RowIterable

class lsst.daf.relation.iteration.RowIterable

Bases: object

An abstract base class for iterables that use mappings for rows.

RowIterable is the payload type for the iteration engine.

Methods Summary

materialized()	Convert this iterable to one that holds its rows in a Python collection of some kind, instead of generating them lazily.
sliced(start, stop, None])	Apply a slice operation to this RowIterable.
to_mapping(unique_key)	Convert this iterable to a RowMapping, unless it already is one.
to_sequence()	Convert this iterable to a RowSequence, unless it already is one.

Methods Documentation

materialized() → lsst.daf.relation.iteration._row_iterable.MaterializedRowIterable

Convert this iterable to one that holds its rows in a Python collection of some kind, instead of generating them lazily.

Returns:

rows : MaterializedRowIterable

A RowIterable that isn’t lazy.

sliced(start: int, stop: int | None[int, None]) → lsst.daf.relation.iteration._row_iterable.RowIterable

Apply a slice operation to this RowIterable.

Parameters:

start : int

Start index.

stop : int or None

Stop index (one-past-the-end), or None to include up through the last row.

Returns:

rows : RowIterable

Iterable representing the slice. May or may not be lazy.

to_mapping(unique_key: collections.abc.Sequence[lsst.daf.relation._columns._tag.ColumnTag]) → lsst.daf.relation.iteration._row_iterable.RowMapping

Convert this iterable to a RowMapping, unless it already is one.

Parameters:

unique_key : Sequence [ ColumnTag ]

Sequence of columns to extract into a tuple to use as keys in the mapping, guaranteeing uniqueness over these columns.

Returns:

rows : RowMapping

A RowIterable backed by a mapping.

to_sequence() → lsst.daf.relation.iteration._row_iterable.RowSequence

Convert this iterable to a RowSequence, unless it already is one.

Returns:

rows : RowSequence

A RowIterable backed by a sequence.