Make numpy/pip_deps a test-only dependency.

Create an isolated build file for the numpy test to separate from runtime.

PiperOrigin-RevId: 524913924

python/BUILD.bazel

@@ -8,7 +8,6 @@
 
 load("@rules_pkg//:mappings.bzl", "pkg_files", "strip_prefix")
 load("@rules_python//python:defs.bzl", "py_library")
-load("@pip_deps//:requirements.bzl", "requirement")
 load("//:protobuf.bzl", "internal_py_proto_library")
 load("//build_defs:arch_tests.bzl", "aarch64_test", "x86_64_test")
 load("//build_defs:cpp_opts.bzl", "COPTS")
@@ -273,6 +272,7 @@ py_library(
         ":python_common_test_protos",
         ":python_specific_test_protos",
     ],
+    visibility = ["//python:__subpackages__"],
 )
 
 internal_py_test(
@@ -326,14 +326,6 @@ internal_py_test(
     data = ["//src/google/protobuf:testdata"],
 )
 
-internal_py_test(
-    name = "numpy_test",
-    srcs = ["google/protobuf/internal/numpy_test.py"],
-    deps = [
-        requirement("numpy"),
-    ],
-)
-
 internal_py_test(
     name = "proto_builder_test",
     srcs = ["google/protobuf/internal/proto_builder_test.py"],

python/google/protobuf/internal/numpy/BUILD.bazel

@@ -0,0 +1,13 @@
+# Protobuf python numpy Tests
+# This is removed from other tests to keep numpy (and @pip_deps) as a test-only dependency
+
+load("@pip_deps//:requirements.bzl", "requirement")
+load("//python:internal.bzl", "internal_py_test")
+
+internal_py_test(
+    name = "numpy_test",
+    srcs = ["numpy_test.py"],
+    deps = [
+        requirement("numpy"),
+    ],
+)

python/google/protobuf/internal/numpy/numpy_test.py

@@ -0,0 +1,215 @@
+# Protocol Buffers - Google's data interchange format
+# Copyright 2008 Google Inc.  All rights reserved.
+# https://developers.google.com/protocol-buffers/
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are
+# met:
+#
+#     * Redistributions of source code must retain the above copyright
+# notice, this list of conditions and the following disclaimer.
+#     * Redistributions in binary form must reproduce the above
+# copyright notice, this list of conditions and the following disclaimer
+# in the documentation and/or other materials provided with the
+# distribution.
+#     * Neither the name of Google Inc. nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
+# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
+# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
+# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
+# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+"""Test use of numpy types with repeated and non-repeated scalar fields."""
+
+import unittest
+
+import numpy as np
+
+from google.protobuf.internal import testing_refleaks
+from google.protobuf import unittest_pb2
+
+message = unittest_pb2.TestAllTypes()
+np_float_scalar = np.float64(0.0)
+np_1_float_array = np.zeros(shape=(1,), dtype=np.float64)
+np_2_float_array = np.zeros(shape=(2,), dtype=np.float64)
+np_11_float_array = np.zeros(shape=(1, 1), dtype=np.float64)
+np_22_float_array = np.zeros(shape=(2, 2), dtype=np.float64)
+
+np_int_scalar = np.int64(0)
+np_1_int_array = np.zeros(shape=(1,), dtype=np.int64)
+np_2_int_array = np.zeros(shape=(2,), dtype=np.int64)
+np_11_int_array = np.zeros(shape=(1, 1), dtype=np.int64)
+np_22_int_array = np.zeros(shape=(2, 2), dtype=np.int64)
+
+np_uint_scalar = np.uint64(0)
+np_1_uint_array = np.zeros(shape=(1,), dtype=np.uint64)
+np_2_uint_array = np.zeros(shape=(2,), dtype=np.uint64)
+np_11_uint_array = np.zeros(shape=(1, 1), dtype=np.uint64)
+np_22_uint_array = np.zeros(shape=(2, 2), dtype=np.uint64)
+
+np_bool_scalar = np.bool_(False)
+np_1_bool_array = np.zeros(shape=(1,), dtype=np.bool_)
+np_2_bool_array = np.zeros(shape=(2,), dtype=np.bool_)
+np_11_bool_array = np.zeros(shape=(1, 1), dtype=np.bool_)
+np_22_bool_array = np.zeros(shape=(2, 2), dtype=np.bool_)
+
+
+@testing_refleaks.TestCase
+class NumpyIntProtoTest(unittest.TestCase):
+
+  # Assigning dim 1 ndarray of ints to repeated field should pass
+  def testNumpyDim1IntArrayToRepeated_IsValid(self):
+    message.repeated_int64[:] = np_1_int_array
+    message.repeated_int64[:] = np_2_int_array
+
+    message.repeated_uint64[:] = np_1_uint_array
+    message.repeated_uint64[:] = np_2_uint_array
+
+  # Assigning dim 2 ndarray of ints to repeated field should fail
+  def testNumpyDim2IntArrayToRepeated_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.repeated_int64[:] = np_11_int_array
+    with self.assertRaises(TypeError):
+      message.repeated_int64[:] = np_22_int_array
+
+    with self.assertRaises(TypeError):
+      message.repeated_uint64[:] = np_11_uint_array
+    with self.assertRaises(TypeError):
+      message.repeated_uint64[:] = np_22_uint_array
+
+  # Assigning any ndarray of floats to repeated int field should fail
+  def testNumpyFloatArrayToRepeated_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.repeated_int64[:] = np_1_float_array
+    with self.assertRaises(TypeError):
+      message.repeated_int64[:] = np_11_float_array
+    with self.assertRaises(TypeError):
+      message.repeated_int64[:] = np_22_float_array
+
+  # Assigning any np int to scalar field should pass
+  def testNumpyIntScalarToScalar_IsValid(self):
+    message.optional_int64 = np_int_scalar
+    message.optional_uint64 = np_uint_scalar
+
+  # Assigning any ndarray of ints to scalar field should fail
+  def testNumpyIntArrayToScalar_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_1_int_array
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_11_int_array
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_22_int_array
+
+    with self.assertRaises(TypeError):
+      message.optional_uint64 = np_1_uint_array
+    with self.assertRaises(TypeError):
+      message.optional_uint64 = np_11_uint_array
+    with self.assertRaises(TypeError):
+      message.optional_uint64 = np_22_uint_array
+
+  # Assigning any ndarray of floats to scalar field should fail
+  def testNumpyFloatArrayToScalar_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_1_float_array
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_11_float_array
+    with self.assertRaises(TypeError):
+      message.optional_int64 = np_22_float_array
+
+
+@testing_refleaks.TestCase
+class NumpyFloatProtoTest(unittest.TestCase):
+
+  # Assigning dim 1 ndarray of floats to repeated field should pass
+  def testNumpyDim1FloatArrayToRepeated_IsValid(self):
+    message.repeated_float[:] = np_1_float_array
+    message.repeated_float[:] = np_2_float_array
+
+  # Assigning dim 2 ndarray of floats to repeated field should fail
+  def testNumpyDim2FloatArrayToRepeated_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.repeated_float[:] = np_11_float_array
+    with self.assertRaises(TypeError):
+      message.repeated_float[:] = np_22_float_array
+
+  # Assigning any np float to scalar field should pass
+  def testNumpyFloatScalarToScalar_IsValid(self):
+    message.optional_float = np_float_scalar
+
+  # Assigning any ndarray of float to scalar field should fail
+  def testNumpyFloatArrayToScalar_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.optional_float = np_1_float_array
+    with self.assertRaises(TypeError):
+      message.optional_float = np_11_float_array
+    with self.assertRaises(TypeError):
+      message.optional_float = np_22_float_array
+
+
+@testing_refleaks.TestCase
+class NumpyBoolProtoTest(unittest.TestCase):
+
+  # Assigning dim 1 ndarray of bool to repeated field should pass
+  def testNumpyDim1BoolArrayToRepeated_IsValid(self):
+    message.repeated_bool[:] = np_1_bool_array
+    message.repeated_bool[:] = np_2_bool_array
+
+  # Assigning dim 2 ndarray of bool to repeated field should fail
+  def testNumpyDim2BoolArrayToRepeated_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.repeated_bool[:] = np_11_bool_array
+    with self.assertRaises(TypeError):
+      message.repeated_bool[:] = np_22_bool_array
+
+  # Assigning any np bool to scalar field should pass
+  def testNumpyBoolScalarToScalar_IsValid(self):
+    message.optional_bool = np_bool_scalar
+
+  # Assigning any ndarray of bool to scalar field should fail
+  def testNumpyBoolArrayToScalar_RaisesTypeError(self):
+    with self.assertRaises(TypeError):
+      message.optional_bool = np_1_bool_array
+    with self.assertRaises(TypeError):
+      message.optional_bool = np_11_bool_array
+    with self.assertRaises(TypeError):
+      message.optional_bool = np_22_bool_array
+
+
+@testing_refleaks.TestCase
+class NumpyProtoIndexingTest(unittest.TestCase):
+
+  def testNumpyIntScalarIndexing_Passes(self):
+    data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2])
+    self.assertEqual(0, data.repeated_int64[np.int64(0)])
+
+  def testNumpyNegative1IntScalarIndexing_Passes(self):
+    data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2])
+    self.assertEqual(2, data.repeated_int64[np.int64(-1)])
+
+  def testNumpyFloatScalarIndexing_Fails(self):
+    data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2])
+    with self.assertRaises(TypeError):
+      _ = data.repeated_int64[np.float64(0.0)]
+
+  def testNumpyIntArrayIndexing_Fails(self):
+    data = unittest_pb2.TestAllTypes(repeated_int64=[0, 1, 2])
+    with self.assertRaises(TypeError):
+      _ = data.repeated_int64[np.array([0])]
+    with self.assertRaises(TypeError):
+      _ = data.repeated_int64[np.ndarray((1,), buffer=np.array([0]), dtype=int)]
+    with self.assertRaises(TypeError):
+      _ = data.repeated_int64[np.ndarray((1, 1),
+                                         buffer=np.array([0]),
+                                         dtype=int)]
+
+if __name__ == '__main__':
+  unittest.main()

python/google/protobuf/internal/numpy_test.py

@@ -1,3 +1,7 @@
+# This file has been replaced by google/protobuf/internal/numpy_test
+# It is just here to allow protobuf tests to pass before we commit to UPB
+# Will be deleted soon, follow along at b/278093274
+#
 # Protocol Buffers - Google's data interchange format
 # Copyright 2008 Google Inc.  All rights reserved.
 # https://developers.google.com/protocol-buffers/

python/internal.bzl

@@ -116,7 +116,7 @@ def internal_py_test(deps = [], **kwargs):
     """
     native.py_test(
         imports = ["."],
-        deps = deps + [":python_test_lib"],
+        deps = deps + ["//python:python_test_lib"],
         target_compatible_with = select({
             "@system_python//:supported": [],
             "//conditions:default": ["@platforms//:incompatible"],