Fix upstream build (#10549)

continuous_integration/scripts/install.sh

@@ -30,7 +30,8 @@ if [[ ${UPSTREAM_DEV} ]]; then
         git+https://github.com/dask/zict \
         git+https://github.com/dask/distributed \
         git+https://github.com/dask/fastparquet \
-        git+https://github.com/zarr-developers/zarr-python
+        git+https://github.com/zarr-developers/zarr-python \
+        git+https://github.com/PyTables/PyTables@ab565af10250922f2778204fd62b42ee12087d12  # numpy 2 support
 
     # FIXME https://github.com/mamba-org/mamba/issues/412
     # mamba uninstall --force ...

dask/array/core.py

@@ -731,7 +731,7 @@ def map_blocks(
     ...     loc = block_info[None]['array-location'][0]
     ...     return np.arange(loc[0], loc[1])
 
-    >>> da.map_blocks(func, chunks=((4, 4),), dtype=np.float_)
+    >>> da.map_blocks(func, chunks=((4, 4),), dtype=np.float64)
     dask.array<func, shape=(8,), dtype=float64, chunksize=(4,), chunktype=numpy.ndarray>
 
     >>> _.compute()

dask/array/creation.py

@@ -22,6 +22,7 @@
     normalize_chunks,
     stack,
 )
+from dask.array.numpy_compat import AxisError
 from dask.array.ufunc import greater_equal, rint
 from dask.array.utils import meta_from_array
 from dask.array.wrap import empty, full, ones, zeros
@@ -693,7 +694,7 @@ def _axis_fmt(axis, name, ndim):
             t = ndim + axis
             if t < 0:
                 msg = "{}: axis {} is out of bounds for array of dimension {}"
-                raise np.AxisError(msg.format(name, axis, ndim))
+                raise AxisError(msg.format(name, axis, ndim))
             axis = t
         return axis
 
@@ -813,16 +814,14 @@ def pop_axes(chunks, axis1, axis2):
 
 @derived_from(np)
 def tri(N, M=None, k=0, dtype=float, chunks="auto", *, like=None):
-    _min_int = np.lib.twodim_base._min_int
-
     if M is None:
         M = N
 
     chunks = normalize_chunks(chunks, shape=(N, M), dtype=dtype)
 
     m = greater_equal(
-        arange(N, chunks=chunks[0][0], dtype=_min_int(0, N), like=like).reshape(1, N).T,
-        arange(-k, M - k, chunks=chunks[1][0], dtype=_min_int(-k, M - k), like=like),
+        arange(N, chunks=chunks[0][0], like=like).reshape(1, N).T,
+        arange(-k, M - k, chunks=chunks[1][0], like=like),
     )
 
     # Avoid making a copy if the requested type is already bool

dask/array/numpy_compat.py

@@ -12,6 +12,14 @@
 _numpy_123 = _np_version >= parse_version("1.23.0")
 _numpy_124 = _np_version >= parse_version("1.24.0")
 _numpy_125 = _np_version.release >= (1, 25, 0)
+_numpy_200 = _np_version.release >= (2, 0, 0)
+
+
+if _numpy_200:
+    from numpy.lib.array_utils import normalize_axis_index, normalize_axis_tuple
+else:
+    from numpy.core.numeric import normalize_axis_index  # type: ignore[attr-defined]
+    from numpy.core.numeric import normalize_axis_tuple  # type: ignore[attr-defined]
 
 
 # Taken from scikit-learn:
@@ -135,10 +143,8 @@ def walk(self, x, index=()):
 # https://github.com/numpy/numpy/blob/d9b1e32cb8ef90d6b4a47853241db2a28146a57d/numpy/core/numeric.py#L1336-L1405
 @derived_from(np)
 def moveaxis(a, source, destination):
-    source = np.core.numeric.normalize_axis_tuple(source, a.ndim, "source")
-    destination = np.core.numeric.normalize_axis_tuple(
-        destination, a.ndim, "destination"
-    )
+    source = normalize_axis_tuple(source, a.ndim, "source")
+    destination = normalize_axis_tuple(destination, a.ndim, "destination")
     if len(source) != len(destination):
         raise ValueError(
             "`source` and `destination` arguments must have "
@@ -158,7 +164,7 @@ def moveaxis(a, source, destination):
 # https://github.com/numpy/numpy/blob/v1.17.0/numpy/core/numeric.py#L1107-L1204
 def rollaxis(a, axis, start=0):
     n = a.ndim
-    axis = np.core.numeric.normalize_axis_index(axis, n)
+    axis = normalize_axis_index(axis, n)
     if start < 0:
         start += n
     msg = "'%s' arg requires %d <= %s < %d, but %d was passed in"
@@ -181,3 +187,7 @@ def percentile(a, q, method="linear"):
         return np.percentile(a, q, method=method)
     else:
         return np.percentile(a, q, interpolation=method)
+
+
+ComplexWarning = np.exceptions.ComplexWarning if _numpy_200 else np.ComplexWarning
+AxisError = np.exceptions.AxisError if _numpy_200 else np.AxisError

dask/array/overlap.py

@@ -10,6 +10,7 @@
 from dask.array import chunk
 from dask.array.core import Array, concatenate, map_blocks, unify_chunks
 from dask.array.creation import empty_like, full_like
+from dask.array.numpy_compat import normalize_axis_tuple
 from dask.base import tokenize
 from dask.highlevelgraph import HighLevelGraph
 from dask.layers import ArrayOverlapLayer
@@ -782,8 +783,6 @@ def coerce_boundary(ndim, boundary):
 
 @derived_from(np.lib.stride_tricks)
 def sliding_window_view(x, window_shape, axis=None):
-    from numpy.core.numeric import normalize_axis_tuple
-
     window_shape = tuple(window_shape) if np.iterable(window_shape) else (window_shape,)
 
     window_shape_array = np.array(window_shape)

dask/array/reductions.py

@@ -27,6 +27,7 @@
 )
 from dask.array.creation import arange, diagonal
 from dask.array.dispatch import divide_lookup, nannumel_lookup, numel_lookup
+from dask.array.numpy_compat import ComplexWarning
 from dask.array.utils import (
     array_safe,
     asarray_safe,
@@ -387,7 +388,7 @@ def partial_reduce(
     else:
         with contextlib.suppress(AttributeError), warnings.catch_warnings():
             if name.startswith("var") or name.startswith("moment"):
-                warnings.simplefilter("ignore", np.ComplexWarning)
+                warnings.simplefilter("ignore", ComplexWarning)
             meta = meta.astype(dtype)
         return Array(graph, name, out_chunks, meta=meta)
 

dask/array/routines.py

@@ -1811,7 +1811,7 @@ def unique(ar, return_index=False, return_inverse=False, return_counts=False):
 
 
 def _isin_kernel(element, test_elements, assume_unique=False):
-    values = np.in1d(element.ravel(), test_elements, assume_unique=assume_unique)
+    values = np.isin(element.ravel(), test_elements, assume_unique=assume_unique)
     return values.reshape(element.shape + (1,) * test_elements.ndim)
 
 

dask/array/tests/test_array_core.py

@@ -1485,7 +1485,7 @@ def test_map_blocks_block_info_with_broadcast():
             None: {
                 "shape": (6, 4),
                 "num-chunks": (2, 2),
-                "dtype": np.float_,
+                "dtype": np.float64,
                 "chunk-shape": (3, 2),
                 "array-location": [(0, 3), (0, 2)],
                 "chunk-location": (0, 0),
@@ -1498,7 +1498,7 @@ def test_map_blocks_block_info_with_broadcast():
             None: {
                 "shape": (6, 4),
                 "num-chunks": (2, 2),
-                "dtype": np.float_,
+                "dtype": np.float64,
                 "chunk-shape": (3, 2),
                 "array-location": [(0, 3), (2, 4)],
                 "chunk-location": (0, 1),
@@ -1511,7 +1511,7 @@ def test_map_blocks_block_info_with_broadcast():
             None: {
                 "shape": (6, 4),
                 "num-chunks": (2, 2),
-                "dtype": np.float_,
+                "dtype": np.float64,
                 "chunk-shape": (3, 2),
                 "array-location": [(3, 6), (0, 2)],
                 "chunk-location": (1, 0),
@@ -1524,7 +1524,7 @@ def test_map_blocks_block_info_with_broadcast():
             None: {
                 "shape": (6, 4),
                 "num-chunks": (2, 2),
-                "dtype": np.float_,
+                "dtype": np.float64,
                 "chunk-shape": (3, 2),
                 "array-location": [(3, 6), (2, 4)],
                 "chunk-location": (1, 1),

dask/array/tests/test_creation.py

@@ -11,6 +11,7 @@
 import dask
 import dask.array as da
 from dask.array.core import normalize_chunks
+from dask.array.numpy_compat import AxisError
 from dask.array.utils import assert_eq, same_keys
 
 
@@ -521,10 +522,10 @@ def test_diagonal():
     with pytest.raises(ValueError):
         da.diagonal(v, axis1=0, axis2=0)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.diagonal(v, axis1=-4)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.diagonal(v, axis2=-4)
 
     v = np.arange(4 * 5 * 6).reshape((4, 5, 6))

dask/array/tests/test_cupy_creation.py

@@ -7,6 +7,7 @@
 
 import dask.array as da
 from dask import config
+from dask.array.numpy_compat import AxisError
 from dask.array.utils import assert_eq
 
 cupy = pytest.importorskip("cupy")
@@ -43,10 +44,10 @@ def test_diagonal():
     with pytest.raises(ValueError):
         da.diagonal(v, axis1=0, axis2=0)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.diagonal(v, axis1=-4)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.diagonal(v, axis2=-4)
 
     v = cupy.arange(4 * 5 * 6).reshape((4, 5, 6))

dask/array/tests/test_image.py

@@ -5,6 +5,13 @@
 
 import pytest
 
+from dask.array.numpy_compat import _numpy_200
+
+if _numpy_200:
+    # `import skimage` fails with `numpy=2`
+    # xref https://github.com/scikit-image/scikit-image/pull/7118
+    pytest.skip("skimage doesn't yet support numpy=2", allow_module_level=True)
+
 pytest.importorskip("skimage")
 import numpy as np
 from skimage.io import imsave

dask/array/tests/test_linalg.py

@@ -4,6 +4,11 @@
 
 import pytest
 
+from dask.array.numpy_compat import _numpy_200
+
+if _numpy_200:
+    pytest.skip("scipy doesn't yet support numpy=2", allow_module_level=True)
+
 pytest.importorskip("numpy")
 pytest.importorskip("scipy")
 

dask/array/tests/test_masked.py

@@ -9,9 +9,10 @@
 import pytest
 
 import dask.array as da
-from dask.array.numpy_compat import _numpy_123
+from dask.array.numpy_compat import ComplexWarning, _numpy_123
 from dask.array.utils import assert_eq
 from dask.base import tokenize
+from dask.utils import typename
 
 pytest.importorskip("dask.array.ma")
 
@@ -123,7 +124,7 @@ def test_tensordot():
 
 
 @pytest.mark.parametrize("func", functions)
-@pytest.mark.filterwarnings("ignore::numpy.ComplexWarning")  # abs() in assert_eq
+@pytest.mark.filterwarnings(f"ignore::{typename(ComplexWarning)}")  # abs() in assert_eq
 def test_mixed_concatenate(func):
     rng = da.random.default_rng()
     x = rng.random((2, 3, 4), chunks=(1, 2, 2))
@@ -141,7 +142,7 @@ def test_mixed_concatenate(func):
 
 
 @pytest.mark.parametrize("func", functions)
-@pytest.mark.filterwarnings("ignore::numpy.ComplexWarning")  # abs() in assert_eq
+@pytest.mark.filterwarnings(f"ignore::{typename(ComplexWarning)}")  # abs() in assert_eq
 def test_mixed_random(func):
     d = da.random.default_rng().random((4, 3, 4), chunks=(1, 2, 2))
     d[d < 0.4] = 0

dask/array/tests/test_reductions.py

@@ -13,7 +13,7 @@
 
 import dask.array as da
 import dask.config as config
-from dask.array.numpy_compat import _numpy_122
+from dask.array.numpy_compat import ComplexWarning, _numpy_122
 from dask.array.utils import assert_eq, same_keys
 from dask.core import get_deps
 
@@ -103,9 +103,7 @@ def reduction_1d_test(da_func, darr, np_func, narr, use_dtype=True, split_every=
     assert same_keys(da_func(darr), da_func(darr))
     assert same_keys(da_func(darr, keepdims=True), da_func(darr, keepdims=True))
     if use_dtype:
-        with pytest.warns(np.ComplexWarning) if np.iscomplexobj(
-            narr
-        ) else does_not_warn():
+        with pytest.warns(ComplexWarning) if np.iscomplexobj(narr) else does_not_warn():
             assert_eq(da_func(darr, dtype="f8"), np_func(narr, dtype="f8"))
             assert_eq(da_func(darr, dtype="i8"), np_func(narr, dtype="i8"))
             assert same_keys(da_func(darr, dtype="i8"), da_func(darr, dtype="i8"))
@@ -123,7 +121,7 @@ def reduction_1d_test(da_func, darr, np_func, narr, use_dtype=True, split_every=
 @pytest.mark.parametrize("dtype", ["f4", "i4", "c8"])
 def test_reductions_1D(dtype):
     with warnings.catch_warnings():
-        warnings.simplefilter("ignore", np.ComplexWarning)
+        warnings.simplefilter("ignore", ComplexWarning)
         x = (np.arange(5) + 1j * np.arange(5)).astype(dtype)
         a = da.from_array(x, chunks=(2,))
 
@@ -167,9 +165,7 @@ def reduction_2d_test(da_func, darr, np_func, narr, use_dtype=True, split_every=
     assert same_keys(da_func(darr, axis=(1, 0)), da_func(darr, axis=(1, 0)))
 
     if use_dtype:
-        with pytest.warns(np.ComplexWarning) if np.iscomplexobj(
-            narr
-        ) else does_not_warn():
+        with pytest.warns(ComplexWarning) if np.iscomplexobj(narr) else does_not_warn():
             assert_eq(da_func(darr, dtype="f8"), np_func(narr, dtype="f8"))
             assert_eq(da_func(darr, dtype="i8"), np_func(narr, dtype="i8"))
 
@@ -212,7 +208,7 @@ def test_reduction_errors():
 @pytest.mark.parametrize("dtype", ["f4", "i4", "c8"])
 def test_reductions_2D(dtype):
     with warnings.catch_warnings():
-        warnings.simplefilter("ignore", np.ComplexWarning)
+        warnings.simplefilter("ignore", ComplexWarning)
         x = (np.arange(1, 122) + 1j * np.arange(1, 122)).reshape((11, 11)).astype(dtype)
     a = da.from_array(x, chunks=(4, 4))
 

dask/array/tests/test_routines.py

@@ -7,15 +7,14 @@
 from numbers import Number
 
 import pytest
-from numpy import AxisError
 
 import dask
 from dask.delayed import delayed
 
 np = pytest.importorskip("numpy")
 
 import dask.array as da
-from dask.array.numpy_compat import _numpy_123
+from dask.array.numpy_compat import AxisError, _numpy_123
 from dask.array.utils import assert_eq, same_keys
 
 
@@ -2252,10 +2251,10 @@ def test_insert():
     with pytest.raises(NotImplementedError):
         da.insert(a, [4, 2], -1, axis=0)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.insert(a, [3], -1, axis=2)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.insert(a, [3], -1, axis=-3)
 
 
@@ -2298,9 +2297,9 @@ def test_append():
     )
 
     # check AxisError
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.append(a, ((0,) * 10,) * 10, axis=2)
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.append(a, ((0,) * 10,) * 10, axis=-3)
 
     # check ValueError if dimensions don't align
@@ -2337,10 +2336,10 @@ def test_delete():
 
     assert_eq(np.delete(a, [4, 2], axis=0), da.delete(a, [4, 2], axis=0))
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.delete(a, [3], axis=2)
 
-    with pytest.raises(np.AxisError):
+    with pytest.raises(AxisError):
         da.delete(a, [3], axis=-3)
 
 

dask/array/tests/test_stats.py

@@ -5,6 +5,11 @@
 import pytest
 from packaging.version import parse as parse_version
 
+from dask.array.numpy_compat import _numpy_200
+
+if _numpy_200:
+    pytest.skip("scipy doesn't yet support numpy=2", allow_module_level=True)
+
 scipy = pytest.importorskip("scipy")
 import numpy as np