Closes Bears-R-Us#3746 remove ForwardRef (Bears-R-Us#3747)

Co-authored-by: Amanda Potts <ajpotts@users.noreply.github.com>

arkouda/categorical.py

@@ -20,15 +20,15 @@
 from typeguard import typechecked
 
 from arkouda.client import generic_msg
-from arkouda.numpy.dtypes import bool_ as akbool
-from arkouda.numpy.dtypes import dtype as akdtype
-from arkouda.numpy.dtypes import int64 as akint64
-from arkouda.numpy.dtypes import int_scalars, resolve_scalar_dtype, str_, str_scalars
 from arkouda.groupbyclass import GroupBy, unique
 from arkouda.infoclass import information
 from arkouda.logger import getArkoudaLogger
 from arkouda.numeric import cast as akcast
 from arkouda.numeric import where
+from arkouda.numpy.dtypes import bool_ as akbool
+from arkouda.numpy.dtypes import dtype as akdtype
+from arkouda.numpy.dtypes import int64 as akint64
+from arkouda.numpy.dtypes import int_scalars, resolve_scalar_dtype, str_, str_scalars
 from arkouda.pdarrayclass import RegistrationError
 from arkouda.pdarrayclass import all as akall
 from arkouda.pdarrayclass import create_pdarray, pdarray

arkouda/numeric.py

@@ -1,6 +1,6 @@
 import json
 from enum import Enum
-from typing import ForwardRef, List, Optional, Sequence, Tuple, Union
+from typing import TYPE_CHECKING, List, Sequence, Tuple, TypeVar, Union
 from typing import cast as type_cast
 from typing import no_type_check
 
@@ -27,8 +27,12 @@
 from arkouda.sorting import sort
 from arkouda.strings import Strings
 
-Categorical = ForwardRef("Categorical")
-SegArray = ForwardRef("SegArray")
+if TYPE_CHECKING:
+ from arkouda.categorical import Categorical
+ from arkouda.segarray import SegArray
+else:
+ Categorical = TypeVar("Categorical")
+ SegArray = TypeVar("SegArray")
 
 __all__ = [
  "cast",
@@ -1981,7 +1985,9 @@ def histogramdd(
 @typechecked
 def value_counts(
  pda: pdarray,
-) -> Union[Categorical, Tuple[Union[pdarray, Strings], Optional[pdarray]]]: # type: ignore
+) -> Tuple[
+ Union[Union[pdarray, Strings, Categorical], Sequence[Union[pdarray, Strings, Categorical]]], pdarray
+]:
  """
  Count the occurrences of the unique values of an array.
 

arkouda/pdarraysetops.py

@@ -1,33 +1,38 @@
 from __future__ import annotations
 
-from typing import ForwardRef, Sequence, Union, cast
+from typing import Sequence, TypeVar, Union, cast
 
 import numpy as np
 from typeguard import typechecked
 
+
 from arkouda.client import generic_msg
 from arkouda.client_dtypes import BitVector
+from arkouda.groupbyclass import GroupBy, groupable, groupable_element_type, unique
+from arkouda.logger import getArkoudaLogger
 from arkouda.numpy.dtypes import bigint
 from arkouda.numpy.dtypes import bool_ as akbool
 from arkouda.numpy.dtypes import int64 as akint64
 from arkouda.numpy.dtypes import uint64 as akuint64
-from arkouda.groupbyclass import GroupBy, groupable, groupable_element_type, unique
-from arkouda.logger import getArkoudaLogger
 from arkouda.pdarrayclass import create_pdarray, pdarray
 from arkouda.pdarraycreation import array, ones, zeros, zeros_like
 from arkouda.sorting import argsort
 from arkouda.strings import Strings
+from typing import TYPE_CHECKING
 
-Categorical = ForwardRef("Categorical")
+if TYPE_CHECKING:
+ from arkouda.categorical import Categorical
+else:
+ Categorical = TypeVar("Categorical")
 
 __all__ = ["in1d", "concatenate", "union1d", "intersect1d", "setdiff1d", "setxor1d", "indexof1d"]
 
 logger = getArkoudaLogger(name="pdarraysetops")
 
 
 def _in1d_single(
- pda1: Union[pdarray, Strings, "Categorical"], # type: ignore
- pda2: Union[pdarray, Strings, "Categorical"], # type: ignore
+ pda1: Union[pdarray, Strings, "Categorical"],
+ pda2: Union[pdarray, Strings, "Categorical"],
  invert: bool = False,
 ) -> pdarray:
  """
@@ -131,7 +136,7 @@ def in1d(
  assume_unique: bool = False,
  symmetric: bool = False,
  invert: bool = False,
-) -> Union[pdarray, groupable]:
+) -> groupable:
  """
  Test whether each element of a 1-D array is also present in a second array.
 
@@ -176,10 +181,16 @@ def in1d(
  raise TypeError("Arguments must have compatible types, Strings/Categorical")
  elif isinstance(pda1, pdarray) and not isinstance(pda2, pdarray):
  raise TypeError("If pda1 is pdarray, pda2 must also be pda2")
- if symmetric:
- return _in1d_single(pda1, pda2), _in1d_single(pda2, pda1, invert)
- else:
+ elif isinstance(pda2, (pdarray, Strings, Categorical_)):
+ if symmetric:
+  return _in1d_single(pda1, pda2), _in1d_single(pda2, pda1, invert)
  return _in1d_single(pda1, pda2, invert)
+ else:
+ raise TypeError(
+ "Inputs should both be Union[pdarray, Strings, Categorical] or both be "
+ "Sequence[pdarray, Strings, Categorical]."
+ " (Do not mix and match.)"
+ )
  atypes = np.array([ai.dtype for ai in pda1])
  btypes = np.array([bi.dtype for bi in pda2])
  if not (atypes == btypes).all():
@@ -291,9 +302,9 @@ def indexof1d(query: groupable, space: groupable) -> pdarray:
 # fmt: off
 @typechecked
 def concatenate(
- arrays: Sequence[Union[pdarray, Strings, "Categorical", ]], # type: ignore
+ arrays: Sequence[Union[pdarray, Strings, "Categorical", ]],
  ordered: bool = True,
-) -> Union[pdarray, Strings, "Categorical"]: # type: ignore
+) -> Union[pdarray, Strings, Categorical, Sequence[Categorical]]:
  """
  Concatenate a list or tuple of ``pdarray`` or ``Strings`` objects into
  one ``pdarray`` or ``Strings`` object, respectively.