fix upstream bugs and modernize project (PRs marcdemers#18, marcdemers#19, marcdemers#20, marcdemers#21, marcdemers#26)

knaps · claude · knaps · commit 8560ab62d584 · 2026-03-26T21:26:56.000-07:00
- Fix model='black' crash: remove extra `b` arg from 5 original greeks, fix wrong arg order in gamma_black and syntax error in rho_black (marcdemers#20) - Fix pandas index-alignment in price_dataframe() with np.asarray() (marcdemers#21) - Fix vectorized_black discounting: apply exp(-r*t) to match py_vollib (marcdemers#19) - Switch all S/F numerical bumps from absolute (dS=0.01) to relative (h=S*1e-4), preventing NaN for small spot prices (marcdemers#18) - Fix test file paths with pathlib so tests run from project root (marcdemers#26) - Add GitHub Actions CI workflow, update Python classifiers to 3.10-3.13, bump numba>=0.61.0, replace distutils with setuptools (marcdemers#26) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -0,0 +1,21 @@
+name: CI
+
+on: [push, pull_request]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: pip install -e '.[test]'
+      - name: Run tests
+        run: pytest tests/ -v
diff --git a/py_vollib_vectorized/_model_calls.py b/py_vollib_vectorized/_model_calls.py
@@ -87,10 +87,10 @@ def _black_scholes_vectorized_call(flags, Ss, Ks, ts, rs, sigmas):
 
 
 @maybe_jit()
-def _black_vectorized_call(Fs, Ks, sigmas, ts, flag):
+def _black_vectorized_call(Fs, Ks, sigmas, ts, rs, flag):
     prices = []
-    for F, K, sigma, T, q in zip(Fs, Ks, sigmas, ts, flag):
-        prices.append(black(F, K, sigma, T, q))
+    for F, K, sigma, T, r, q in zip(Fs, Ks, sigmas, ts, rs, flag):
+        prices.append(np.exp(-r * T) * black(F, K, sigma, T, q))
     return prices
 
 
diff --git a/py_vollib_vectorized/_numerical_greeks.py b/py_vollib_vectorized/_numerical_greeks.py
diff --git a/py_vollib_vectorized/api.py b/py_vollib_vectorized/api.py
@@ -141,9 +141,9 @@ def price_dataframe(df, *, flag_col=None, underlying_price_col=None, strike_col=
             raise ValueError("Model must be one of: `black`, `black_scholes`, `black_scholes_merton`")
 
         if inplace:
-            df["Price"] = price
+            df["Price"] = np.asarray(price)
         else:
-            output_df["Price"] = price
+            output_df["Price"] = np.asarray(price)
 
     if _iv_calc:
         if model == "black":
@@ -170,18 +170,18 @@ def price_dataframe(df, *, flag_col=None, underlying_price_col=None, strike_col=
             raise ValueError("Model must be one of: `black`, `black_scholes`, `black_scholes_merton`")
 
         if inplace:
-            df["IV"] = sigma
+            df["IV"] = np.asarray(sigma)
         else:
-            output_df["IV"] = sigma
+            output_df["IV"] = np.asarray(sigma)
 
     if _greek_calc:
         greeks = get_all_greeks(flag, S, K, t, r, sigma, q, model=model, return_as="dataframe")
 
         for col in greeks:
             if inplace:
-                df[col] = greeks[col]
+                df[col] = np.asarray(greeks[col])
             else:
-                output_df[col] = greeks[col]
+                output_df[col] = np.asarray(greeks[col])
 
     if not inplace:
         return output_df
diff --git a/py_vollib_vectorized/greeks.py b/py_vollib_vectorized/greeks.py
@@ -70,8 +70,7 @@ def delta(flag, S, K, t, r, sigma, q=None, *, model="black_scholes", return_as="
     _validate_data(flag, S, K, t, r, sigma)
 
     if model == "black":
-        b = 0
-        delta = numerical_delta_black(flag, S, K, t, r, sigma, b)
+        delta = numerical_delta_black(flag, S, K, t, r, sigma)
     elif model == "black_scholes":
         b = r
         delta = numerical_delta_black_scholes(flag, S, K, t, r, sigma, b)
@@ -126,8 +125,7 @@ def theta(flag, S, K, t, r, sigma, q=None, *,  model="black_scholes", return_as=
     _validate_data(flag, S, K, t, r, sigma)
 
     if model == "black":
-        b = 0
-        theta = numerical_theta_black(flag, S, K, t, r, sigma, b)
+        theta = numerical_theta_black(flag, S, K, t, r, sigma)
 
     elif model == "black_scholes":
         b = r
@@ -181,8 +179,7 @@ def vega(flag, S, K, t, r, sigma, q=None, *, model="black_scholes", return_as="d
     _validate_data(flag, S, K, t, r, sigma)
 
     if model == "black":
-        b = 0
-        vega = numerical_vega_black(flag, S, K, t, r, sigma, b)
+        vega = numerical_vega_black(flag, S, K, t, r, sigma)
 
     elif model == "black_scholes":
         b = r
@@ -237,8 +234,7 @@ def rho(flag, S, K, t, r, sigma, q=None, *, model="black_scholes", return_as="da
     _validate_data(flag, S, K, t, r, sigma)
 
     if model == "black":
-        b = 0
-        rho = numerical_rho_black(flag, S, K, t, r, sigma, b)
+        rho = numerical_rho_black(flag, S, K, t, r, sigma)
 
     elif model == "black_scholes":
         b = r
@@ -292,9 +288,8 @@ def gamma(flag, S, K, t, r, sigma, q=None, *,  model="black_scholes", return_as=
     _validate_data(flag, S, K, t, r, sigma)
 
     if model == "black":
-        b = 0
         # black scholes, it calls the black_scholes function and not the black function.
-        gamma = numerical_gamma_black(flag, S, K, t, r, sigma, b)
+        gamma = numerical_gamma_black(flag, S, K, t, r, sigma)
     elif model == "black_scholes":
         b = r
         gamma = numerical_gamma_black_scholes(flag, S, K, t, r, sigma, b)
diff --git a/py_vollib_vectorized/models.py b/py_vollib_vectorized/models.py
@@ -29,13 +29,13 @@ def vectorized_black(flag, F, K, t, r, sigma, *, return_as="dataframe", dtype=np
     >>> py_vollib.black.black(flag, F, K, t, r, sigma, return_as='numpy')
     array([1.53408169, 1.38409245])
     >>> py_vollib_vectorized.vectorized_black(flag, F, K, t, r, sigma, return_as='numpy')  # equivalent
-    array([1.53408169, 1.38409245])
+    array([1.47392948, 1.3298214 ])
     """
     flag = _preprocess_flags(flag, dtype=dtype)
-    F, K, sigma, t, flag = maybe_format_data_and_broadcast(F, K, sigma, t, flag, dtype=dtype)
-    _validate_data(F, K, sigma, t, flag)
+    F, K, sigma, t, r, flag = maybe_format_data_and_broadcast(F, K, sigma, t, r, flag, dtype=dtype)
+    _validate_data(F, K, sigma, t, r, flag)
 
-    prices = _black_vectorized_call(F, K, sigma, t, flag)
+    prices = _black_vectorized_call(F, K, sigma, t, r, flag)
     prices = np.ascontiguousarray(prices)
 
     if return_as == "series":
diff --git a/setup.py b/setup.py
@@ -1,6 +1,6 @@
 import io
 import os
-from distutils.core import setup
+from setuptools import setup
 
 from setuptools import find_packages
 
@@ -27,16 +27,24 @@
           'Topic :: Scientific/Engineering :: Mathematics',
           'Topic :: Scientific/Engineering :: Information Analysis',
           'Topic :: Software Development :: Libraries',
-          'Programming Language :: Python :: 3.3',
-          'Programming Language :: Python :: 3.4',
-          'Programming Language :: Python :: 3.5',
-          'Programming Language :: Python :: 3.6',
-          'Programming Language :: Python :: 3.7',
-          'Programming Language :: Python :: Implementation',
+          'Programming Language :: Python :: 3.10',
+          'Programming Language :: Python :: 3.11',
+          'Programming Language :: Python :: 3.12',
+          'Programming Language :: Python :: 3.13',
           'License :: OSI Approved :: MIT License',
           'Topic :: Office/Business :: Financial',
           'Topic :: Office/Business :: Financial :: Investment',
       ],
-      install_requires=['py_vollib>=1.0.1', 'numba>=0.51.0', 'py_lets_be_rational', 'numpy', 'pandas', 'scipy'],
+      install_requires=[
+          'py_vollib>=1.0.1',
+          'numba>=0.61.0',
+          'py_lets_be_rational',
+          'numpy',
+          'pandas',
+          'scipy',
+      ],
+      extras_require={
+          'test': ['pytest'],
+      },
       packages=find_packages()
       )
diff --git a/tests/test_entrypoints.py b/tests/test_entrypoints.py
@@ -1,6 +1,9 @@
+from pathlib import Path
 from unittest import TestCase
 import json
 import pandas as pd, numpy as np
+
+_TEST_DIR = Path(__file__).parent
 from numpy.testing import assert_array_almost_equal
 
 from py_vollib_vectorized.implied_volatility import vectorized_implied_volatility
@@ -11,7 +14,7 @@
 
 class Test(TestCase):
     def setUp(self) -> None:
-        with open("test_data_py_vollib.json", "rb") as f:
+        with open(_TEST_DIR / "test_data_py_vollib.json", "rb") as f:
             d = json.load(f)
             self.test_df = pd.DataFrame(d["data"], index=d["index"], columns=d["columns"])
             self.test_df_calls = self.test_df.copy()
@@ -184,7 +187,7 @@ def test_validity_greeks(self):
         from py_vollib.black_scholes.greeks.numerical import delta as original_delta, gamma as original_gamma, \
             rho as original_rho, theta as original_theta, vega as original_vega
 
-        data = pd.read_csv("fake_data.csv")
+        data = pd.read_csv(_TEST_DIR / "fake_data.csv")
         ivs = vectorized_implied_volatility(
             price=data["MidPx"].values,  # current option price
             S=data["Px"].values,  # underlying asset price
diff --git a/tests/test_upstream_fixes.py b/tests/test_upstream_fixes.py
