TYP: Fix some PythonParser and Plotting types

pandas/core/interchange/from_dataframe.py

@@ -2,7 +2,10 @@
 
 import ctypes
 import re
-from typing import Any
+from typing import (
+    Any,
+    overload,
+)
 
 import numpy as np
 
@@ -459,12 +462,42 @@ def buffer_to_ndarray(
         return np.array([], dtype=ctypes_type)
 
 
+@overload
+def set_nulls(
+    data: np.ndarray,
+    col: Column,
+    validity: tuple[Buffer, tuple[DtypeKind, int, str, str]] | None,
+    allow_modify_inplace: bool = ...,
+) -> np.ndarray:
+    ...
+
+
+@overload
+def set_nulls(
+    data: pd.Series,
+    col: Column,
+    validity: tuple[Buffer, tuple[DtypeKind, int, str, str]] | None,
+    allow_modify_inplace: bool = ...,
+) -> pd.Series:
+    ...
+
+
+@overload
+def set_nulls(
+    data: np.ndarray | pd.Series,
+    col: Column,
+    validity: tuple[Buffer, tuple[DtypeKind, int, str, str]] | None,
+    allow_modify_inplace: bool = ...,
+) -> np.ndarray | pd.Series:
+    ...
+
+
 def set_nulls(
     data: np.ndarray | pd.Series,
     col: Column,
     validity: tuple[Buffer, tuple[DtypeKind, int, str, str]] | None,
     allow_modify_inplace: bool = True,
-):
+) -> np.ndarray | pd.Series:
     """
     Set null values for the data according to the column null kind.
 

pandas/io/parsers/python_parser.py

@@ -4,12 +4,6 @@
     abc,
     defaultdict,
 )
-from collections.abc import (
-    Hashable,
-    Iterator,
-    Mapping,
-    Sequence,
-)
 import csv
 from io import StringIO
 import re
@@ -50,15 +44,24 @@
 )
 
 if TYPE_CHECKING:
+    from collections.abc import (
+        Hashable,
+        Iterator,
+        Mapping,
+        Sequence,
+    )
+
     from pandas._typing import (
         ArrayLike,
         ReadCsvBuffer,
         Scalar,
+        T,
     )
 
     from pandas import (
         Index,
         MultiIndex,
+        Series,
     )
 
 # BOM character (byte order mark)
@@ -77,7 +80,7 @@ def __init__(self, f: ReadCsvBuffer[str] | list, **kwds) -> None:
         """
         super().__init__(kwds)
 
-        self.data: Iterator[str] | None = None
+        self.data: Iterator[list[str]] | list[list[Scalar]] = []
         self.buf: list = []
         self.pos = 0
         self.line_pos = 0
@@ -116,10 +119,11 @@ def __init__(self, f: ReadCsvBuffer[str] | list, **kwds) -> None:
 
         # Set self.data to something that can read lines.
         if isinstance(f, list):
-            # read_excel: f is a list
-            self.data = cast(Iterator[str], f)
+            # read_excel: f is a nested list, can contain non-str
+            self.data = f
         else:
             assert hasattr(f, "readline")
+            # yields list of str
             self.data = self._make_reader(f)
 
         # Get columns in two steps: infer from data, then
@@ -179,7 +183,7 @@ def num(self) -> re.Pattern:
             )
         return re.compile(regex)
 
-    def _make_reader(self, f: IO[str] | ReadCsvBuffer[str]):
+    def _make_reader(self, f: IO[str] | ReadCsvBuffer[str]) -> Iterator[list[str]]:
         sep = self.delimiter
 
         if sep is None or len(sep) == 1:
@@ -246,7 +250,9 @@ def _read():
     def read(
         self, rows: int | None = None
     ) -> tuple[
-        Index | None, Sequence[Hashable] | MultiIndex, Mapping[Hashable, ArrayLike]
+        Index | None,
+        Sequence[Hashable] | MultiIndex,
+        Mapping[Hashable, ArrayLike | Series],
     ]:
         try:
             content = self._get_lines(rows)
@@ -326,7 +332,9 @@ def _exclude_implicit_index(
     def get_chunk(
         self, size: int | None = None
     ) -> tuple[
-        Index | None, Sequence[Hashable] | MultiIndex, Mapping[Hashable, ArrayLike]
+        Index | None,
+        Sequence[Hashable] | MultiIndex,
+        Mapping[Hashable, ArrayLike | Series],
     ]:
         if size is None:
             # error: "PythonParser" has no attribute "chunksize"
@@ -689,7 +697,7 @@ def _check_for_bom(self, first_row: list[Scalar]) -> list[Scalar]:
         new_row_list: list[Scalar] = [new_row]
         return new_row_list + first_row[1:]
 
-    def _is_line_empty(self, line: list[Scalar]) -> bool:
+    def _is_line_empty(self, line: Sequence[Scalar]) -> bool:
         """
         Check if a line is empty or not.
 
@@ -730,8 +738,6 @@ def _next_line(self) -> list[Scalar]:
         else:
             while self.skipfunc(self.pos):
                 self.pos += 1
-                # assert for mypy, data is Iterator[str] or None, would error in next
-                assert self.data is not None
                 next(self.data)
 
             while True:
@@ -800,12 +806,10 @@ def _next_iter_line(self, row_num: int) -> list[Scalar] | None:
             The row number of the line being parsed.
         """
         try:
-            # assert for mypy, data is Iterator[str] or None, would error in next
-            assert self.data is not None
+            assert not isinstance(self.data, list)
             line = next(self.data)
-            # for mypy
-            assert isinstance(line, list)
-            return line
+            # lie about list[str] vs list[Scalar] to minimize ignores
+            return line  # type: ignore[return-value]
         except csv.Error as e:
             if self.on_bad_lines in (
                 self.BadLineHandleMethod.ERROR,
@@ -855,7 +859,7 @@ def _check_comments(self, lines: list[list[Scalar]]) -> list[list[Scalar]]:
             ret.append(rl)
         return ret
 
-    def _remove_empty_lines(self, lines: list[list[Scalar]]) -> list[list[Scalar]]:
+    def _remove_empty_lines(self, lines: list[list[T]]) -> list[list[T]]:
         """
         Iterate through the lines and remove any that are
         either empty or contain only one whitespace value
@@ -1121,9 +1125,6 @@ def _get_lines(self, rows: int | None = None) -> list[list[Scalar]]:
                         row_ct = 0
                         offset = self.pos if self.pos is not None else 0
                         while row_ct < rows:
-                            # assert for mypy, data is Iterator[str] or None, would
-                            # error in next
-                            assert self.data is not None
                             new_row = next(self.data)
                             if not self.skipfunc(offset + row_index):
                                 row_ct += 1
@@ -1338,7 +1339,7 @@ def _make_reader(self, f: IO[str] | ReadCsvBuffer[str]) -> FixedWidthReader:
             self.infer_nrows,
         )
 
-    def _remove_empty_lines(self, lines: list[list[Scalar]]) -> list[list[Scalar]]:
+    def _remove_empty_lines(self, lines: list[list[T]]) -> list[list[T]]:
         """
         Returns the list of lines without the empty ones. With fixed-width
         fields, empty lines become arrays of empty strings.

pandas/plotting/_matplotlib/boxplot.py

@@ -371,8 +371,8 @@ def _get_colors():
         #  num_colors=3 is required as method maybe_color_bp takes the colors
         #  in positions 0 and 2.
         #  if colors not provided, use same defaults as DataFrame.plot.box
-        result = get_standard_colors(num_colors=3)
-        result = np.take(result, [0, 0, 2])
+        result_list = get_standard_colors(num_colors=3)
+        result = np.take(result_list, [0, 0, 2])
         result = np.append(result, "k")
 
         colors = kwds.pop("color", None)

pandas/plotting/_matplotlib/hist.py

@@ -457,10 +457,8 @@ def hist_series(
         ax.grid(grid)
         axes = np.array([ax])
 
-        # error: Argument 1 to "set_ticks_props" has incompatible type "ndarray[Any,
-        # dtype[Any]]"; expected "Axes | Sequence[Axes]"
         set_ticks_props(
-            axes,  # type: ignore[arg-type]
+            axes,
             xlabelsize=xlabelsize,
             xrot=xrot,
             ylabelsize=ylabelsize,

pandas/plotting/_matplotlib/style.py

@@ -3,11 +3,13 @@
 from collections.abc import (
     Collection,
     Iterator,
+    Sequence,
 )
 import itertools
 from typing import (
     TYPE_CHECKING,
     cast,
+    overload,
 )
 import warnings
 
@@ -26,12 +28,46 @@
     from matplotlib.colors import Colormap
 
 
+@overload
+def get_standard_colors(
+    num_colors: int,
+    colormap: Colormap | None = ...,
+    color_type: str = ...,
+    *,
+    color: dict[str, Color],
+) -> dict[str, Color]:
+    ...
+
+
+@overload
+def get_standard_colors(
+    num_colors: int,
+    colormap: Colormap | None = ...,
+    color_type: str = ...,
+    *,
+    color: Color | Sequence[Color] | None = ...,
+) -> list[Color]:
+    ...
+
+
+@overload
+def get_standard_colors(
+    num_colors: int,
+    colormap: Colormap | None = ...,
+    color_type: str = ...,
+    *,
+    color: dict[str, Color] | Color | Sequence[Color] | None = ...,
+) -> dict[str, Color] | list[Color]:
+    ...
+
+
 def get_standard_colors(
     num_colors: int,
     colormap: Colormap | None = None,
     color_type: str = "default",
-    color: dict[str, Color] | Color | Collection[Color] | None = None,
-):
+    *,
+    color: dict[str, Color] | Color | Sequence[Color] | None = None,
+) -> dict[str, Color] | list[Color]:
     """
     Get standard colors based on `colormap`, `color_type` or `color` inputs.
 

pandas/plotting/_matplotlib/tools.py

@@ -19,10 +19,7 @@
 )
 
 if TYPE_CHECKING:
-    from collections.abc import (
-        Iterable,
-        Sequence,
-    )
+    from collections.abc import Iterable
 
     from matplotlib.axes import Axes
     from matplotlib.axis import Axis
@@ -442,7 +439,7 @@ def handle_shared_axes(
                     _remove_labels_from_axis(ax.yaxis)
 
 
-def flatten_axes(axes: Axes | Sequence[Axes]) -> np.ndarray:
+def flatten_axes(axes: Axes | Iterable[Axes]) -> np.ndarray:
     if not is_list_like(axes):
         return np.array([axes])
     elif isinstance(axes, (np.ndarray, ABCIndex)):
@@ -451,7 +448,7 @@ def flatten_axes(axes: Axes | Sequence[Axes]) -> np.ndarray:
 
 
 def set_ticks_props(
-    axes: Axes | Sequence[Axes],
+    axes: Axes | Iterable[Axes],
     xlabelsize: int | None = None,
     xrot=None,
     ylabelsize: int | None = None,

pyright_reportGeneralTypeIssues.json

@@ -99,11 +99,11 @@
         "pandas/io/parsers/base_parser.py",
         "pandas/io/parsers/c_parser_wrapper.py",
         "pandas/io/pytables.py",
-        "pandas/io/sas/sas_xport.py",
         "pandas/io/sql.py",
         "pandas/io/stata.py",
         "pandas/plotting/_matplotlib/boxplot.py",
         "pandas/plotting/_matplotlib/core.py",
+        "pandas/plotting/_matplotlib/misc.py",
         "pandas/plotting/_matplotlib/timeseries.py",
         "pandas/plotting/_matplotlib/tools.py",
         "pandas/tseries/frequencies.py",