78 lines
2.2 KiB
Python
78 lines
2.2 KiB
Python
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from __future__ import annotations
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import numpy as np
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from pandas.core.interchange.dataframe_protocol import (
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Buffer,
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DlpackDeviceType,
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)
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from pandas.util.version import Version
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_NUMPY_HAS_DLPACK = Version(np.__version__) >= Version("1.22.0")
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class PandasBuffer(Buffer):
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"""
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Data in the buffer is guaranteed to be contiguous in memory.
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"""
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def __init__(self, x: np.ndarray, allow_copy: bool = True) -> None:
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"""
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Handle only regular columns (= numpy arrays) for now.
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"""
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if not x.strides == (x.dtype.itemsize,):
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# The protocol does not support strided buffers, so a copy is
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# necessary. If that's not allowed, we need to raise an exception.
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if allow_copy:
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x = x.copy()
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else:
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raise RuntimeError(
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"Exports cannot be zero-copy in the case "
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"of a non-contiguous buffer"
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)
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# Store the numpy array in which the data resides as a private
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# attribute, so we can use it to retrieve the public attributes
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self._x = x
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@property
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def bufsize(self) -> int:
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"""
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Buffer size in bytes.
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"""
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return self._x.size * self._x.dtype.itemsize
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@property
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def ptr(self) -> int:
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"""
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Pointer to start of the buffer as an integer.
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"""
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return self._x.__array_interface__["data"][0]
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def __dlpack__(self):
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"""
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Represent this structure as DLPack interface.
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"""
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if _NUMPY_HAS_DLPACK:
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return self._x.__dlpack__()
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raise NotImplementedError("__dlpack__")
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def __dlpack_device__(self) -> tuple[DlpackDeviceType, int | None]:
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"""
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Device type and device ID for where the data in the buffer resides.
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"""
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return (DlpackDeviceType.CPU, None)
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def __repr__(self) -> str:
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return (
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"PandasBuffer("
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+ str(
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{
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"bufsize": self.bufsize,
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"ptr": self.ptr,
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"device": self.__dlpack_device__()[0].name,
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}
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)
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+ ")"
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)
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