RowMapping¶
- class lsst.daf.relation.iteration.RowMapping(unique_key: Sequence[ColumnTag], rows: Mapping[tuple, Mapping[ColumnTag, Any]])¶
Bases:
MaterializedRowIterable
A
RowIterable
backed by aMapping
.- 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.- rows
collections.abc.Mapping
Nested mapping with
tuple
keys and row values, where each row is (as usual forRowIterable
types) itself aMapping
withColumnTag
keys.
- unique_key
Methods Summary
Convert this iterable to one that holds its rows in a Python collection of some kind, instead of generating them lazily.
sliced
(start, stop)Apply a slice operation to this
RowIterable
.to_mapping
(unique_key)Convert this iterable to a
RowMapping
, unless it already is one.Convert this iterable to a
RowSequence
, unless it already is one.Methods Documentation
- materialized() 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.
- rows
- sliced(start: int, stop: int | None) RowIterable ¶
Apply a slice operation to this
RowIterable
.- Parameters:
- Returns:
- rows
RowIterable
Iterable representing the slice. May or may not be lazy.
- rows
- to_mapping(unique_key: Sequence[ColumnTag]) RowMapping ¶
Convert this iterable to a
RowMapping
, unless it already is one.- Parameters:
- Returns:
- rows
RowMapping
A
RowIterable
backed by a mapping.
- rows
- to_sequence() RowSequence ¶
Convert this iterable to a
RowSequence
, unless it already is one.- Returns:
- rows
RowSequence
A
RowIterable
backed by a sequence.
- rows