ProvenanceQuantumGraphReader

class lsst.pipe.base.quantum_graph.ProvenanceQuantumGraphReader(header: HeaderModel, pipeline_graph: PipelineGraph, zf: zipfile.ZipFile, decompressor: Decompressor, address_reader: AddressReader, page_size: int)

Bases: BaseQuantumGraphReader

A helper class for reading provenance quantum graphs.

Notes

The open context manager should be used to construct new instances. Instances cannot be used after the context manager exits, except to access the graph attribute`.

The various read_* methods in this class update the graph attribute in place and return self.

Methods Summary

fetch_logs(nodes)	Fetch log datasets.
fetch_metadata(nodes)	Fetch metadata datasets.
fetch_packages()	Fetch package version information.
open(uri, *[, page_size, import_mode])	Construct a reader from a URI.
read_datasets([datasets])	Read information about the given datasets.
read_full_graph()	Read all bipartite edges and all quantum and dataset node attributes, fully populating the graph attribute.
read_init_quanta()	Read the thin graph, with all edge information and categorization of quanta by task label.
read_quanta([quanta])	Read information about the given quanta.

Methods Documentation

fetch_logs(nodes: Iterable[uuid.UUID | DatasetIndex | QuantumIndex]) → dict[uuid.UUID | DatasetIndex | QuantumIndex, ButlerLogRecords]

Fetch log datasets.

Parameters:

nodesIterable [ uuid.UUID ]

UUIDs of the log datasets themselves or of the quanta they correspond to.

Returns:

logsdict [ uuid.UUID, ButlerLogRecords]

Logs for the given IDs.

fetch_metadata(nodes: Iterable[uuid.UUID | DatasetIndex | QuantumIndex]) → dict[uuid.UUID | DatasetIndex | QuantumIndex, TaskMetadata]

Fetch metadata datasets.

Parameters:

nodesIterable [ uuid.UUID ]

UUIDs of the metadata datasets themselves or of the quanta they correspond to.

Returns:

metadatadict [ uuid.UUID, TaskMetadata]

Metadata for the given IDs.

fetch_packages() → Packages

Fetch package version information.

classmethod open(uri: str | ParseResult | ResourcePath | Path, *, page_size: int | None = None, import_mode: TaskImportMode = TaskImportMode.DO_NOT_IMPORT) → Iterator[ProvenanceQuantumGraphReader]

Construct a reader from a URI.

Parameters:

uriconvertible to lsst.resources.ResourcePath

URI to open. Should have a .qg extension.

page_sizeint, optional

Approximate number of bytes to read at once from address files and multi-block files. Note that this does not set a page size for all reads, but it does affect the smallest, most numerous reads. Can also be set via the LSST_QG_PAGE_SIZE environment variable.

import_modepipeline_graph.TaskImportMode, optional

How to handle importing the task classes referenced in the pipeline graph.

Returns:

readercontextlib.AbstractContextManager [ ProvenanceQuantumGraphReader ]

A context manager that returns the reader when entered.

read_datasets(datasets: Iterable[UUID | int] | None = None) → Self

Read information about the given datasets.

Parameters:

datasetsIterable [uuid.UUID or int], optional

Iterable of dataset IDs or indices to load. If not provided, all datasets will be loaded. The UUIDs and indices of quanta will be ignored.

read_full_graph() → Self

Read all bipartite edges and all quantum and dataset node attributes, fully populating the graph attribute.

Returns:

selfProvenanceQuantumGraphReader

The reader (to permit method-chaining).

Notes

This does not read logs, metadata, or packages ; those must always be fetched explicitly.

read_init_quanta() → Self

Read the thin graph, with all edge information and categorization of quanta by task label.

Returns:

selfProvenanceQuantumGraphReader

The reader (to permit method-chaining).

read_quanta(quanta: Iterable[UUID | int] | None = None) → Self

Read information about the given quanta.

Parameters:

quantaIterable [uuid.UUID or int], optional

Iterable of quantum IDs or indices to load. If not provided, all quanta will be loaded. The UUIDs and indices of datasets and special init quanta will be ignored.