Fix gt deps

.github/workflows/ci.yml

@@ -29,7 +29,6 @@ jobs:
           # we are using the -e flag, so that code cov finds the source.
           # this is not ideal, since installing an editable can technically
           # differ from a normal install in surprising ways.
-          python -m pip install "git+https://github.com/posit-dev/great-tables.git@feat-interactive"
           pip install -e '.[all]'
       - name: Unit tests
         run: |

.github/workflows/docs.yml

@@ -18,7 +18,6 @@ jobs:
           python-version: "3.10"
       - name: Install dependencies
         run: |
-          python -m pip install "git+https://github.com/posit-dev/great-tables.git@feat-interactive"
           python -m pip install ".[dev]"
       - uses: quarto-dev/quarto-actions/setup@v2
         with:

reactable/_tbl_data.py

@@ -4,7 +4,7 @@
 
 from datetime import datetime, date, time
 from functools import singledispatch
-from typing import TYPE_CHECKING, Any, Union, Literal
+from typing import TYPE_CHECKING, Any, Union, Literal, Optional
 from typing_extensions import TypeAlias
 
 from abc import ABC
@@ -163,3 +163,33 @@ def _(data: PdDataFrame) -> "list[str]":
 @column_names.register
 def _(data: SimpleFrame) -> "list[str]":
     return list(data.columns)
+
+
+# subset_frame --------------------------------------------------------
+@singledispatch
+def subset_frame(
+    data: DataFrameLike, row: Optional[list[int]], column: Optional[list[str]]
+) -> DataFrameLike:
+    raise TypeError(f"Unsupported type: {type(data)}")
+
+
+@subset_frame.register
+def _(
+    data: PdDataFrame, rows: Optional[list[int]] = None, cols: Optional[list[str]] = None
+) -> PdDataFrame:
+
+    cols_indx = slice(None) if cols is None else data.columns.get_indexer_for(cols)
+    rows_indx = slice(None) if rows is None else rows
+
+    return data.iloc[rows_indx, cols_indx]
+
+
+@subset_frame.register
+def _(
+    data: PlDataFrame, rows: Optional[list[int]] = None, cols: Optional[list[str]] = None
+) -> PlDataFrame:
+
+    cols_indx = slice(None) if cols is None else cols
+    rows_indx = slice(None) if rows is None else rows
+
+    return data[rows_indx, cols_indx]

reactable/render_gt.py

@@ -5,19 +5,30 @@
 import ipywidgets
 
 from great_tables import GT
-from great_tables._tbl_data import n_rows, subset_frame
+from great_tables._tbl_data import n_rows
 from great_tables._helpers import random_id
 from great_tables._text import _process_text
 from great_tables._gt_data import ColInfoTypeEnum
 from great_tables._scss import compile_scss
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 
 from .models import Column, Language, Theme, ColGroup
 from . import Reactable
 from .tags import as_react_style, to_widget
+from ._tbl_data import subset_frame, to_dict
 
 if TYPE_CHECKING:
-    from great_tables._gt_data import Locale, Spanners, Heading, Footnotes, SourceNotes
+    from great_tables._gt_data import Locale, Spanners, Heading, Footnotes, SourceNotes, Options
+
+
+class OptWrapper:
+    _d: Options
+
+    def __init__(self, d: Options):
+        self._d = d
+
+    def __getitem__(self, k: str) -> Any:
+        return getattr(self._d, k).value
 
 
 def dict_to_css(dict_: dict[str, str]) -> str:
@@ -48,8 +59,14 @@ def create_col_groups(spanners: Spanners) -> list[ColGroup]:
     return col_groups
 
 
+def _is_empty(heading: Heading):
+    # TODO: this should be moved into great tables
+    self = heading
+    return self.title is None and self.subtitle is None and self.preheader is None
+
+
 def create_heading(heading: Heading, use_search: bool) -> html.Tag | None:
-    if heading.is_empty():
+    if _is_empty(heading):
         return None
 
     el = html.div(
@@ -117,8 +134,6 @@ def extract_cells(
     from great_tables._tbl_data import (
         cast_frame_to_string,
         replace_null_frame,
-        subset_frame,
-        to_column_dict,
     )
 
     if rows is not None:
@@ -137,7 +152,7 @@ def extract_cells(
 
     # TODO: get_cell gets individual cell, need one that gets columns
     df_subset = subset_frame(df_stringified, cols=columns)
-    return to_column_dict(df_subset)
+    return to_dict(df_subset)
 
 
 def _render(self: GT):
@@ -146,7 +161,7 @@ def _render(self: GT):
 
     # add_css_styles()
 
-    table_id = self._options["table_id"] or random_id()
+    table_id = OptWrapper(self._options)["table_id"] or random_id()
     locale = self._locale
 
     # generate Language -------------------------------------------------------
@@ -243,7 +258,7 @@ def _render(self: GT):
     )
 
     # Generate theme ----------------------------------------------------------
-    opts = self._options
+    opts = OptWrapper(self._options)
     theme = Theme(
         color=opts["table_font_color"],
         background_color=opts["table_background_color"],

tests/test_tbl_data.py

@@ -0,0 +1,40 @@
+import pandas as pd
+import polars as pl
+import polars.testing
+import pytest
+
+from reactable._tbl_data import subset_frame, SimpleFrame, SimpleColumn
+
+params_frames = [pytest.param(pd.DataFrame, id="pandas"), pytest.param(pl.DataFrame, id="polars")]
+params_series = [pytest.param(pd.Series, id="pandas"), pytest.param(pl.Series, id="polars")]
+
+
+@pytest.fixture(params=params_frames, scope="function")
+def df(request) -> pd.DataFrame:
+    return request.param({"col1": [1, 2, 3], "col2": ["a", "b", "c"], "col3": [4.0, 5.0, 6.0]})
+
+
+@pytest.fixture(params=params_series, scope="function")
+def ser(request):
+    return request.param([1.0, 2.0, None])
+
+
+def assert_frame_equal(src, target, include_index=True):
+    if isinstance(src, pd.DataFrame):
+        if not include_index:
+            src = src.reset_index(drop=True)
+            target = target.reset_index(drop=True)
+        pd.testing.assert_frame_equal(src, target)
+    elif isinstance(src, pl.DataFrame):
+        pl.testing.assert_frame_equal(src, target)
+    else:
+        raise NotImplementedError(f"Unsupported data type: {type(src)}")
+
+
+def test_subset_frame(df):
+    res = subset_frame(df, rows=[0, 2], cols=["col1", "col3"])
+    assert_frame_equal(
+        res,
+        df.__class__({"col1": [1, 3], "col3": [4.0, 6.0]}),
+        include_index=False,
+    )