feat: Support Narwhals

.github/workflows/test.yaml

@@ -113,7 +113,8 @@ jobs:
     steps:
       - uses: holoviz-dev/holoviz_tasks/pixi_lock@v0
         with:
-          cache: ${{ github.event.inputs.cache == 'true' || github.event.inputs.cache == '' }}
+          cache: false  # NOTE: REVERT
+          # cache: ${{ github.event.inputs.cache == 'true' || github.event.inputs.cache == '' }}
 
   unit_test_suite:
     name: unit:${{ matrix.environment }}:${{ matrix.os }}

hvplot/converter.py

@@ -8,6 +8,7 @@
 import pandas as pd
 import numpy as np
 import colorcet as cc
+import narwhals as nw
 
 from bokeh.models import HoverTool
 from holoviews.core.dimension import Dimension
@@ -55,6 +56,7 @@
     _HV_GE_1_21_0,
     _Undefined,
     filter_opts,
+    is_narwhals,
     is_tabular,
     is_series,
     is_dask,
@@ -73,7 +75,6 @@
     relabel_redim,
     redim_,
     support_index,
-    check_library,
     is_geodataframe,
     process_derived_datetime_xarray,
     process_derived_datetime_pandas,
@@ -1422,6 +1423,9 @@ def _process_data(
         elif isinstance(data, pd.DataFrame):
             datatype = 'pandas'
             self.data = data
+        elif isinstance(data, (nw.LazyFrame, nw.DataFrame, nw.Series)):
+            datatype = 'narwhals'
+            self.data = data
         elif is_dask(data):
             datatype = 'dask'
             self.data = data.persist() if persist else data
@@ -2638,19 +2642,29 @@ def _category_plot(self, element, x: str, y: list[str], data):
 
         cur_opts, compat_opts = self._get_compat_opts(element.name, labelled=labelled)
 
-        id_vars = [x]
-        if any(v in self.indexes for v in id_vars):
-            # Calling reset_index() is required since id_vars from melt
-            # only accepts column names, not index names.
-            data = data.reset_index()
-        data = data[y + [x]]
-
-        if check_library(data, 'dask'):
-            from dask.dataframe import melt
-        else:
-            melt = pd.melt
+        # id_vars = [x]
+        # if any(v in self.indexes for v in id_vars):
+        #     # Calling reset_index() is required since id_vars from melt
+        #     # only accepts column names, not index names.
+        #     data = data.reset_index()
+        # if x is "index":
+
+        #
+        # if check_library(data, 'dask'):
+        #     from dask.dataframe import melt
+        # else:
+        #     melt = pd.melt
+
+        # df = melt(data, id_vars=[x], var_name=self.group_label, value_name=self.value_label)
+
+        data = nw.from_native(data)
+        data = data.select([*y, x])
+        df = data.unpivot(
+            index=x,
+            variable_name=self.group_label,
+            value_name=self.value_label,
+        ).to_native()
 
-        df = melt(data, id_vars=[x], var_name=self.group_label, value_name=self.value_label)
         kdims = [x, self.group_label]
         vdims = [self.value_label] + self.hover_cols
         if self.subplots:
@@ -2707,14 +2721,23 @@ def _stats_plot(self, element, y, data=None):
         cur_opts['labelled'] = labelled
 
         kdims = [self.group_label]
-        data = data[list(y)]
-        if check_library(data, 'dask'):
-            from dask.dataframe import melt
-        else:
-            melt = pd.melt
-        df = melt(data, var_name=self.group_label, value_name=self.value_label)
-        if list(y) and df[self.value_label].dtype is not data[y[0]].dtype:
-            df[self.value_label] = df[self.value_label].astype(data[y[0]].dtype)
+        # if check_library(data, 'narwhals'):
+        #     data = data.lazy().collect().to_pandas()   # HACK: Should likely be handled more elegant
+        # data = data[list(y)]
+        # if check_library(data, 'dask'):
+        #     from dask.dataframe import melt
+        # else:
+        #     melt = pd.melt
+        # df = melt(data, var_name=self.group_label, value_name=self.value_label)
+        data = nw.from_native(data)
+        data = data.select(list(y))
+        df = data.unpivot(
+            index=x,
+            variable_name=self.group_label,
+            value_name=self.value_label,
+        ).to_native()
+        # if list(y) and df[self.value_label].dtype is not data[y[0]].dtype:
+        #     df[self.value_label] = df[self.value_label].astype(data[y[0]].dtype)
         redim = self._merge_redim({self.value_label: ylim})
         return relabel_redim(
             element(df, kdims, self.value_label),
@@ -2794,13 +2817,11 @@ def hist(self, x=None, y=None, data=None):
 
         if hist_opts['bin_range'] is None and not self._norm_opts.get('axiswise'):
             ranges = []
+            nw_data = nw.from_native(data)
+
             for col in y:
-                ys = data[col]
-                ymin, ymax = (ys.min(), ys.max())
-                if is_dask(ys):
-                    ymin, ymax = ymin.compute(), ymax.compute()
-                elif is_ibis(ys):
-                    ymin, ymax = ymin.execute(), ymax.execute()
+                ymin = nw_data.select(nw.col(col).min()).lazy().collect().item()
+                ymax = nw_data.select(nw.col(col).max()).lazy().collect().item()
                 ranges.append((ymin, ymax))
             if ranges:
                 hist_opts['bin_range'] = max_range(ranges)
@@ -2855,10 +2876,17 @@ def kde(self, x=None, y=None, data=None):
                 dists = Distribution(data, y, [])
         else:
             ranges = {self.value_label: xlim}
-            data = data[y]
-            df = data.melt(var_name=self.group_label, value_name=self.value_label)
+            data = nw.from_native(data)
+            data = data.select([x, *y])
+            df = data.unpivot(
+                index=x,
+                variable_name=self.group_label,
+                value_name=self.value_label,
+            ).to_native()
+            # data = data[y]
+            # df = data.melt(var_name=self.group_label, value_name=self.value_label)
             ds = Dataset(df)
-            if len(df):
+            if len(ds):
                 dists = ds.to(Distribution, self.value_label)
                 dists = dists.layout() if self.subplots else dists.overlay(sort=False)
             else:
@@ -2946,15 +2974,20 @@ def bivariate(self, x=None, y=None, data=None):
         )
 
     def ohlc(self, x=None, y=None, data=None):
+        from holoviews.core.util import dtype_kind
+
         self._error_if_unavailable('ohlc', Rectangles)
         self._error_if_unavailable('ohlc', Segments)
         data = self.data if data is None else data
         if x is None:
             variables = [var for var in self.variables if var not in self.indexes]
-            if data[variables[0]].dtype.kind == 'M':
+            dtype = nw.from_native(data).schema[variables[0]]
+            if dtype_kind(dtype) == 'M':
                 x = variables[0]
-            else:
+            elif self.indexes:
                 x = self.indexes[0]
+            else:
+                x = 'index'
         width = self.kwds.get('bar_width', 0.5)
         if y is None:
             o, h, l, c = [col for col in data.columns if col != x][:4]  # noqa: E741
@@ -2967,7 +3000,7 @@ def ohlc(self, x=None, y=None, data=None):
             self.hover_cols.remove(x)
         vdims = list(dict.fromkeys(ohlc_cols + self.hover_cols))
         ds = Dataset(data, [x], vdims)
-        if ds.dimension_values(x).dtype.kind in 'SUO':
+        if dtype_kind(ds.dimension_values(x)) in 'SUO':
             rects = Rectangles(ds, [x, o, x, c])
         else:
             if len(ds):
@@ -2983,8 +3016,9 @@ def ohlc(self, x=None, y=None, data=None):
         seg_cur_opts, seg_compat_opts = self._get_compat_opts('Segments')
         tools = seg_cur_opts.pop('tools', [])
         if 'hover' in tools:
-            x_data = data[x] if x in data.columns else data.index
-            if pd.api.types.is_datetime64_any_dtype(x_data):
+            # x_data = data[x] if x in data.columns else data.index
+            dtype = nw.from_native(data).schema[x]
+            if dtype_kind(dtype) == 'M':
                 # %F %T: strftime code for %Y-%m-%d %H:%M:%S.
                 # See https://man7.org/linux/man-pages/man3/strftime.3.html
                 x_tooltip = f'@{x}{{%F %T}}'
@@ -3020,7 +3054,7 @@ def ohlc(self, x=None, y=None, data=None):
     def table(self, x=None, y=None, data=None):
         self._error_if_unavailable('table')
         data = self.data if data is None else data
-        if isinstance(data.index, (DatetimeIndex, MultiIndex)):
+        if isinstance(getattr(data, 'index', None), (DatetimeIndex, MultiIndex)):
             # To get the index displayed in the table as Bokeh doesn't show it.
             data = data.reset_index()
 
@@ -3260,6 +3294,8 @@ def _geom_plot(self, x=None, y=None, data=None, kind='polygons'):
         data, x, y, _ = self._process_gridded_args(data, x, y, z=None)
         params = dict(self._relabel)
 
+        if is_narwhals(self.data) and x == 'index':
+            x = None
         if not (x and y):
             if is_geodataframe(data):
                 x, y = ('Longitude', 'Latitude') if self.geo else ('x', 'y')

hvplot/plotting/core.py

@@ -1600,15 +1600,21 @@ def _get_converter(self, x=None, y=None, kind=None, **kwds):
                 # Reorder the columns as in the data.
                 columns = sorted(columns, key=lambda c: column_names.index(c))
 
-        if isinstance(self._data, pl.DataFrame):
-            data = self._data.select(columns).to_pandas()
+        if isinstance(self._data, (pl.LazyFrame, pl.DataFrame)):
+            data = self._data.select(columns)  # .to_pandas()
         elif isinstance(self._data, pl.Series):
-            data = self._data.to_pandas()
-        elif isinstance(self._data, pl.LazyFrame):
-            data = self._data.select(columns).collect().to_pandas()
+            data = self._data.to_frame()  # .to_pandas()
+        # elif isinstance(self._data, pl.LazyFrame):
+        #     data = self._data.select(columns).collect()# .to_pandas()
         else:
             raise ValueError('Only Polars DataFrame, Series, and LazyFrame are supported')
 
+        x = x or 'index'
+        if x == 'index':
+            data = data.with_row_index()
+        import narwhals as nw
+
+        data = nw.from_native(data)
         return HoloViewsConverter(data, x, y, kind=kind, **params)
 
 

hvplot/util.py

@@ -426,7 +426,7 @@ def is_list_like(obj):
 
 
 def is_tabular(data):
-    if check_library(data, ['dask', 'streamz', 'pandas', 'geopandas', 'cudf']):
+    if check_library(data, ['dask', 'streamz', 'pandas', 'geopandas', 'cudf', 'narwhals']):
         return True
     elif check_library(data, 'intake'):
         from intake.source.base import DataSource
@@ -438,7 +438,7 @@ def is_tabular(data):
 
 
 def is_series(data):
-    if not check_library(data, ['dask', 'streamz', 'pandas', 'cudf']):
+    if not check_library(data, ['dask', 'streamz', 'pandas', 'cudf', 'narwhals']):
         return False
     elif isinstance(data, pd.Series):
         return True
@@ -454,6 +454,10 @@ def is_series(data):
         import cudf
 
         return isinstance(data, cudf.Series)
+    elif check_library(data, 'narwhals'):
+        import narwhals as nw
+
+        return isinstance(data, nw.Series)
     else:
         return False
 
@@ -487,6 +491,14 @@ def is_duckdb(data):
     return isinstance(data, (duckdb.DuckDBPyRelation, duckdb.DuckDBPyConnection))
 
 
+def is_narwhals(data):
+    if not check_library(data, 'narwhals'):
+        return False
+    import narwhals as nw
+
+    return isinstance(data, (nw.DataFrame, nw.Series, nw.LazyFrame))
+
+
 def is_polars(data):
     if not check_library(data, 'polars'):
         return False
@@ -530,7 +542,7 @@ def is_xarray(data):
 def is_lazy_data(data):
     """Check if data is lazy
 
-    This checks if the datatype is Dask, Ibis, or Polars' LazyFrame.
+    This checks if the datatype is Dask, Ibis, Polars' LazyFrame, or Narwhals' LazyFrame.
     It is useful to avoid eager evaluation of the data.
     """
     if is_dask(data) or is_ibis(data):
@@ -539,6 +551,10 @@ def is_lazy_data(data):
         import polars as pl
 
         return isinstance(data, pl.LazyFrame)
+    elif is_narwhals(data):
+        import narwhals as nw
+
+        return isinstance(data, nw.LazyFrame)
     return False
 
 

pixi.toml

@@ -55,13 +55,17 @@ pip = "*"
 # Required
 bokeh = ">=3.1"
 colorcet = ">=2"
-holoviews = ">=1.19.0"
+# holoviews = ">=1.19.0"  # NOTE: REVERT
 numpy = ">=1.21"
 packaging = "*"
 pandas = ">=1.3"
-panel = ">=1.0"
+# panel = ">=1.0"
 param = ">=1.12.0,<3.0"
 
+[feature.required.pypi-dependencies]
+holoviews = { git = "https://github.com/holoviz/holoviews" , branch = "feat_narwhals"}  # NOTE: REVERT
+panel = ">=1.8.0rc0"  # Until an release
+
 [feature.required.tasks]
 download-data = 'python scripts/download_data.py'
 install = 'python -m pip install --no-deps --disable-pip-version-check -e .'
@@ -205,11 +209,11 @@ pygraphviz = "*"
 
 [feature.test.tasks]
 test-unit-geo = 'pytest -v hvplot --geo'
-test-unit-cov = 'pytest -v hvplot --cov=hvplot --cov-branch --cov-append'
+test-unit-cov = 'pytest hvplot --cov=hvplot --cov-branch --cov-append -k polars'  # NOTE: REVERT
 test-unit-geo-cov = 'pytest -v hvplot --geo --cov=hvplot --cov-branch --cov-append'
 
 [feature.test-core.tasks]
-test-unit = 'pytest -v hvplot'
+test-unit = 'pytest hvplot -k polars'  # NOTE: REVERT
 
 [feature.test-example.tasks]
 test-example = 'pytest -n logical --dist loadscope --nbval-lax -p no:python'