diff --git a/pandas/_libs/hashtable.pxd b/pandas/_libs/hashtable.pxd index eaec9e8462450..22b923580c491 100644 --- a/pandas/_libs/hashtable.pxd +++ b/pandas/_libs/hashtable.pxd @@ -180,7 +180,7 @@ cdef class Vector: cdef bint external_view_exists cdef class Int64Vector(Vector): - cdef Int64VectorData *data + cdef Int64VectorData data cdef ndarray ao cdef resize(self) diff --git a/pandas/_libs/hashtable.pyx b/pandas/_libs/hashtable.pyx index ccac3d0b50d45..8250d0242c31f 100644 --- a/pandas/_libs/hashtable.pyx +++ b/pandas/_libs/hashtable.pyx @@ -1,8 +1,4 @@ cimport cython -from cpython.mem cimport ( - PyMem_Free, - PyMem_Malloc, -) from cpython.ref cimport ( Py_INCREF, PyObject, diff --git a/pandas/_libs/hashtable_class_helper.pxi.in b/pandas/_libs/hashtable_class_helper.pxi.in index 26dcf0b6c4ce3..629b6b42db852 100644 --- a/pandas/_libs/hashtable_class_helper.pxi.in +++ b/pandas/_libs/hashtable_class_helper.pxi.in @@ -204,15 +204,11 @@ cdef class {{name}}Vector(Vector): # Int64Vector is the only one we need exposed for other cython files. {{if dtype != 'int64'}} cdef: - {{name}}VectorData *data + {{name}}VectorData data ndarray ao {{endif}} def __cinit__(self): - self.data = <{{name}}VectorData *>PyMem_Malloc( - sizeof({{name}}VectorData)) - if not self.data: - raise MemoryError() self.data.n = 0 self.data.m = _INIT_VEC_CAP self.ao = np.empty(self.data.m, dtype=np.{{dtype}}) @@ -223,11 +219,6 @@ cdef class {{name}}Vector(Vector): self.ao.resize(self.data.m, refcheck=False) self.data.data = <{{c_type}}*>self.ao.data - def __dealloc__(self): - if self.data is not NULL: - PyMem_Free(self.data) - self.data = NULL - def __len__(self) -> int: return self.data.n @@ -243,13 +234,13 @@ cdef class {{name}}Vector(Vector): cdef void append(self, {{c_type}} x) noexcept: - if needs_resize(self.data): + if needs_resize(&self.data): if self.external_view_exists: raise ValueError("external reference but " "Vector.resize() needed") self.resize() - append_data_{{dtype}}(self.data, x) + append_data_{{dtype}}(&self.data, x) cdef extend(self, const {{c_type}}[:] x): for i in range(len(x)): @@ -260,12 +251,9 @@ cdef class {{name}}Vector(Vector): cdef class StringVector(Vector): cdef: - StringVectorData *data + StringVectorData data def __cinit__(self): - self.data = PyMem_Malloc(sizeof(StringVectorData)) - if not self.data: - raise MemoryError() self.data.n = 0 self.data.m = _INIT_VEC_CAP self.data.data = malloc(self.data.m * sizeof(char *)) @@ -288,11 +276,7 @@ cdef class StringVector(Vector): self.data.data[i] = orig_data[i] def __dealloc__(self): - if self.data is not NULL: - if self.data.data is not NULL: - free(self.data.data) - PyMem_Free(self.data) - self.data = NULL + free(self.data.data) def __len__(self) -> int: return self.data.n @@ -313,10 +297,10 @@ cdef class StringVector(Vector): cdef void append(self, char *x) noexcept: - if needs_resize(self.data): + if needs_resize(&self.data): self.resize() - append_data_string(self.data, x) + append_data_string(&self.data, x) cdef extend(self, ndarray[object] x): for i in range(len(x)): @@ -652,7 +636,7 @@ cdef class {{name}}HashTable(HashTable): if return_inverse: labels = np.empty(n, dtype=np.intp) - ud = uniques.data + ud = &uniques.data use_na_value = na_value is not None use_mask = mask is not None if not use_mask and use_result_mask: @@ -662,7 +646,7 @@ cdef class {{name}}HashTable(HashTable): raise NotImplementedError # pragma: no cover result_mask = UInt8Vector() - rmd = result_mask.data + rmd = &result_mask.data if use_mask: mask_values = mask.view("uint8") @@ -846,7 +830,7 @@ cdef class {{name}}HashTable(HashTable): {{name}}VectorData *ud labels = np.empty(n, dtype=np.intp) - ud = uniques.data + ud = &uniques.data with nogil: for i in range(n): diff --git a/pandas/_libs/hashtable_func_helper.pxi.in b/pandas/_libs/hashtable_func_helper.pxi.in index 336af306d410f..ca1b28b9442ca 100644 --- a/pandas/_libs/hashtable_func_helper.pxi.in +++ b/pandas/_libs/hashtable_func_helper.pxi.in @@ -472,7 +472,7 @@ def _unique_label_indices_{{dtype}}(const {{c_type}}[:] labels) -> ndarray: kh_{{ttype}}_t *table = kh_init_{{ttype}}() {{name}}Vector idx = {{name}}Vector() ndarray[{{c_type}}, ndim=1] arr - {{name}}VectorData *ud = idx.data + {{name}}VectorData *ud = &idx.data kh_resize_{{ttype}}(table, min(kh_needed_n_buckets(n), SIZE_HINT_LIMIT))