numpy · ngoldbaum · Sep 18, 2023 · Aug 30, 2023 · Aug 30, 2023 · Aug 30, 2023
diff --git a/doc/release/upcoming_changes/24587.python_removal.rst b/doc/release/upcoming_changes/24587.python_removal.rst
@@ -0,0 +1,9 @@
+* ``np.compare_chararrays`` has been removed from the main namespace. 
+  Use ``np.char.compare_chararrays`` instead.
+
+* The ``charrarray`` in the main namespace has been deprecated. It can be imported
+  without a deprecation warning from ``np.char.chararray`` for now,
+  but we are planning to fully deprecate and remove ``chararray`` in the future.
+
+* ``np.format_parser`` has been removed from the main namespace. 
+  Use ``np.rec.format_parser`` instead.
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst
@@ -494,14 +494,14 @@ executing them on an element-by-element basis. Perhaps the easiest
 way to create a chararray is to use :meth:`self.view(chararray)
 <ndarray.view>` where *self* is an ndarray of str or unicode
 data-type. However, a chararray can also be created using the
-:meth:`numpy.chararray` constructor, or via the
+:meth:`numpy.char.chararray` constructor, or via the
 :func:`numpy.char.array <core.defchararray.array>` function:
 
 .. autosummary::
    :toctree: generated/
 
-   chararray
-   core.defchararray.array
+   char.chararray
+   char.array
 
 Another difference with the standard ndarray of str data-type is
 that the chararray inherits the feature introduced by Numarray that

diff --git a/doc/source/reference/routines.dtype.rst b/doc/source/reference/routines.dtype.rst
@@ -20,7 +20,7 @@ Creating data types
    :toctree: generated/
 
    dtype
-   format_parser
+   rec.format_parser
 
 Data type information
 ---------------------

diff --git a/doc/source/user/basics.rec.rst b/doc/source/user/basics.rec.rst
@@ -630,8 +630,8 @@ Record Arrays
 =============
 
 As an optional convenience numpy provides an ndarray subclass,
-:class:`numpy.recarray` that allows access to fields of structured arrays by
-attribute instead of only by index.
+:class:`numpy.recarray` that allows access to fields of structured arrays
+by attribute instead of only by index.
 Record arrays use a special datatype, :class:`numpy.record`, that allows
 field access by attribute on the structured scalars obtained from the array.
 The ``numpy.rec`` module provides functions for creating recarrays from
@@ -697,7 +697,7 @@ array if the field has a structured type but as a plain ndarray otherwise. ::
  >>> type(recordarr.foo)
  <class 'numpy.ndarray'>
  >>> type(recordarr.bar)
- <class 'numpy.recarray'>
+ <class 'numpy.rec.recarray'>
 
 Note that if a field has the same name as an ndarray attribute, the ndarray
 attribute takes precedence. Such fields will be inaccessible by attribute but

diff --git a/numpy/__init__.py b/numpy/__init__.py
@@ -120,7 +120,7 @@
 
     from . import core
     from .core import (
-        _no_nep50_warning, memmap, iinfo, finfo,
+        _no_nep50_warning, memmap, iinfo, finfo, recarray,
         False_, ScalarType, True_, abs, absolute, add, all, allclose, alltrue,
         amax, amin, any, arange, arccos, arccosh, arcsin, arcsinh, arctan,
         arctan2, arctanh, argmax, argmin, argpartition, argsort, argwhere,
@@ -129,8 +129,7 @@
         atleast_1d, atleast_2d, atleast_3d, base_repr, binary_repr, 
         bitwise_and, bitwise_not, bitwise_or, bitwise_xor, block, bool_,
         broadcast, busday_count, busday_offset, busdaycalendar, byte, bytes_,
-        can_cast, cbrt, cdouble, ceil, char, character, chararray,
-        choose, clip, clongdouble, compare_chararrays,
+        can_cast, cbrt, cdouble, ceil, character, choose, clip, clongdouble,
         complexfloating, compress, concatenate, conj, conjugate, convolve,
         copysign, copyto, correlate, cos, cosh, count_nonzero, cross, csingle,
         cumprod, cumproduct, cumsum, datetime64, datetime_as_string, 
@@ -139,7 +138,7 @@
         errstate, euler_gamma, exp, exp2, expm1, fabs, 
         flatiter, flatnonzero, flexible, sctypeDict,
         float_power, floating, floor, floor_divide, fmax, fmin, fmod, 
-        format_float_positional, format_float_scientific, format_parser, 
+        format_float_positional, format_float_scientific, 
         frexp, from_dlpack, frombuffer, fromfile, fromfunction, fromiter, 
         frompyfunc, fromstring, full, full_like, gcd, generic, geomspace, 
         get_printoptions, getbufsize, geterr, geterrcall, greater, 
@@ -156,7 +155,7 @@
         negative, nested_iters, newaxis, nextafter, nonzero, not_equal,
         number, object_, ones, ones_like, outer, partition,
         pi, positive, power, printoptions, prod, product, promote_types, 
-        ptp, put, putmask, rad2deg, radians, ravel, rec, recarray, reciprocal,
+        ptp, put, putmask, rad2deg, radians, ravel, reciprocal,
         record, remainder, repeat, require, reshape, resize, result_type, 
         right_shift, rint, roll, rollaxis, round, 
         searchsorted, set_printoptions,
@@ -248,7 +247,7 @@
     __numpy_submodules__ = {
         "linalg", "fft", "dtypes", "random", "polynomial", "ma", 
         "exceptions", "lib", "ctypeslib", "testing", "typing",
-        "f2py", "test"
+        "f2py", "test", "rec", "char"
     }
 
     # We build warning messages for former attributes
@@ -358,6 +357,12 @@ def __getattr__(attr):
         elif attr == "typing":
             import numpy.typing as typing
             return typing
+        elif attr == "rec":
+            import numpy.rec as rec
+            return rec
+        elif attr == "char":
+            import numpy.char as char
+            return char
         elif attr == "array_api":
             import numpy.array_api as array_api
             return array_api
@@ -385,6 +390,14 @@ def __getattr__(attr):
                 f"{__expired_attributes__[attr]}"
             )
 
+        if attr == "chararray":
+            warnings.warn(
+                "`np.chararray` is deprecated and will be removed from "
+                "the main namespace in the future. Use an array with a string "
+                "or bytes dtype instead.", DeprecationWarning, stacklevel=2)
+            import numpy.char as char
+            return char.chararray
+
         raise AttributeError("module {!r} has no attribute "
                              "{!r}".format(__name__, attr))