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array

Provide internal nodes for the Arrow-backed array runtime plus the higher- level ndarray abstraction layered on the canonical buffer/view substrate.

Classes:

ArrayInt32ArrayLength 

ArrayInt32ArrayLength(values: list[AST])

Bases: DataType

Build an int32 array using the IRx builtin array runtime, then return its length. attributes: values: type: list[astx.AST] type_: type: astx.Int32

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, values: list[astx.AST]) -> None:
    """
    title: Initialize ArrayInt32ArrayLength.
    parameters:
      values:
        type: list[astx.AST]
    """
    super().__init__()
    self.values = values
    self.type_ = astx.Int32()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the array helper.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = cast(
        astx.base.ReprStruct,
        [item.get_struct(simplified) for item in self.values],
    )
    return self._prepare_struct(
        "ArrayInt32ArrayLength",
        value,
        simplified,
    )

NDArrayByteOffset 

NDArrayByteOffset(base: AST, indices: Sequence[AST])

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(
    self,
    base: astx.AST,
    indices: Sequence[astx.AST],
) -> None:
    """
    title: Initialize one NDArray byte-offset query.
    parameters:
      base:
        type: astx.AST
      indices:
        type: Sequence[astx.AST]
    """
    super().__init__()
    if not indices:
        raise ValueError("ndarray indexing requires at least one index")
    self.base = base
    self.indices = list(indices)
    self.type_ = astx.Int64()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the byte-offset query.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "indices": [
            index.get_struct(simplified) for index in self.indices
        ],
    }
    return self._prepare_struct(
        "NDArrayByteOffset",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayElementCount 

NDArrayElementCount(base: AST)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST) -> None:
    """
    title: Initialize one NDArray element-count query.
    parameters:
      base:
        type: astx.AST
    """
    super().__init__()
    self.base = base
    self.type_ = astx.Int64()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the element-count query.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    return self._prepare_struct(
        "NDArrayElementCount",
        self.base.get_struct(simplified),
        simplified,
    )

NDArrayIndex 

NDArrayIndex(base: AST, indices: Sequence[AST])

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(
    self,
    base: astx.AST,
    indices: Sequence[astx.AST],
) -> None:
    """
    title: Initialize one NDArray indexed read.
    parameters:
      base:
        type: astx.AST
      indices:
        type: Sequence[astx.AST]
    """
    super().__init__()
    if not indices:
        raise ValueError("ndarray indexing requires at least one index")
    self.base = base
    self.indices = list(indices)
    self.type_ = AnyType()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the indexed read.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "indices": [
            index.get_struct(simplified) for index in self.indices
        ],
    }
    return self._prepare_struct(
        "NDArrayIndex",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayLiteral 

NDArrayLiteral(
    values: Sequence[AST],
    *,
    element_type: DataType,
    shape: Sequence[int],
    strides: Sequence[int] | None = None,
    offset_bytes: int = 0,
)

Bases: DataType

Build one flat Arrow array from scalar values, then attach ndarray shape and stride metadata over the resulting storage. attributes: values: type: list[astx.AST] element_type: type: astx.DataType shape: type: tuple[int, Ellipsis] strides: type: tuple[int, Ellipsis] | None offset_bytes: type: int type_: type: NDArrayType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(
    self,
    values: Sequence[astx.AST],
    *,
    element_type: astx.DataType,
    shape: Sequence[int],
    strides: Sequence[int] | None = None,
    offset_bytes: int = 0,
) -> None:
    """
    title: Initialize one NDArray literal.
    parameters:
      values:
        type: Sequence[astx.AST]
      element_type:
        type: astx.DataType
      shape:
        type: Sequence[int]
      strides:
        type: Sequence[int] | None
      offset_bytes:
        type: int
    """
    super().__init__()
    self.values = list(values)
    self.element_type = element_type
    self.shape = tuple(shape)
    self.strides = None if strides is None else tuple(strides)
    self.offset_bytes = offset_bytes
    self.type_ = NDArrayType(element_type)

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the NDArray literal.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "values": [item.get_struct(simplified) for item in self.values],
        "element_type": self.element_type.get_struct(simplified),
        "shape": list(self.shape),
        "strides": (None if self.strides is None else list(self.strides)),
        "offset_bytes": self.offset_bytes,
    }
    return self._prepare_struct(
        "NDArrayLiteral",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayNDim 

NDArrayNDim(base: AST)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST) -> None:
    """
    title: Initialize one NDArray rank query.
    parameters:
      base:
        type: astx.AST
    """
    super().__init__()
    self.base = base
    self.type_ = astx.Int32()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the rank query.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    return self._prepare_struct(
        "NDArrayNDim",
        self.base.get_struct(simplified),
        simplified,
    )

NDArrayRelease 

NDArrayRelease(base: AST)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST) -> None:
    """
    title: Initialize one NDArray release helper.
    parameters:
      base:
        type: astx.AST
    """
    super().__init__()
    self.base = base
    self.type_ = astx.Int32()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the release helper.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    return self._prepare_struct(
        "NDArrayRelease",
        self.base.get_struct(simplified),
        simplified,
    )

NDArrayRetain 

NDArrayRetain(base: AST)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST) -> None:
    """
    title: Initialize one NDArray retain helper.
    parameters:
      base:
        type: astx.AST
    """
    super().__init__()
    self.base = base
    self.type_ = astx.Int32()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the retain helper.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    return self._prepare_struct(
        "NDArrayRetain",
        self.base.get_struct(simplified),
        simplified,
    )

NDArrayShape 

NDArrayShape(base: AST, axis: int)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST, axis: int) -> None:
    """
    title: Initialize one NDArray shape query.
    parameters:
      base:
        type: astx.AST
      axis:
        type: int
    """
    super().__init__()
    self.base = base
    self.axis = axis
    self.type_ = astx.Int64()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the shape query.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "axis": self.axis,
    }
    return self._prepare_struct(
        "NDArrayShape",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayStore 

NDArrayStore(base: AST, indices: Sequence[AST], value: AST)

Bases: DataType

Stores one scalar through ndarray shape and stride metadata. Arrow-backed ndarrays remain readonly in this phase, but the node keeps the surface aligned with future writable views. attributes: base: type: astx.AST indices: type: list[astx.AST] value: type: astx.AST type_: type: astx.Int32

Methods:

Source code in src/irx/astx/array.py 
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def __init__(
    self,
    base: astx.AST,
    indices: Sequence[astx.AST],
    value: astx.AST,
) -> None:
    """
    title: Initialize one NDArray indexed store.
    parameters:
      base:
        type: astx.AST
      indices:
        type: Sequence[astx.AST]
      value:
        type: astx.AST
    """
    super().__init__()
    if not indices:
        raise ValueError("ndarray indexing requires at least one index")
    self.base = base
    self.indices = list(indices)
    self.value = value
    self.type_ = astx.Int32()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the indexed store.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "indices": [
            index.get_struct(simplified) for index in self.indices
        ],
        "value": self.value.get_struct(simplified),
    }
    return self._prepare_struct(
        "NDArrayStore",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayStride 

NDArrayStride(base: AST, axis: int)

Bases: DataType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(self, base: astx.AST, axis: int) -> None:
    """
    title: Initialize one NDArray stride query.
    parameters:
      base:
        type: astx.AST
      axis:
        type: int
    """
    super().__init__()
    self.base = base
    self.axis = axis
    self.type_ = astx.Int64()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the stride query.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "axis": self.axis,
    }
    return self._prepare_struct(
        "NDArrayStride",
        cast(astx.base.ReprStruct, value),
        simplified,
    )

NDArrayType 

NDArrayType(element_type: DataType | None = None)

Bases: AnyType

Represent the higher-level multidimensional array abstraction while reusing the canonical buffer/view representation during lowering. attributes: element_type: type: astx.DataType | None

Source code in src/irx/astx/array.py 
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def __init__(self, element_type: astx.DataType | None = None) -> None:
    """
    title: Initialize one NDArray type.
    parameters:
      element_type:
        type: astx.DataType | None
    """
    super().__init__()
    self.element_type = element_type

NDArrayView 

NDArrayView(
    base: AST,
    *,
    shape: Sequence[int],
    strides: Sequence[int] | None = None,
    offset_bytes: int = 0,
)

Bases: DataType

Build one shallow ndarray view by reusing the base storage and replacing the logical shape, strides, and offset metadata. attributes: base: type: astx.AST shape: type: tuple[int, Ellipsis] strides: type: tuple[int, Ellipsis] | None offset_bytes: type: int type_: type: NDArrayType

Methods:

Source code in src/irx/astx/array.py 
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def __init__(
    self,
    base: astx.AST,
    *,
    shape: Sequence[int],
    strides: Sequence[int] | None = None,
    offset_bytes: int = 0,
) -> None:
    """
    title: Initialize one NDArray view.
    parameters:
      base:
        type: astx.AST
      shape:
        type: Sequence[int]
      strides:
        type: Sequence[int] | None
      offset_bytes:
        type: int
    """
    super().__init__()
    self.base = base
    self.shape = tuple(shape)
    self.strides = None if strides is None else tuple(strides)
    self.offset_bytes = offset_bytes
    self.type_ = NDArrayType()

get_struct 

get_struct(simplified: bool = False) -> ReprStruct
Source code in src/irx/astx/array.py 
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def get_struct(self, simplified: bool = False) -> astx.base.ReprStruct:
    """
    title: Return the structured representation of the NDArray view.
    parameters:
      simplified:
        type: bool
    returns:
      type: astx.base.ReprStruct
    """
    value = {
        "base": self.base.get_struct(simplified),
        "shape": list(self.shape),
        "strides": (None if self.strides is None else list(self.strides)),
        "offset_bytes": self.offset_bytes,
    }
    return self._prepare_struct(
        "NDArrayView",
        cast(astx.base.ReprStruct, value),
        simplified,
    )