refactor: apply new ruff rules, fix and reformat

altair/_magics.py

@@ -45,22 +45,22 @@ def _prepare_data(data, data_transformers):
     elif isinstance(data, str):
         return {"url": data}
     else:
-        warnings.warn("data of type {} not recognized".format(type(data)), stacklevel=1)
+        warnings.warn(f"data of type {type(data)} not recognized", stacklevel=1)
         return data
 
 
 def _get_variable(name):
     """Get a variable from the notebook namespace."""
     ip = IPython.get_ipython()
     if ip is None:
-        raise ValueError(
+        msg = (
             "Magic command must be run within an IPython "
             "environment, in which get_ipython() is defined."
         )
+        raise ValueError(msg)
     if name not in ip.user_ns:
-        raise NameError(
-            "argument '{}' does not match the name of any defined variable".format(name)
-        )
+        msg = f"argument '{name}' does not match the name of any defined variable"
+        raise NameError(msg)
     return ip.user_ns[name]
 
 
@@ -95,10 +95,11 @@ def vegalite(line, cell):
         try:
             spec = json.loads(cell)
         except json.JSONDecodeError as err:
-            raise ValueError(
+            msg = (
                 "%%vegalite: spec is not valid JSON. "
                 "Install pyyaml to parse spec as yaml"
-            ) from err
+            )
+            raise ValueError(msg) from err
     else:
         spec = yaml.load(cell, Loader=yaml.SafeLoader)
 

altair/expr/core.py

@@ -184,51 +184,49 @@ def __getitem__(self, val):
 
 class UnaryExpression(Expression):
     def __init__(self, op, val):
-        super(UnaryExpression, self).__init__(op=op, val=val)
+        super().__init__(op=op, val=val)
 
     def __repr__(self):
-        return "({op}{val})".format(op=self.op, val=_js_repr(self.val))
+        return f"({self.op}{_js_repr(self.val)})"
 
 
 class BinaryExpression(Expression):
     def __init__(self, op, lhs, rhs):
-        super(BinaryExpression, self).__init__(op=op, lhs=lhs, rhs=rhs)
+        super().__init__(op=op, lhs=lhs, rhs=rhs)
 
     def __repr__(self):
-        return "({lhs} {op} {rhs})".format(
-            op=self.op, lhs=_js_repr(self.lhs), rhs=_js_repr(self.rhs)
-        )
+        return f"({_js_repr(self.lhs)} {self.op} {_js_repr(self.rhs)})"
 
 
 class FunctionExpression(Expression):
     def __init__(self, name, args):
-        super(FunctionExpression, self).__init__(name=name, args=args)
+        super().__init__(name=name, args=args)
 
     def __repr__(self):
         args = ",".join(_js_repr(arg) for arg in self.args)
-        return "{name}({args})".format(name=self.name, args=args)
+        return f"{self.name}({args})"
 
 
 class ConstExpression(Expression):
     def __init__(self, name, doc):
-        self.__doc__ = """{}: {}""".format(name, doc)
-        super(ConstExpression, self).__init__(name=name, doc=doc)
+        self.__doc__ = f"""{name}: {doc}"""
+        super().__init__(name=name, doc=doc)
 
     def __repr__(self):
         return str(self.name)
 
 
 class GetAttrExpression(Expression):
     def __init__(self, group, name):
-        super(GetAttrExpression, self).__init__(group=group, name=name)
+        super().__init__(group=group, name=name)
 
     def __repr__(self):
-        return "{}.{}".format(self.group, self.name)
+        return f"{self.group}.{self.name}"
 
 
 class GetItemExpression(Expression):
     def __init__(self, group, name):
-        super(GetItemExpression, self).__init__(group=group, name=name)
+        super().__init__(group=group, name=name)
 
     def __repr__(self):
-        return "{}[{!r}]".format(self.group, self.name)
+        return f"{self.group}[{self.name!r}]"

altair/expr/funcs.py

@@ -172,13 +172,13 @@ class ExprFunc:
     def __init__(self, name, doc):
         self.name = name
         self.doc = doc
-        self.__doc__ = """{}(*args)\n    {}""".format(name, doc)
+        self.__doc__ = f"""{name}(*args)\n    {doc}"""
 
     def __call__(self, *args):
         return FunctionExpression(self.name, args)
 
     def __repr__(self):
-        return "<function expr.{}(*args)>".format(self.name)
+        return f"<function expr.{self.name}(*args)>"
 
 
 def _populate_namespace():

altair/jupyter/__init__.py

@@ -7,14 +7,15 @@
     # when anywidget is not installed
     class JupyterChart:
         def __init__(self, *args, **kwargs):
-            raise ImportError(
+            msg = (
                 "The Altair JupyterChart requires the anywidget \n"
                 "Python package which may be installed using pip with\n"
                 "    pip install anywidget\n"
                 "or using conda with\n"
                 "    conda install -c conda-forge anywidget\n"
                 "Afterwards, you will need to restart your Python kernel."
             )
+            raise ImportError(msg)
 
 else:
     from .jupyter_chart import JupyterChart  # noqa: F401

altair/jupyter/jupyter_chart.py

@@ -61,7 +61,8 @@ def __init__(self, trait_values):
             elif isinstance(value, IntervalSelection):
                 traitlet_type = traitlets.Instance(IntervalSelection)
             else:
-                raise ValueError(f"Unexpected selection type: {type(value)}")
+                msg = f"Unexpected selection type: {type(value)}"
+                raise ValueError(msg)
 
             # Add the new trait.
             self.add_traits(**{key: traitlet_type})
@@ -82,10 +83,11 @@ def _make_read_only(self, change):
         """
         if change["name"] in self.traits() and change["old"] != change["new"]:
             self._set_value(change["name"], change["old"])
-        raise ValueError(
+        msg = (
             "Selections may not be set from Python.\n"
             f"Attempted to set select: {change['name']}"
         )
+        raise ValueError(msg)
 
     def _set_value(self, key, value):
         self.unobserve(self._make_read_only, names=key)
@@ -278,7 +280,8 @@ def _on_change_chart(self, change):
                             name=clean_name, value={}, store=[]
                         )
                     else:
-                        raise ValueError(f"Unexpected selection type {select.type}")
+                        msg = f"Unexpected selection type {select.type}"
+                        raise ValueError(msg)
                     selection_watches.append(clean_name)
                     initial_vl_selections[clean_name] = {"value": None, "store": []}
                 else:

altair/utils/_dfi_types.py

@@ -76,7 +76,6 @@ def dtype(self) -> Dtype:
             - Data types not included: complex, Arrow-style null, binary, decimal,
               and nested (list, struct, map, union) dtypes.
         """
-        pass
 
     # Have to use a generic Any return type as not all libraries who implement
     # the dataframe interchange protocol implement the TypedDict that is usually
@@ -103,7 +102,6 @@ def describe_categorical(self) -> Any:
 
         TBD: are there any other in-memory representations that are needed?
         """
-        pass
 
 
 class DataFrame(Protocol):
@@ -136,19 +134,16 @@ def __dataframe__(
         necessary if a library supports strided buffers, given that this protocol
         specifies contiguous buffers.
         """
-        pass
 
     def column_names(self) -> Iterable[str]:
         """
         Return an iterator yielding the column names.
         """
-        pass
 
     def get_column_by_name(self, name: str) -> Column:
         """
         Return the column whose name is the indicated name.
         """
-        pass
 
     def get_chunks(self, n_chunks: Optional[int] = None) -> Iterable["DataFrame"]:
         """
@@ -162,4 +157,3 @@ def get_chunks(self, n_chunks: Optional[int] = None) -> Iterable["DataFrame"]:
         Note that the producer must ensure that all columns are chunked the
         same way.
         """
-        pass

altair/utils/_importers.py

@@ -9,18 +9,19 @@ def import_vegafusion() -> ModuleType:
         version = importlib_version("vegafusion")
         embed_version = importlib_version("vegafusion-python-embed")
         if version != embed_version or Version(version) < Version(min_version):
-            raise RuntimeError(
+            msg = (
                 "The versions of the vegafusion and vegafusion-python-embed packages must match\n"
                 f"and must be version {min_version} or greater.\n"
                 f"Found:\n"
                 f" - vegafusion=={version}\n"
                 f" - vegafusion-python-embed=={embed_version}\n"
             )
+            raise RuntimeError(msg)
         import vegafusion as vf  # type: ignore
 
         return vf
     except ImportError as err:
-        raise ImportError(
+        msg = (
             'The "vegafusion" data transformer and chart.transformed_data feature requires\n'
             f"version {min_version} or greater of the 'vegafusion-python-embed' and 'vegafusion' packages.\n"
             "These can be installed with pip using:\n"
@@ -29,31 +30,34 @@ def import_vegafusion() -> ModuleType:
             f'    conda install -c conda-forge "vegafusion-python-embed>={min_version}" '
             f'"vegafusion>={min_version}"\n\n'
             f"ImportError: {err.args[0]}"
-        ) from err
+        )
+        raise ImportError(msg) from err
 
 
 def import_vl_convert() -> ModuleType:
     min_version = "1.3.0"
     try:
         version = importlib_version("vl-convert-python")
         if Version(version) < Version(min_version):
-            raise RuntimeError(
+            msg = (
                 f"The vl-convert-python package must be version {min_version} or greater. "
                 f"Found version {version}"
             )
+            raise RuntimeError(msg)
         import vl_convert as vlc
 
         return vlc
     except ImportError as err:
-        raise ImportError(
+        msg = (
             f"The vl-convert Vega-Lite compiler and file export feature requires\n"
             f"version {min_version} or greater of the 'vl-convert-python' package. \n"
             f"This can be installed with pip using:\n"
             f'   pip install "vl-convert-python>={min_version}"\n'
             "or conda:\n"
             f'   conda install -c conda-forge "vl-convert-python>={min_version}"\n\n'
             f"ImportError: {err.args[0]}"
-        ) from err
+        )
+        raise ImportError(msg) from err
 
 
 def vl_version_for_vl_convert() -> str:
@@ -70,23 +74,25 @@ def import_pyarrow_interchange() -> ModuleType:
         version = importlib_version("pyarrow")
 
         if Version(version) < Version(min_version):
-            raise RuntimeError(
+            msg = (
                 f"The pyarrow package must be version {min_version} or greater. "
                 f"Found version {version}"
             )
+            raise RuntimeError(msg)
         import pyarrow.interchange as pi
 
         return pi
     except ImportError as err:
-        raise ImportError(
+        msg = (
             f"Usage of the DataFrame Interchange Protocol requires\n"
             f"version {min_version} or greater of the pyarrow package. \n"
             f"This can be installed with pip using:\n"
             f'   pip install "pyarrow>={min_version}"\n'
             "or conda:\n"
             f'   conda install -c conda-forge "pyarrow>={min_version}"\n\n'
             f"ImportError: {err.args[0]}"
-        ) from err
+        )
+        raise ImportError(msg) from err
 
 
 def pyarrow_available() -> bool:

altair/utils/_show.py

@@ -26,10 +26,7 @@ def open_html_in_browser(
         Port to use. Defaults to a random port
     """
     # Encode html to bytes
-    if isinstance(html, str):
-        html_bytes = html.encode("utf8")
-    else:
-        html_bytes = html
+    html_bytes = html.encode("utf8") if isinstance(html, str) else html
 
     browser = None
 
@@ -69,5 +66,5 @@ def log_message(self, format, *args):
     server = HTTPServer(
         ("127.0.0.1", port if port is not None else 0), OneShotRequestHandler
     )
-    browser.open("http://127.0.0.1:%s" % server.server_port)
+    browser.open(f"http://127.0.0.1:{server.server_port}")
     server.handle_request()

altair/utils/_transformed_data.py

@@ -90,11 +90,9 @@ def transformed_data(chart, row_limit=None, exclude=None):
         transformed data
     """
     vf = import_vegafusion()
-
-    if isinstance(chart, Chart):
-        # Add mark if none is specified to satisfy Vega-Lite
-        if chart.mark == Undefined:
-            chart = chart.mark_point()
+    # Add mark if none is specified to satisfy Vega-Lite
+    if isinstance(chart, Chart) and chart.mark == Undefined:
+        chart = chart.mark_point()
 
     # Deep copy chart so that we can rename marks without affecting caller
     chart = chart.copy(deep=True)
@@ -119,7 +117,8 @@ def transformed_data(chart, row_limit=None, exclude=None):
         if chart_name in dataset_mapping:
             dataset_names.append(dataset_mapping[chart_name])
         else:
-            raise ValueError("Failed to locate all datasets")
+            msg = "Failed to locate all datasets"
+            raise ValueError(msg)
 
     # Extract transformed datasets with VegaFusion
     datasets, warnings = vf.runtime.pre_transform_datasets(
@@ -200,11 +199,12 @@ def name_views(
         elif isinstance(chart, _chart_class_mapping[ConcatChart]):
             subcharts = chart.concat
         else:
-            raise ValueError(
+            msg = (
                 "transformed_data accepts an instance of "
                 "Chart, FacetChart, LayerChart, HConcatChart, VConcatChart, or ConcatChart\n"
                 f"Received value of type: {type(chart)}"
             )
+            raise ValueError(msg)
 
         chart_names: List[str] = []
         for subchart in subcharts:
@@ -444,7 +444,7 @@ def get_facet_mapping(group: dict, scope: Scope = ()) -> FacetMapping:
     for mark in mark_group.get("marks", []):
         if mark.get("type", None) == "group":
             # Get facet for this group
-            group_scope = scope + (group_index,)
+            group_scope = (*scope, group_index)
             facet = mark.get("from", {}).get("facet", None)
             if facet is not None:
                 facet_name = facet.get("name", None)
@@ -536,7 +536,7 @@ def get_datasets_for_view_names(
         name = mark.get("name", "")
         if mark.get("type", "") == "group":
             group_data_names = get_datasets_for_view_names(
-                group, vl_chart_names, facet_mapping, scope=scope + (group_index,)
+                group, vl_chart_names, facet_mapping, scope=(*scope, group_index)
             )
             for k, v in group_data_names.items():
                 datasets.setdefault(k, v)