Merge branch 'main' into parallel

.github/workflows/test.yaml

@@ -146,7 +146,7 @@ jobs:
           echo "ENVS=$envs" >> $GITHUB_ENV
       - uses: holoviz-dev/holoviz_tasks/install@v0
         with:
-          name: unit_test_suite
+          name: unit_test_suite_np${{ matrix.numpy-version }}
           python-version: ${{ matrix.python-version }}
           channel-priority: flexible
           channels: ${{ env.CHANNELS }}

datashader/data_libraries/dask.py

@@ -16,6 +16,20 @@
 __all__ = ()
 
 
+def _dask_compat(df):
+    """
+    Places where this is done, are to be compatible with both
+    `dask-expr` and classic `dask.dataframe` (where `optimize` does not exist).
+    With dask-expr calling df.__dask_graph__() or df.__dask_keys__() will
+    make the graph no longer match the df._name, so we preemptively call it
+    to make it match.
+
+    For more information, see the following comment:
+    https://github.com/holoviz/datashader/pull/1317#issuecomment-2039986852
+    """
+    return getattr(df, 'optimize', lambda: df)()
+
+
 @bypixel.pipeline.register(dd.DataFrame)
 def dask_pipeline(df, schema, canvas, glyph, summary, *, antialias=False, cuda=False):
     dsk, name = glyph_dispatch(glyph, df, schema, canvas, summary, antialias=antialias, cuda=cuda)
@@ -27,6 +41,7 @@ def dask_pipeline(df, schema, canvas, glyph, summary, *, antialias=False, cuda=F
     if isinstance(dsk, da.Array):
         return da.compute(dsk, scheduler=scheduler)[0]
 
+    df = _dask_compat(df)
     keys = df.__dask_keys__()
     optimize = df.__dask_optimize__
     graph = df.__dask_graph__()
@@ -100,7 +115,7 @@ def func(partition: pd.DataFrame, cumulative_lens, partition_info=None):
 
     # Here be dragons
     # Get the dataframe graph
-    df = getattr(df, 'optimize', lambda: df)()  # Work with new dask_expr
+    df = _dask_compat(df)
     graph = df.__dask_graph__()
 
     # Guess a reasonable output dtype from combination of dataframe dtypes
@@ -211,7 +226,7 @@ def line(glyph, df, schema, canvas, summary, *, antialias=False, cuda=False):
     shape, bounds, st, axis = shape_bounds_st_and_axis(df, canvas, glyph)
 
     # Compile functions
-    df = getattr(df, 'optimize', lambda: df)()  # Work with new dask_expr
+    df = _dask_compat(df)
     partitioned = isinstance(df, dd.DataFrame) and df.npartitions > 1
     create, info, append, combine, finalize, antialias_stage_2, antialias_stage_2_funcs, _ = \
         compile_components(summary, schema, glyph, antialias=antialias, cuda=cuda,

datashader/tests/test_dask.py

@@ -2636,3 +2636,18 @@ def test_categorical_where_last_n(ddf, npartitions):
             assert_eq_ndarray(agg[:, :, :, 0].data,
                               c.points(ddf, 'x', 'y', ds.by('cat2', ds.where(ds.last('plusminus'),
                                                                              'reverse'))).data)
+
+@pytest.mark.parametrize('ddf', ddfs)
+@pytest.mark.parametrize('npartitions', [1, 2, 3, 4])
+def test_series_reset_index(ddf, npartitions):
+    # Test for: https://github.com/holoviz/datashader/issues/1331
+    ser = ddf['i32'].reset_index()
+    cvs = ds.Canvas(plot_width=2, plot_height=2)
+    out = cvs.line(ser, x='index', y='i32')
+
+    expected = xr.DataArray(
+        data=[[True, False], [False, True]],
+        coords={"index": [4.75, 14.25], "i32": [4.75, 14.25]},
+        dims=['i32', 'index'],
+    )
+    assert_eq_xr(out, expected)

pyproject.toml

@@ -8,7 +8,7 @@ requires = [
 
 
 [tool.codespell]
-ignore-words-list = "trough,thi"
+ignore-words-list = "trough,thi,ser"
 
 
 [tool.ruff]