Remove inline from cython classes (#49873)

* removed inline class functions

* removed all cdef inline

* revert pxd

* removed unused code

* cython lint fixups

pandas/_libs/algos.pyx

@@ -70,7 +70,7 @@ tiebreakers = {
 }
 
 
-cdef inline bint are_diff(object left, object right):
+cdef bint are_diff(object left, object right):
     try:
         return fabs(left - right) > FP_ERR
     except TypeError:
@@ -257,7 +257,7 @@ def groupsort_indexer(const intp_t[:] index, Py_ssize_t ngroups):
     return indexer.base, counts.base
 
 
-cdef inline Py_ssize_t swap(numeric_t *a, numeric_t *b) nogil:
+cdef Py_ssize_t swap(numeric_t *a, numeric_t *b) nogil:
     cdef:
         numeric_t t
 
@@ -268,7 +268,7 @@ cdef inline Py_ssize_t swap(numeric_t *a, numeric_t *b) nogil:
     return 0
 
 
-cdef inline numeric_t kth_smallest_c(numeric_t* arr, Py_ssize_t k, Py_ssize_t n) nogil:
+cdef numeric_t kth_smallest_c(numeric_t* arr, Py_ssize_t k, Py_ssize_t n) nogil:
     """
     See kth_smallest.__doc__. The additional parameter n specifies the maximum
     number of elements considered in arr, needed for compatibility with usage

pandas/_libs/groupby.pyx

@@ -60,7 +60,7 @@ cdef enum InterpolationEnumType:
     INTERPOLATION_MIDPOINT
 
 
-cdef inline float64_t median_linear_mask(float64_t* a, int n, uint8_t* mask) nogil:
+cdef float64_t median_linear_mask(float64_t* a, int n, uint8_t* mask) nogil:
     cdef:
         int i, j, na_count = 0
         float64_t* tmp
@@ -97,7 +97,7 @@ cdef inline float64_t median_linear_mask(float64_t* a, int n, uint8_t* mask) nog
     return result
 
 
-cdef inline float64_t median_linear(float64_t* a, int n) nogil:
+cdef float64_t median_linear(float64_t* a, int n) nogil:
     cdef:
         int i, j, na_count = 0
         float64_t* tmp
@@ -134,7 +134,7 @@ cdef inline float64_t median_linear(float64_t* a, int n) nogil:
     return result
 
 
-cdef inline float64_t calc_median_linear(float64_t* a, int n, int na_count) nogil:
+cdef float64_t calc_median_linear(float64_t* a, int n, int na_count) nogil:
     cdef:
         float64_t result
 
@@ -1231,7 +1231,7 @@ def group_quantile(
 # group_nth, group_last, group_rank
 # ----------------------------------------------------------------------
 
-cdef inline bint _treat_as_na(numeric_object_t val, bint is_datetimelike) nogil:
+cdef bint _treat_as_na(numeric_object_t val, bint is_datetimelike) nogil:
     if numeric_object_t is object:
         # Should never be used, but we need to avoid the `val != val` below
         #  or else cython will raise about gil acquisition.

pandas/_libs/hashing.pyx

@@ -110,11 +110,11 @@ def hash_object_array(
     return result.base  # .base to retrieve underlying np.ndarray
 
 
-cdef inline uint64_t _rotl(uint64_t x, uint64_t b) nogil:
+cdef uint64_t _rotl(uint64_t x, uint64_t b) nogil:
     return (x << b) | (x >> (64 - b))
 
 
-cdef inline uint64_t u8to64_le(uint8_t* p) nogil:
+cdef uint64_t u8to64_le(uint8_t* p) nogil:
     return (<uint64_t>p[0] |
             <uint64_t>p[1] << 8 |
             <uint64_t>p[2] << 16 |
@@ -125,8 +125,8 @@ cdef inline uint64_t u8to64_le(uint8_t* p) nogil:
             <uint64_t>p[7] << 56)
 
 
-cdef inline void _sipround(uint64_t* v0, uint64_t* v1,
-                           uint64_t* v2, uint64_t* v3) nogil:
+cdef void _sipround(uint64_t* v0, uint64_t* v1,
+                    uint64_t* v2, uint64_t* v3) nogil:
     v0[0] += v1[0]
     v1[0] = _rotl(v1[0], 13)
     v1[0] ^= v0[0]

pandas/_libs/hashtable.pxd

@@ -185,5 +185,5 @@ cdef class Int64Vector(Vector):
 
     cdef resize(self)
     cpdef ndarray to_array(self)
-    cdef inline void append(self, int64_t x)
+    cdef void append(self, int64_t x)
     cdef extend(self, int64_t[:] x)

pandas/_libs/hashtable_class_helper.pxi.in

@@ -140,7 +140,7 @@ ctypedef struct {{name}}VectorData:
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-cdef inline void append_data_{{dtype}}({{name}}VectorData *data,
+cdef void append_data_{{dtype}}({{name}}VectorData *data,
                                        {{c_type}} x) nogil:
 
     data.data[data.n] = x
@@ -163,7 +163,7 @@ ctypedef fused vector_data:
     Complex64VectorData
     StringVectorData
 
-cdef inline bint needs_resize(vector_data *data) nogil:
+cdef bint needs_resize(vector_data *data) nogil:
     return data.n == data.m
 
 # ----------------------------------------------------------------------
@@ -241,7 +241,7 @@ cdef class {{name}}Vector(Vector):
         self.external_view_exists = True
         return self.ao
 
-    cdef inline void append(self, {{c_type}} x):
+    cdef void append(self, {{c_type}} x):
 
         if needs_resize(self.data):
             if self.external_view_exists:
@@ -311,7 +311,7 @@ cdef class StringVector(Vector):
         self.data.m = self.data.n
         return ao
 
-    cdef inline void append(self, char *x):
+    cdef void append(self, char *x):
 
         if needs_resize(self.data):
             self.resize()
@@ -339,7 +339,7 @@ cdef class ObjectVector(Vector):
     def __len__(self) -> int:
         return self.n
 
-    cdef inline append(self, object obj):
+    cdef append(self, object obj):
         if self.n == self.m:
             if self.external_view_exists:
                 raise ValueError("external reference but "

pandas/_libs/index.pyx

@@ -40,7 +40,7 @@ from pandas._libs.missing cimport (
 multiindex_nulls_shift = 2
 
 
-cdef inline bint is_definitely_invalid_key(object val):
+cdef bint is_definitely_invalid_key(object val):
     try:
         hash(val)
     except TypeError:
@@ -176,7 +176,7 @@ cdef class IndexEngine:
         loc = self.values.searchsorted(self._np_type(val), side="left")
         return loc
 
-    cdef inline _get_loc_duplicates(self, object val):
+    cdef _get_loc_duplicates(self, object val):
         # -> Py_ssize_t | slice | ndarray[bool]
         cdef:
             Py_ssize_t diff, left, right
@@ -225,7 +225,7 @@ cdef class IndexEngine:
 
         return self.unique == 1
 
-    cdef inline _do_unique_check(self):
+    cdef _do_unique_check(self):
 
         # this de-facto the same
         self._ensure_mapping_populated()
@@ -244,7 +244,7 @@ cdef class IndexEngine:
 
         return self.monotonic_dec == 1
 
-    cdef inline _do_monotonic_check(self):
+    cdef _do_monotonic_check(self):
         cdef:
             bint is_unique
         try:
@@ -277,7 +277,7 @@ cdef class IndexEngine:
     def is_mapping_populated(self) -> bool:
         return self.mapping is not None
 
-    cdef inline _ensure_mapping_populated(self):
+    cdef _ensure_mapping_populated(self):
         # this populates the mapping
         # if its not already populated
         # also satisfies the need_unique_check
@@ -932,7 +932,7 @@ cdef class SharedEngine:
 
         return self._get_loc_duplicates(val)
 
-    cdef inline _get_loc_duplicates(self, object val):
+    cdef _get_loc_duplicates(self, object val):
         # -> Py_ssize_t | slice | ndarray[bool]
         cdef:
             Py_ssize_t diff