ENH: add type stubs from numpy-stubs

Add the type stubs and tests from numpy-stubs. Things this entails:

- Copy over the stubs (numpy/__init__.pyi and
  numpy/core/_internal.pyi)
  - The only modification made was removing `ndarray.tostring` since
    it is deprecated
- Update some setup.py files to include pyi files
- Move the tests from numpy-stubs/tests into numpy/tests
  - Skip them if mypy is not installed (planning on setting up CI in a
    future PR)
  - Add a mypy.ini; use it to configure mypy in the tests
    - It tells mypy where to find NumPy in the test env
    - It ignores internal NumPy type errors (since we only want to
      consider errors from the tests cases)
  - Some small edits were made to fix test cases that were emitting
    deprecation warnings
 - Add numpy/py.typed so that the types are picked up in an
   installed version of NumPy

1 files changed, 175 insertions, 0 deletions

diff --git a/numpy/tests/pass/simple.py b/numpy/tests/pass/simple.py
new file mode 100644
index 000000000..b9715da5d
--- /dev/null
+++ b/numpy/tests/pass/simple.py
@@ -0,0 +1,175 @@
+"""Simple expression that should pass with mypy."""
+import operator
+
+import numpy as np
+from typing import Iterable  # noqa: F401
+
+# Basic checks
+array = np.array([1, 2])
+
+
+def ndarray_func(x):
+    # type: (np.ndarray) -> np.ndarray
+    return x
+
+
+ndarray_func(np.array([1, 2]))
+array == 1
+array.dtype == float
+
+# Array creation routines checks
+ndarray_func(np.zeros([1, 2]))
+ndarray_func(np.ones([1, 2]))
+ndarray_func(np.empty([1, 2]))
+
+ndarray_func(np.zeros_like(array))
+ndarray_func(np.ones_like(array))
+ndarray_func(np.empty_like(array))
+
+# Dtype construction
+np.dtype(float)
+np.dtype(np.float64)
+np.dtype(None)
+np.dtype("float64")
+np.dtype(np.dtype(float))
+np.dtype(("U", 10))
+np.dtype((np.int32, (2, 2)))
+# Define the arguments on the previous line to prevent bidirectional
+# type inference in mypy from broadening the types.
+two_tuples_dtype = [("R", "u1"), ("G", "u1"), ("B", "u1")]
+np.dtype(two_tuples_dtype)
+
+three_tuples_dtype = [("R", "u1", 2)]
+np.dtype(three_tuples_dtype)
+
+mixed_tuples_dtype = [("R", "u1"), ("G", np.unicode_, 1)]
+np.dtype(mixed_tuples_dtype)
+
+shape_tuple_dtype = [("R", "u1", (2, 2))]
+np.dtype(shape_tuple_dtype)
+
+shape_like_dtype = [("R", "u1", (2, 2)), ("G", np.unicode_, 1)]
+np.dtype(shape_like_dtype)
+
+object_dtype = [("field1", object)]
+np.dtype(object_dtype)
+
+np.dtype({"col1": ("U10", 0), "col2": ("float32", 10)})
+np.dtype((np.int32, {"real": (np.int16, 0), "imag": (np.int16, 2)}))
+np.dtype((np.int32, (np.int8, 4)))
+
+# Dtype comparision
+np.dtype(float) == float
+np.dtype(float) != np.float64
+np.dtype(float) < None
+np.dtype(float) <= "float64"
+np.dtype(float) > np.dtype(float)
+np.dtype(float) >= np.dtype(("U", 10))
+
+# Iteration and indexing
+def iterable_func(x):
+    # type: (Iterable) -> Iterable
+    return x
+
+
+iterable_func(array)
+[element for element in array]
+iter(array)
+zip(array, array)
+array[1]
+array[:]
+array[...]
+array[:] = 0
+
+array_2d = np.ones((3, 3))
+array_2d[:2, :2]
+array_2d[..., 0]
+array_2d[:2, :2] = 0
+
+# Other special methods
+len(array)
+str(array)
+array_scalar = np.array(1)
+int(array_scalar)
+float(array_scalar)
+# currently does not work due to https://github.com/python/typeshed/issues/1904
+# complex(array_scalar)
+bytes(array_scalar)
+operator.index(array_scalar)
+bool(array_scalar)
+
+# comparisons
+array < 1
+array <= 1
+array == 1
+array != 1
+array > 1
+array >= 1
+1 < array
+1 <= array
+1 == array
+1 != array
+1 > array
+1 >= array
+
+# binary arithmetic
+array + 1
+1 + array
+array += 1
+
+array - 1
+1 - array
+array -= 1
+
+array * 1
+1 * array
+array *= 1
+
+array / 1
+1 / array
+float_array = np.array([1.0, 2.0])
+float_array /= 1
+
+array // 1
+1 // array
+array //= 1
+
+array % 1
+1 % array
+array %= 1
+
+divmod(array, 1)
+divmod(1, array)
+
+array ** 1
+1 ** array
+array **= 1
+
+array << 1
+1 << array
+array <<= 1
+
+array >> 1
+1 >> array
+array >>= 1
+
+array & 1
+1 & array
+array &= 1
+
+array ^ 1
+1 ^ array
+array ^= 1
+
+array | 1
+1 | array
+array |= 1
+
+# unary arithmetic
+-array
++array
+abs(array)
+~array
+
+# Other methods
+np.array([1, 2]).transpose()