Class _ExprSequence

dask/_expr.py:1195–1277

A sequence of expressions This is used to be able to optimize multiple collections combined, e.g. when being computed simultaneously with ``dask.compute((Expr1, Expr2))``.

class _ExprSequence(Expr):
    """A sequence of expressions

    This is used to be able to optimize multiple collections combined, e.g. when
    being computed simultaneously with ``dask.compute((Expr1, Expr2))``.
    """

    def __getitem__(self, other):
        return self.operands[other]

    def _layer(self) -> dict:
        return toolz.merge(op._layer() for op in self.operands)

    def __dask_keys__(self) -> list:
        all_keys = []
        for op in self.operands:
            all_keys.append(list(op.__dask_keys__()))
        return all_keys

    def __repr__(self):
        return "ExprSequence(" + ", ".join(map(repr, self.operands)) + ")"

    __str__ = __repr__

    def finalize_compute(self):
        return _ExprSequence(
            *(op.finalize_compute() for op in self.operands),
        )

    def __dask_annotations__(self):
        annotations_by_type = {}
        for op in self.operands:
            for k, v in op.__dask_annotations__().items():
                annotations_by_type.setdefault(k, {}).update(v)
        return annotations_by_type

    def __len__(self):
        return len(self.operands)

    def __iter__(self):
        return iter(self.operands)

    def _simplify_down(self):
        from dask.highlevelgraph import HighLevelGraph

        issue_warning = False
        hlgs = []
        if any(
            isinstance(op, (HLGExpr, HLGFinalizeCompute, dict)) for op in self.operands
        ):
            for op in self.operands:
                if isinstance(op, (HLGExpr, HLGFinalizeCompute)):
                    hlgs.append(op)
                elif isinstance(op, dict):
                    hlgs.append(
                        HLGExpr(
                            dsk=HighLevelGraph.from_collections(
                                str(id(op)), op, dependencies=()