None):
         if not h[0] is None and not h[1] is None and len(h[0]) != len(h[1]): #not strict requirement, but contextually ideal