attempt to copy prettier from spatialdata

Author: timtreis

.pre-commit-config.yaml

@@ -8,26 +8,19 @@ minimum_pre_commit_version: 2.16.0
 ci:
   skip: []
 repos:
-  - repo: https://github.com/psf/black
-    rev: 24.10.0
-    hooks:
-      - id: black
   - repo: https://github.com/rbubley/mirrors-prettier
     rev: v3.5.1
     hooks:
       - id: prettier
-  - repo: https://github.com/asottile/blacken-docs
-    rev: 1.19.1
-    hooks:
-      - id: blacken-docs
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.14.1
+    rev: v1.15.0
     hooks:
       - id: mypy
         additional_dependencies: [numpy, types-requests]
         exclude: tests/|docs/
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.9.3
+    rev: v0.9.6
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
+      - id: ruff-format

docs/extensions/typed_returns.py

@@ -12,7 +12,7 @@
 def _process_return(lines: Iterable[str]) -> Generator[str, None, None]:
     for line in lines:
         if m := re.fullmatch(r"(?P<param>\w+)\s+:\s+(?P<type>[\w.]+)", line):
-            yield f'-{m["param"]} (:class:`~{m["type"]}`)'
+            yield f"-{m['param']} (:class:`~{m['type']}`)"
         else:
             yield line
 

src/spatialdata_plot/pl/basic.py

@@ -290,7 +290,7 @@ def render_shapes(
                 norm=norm,
                 na_color=params_dict[element]["na_color"],  # type: ignore[arg-type]
             )
-            sdata.plotting_tree[f"{n_steps+1}_render_shapes"] = ShapesRenderParams(
+            sdata.plotting_tree[f"{n_steps + 1}_render_shapes"] = ShapesRenderParams(
                 element=element,
                 color=param_values["color"],
                 col_for_color=param_values["col_for_color"],
@@ -433,7 +433,7 @@ def render_points(
                 norm=norm,
                 na_color=param_values["na_color"],  # type: ignore[arg-type]
             )
-            sdata.plotting_tree[f"{n_steps+1}_render_points"] = PointsRenderParams(
+            sdata.plotting_tree[f"{n_steps + 1}_render_points"] = PointsRenderParams(
                 element=element,
                 color=param_values["color"],
                 col_for_color=param_values["col_for_color"],
@@ -538,7 +538,6 @@ def render_images(
         n_steps = len(sdata.plotting_tree.keys())
 
         for element, param_values in params_dict.items():
-
             cmap_params: list[CmapParams] | CmapParams
             if isinstance(cmap, list):
                 cmap_params = [
@@ -557,7 +556,7 @@ def render_images(
                     na_color=param_values["na_color"],
                     **kwargs,
                 )
-            sdata.plotting_tree[f"{n_steps+1}_render_images"] = ImageRenderParams(
+            sdata.plotting_tree[f"{n_steps + 1}_render_images"] = ImageRenderParams(
                 element=element,
                 channel=param_values["channel"],
                 cmap_params=cmap_params,
@@ -683,7 +682,7 @@ def render_labels(
                 norm=norm,
                 na_color=param_values["na_color"],  # type: ignore[arg-type]
             )
-            sdata.plotting_tree[f"{n_steps+1}_render_labels"] = LabelsRenderParams(
+            sdata.plotting_tree[f"{n_steps + 1}_render_labels"] = LabelsRenderParams(
                 element=element,
                 color=param_values["color"],
                 groups=param_values["groups"],

src/spatialdata_plot/pl/render.py

@@ -730,7 +730,6 @@ def _render_images(
     legend_params: LegendParams,
     rasterize: bool,
 ) -> None:
-
     sdata_filt = sdata.filter_by_coordinate_system(
         coordinate_system=coordinate_system,
         filter_tables=False,

src/spatialdata_plot/pl/utils.py

@@ -305,7 +305,6 @@ def _get_centroid_of_pathpatch(pathpatch: mpatches.PathPatch) -> tuple[float, fl
 
 
 def _scale_pathpatch_around_centroid(pathpatch: mpatches.PathPatch, scale_factor: float) -> None:
-
     centroid = _get_centroid_of_pathpatch(pathpatch)
     vertices = pathpatch.get_path().vertices
     scaled_vertices = np.array([centroid + (vertex - centroid) * scale_factor for vertex in vertices])
@@ -677,7 +676,7 @@ def _get_colors_for_categorical_obs(
             palette = default_102
         else:
             palette = ["grey" for _ in range(len_cat)]
-            logger.info("input has more than 103 categories. Uniform " "'grey' color will be used for all categories.")
+            logger.info("input has more than 103 categories. Uniform 'grey' color will be used for all categories.")
     else:
         # raise error when user didn't provide the right number of colors in palette
         if isinstance(palette, list) and len(palette) != len(categories):
@@ -1654,7 +1653,7 @@ def _ensure_table_and_layer_exist_in_sdata(
                 if table_layer in sdata.tables[tname].layers:
                     if found_table:
                         raise ValueError(
-                            "Trying to guess 'table_name' based on 'table_layer', " "but found multiple matches."
+                            "Trying to guess 'table_name' based on 'table_layer', but found multiple matches."
                         )
                     found_table = True
 
@@ -1727,7 +1726,6 @@ def _validate_label_render_params(
 
     element_params: dict[str, dict[str, Any]] = {}
     for el in param_dict["element"]:
-
         # ensure that the element exists in the SpatialData object
         _ = param_dict["sdata"][el]
 
@@ -1788,7 +1786,6 @@ def _validate_points_render_params(
 
     element_params: dict[str, dict[str, Any]] = {}
     for el in param_dict["element"]:
-
         # ensure that the element exists in the SpatialData object
         _ = param_dict["sdata"][el]
 
@@ -1859,7 +1856,6 @@ def _validate_shape_render_params(
 
     element_params: dict[str, dict[str, Any]] = {}
     for el in param_dict["element"]:
-
         # ensure that the element exists in the SpatialData object
         _ = param_dict["sdata"][el]
 
@@ -1896,7 +1892,6 @@ def _validate_shape_render_params(
 def _validate_col_for_column_table(
     sdata: SpatialData, element_name: str, col_for_color: str | None, table_name: str | None, labels: bool = False
 ) -> tuple[str | None, str | None]:
-
     if not labels and col_for_color in sdata[element_name].columns:
         table_name = None
     elif table_name is not None:
@@ -2204,7 +2199,7 @@ def _datashader_aggregate_with_function(
 
 
 def _datshader_get_how_kw_for_spread(
-    reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None
+    reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None,
 ) -> str:
     # Get the best input for the how argument of ds.tf.spread(), needed for numerical values
     reduction = reduction or "sum"