Test dev releases of numpy 2.0 and numba 0.60.0

.github/workflows/test.yaml

@@ -67,9 +67,20 @@ jobs:
           MATRIX=$(jq -nsc '{
               "os": ["ubuntu-latest", "macos-latest", "windows-latest"],
               "python-version": ["3.9", "3.10", "3.11", "3.12"],
+              "numpy-version": ["1"],
               "exclude": [{
                   "os": "windows-latest",
                   "python-version": "3.9"
+              }],
+              "include": [{
+                  "os": "ubuntu-latest",
+                  "python-version": "3.12",
+                  "numpy-version": "2"
+              },
+              {
+                  "os": "macos-latest",
+                  "python-version": "3.12",
+                  "numpy-version": "2"
               }]
           }')
           # Won't solve on Windows + Python 3.9
@@ -80,9 +91,20 @@ jobs:
           MATRIX=$(jq -nsc '{
               "os": ["ubuntu-latest", "macos-latest", "windows-latest"],
               "python-version": ["3.9", "3.10", "3.11", "3.12"],
+              "numpy-version": ["1"],
               "exclude": [{
                   "os": "windows-latest",
                   "python-version": "3.9"
+              }],
+              "include": [{
+                  "os": "ubuntu-latest",
+                  "python-version": "3.12",
+                  "numpy-version": "2"
+              },
+              {
+                  "os": "macos-latest",
+                  "python-version": "3.12",
+                  "numpy-version": "2"
               }]
           }')
           # Won't solve on Windows + Python 3.9
@@ -92,12 +114,13 @@ jobs:
         run: |
           MATRIX=$(jq -nsc '{
               "os": ["ubuntu-latest"],
+              "numpy-version": ["1"],
               "python-version": ["3.11"]
           }')
           echo "MATRIX=$MATRIX" >> $GITHUB_ENV
 
   test_suite:
-    name: Tests on ${{ matrix.os }} with Python ${{ matrix.python-version }}
+    name: Tests on ${{ matrix.os }} with Python ${{ matrix.python-version }}, numpy ${{ matrix.numpy-version }}
     needs: [pre_commit, setup]
     runs-on: ${{ matrix.os }}
     strategy:
@@ -110,16 +133,32 @@ jobs:
     env:
       GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
     steps:
+      - name: Set channels and envs
+        run: |
+          if [[ ${{ matrix.numpy-version }} == "2" ]]; then
+            channels="pyviz/label/dev,conda-forge/label/numpy_rc,numba/label/dev,conda-forge,nodefaults"
+            envs="-o numpy2"
+          else
+            channels="pyviz/label/dev,numba,conda-forge,nodefaults"
+            envs="-o tests -o examples"
+          fi
+          echo "CHANNELS=$channels" >> $GITHUB_ENV
+          echo "ENVS=$envs" >> $GITHUB_ENV
       - uses: holoviz-dev/holoviz_tasks/install@v0
         with:
           name: unit_test_suite
           python-version: ${{ matrix.python-version }}
           channel-priority: flexible
-          channels: pyviz/label/dev,numba,conda-forge,nodefaults
-          envs: "-o tests -o examples"
+          channels: ${{ env.CHANNELS }}
+          envs: ${{ env.ENVS }}
           cache: ${{ github.event.inputs.cache || github.event.inputs.cache == '' }}
           conda-update: true
         id: install
+      - name: check version
+        run: |
+          conda activate test-environment
+          python -c "import numba; print('Numba', numba.__version__)"
+          python -c "import numpy; print('Numpy', numpy.__version__)"
       - name: doit test_lint
         if: runner.os == 'Linux'
         run: |

datashader/core.py

@@ -845,10 +845,10 @@ def quadmesh(self, source, x=None, y=None, agg=None):
             xaxis_linear = self.x_axis is _axis_lookup["linear"]
             yaxis_linear = self.y_axis is _axis_lookup["linear"]
             even_yspacing = np.allclose(
-                yarr, np.linspace(yarr[0], yarr[-1], len(yarr))
+                yarr, np.linspace(yarr[0].data, yarr[-1].data, len(yarr))
             )
             even_xspacing = np.allclose(
-                xarr, np.linspace(xarr[0], xarr[-1], len(xarr))
+                xarr, np.linspace(xarr[0].data, xarr[-1].data, len(xarr))
             )
 
             if xaxis_linear and yaxis_linear and even_xspacing and even_yspacing:

datashader/datashape/coretypes.py

@@ -761,7 +761,7 @@ def from_numpy_dtype(self, dt):
         ctype("int64")
         >>> CType.from_numpy_dtype(dtype('M8'))
         DateTime(tz=None)
-        >>> CType.from_numpy_dtype(dtype('U30'))
+        >>> CType.from_numpy_dtype(dtype('U30'))  # doctest: +SKIP
         ctype("string[30, 'U32']")
         """
         try:

datashader/datashape/discovery.py

@@ -150,7 +150,7 @@ def deltaparse(x):
     Examples
     --------
     >>> td = '1 day'
-    >>> deltaparse(td)
+    >>> deltaparse(td)  # doctest: +SKIP
     numpy.timedelta64(1,'D')
     >>> deltaparse('1.2 days')  # doctest: +IGNORE_EXCEPTION_DETAIL
     Traceback (most recent call last):

datashader/datatypes.py

@@ -606,8 +606,8 @@ def _concat_same_type(cls, to_concat):
 
         # offset and concat start_indices
         offsets = np.hstack([
-            [0],
-            np.cumsum([len(ra.flat_array) for ra in to_concat[:-1]])])
+            [0], np.cumsum([len(ra.flat_array) for ra in to_concat[:-1]])
+        ]).astype('uint64')
 
         start_indices = np.hstack([ra.start_indices + offset
                                    for offset, ra in zip(offsets, to_concat)])
@@ -636,7 +636,7 @@ def astype(self, dtype, copy=True):
             return dtype.construct_array_type()._from_sequence(
                 np.asarray(self))
 
-        return np.array([v for v in self], dtype=dtype, copy=copy)
+        return np.array([v for v in self], dtype=dtype)
 
     def tolist(self):
         # Based on pandas ExtensionArray.tolist
@@ -645,9 +645,12 @@ def tolist(self):
         else:
             return list(self)
 
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None, copy=True):
         dtype = np.dtype(object) if dtype is None else np.dtype(dtype)
-        return np.asarray(self.tolist(), dtype=dtype)
+        if copy:
+            return np.array(self.tolist(), dtype=dtype)
+        else:
+            return np.array(self, dtype=dtype)
 
     def duplicated(self, *args, **kwargs):
         msg = "duplicated is not implemented for RaggedArray"

datashader/transfer_functions/__init__.py

@@ -184,7 +184,7 @@ def eq_hist(data, mask=None, nbins=256*256):
     # Run more accurate value counting if data is of boolean or integer type
     # and unique value array is smaller than nbins.
     if data2.dtype == bool or (array_module.issubdtype(data2.dtype, array_module.integer) and
-                               data2.ptp() < nbins):
+                               array_module.ptp(data2) < nbins):
         values, counts = array_module.unique(data2, return_counts=True)
         vmin, vmax = values[0].item(), values[-1].item()  # Convert from arrays to scalars.
         interval = vmax-vmin

datashader/utils.py

@@ -520,7 +520,9 @@ def _pd_mesh(vertices, simplices):
     winding = [0, 1, 2]
     first_tri = vertices.values[simplices.values[0, winding].astype(np.int64), :2]
     a, b, c = first_tri
-    if np.cross(b-a, c-a).item() >= 0:
+    p1, p2 = b - a, c - a
+    cross_product = p1[0] * p2[1] - p1[1] * p2[0]
+    if cross_product >= 0:
         winding = [0, 2, 1]
 
     # Construct mesh by indexing into vertices with simplex indices

examples/conftest.py

@@ -1,7 +1,20 @@
+from importlib.util import find_spec
+
 import platform
 
 collect_ignore_glob = []
 
+if find_spec("geopandas") is None:
+    collect_ignore_glob += [
+        "user_guide/13_Geopandas.ipynb",
+    ]
+
+if find_spec("spatialpandas") is None:
+    collect_ignore_glob += [
+        "user_guide/7_Networks.ipynb",
+        "user_guide/8_Polygons.ipynb",
+    ]
+
 # 2023-07-21 with following error:
 # nbclient.exceptions.CellTimeoutError: A cell timed out while it was being executed, after 300 seconds.
 # Here is a preview of the cell contents:

setup.py

@@ -40,6 +40,44 @@
     'spatialpandas',
 ]
 
+# Numpy 2 packages, should be removed when all commented out packages works with Numpy 2
+numpy2 = [
+    'numba ==0.60.0rc1',
+    'numpy ==2.0.0rc2',
+
+    # [geopandas]
+    # 'dask-geopandas',
+    # 'geopandas',
+    # 'shapely >=2.0.0',
+
+    # [examples]
+    'bokeh >3.1',
+    'geodatasets',
+    'holoviews',
+    'matplotlib >=3.3',
+    'panel >1.1',
+    # 'scikit-image',
+    # 'spatialpandas',
+
+    # [tests]
+    'codecov',
+    'geodatasets',
+    'flake8',
+    'nbconvert',
+    'nbformat',
+    'nbsmoke[verify] >0.5',
+    'netcdf4',
+    # 'pyarrow',
+    'pytest <8',  # Fails lint with IPynbFile is deprecated
+    'pytest-benchmark',
+    'pytest-cov',
+    # 'rasterio',
+    # 'rioxarray',  # rasterio
+    # 'scikit-image',
+    # 'spatialpandas',
+    # 'dask-expr',  # pyarrow
+]
+
 extras_require = {
     'tests': geopandas + [
         'codecov',
@@ -71,6 +109,7 @@
         'rasterio',
     ],
     'geopandas': geopandas,
+    'numpy2': numpy2,
 }