done

lib/python3.11/site-packages/pandas-stubs/core/interchange/dataframe_protocol.pyi

@@ -0,0 +1,120 @@
+import abc
+from abc import (
+    ABC,
+    abstractmethod,
+)
+from collections.abc import (
+    Iterable,
+    Sequence,
+)
+import enum
+from typing import (
+    Any,
+    TypedDict,
+    cast,
+)
+
+class DlpackDeviceType(enum.IntEnum):
+    CPU = cast(int, ...)
+    CUDA = cast(int, ...)
+    CPU_PINNED = cast(int, ...)
+    OPENCL = cast(int, ...)
+    VULKAN = cast(int, ...)
+    METAL = cast(int, ...)
+    VPI = cast(int, ...)
+    ROCM = cast(int, ...)
+
+class DtypeKind(enum.IntEnum):
+    INT = cast(int, ...)
+    UINT = cast(int, ...)
+    FLOAT = cast(int, ...)
+    BOOL = cast(int, ...)
+    STRING = cast(int, ...)
+    DATETIME = cast(int, ...)
+    CATEGORICAL = cast(int, ...)
+
+class ColumnNullType(enum.IntEnum):
+    NON_NULLABLE = cast(int, ...)
+    USE_NAN = cast(int, ...)
+    USE_SENTINEL = cast(int, ...)
+    USE_BITMASK = cast(int, ...)
+    USE_BYTEMASK = cast(int, ...)
+
+class ColumnBuffers(TypedDict):
+    data: tuple[Buffer, Any]
+    validity: tuple[Buffer, Any] | None
+    offsets: tuple[Buffer, Any] | None
+
+class CategoricalDescription(TypedDict):
+    is_ordered: bool
+    is_dictionary: bool
+    categories: Column | None
+
+class Buffer(ABC, metaclass=abc.ABCMeta):
+    @property
+    @abstractmethod
+    def bufsize(self) -> int: ...
+    @property
+    @abstractmethod
+    def ptr(self) -> int: ...
+    @abstractmethod
+    def __dlpack__(self): ...
+    @abstractmethod
+    def __dlpack_device__(self) -> tuple[DlpackDeviceType, int | None]: ...
+
+class Column(ABC, metaclass=abc.ABCMeta):
+    @property
+    @abstractmethod
+    def size(self) -> int: ...
+    @property
+    @abstractmethod
+    def offset(self) -> int: ...
+    @property
+    @abstractmethod
+    def dtype(self) -> tuple[DtypeKind, int, str, str]: ...
+    @property
+    @abstractmethod
+    def describe_categorical(self) -> CategoricalDescription: ...
+    @property
+    @abstractmethod
+    def describe_null(self) -> tuple[ColumnNullType, Any]: ...
+    @property
+    @abstractmethod
+    def null_count(self) -> int | None: ...
+    @property
+    @abstractmethod
+    def metadata(self) -> dict[str, Any]: ...
+    @abstractmethod
+    def num_chunks(self) -> int: ...
+    @abstractmethod
+    def get_chunks(self, n_chunks: int | None = ...) -> Iterable[Column]: ...
+    @abstractmethod
+    def get_buffers(self) -> ColumnBuffers: ...
+
+class DataFrame(ABC, metaclass=abc.ABCMeta):
+    version: int
+    @abstractmethod
+    def __dataframe__(self, nan_as_null: bool = ..., allow_copy: bool = ...): ...
+    @property
+    @abstractmethod
+    def metadata(self) -> dict[str, Any]: ...
+    @abstractmethod
+    def num_columns(self) -> int: ...
+    @abstractmethod
+    def num_rows(self) -> int | None: ...
+    @abstractmethod
+    def num_chunks(self) -> int: ...
+    @abstractmethod
+    def column_names(self) -> Iterable[str]: ...
+    @abstractmethod
+    def get_column(self, i: int) -> Column: ...
+    @abstractmethod
+    def get_column_by_name(self, name: str) -> Column: ...
+    @abstractmethod
+    def get_columns(self) -> Iterable[Column]: ...
+    @abstractmethod
+    def select_columns(self, indices: Sequence[int]) -> DataFrame: ...
+    @abstractmethod
+    def select_columns_by_name(self, names: Sequence[str]) -> DataFrame: ...
+    @abstractmethod
+    def get_chunks(self, n_chunks: int | None = ...) -> Iterable[DataFrame]: ...

lib/python3.11/site-packages/pandas-stubs/core/interchange/from_dataframe.pyi

@@ -0,0 +1,3 @@
+import pandas as pd
+
+def from_dataframe(df, allow_copy: bool = True) -> pd.DataFrame: ...