works again when pandas isn't installed

Author: ngoldbaum

stringdtype/stringdtype/src/umath.c

@@ -391,17 +391,6 @@ init_ufuncs(void)
         goto error;
     }
 
-    PyArray_DTypeMeta *peq_dtypes[] = {(PyArray_DTypeMeta *)&PandasStringDType,
-                                       (PyArray_DTypeMeta *)&PandasStringDType,
-                                       &PyArray_BoolDType};
-
-    if (init_ufunc(numpy, "equal", peq_dtypes,
-                   &string_equal_resolve_descriptors,
-                   &string_equal_strided_loop, "string_equal", 2, 1,
-                   NPY_NO_CASTING, 0) < 0) {
-        goto error;
-    }
-
     PyArray_DTypeMeta *promoter_dtypes[2][3] = {
             {(PyArray_DTypeMeta *)&StringDType, &PyArray_UnicodeDType,
              &PyArray_BoolDType},
@@ -417,21 +406,6 @@ init_ufuncs(void)
         goto error;
     }
 
-    PyArray_DTypeMeta *p_promoter_dtypes[2][3] = {
-            {(PyArray_DTypeMeta *)&PandasStringDType, &PyArray_UnicodeDType,
-             &PyArray_BoolDType},
-            {&PyArray_UnicodeDType, (PyArray_DTypeMeta *)&PandasStringDType,
-             &PyArray_BoolDType},
-    };
-
-    if (add_promoter(numpy, "equal", p_promoter_dtypes[0]) < 0) {
-        goto error;
-    }
-
-    if (add_promoter(numpy, "equal", p_promoter_dtypes[1]) < 0) {
-        goto error;
-    }
-
     PyArray_DTypeMeta *isnan_dtypes[] = {(PyArray_DTypeMeta *)&StringDType,
                                          &PyArray_BoolDType};
 
@@ -442,16 +416,6 @@ init_ufuncs(void)
         goto error;
     }
 
-    PyArray_DTypeMeta *p_isnan_dtypes[] = {
-            (PyArray_DTypeMeta *)&PandasStringDType, &PyArray_BoolDType};
-
-    if (init_ufunc(numpy, "isnan", p_isnan_dtypes,
-                   &string_isnan_resolve_descriptors,
-                   &string_isnan_strided_loop, "string_isnan", 1, 1,
-                   NPY_NO_CASTING, 0) < 0) {
-        goto error;
-    }
-
     PyArray_DTypeMeta *minmax_dtypes[] = {
             (PyArray_DTypeMeta *)&StringDType,
             (PyArray_DTypeMeta *)&StringDType,
@@ -469,6 +433,57 @@ init_ufuncs(void)
         goto error;
     }
 
+    PyArray_DTypeMeta *add_dtypes[] = {
+            (PyArray_DTypeMeta *)&StringDType,
+            (PyArray_DTypeMeta *)&StringDType,
+            (PyArray_DTypeMeta *)&StringDType,
+    };
+
+    if (init_ufunc(numpy, "add", add_dtypes, NULL, &add_strided_loop,
+                   "string_add", 2, 1, NPY_NO_CASTING, 0) < 0) {
+        goto error;
+    }
+
+    if (!PANDAS_AVAILABLE) {
+        goto finish;
+    }
+
+    PyArray_DTypeMeta *peq_dtypes[] = {(PyArray_DTypeMeta *)&PandasStringDType,
+                                       (PyArray_DTypeMeta *)&PandasStringDType,
+                                       &PyArray_BoolDType};
+
+    if (init_ufunc(numpy, "equal", peq_dtypes,
+                   &string_equal_resolve_descriptors,
+                   &string_equal_strided_loop, "string_equal", 2, 1,
+                   NPY_NO_CASTING, 0) < 0) {
+        goto error;
+    }
+
+    PyArray_DTypeMeta *p_promoter_dtypes[2][3] = {
+            {(PyArray_DTypeMeta *)&PandasStringDType, &PyArray_UnicodeDType,
+             &PyArray_BoolDType},
+            {&PyArray_UnicodeDType, (PyArray_DTypeMeta *)&PandasStringDType,
+             &PyArray_BoolDType},
+    };
+
+    if (add_promoter(numpy, "equal", p_promoter_dtypes[0]) < 0) {
+        goto error;
+    }
+
+    if (add_promoter(numpy, "equal", p_promoter_dtypes[1]) < 0) {
+        goto error;
+    }
+
+    PyArray_DTypeMeta *p_isnan_dtypes[] = {
+            (PyArray_DTypeMeta *)&PandasStringDType, &PyArray_BoolDType};
+
+    if (init_ufunc(numpy, "isnan", p_isnan_dtypes,
+                   &string_isnan_resolve_descriptors,
+                   &string_isnan_strided_loop, "string_isnan", 1, 1,
+                   NPY_NO_CASTING, 0) < 0) {
+        goto error;
+    }
+
     PyArray_DTypeMeta *p_minmax_dtypes[] = {
             (PyArray_DTypeMeta *)&PandasStringDType,
             (PyArray_DTypeMeta *)&PandasStringDType,
@@ -487,17 +502,6 @@ init_ufuncs(void)
         goto error;
     }
 
-    PyArray_DTypeMeta *add_dtypes[] = {
-            (PyArray_DTypeMeta *)&StringDType,
-            (PyArray_DTypeMeta *)&StringDType,
-            (PyArray_DTypeMeta *)&StringDType,
-    };
-
-    if (init_ufunc(numpy, "add", add_dtypes, NULL, &add_strided_loop,
-                   "string_add", 2, 1, NPY_NO_CASTING, 0) < 0) {
-        goto error;
-    }
-
     PyArray_DTypeMeta *p_add_dtypes[] = {
             (PyArray_DTypeMeta *)&PandasStringDType,
             (PyArray_DTypeMeta *)&PandasStringDType,
@@ -509,6 +513,7 @@ init_ufuncs(void)
         goto error;
     }
 
+finish:
     Py_DECREF(numpy);
     return 0;
 

stringdtype/tests/test_stringdtype.py

@@ -5,7 +5,11 @@
 import tempfile
 
 import numpy as np
-import pandas
+
+try:
+    import pandas
+except ImportError:
+    pandas = None
 import pytest
 
 from stringdtype import (
@@ -22,16 +26,17 @@ def string_list():
     return ["abc", "def", "ghi", "A¢☃€ 😊", "Abc", "DEF"]
 
 
-@pytest.fixture(params=["StringDtype", "PandasStringDType"])
+@pytest.fixture(params=["StringDType", "PandasStringDType"])
 def dtype(request):
     if request.param == "StringDType":
         return StringDType()
-    try:
-        from stringdtype import PandasStringDType
+    elif request.param == "PandasStringDType":
+        try:
+            from stringdtype import PandasStringDType
 
-        return PandasStringDType()
-    except ImportError:
-        pytest.skip("cannot import pandas")
+            return PandasStringDType()
+        except ImportError:
+            pytest.skip("cannot import pandas")
 
 
 @pytest.fixture
@@ -361,9 +366,13 @@ def test_ufunc_add(dtype, string_list, other_strings):
     )
 
 
-@pytest.mark.parametrize("na_val", [float("nan"), np.nan, NA, pandas.NA])
+@pytest.mark.parametrize(
+    "na_val", [float("nan"), np.nan, NA, getattr(pandas, "NA", None)]
+)
 def test_create_with_na(dtype, na_val):
-    if dtype == StringDType() and na_val is pandas.NA:
+    if not hasattr(pandas, "NA") or (
+        dtype == StringDType() and na_val is pandas.NA
+    ):
         return
     if dtype != StringDType and na_val is NA:
         return