cleanup

Author: matiaslindgren

pandas/_libs/hashtable_func_helper.pxi.in

@@ -6,7 +6,7 @@ WARNING: DO NOT edit .pxi FILE directly, .pxi is generated from .pxi.in
 
 {{py:
 
-# name, dtype, ttype, tfunc_type, c_type, to_c_type
+# name, dtype, ttype, tfunc, c_type, to_c_type
 dtypes = [('Complex128', 'complex128', 'complex128', 'complex128', 'khcomplex128_t', 'to_khcomplex128_t'),
           ('Complex64', 'complex64', 'complex64', 'complex64', 'khcomplex64_t', 'to_khcomplex64_t'),
           ('Float64', 'float64', 'float64', 'float64', 'float64_t', ''),
@@ -23,7 +23,7 @@ dtypes = [('Complex128', 'complex128', 'complex128', 'complex128', 'khcomplex128
 
 }}
 
-{{for name, dtype, ttype, tfunc_type, c_type, to_c_type in dtypes}}
+{{for name, dtype, ttype, tfunc, c_type, to_c_type in dtypes}}
 
 
 @cython.wraparound(False)
@@ -53,26 +53,26 @@ cdef value_count_{{dtype}}(const {{dtype}}_t[:] values, bint dropna, const uint8
     #    result_keys remembers the original order of keys
 
     result_keys = {{name}}Vector()
-    table = kh_init_{{tfunc_type}}()
+    table = kh_init_{{tfunc}}()
 
     {{if dtype == 'object'}}
     if uses_mask:
         raise NotImplementedError("uses_mask not implemented with object dtype")
 
-    kh_resize_{{tfunc_type}}(table, n // 10)
+    kh_resize_{{tfunc}}(table, n // 10)
 
     for i in range(n):
         val = values[i]
         if not dropna or not checknull(val):
-            k = kh_get_{{tfunc_type}}(table, {{to_c_type}}val)
+            k = kh_get_{{tfunc}}(table, {{to_c_type}}val)
             if k != table.n_buckets:
                 table.vals[k] += 1
             else:
-                k = kh_put_{{tfunc_type}}(table, {{to_c_type}}val, &ret)
+                k = kh_put_{{tfunc}}(table, {{to_c_type}}val, &ret)
                 table.vals[k] = 1
                 result_keys.append(val)
     {{else}}
-    kh_resize_{{tfunc_type}}(table, n)
+    kh_resize_{{tfunc}}(table, n)
 
     for i in range(n):
         val = {{to_c_type}}(values[i])
@@ -88,11 +88,11 @@ cdef value_count_{{dtype}}(const {{dtype}}_t[:] values, bint dropna, const uint8
             if uses_mask and isna_entry:
                 na_counter += 1
             else:
-                k = kh_get_{{tfunc_type}}(table, val)
+                k = kh_get_{{tfunc}}(table, val)
                 if k != table.n_buckets:
                     table.vals[k] += 1
                 else:
-                    k = kh_put_{{tfunc_type}}(table, val, &ret)
+                    k = kh_put_{{tfunc}}(table, val, &ret)
                     table.vals[k] = 1
                     result_keys.append(val)
     {{endif}}
@@ -105,17 +105,17 @@ cdef value_count_{{dtype}}(const {{dtype}}_t[:] values, bint dropna, const uint8
 
     for i in range(table.size):
         {{if dtype == 'object'}}
-        k = kh_get_{{tfunc_type}}(table, result_keys.data[i])
+        k = kh_get_{{tfunc}}(table, result_keys.data[i])
         {{else}}
-        k = kh_get_{{tfunc_type}}(table, result_keys.data.data[i])
+        k = kh_get_{{tfunc}}(table, result_keys.data.data[i])
         {{endif}}
         result_counts[i] = table.vals[k]
 
     if na_counter > 0:
         result_counts[table.size] = na_counter
         result_keys.append(val)
 
-    kh_destroy_{{tfunc_type}}(table)
+    kh_destroy_{{tfunc}}(table)
 
     return result_keys.to_array(), result_counts.base, na_counter
 
@@ -136,12 +136,12 @@ cdef duplicated_{{dtype}}(const {{dtype}}_t[:] values, object keep='first', cons
         {{endif}}
         Py_ssize_t i, n = len(values), first_na = -1
         khiter_t k
-        kh_{{ttype}}_t *table = kh_init_{{tfunc_type}}()
+        kh_{{ttype}}_t *table = kh_init_{{tfunc}}()
         ndarray[uint8_t, ndim=1, cast=True] out = np.empty(n, dtype='bool')
         bint seen_na = False, uses_mask = mask is not None
         bint seen_multiple_na = False
 
-    kh_resize_{{tfunc_type}}(table, min(kh_needed_n_buckets(n), SIZE_HINT_LIMIT))
+    kh_resize_{{tfunc}}(table, min(kh_needed_n_buckets(n), SIZE_HINT_LIMIT))
 
     if keep not in ('last', 'first', False):
         raise ValueError('keep must be either "first", "last" or False')
@@ -166,7 +166,7 @@ cdef duplicated_{{dtype}}(const {{dtype}}_t[:] values, object keep='first', cons
                         seen_na = True
                 else:
                     value = {{to_c_type}}(values[i])
-                    kh_put_{{tfunc_type}}(table, value, &ret)
+                    kh_put_{{tfunc}}(table, value, &ret)
                     out[i] = ret == 0
     {{endfor}}
 
@@ -191,16 +191,16 @@ cdef duplicated_{{dtype}}(const {{dtype}}_t[:] values, object keep='first', cons
 
                 else:
                     value = {{to_c_type}}(values[i])
-                    k = kh_get_{{tfunc_type}}(table, value)
+                    k = kh_get_{{tfunc}}(table, value)
                     if k != table.n_buckets:
                         out[table.vals[k]] = 1
                         out[i] = 1
                     else:
-                        k = kh_put_{{tfunc_type}}(table, value, &ret)
+                        k = kh_put_{{tfunc}}(table, value, &ret)
                         table.vals[k] = i
                         out[i] = 0
 
-    kh_destroy_{{tfunc_type}}(table)
+    kh_destroy_{{tfunc}}(table)
     return out
 
 
@@ -241,11 +241,11 @@ cdef ismember_{{dtype}}(const {{dtype}}_t[:] arr, const {{dtype}}_t[:] values):
         {{c_type}} val
         {{endif}}
 
-        kh_{{ttype}}_t *table = kh_init_{{tfunc_type}}()
+        kh_{{ttype}}_t *table = kh_init_{{tfunc}}()
 
     # construct the table
     n = len(values)
-    kh_resize_{{tfunc_type}}(table, n)
+    kh_resize_{{tfunc}}(table, n)
 
     {{if dtype == 'object'}}
     if True:
@@ -254,7 +254,7 @@ cdef ismember_{{dtype}}(const {{dtype}}_t[:] arr, const {{dtype}}_t[:] values):
     {{endif}}
         for i in range(n):
             val = {{to_c_type}}(values[i])
-            kh_put_{{tfunc_type}}(table, val, &ret)
+            kh_put_{{tfunc}}(table, val, &ret)
 
     # test membership
     n = len(arr)
@@ -267,10 +267,10 @@ cdef ismember_{{dtype}}(const {{dtype}}_t[:] arr, const {{dtype}}_t[:] values):
     {{endif}}
         for i in range(n):
             val = {{to_c_type}}(arr[i])
-            k = kh_get_{{tfunc_type}}(table, val)
+            k = kh_get_{{tfunc}}(table, val)
             result[i] = (k != table.n_buckets)
 
-    kh_destroy_{{tfunc_type}}(table)
+    kh_destroy_{{tfunc}}(table)
     return result.view(np.bool_)
 
 # ----------------------------------------------------------------------

pandas/_libs/include/pandas/vendored/klib/khash_python.h

@@ -3,7 +3,6 @@
 #pragma once
 
 #include <Python.h>
-
 #include <pymem.h>
 #include <string.h>
 
@@ -218,9 +217,6 @@ static inline int pyobject_cmp(PyObject *a, PyObject *b) {
 
   int result = PyObject_RichCompareBool(a, b, Py_EQ);
   if (result < 0) {
-    if (PyErr_Occurred() != NULL) {
-      return 0;
-    }
     return 0;
   }
   return result;
@@ -323,9 +319,6 @@ static inline khuint32_t kh_python_hash_func(PyObject *key) {
   }
 
   if (hash == -1) {
-    if (PyErr_Occurred() != NULL) {
-      return 0;
-    }
     return 0;
   }
 #if SIZEOF_PY_HASH_T == 4