COMPAT/PERF move uniques to method scope

Author: mattip

pandas/_libs/hashtable.pyx

@@ -46,12 +46,10 @@ include "hashtable_func_helper.pxi"
 
 cdef class Factorizer:
  cdef public PyObjectHashTable table
- cdef public ObjectVector uniques
  cdef public Py_ssize_t count
 
  def __init__(self, size_hint):
  self.table = PyObjectHashTable(size_hint)
- self.uniques = ObjectVector()
  self.count = 0
 
  def get_count(self):
@@ -64,19 +62,22 @@ cdef class Factorizer:
  >>> factorize(np.array([1,2,np.nan], dtype='O'), na_sentinel=20)
  array([ 0, 1, 20])
  """
- labels = self.table.get_labels(values, self.uniques,
+ uniques = ObjectVector()
+ labels = self.table.get_labels(values, uniques,
  self.count, na_sentinel, check_null)
  mask = (labels == na_sentinel)
+ if len(labels) == 0:
+ return labels
  # sort on
  if sort:
  if labels.dtype != np.intp:
  labels = labels.astype(np.intp)
- sorter = self.uniques.to_array().argsort()
+ sorter = uniques.to_array().argsort()
  reverse_indexer = np.empty(len(sorter), dtype=np.intp)
  reverse_indexer.put(sorter, np.arange(len(sorter)))
  labels = reverse_indexer.take(labels, mode='clip')
  labels[mask] = na_sentinel
- self.count = len(self.uniques)
+ self.count = len(uniques)
  return labels
 
  def unique(self, ndarray[object] values):
@@ -86,35 +87,36 @@ cdef class Factorizer:
 
 cdef class Int64Factorizer:
  cdef public Int64HashTable table
- cdef public Int64Vector uniques
  cdef public Py_ssize_t count
 
  def __init__(self, size_hint):
  self.table = Int64HashTable(size_hint)
- self.uniques = Int64Vector()
  self.count = 0
 
  def get_count(self):
  return self.count
 
  def factorize(self, int64_t[:] values, sort=False,
  na_sentinel=-1, check_null=True):
+ uniques = Int64Vector()
  labels = self.table.get_labels(values, self.uniques,
  self.count, na_sentinel,
  check_null)
 
  # sort on
+ if len(labels) == 0:
+ return labels
  if sort:
  if labels.dtype != np.intp:
  labels = labels.astype(np.intp)
 
- sorter = self.uniques.to_array().argsort()
+ sorter = uniques.to_array().argsort()
  reverse_indexer = np.empty(len(sorter), dtype=np.intp)
  reverse_indexer.put(sorter, np.arange(len(sorter)))
 
  labels = reverse_indexer.take(labels)
 
- self.count = len(self.uniques)
+ self.count = len(uniques)
  return labels