QuantumGraph¶

class lsst.pipe.base.QuantumGraph(quanta: Mapping[TaskDef, Set[Quantum]], metadata: Optional[Mapping[str, Any]] = None, pruneRefs: Optional[Iterable[DatasetRef]] = None, universe: Optional[DimensionUniverse] = None)¶

Bases: object

QuantumGraph is a directed acyclic graph of QuantumNode objects

This data structure represents a concrete workflow generated from a Pipeline.

Parameters:

quantaMapping of TaskDef to sets of Quantum: This maps tasks (and their configs) to the sets of data they are to process.
metadataOptional Mapping of str to primitives: This is an optional parameter of extra data to carry with the graph. Entries in this mapping should be able to be serialized in JSON.

Raises:

ValueError: Raised if the graph is pruned such that some tasks no longer have nodes associated with them.

Attributes Summary

`allDatasetTypes`	Return all the `DatasetTypeName` objects that are contained inside the graph.
`graph`	Return a graph representing the relations between all the `QuantumNode` objects.
`graphID`	Returns the ID generated by the graph at construction time
`inputQuanta`	Make a `list` of all `QuantumNode` objects that are 'input' nodes to the graph, meaning those nodes to not depend on any other nodes in the graph.
`isConnected`	Return True if all of the nodes in the graph are connected, ignores directionality of connections.
`metadata`
`outputQuanta`	Make a `list` of all `QuantumNode` objects that are 'output' nodes to the graph, meaning those nodes have no nodes that depend them in the graph.
`taskGraph`	Return a graph representing the relations between the tasks inside the quantum graph.

Methods Summary

`buildAndPrintHeader`()	Creates a header that would be used in a save of this object and prints it out to standard out.
`checkQuantumInGraph`(quantum)	Check if specified quantum appears in the graph as part of a node.
`determineAncestorsOfQuantumNode`(node)	Return a graph of the specified node and all the ancestor nodes directly reachable by walking edges.
`determineConnectionsOfQuantumNode`(node)	Return a graph of `QuantumNode` that are direct inputs and outputs of a specified node.
`determineInputsToQuantumNode`(node)	Return a set of `QuantumNode` that are direct inputs to a specified node.
`determineOutputsOfQuantumNode`(node)	Return a set of `QuantumNode` that are direct outputs of a specified node.
`findCycle`()	Check a graph for the presense of cycles and returns the edges of any cycles found, or an empty list if there is no cycle.
`findQuantaWithDSType`(datasetTypeName)	Return all the `Quantum` that contain a specified `DatasetTypeName`.
`findTaskDefByLabel`(label)	Determine which `TaskDef` objects in this graph are associated with a `str` representing a tasks label.
`findTaskDefByName`(taskName)	Determine which `TaskDef` objects in this graph are associated with a `str` representing a task name (looks at the taskName property of `TaskDef` objects).
`findTaskWithOutput`(datasetTypeName)	Find all tasks that have the specified dataset type name as an output.
`findTasksWithInput`(datasetTypeName)	Find all tasks that have the specified dataset type name as an input.
`getNodesForTask`(taskDef)	Return all the `QuantumNodes` associated with a `TaskDef`.
`getQuantaForTask`(taskDef)	Return all the `Quantum` associated with a `TaskDef`.
`getQuantumNodeByNodeId`(nodeId)	Lookup a `QuantumNode` from an id associated with the node.
`iterTaskGraph`()	Iterate over the `taskGraph` attribute in topological order
`load`(file[, universe, nodes, graphID, ...])	Read QuantumGraph from a file that was made by `save`.
`loadUri`(uri[, universe, nodes, graphID, ...])	Read `QuantumGraph` from a URI.
`pruneGraphFromRefs`(refs)	Return a graph pruned of input `DatasetRef`s and nodes which depend on them.
`readHeader`(uri[, minimumVersion])	Read the header of a `QuantumGraph` pointed to by the uri parameter and return it as a string.
`save`(file)	Save QuantumGraph to a file.
`saveUri`(uri)	Save `QuantumGraph` to the specified URI.
`subset`(nodes)	Create a new graph object that contains the subset of the nodes specified as input.
`subsetToConnected`()	Generate a list of subgraphs where each is connected.
`tasksWithDSType`(datasetTypeName)	Find all tasks that are associated with the specified dataset type name.
`writeDotGraph`(output)	Write out the graph as a dot graph.

Attributes Documentation

allDatasetTypes¶

Return all the DatasetTypeName objects that are contained inside the graph.

Returns:

tuple of DatasetTypeName: All the data set type names that are present in the graph

graph¶

Return a graph representing the relations between all the QuantumNode objects. Largely it should be preferred to iterate over, and use methods of this class, but sometimes direct access to the networkx object may be helpful

Returns:

graphnetworkx.Digraph: Internal datastructure that holds relations of QuantumNode objects

graphID¶: Returns the ID generated by the graph at construction time

inputQuanta¶

Make a list of all QuantumNode objects that are ‘input’ nodes to the graph, meaning those nodes to not depend on any other nodes in the graph.

Returns:

inputNodesiterable of QuantumNode: A list of nodes that are inputs to the graph

isConnected¶: Return True if all of the nodes in the graph are connected, ignores directionality of connections.

metadata¶

outputQuanta¶

Make a list of all QuantumNode objects that are ‘output’ nodes to the graph, meaning those nodes have no nodes that depend them in the graph.

Returns:

outputNodesiterable of QuantumNode: A list of nodes that are outputs of the graph

taskGraph¶

Return a graph representing the relations between the tasks inside the quantum graph.

Returns:

taskGraphnetworkx.Digraph: Internal datastructure that holds relations of TaskDef objects

Methods Documentation

buildAndPrintHeader() → None¶: Creates a header that would be used in a save of this object and prints it out to standard out.

checkQuantumInGraph(quantum: Quantum) → bool¶

Check if specified quantum appears in the graph as part of a node.

Parameters:

quantumQuantum: The quantum to search for

Returns:

bool: The result of searching for the quantum

determineAncestorsOfQuantumNode(node: QuantumNode) → _T¶

Return a graph of the specified node and all the ancestor nodes directly reachable by walking edges.

Parameters:

nodeQuantumNode: The node for which all ansestors are to be determined

Returns:

graph of QuantumNode: Graph of node and all of its ansestors

determineConnectionsOfQuantumNode(node: QuantumNode) → _T¶

Return a graph of QuantumNode that are direct inputs and outputs of a specified node.

Parameters:

nodeQuantumNode: The node of the graph for which connected nodes are to be determined.

Returns:

graphgraph of QuantumNode: All the nodes that are directly connected to specified node

determineInputsToQuantumNode(node: QuantumNode) → Set[QuantumNode]¶

Return a set of QuantumNode that are direct inputs to a specified node.

Parameters:

nodeQuantumNode: The node of the graph for which inputs are to be determined

Returns:

set of QuantumNode: All the nodes that are direct inputs to specified node

determineOutputsOfQuantumNode(node: QuantumNode) → Set[QuantumNode]¶

Return a set of QuantumNode that are direct outputs of a specified node.

Parameters:

nodeQuantumNode: The node of the graph for which outputs are to be determined

Returns:

set of QuantumNode: All the nodes that are direct outputs to specified node

findCycle() → List[Tuple[QuantumNode, QuantumNode]]¶

Check a graph for the presense of cycles and returns the edges of any cycles found, or an empty list if there is no cycle.

Returns:

resultlist of tuple of QuantumNode, QuantumNode: A list of any graph edges that form a cycle, or an empty list if there is no cycle. Empty list to so support if graph.find_cycle() syntax as an empty list is falsy.

findQuantaWithDSType(datasetTypeName: DatasetTypeName) → Set[Quantum]¶

Return all the Quantum that contain a specified DatasetTypeName.

Parameters:

datasetTypeNamestr: The name of the dataset type to search for as a string, can also accept a DatasetTypeName which is a NewType of str for type safety in static type checking.

Returns:

resultset of QuantumNode objects: A set of QuantumNode`s that contain specified `DatasetTypeName

Raises:

KeyError: Raised if the DatasetTypeName is not part of the QuantumGraph

findTaskDefByLabel(label: str) → Optional[TaskDef]¶

Determine which TaskDef objects in this graph are associated with a str representing a tasks label.

Parameters:

taskNamestr: Name of a task to search for

Returns:

resultTaskDef: TaskDef objects that has the specified label.

findTaskDefByName(taskName: str) → List[TaskDef]¶

Determine which TaskDef objects in this graph are associated with a str representing a task name (looks at the taskName property of TaskDef objects).

Returns a list of TaskDef objects as a PipelineTask may appear multiple times in a graph with different labels.

Parameters:

taskNamestr: Name of a task to search for

Returns:

resultlist of TaskDef: List of the TaskDef objects that have the name specified. Multiple values are returned in the case that a task is used multiple times with different labels.

findTaskWithOutput(datasetTypeName: DatasetTypeName) → Optional[TaskDef]¶

Find all tasks that have the specified dataset type name as an output.

Parameters:

datasetTypeNamestr: A string representing the name of a dataset type to be queried, can also accept a DatasetTypeName which is a NewType of str for type safety in static type checking.

Returns:

TaskDef or None: TaskDef that outputs DatasetTypeName as an output or None if none of the tasks produce this DatasetTypeName.

Raises:

KeyError: Raised if the DatasetTypeName is not part of the QuantumGraph

findTasksWithInput(datasetTypeName: DatasetTypeName) → Iterable[TaskDef]¶

Find all tasks that have the specified dataset type name as an input.

Parameters:

datasetTypeNamestr: A string representing the name of a dataset type to be queried, can also accept a DatasetTypeName which is a NewType of str for type safety in static type checking.

Returns:

tasksiterable of TaskDef: TaskDef objects that have the specified DatasetTypeName as an input, list will be empty if no tasks use specified DatasetTypeName as an input.

Raises:

KeyError: Raised if the DatasetTypeName is not part of the QuantumGraph

getNodesForTask(taskDef: TaskDef) → FrozenSet[QuantumNode]¶

Return all the QuantumNodes associated with a TaskDef.

Parameters:

taskDefTaskDef: The TaskDef for which Quantum are to be queried

Returns:

frozenset of QuantumNodes: The frozenset of QuantumNodes that is associated with the specified TaskDef.

getQuantaForTask(taskDef: TaskDef) → FrozenSet[Quantum]¶

Return all the Quantum associated with a TaskDef.

Parameters:

taskDefTaskDef: The TaskDef for which Quantum are to be queried

Returns:

frozenset of Quantum: The set of Quantum that is associated with the specified TaskDef.

getQuantumNodeByNodeId(nodeId: UUID) → QuantumNode¶

Lookup a QuantumNode from an id associated with the node.

Parameters:

nodeIdNodeId: The number associated with a node

Returns:

nodeQuantumNode: The node corresponding with input number

Raises:

KeyError: Raised if the requested nodeId is not in the graph.

iterTaskGraph() → Generator[TaskDef, None, None]¶

Iterate over the taskGraph attribute in topological order

Yields:

taskDefTaskDef: TaskDef objects in topological order

classmethod load(file: BinaryIO, universe: Optional[DimensionUniverse] = None, nodes: Optional[Iterable[UUID]] = None, graphID: Optional[BuildId] = None, minimumVersion: int = 3) → QuantumGraph¶

Read QuantumGraph from a file that was made by save.

Parameters:

fileio.IO of bytes: File with pickle data open in binary mode.
universe: `~lsst.daf.butler.DimensionUniverse`, optional: DimensionUniverse instance, not used by the method itself but needed to ensure that registry data structures are initialized. If None it is loaded from the QuantumGraph saved structure. If supplied, the DimensionUniverse from the loaded QuantumGraph will be validated against the supplied argument for compatibility.
nodes: iterable of `int` or None: Numbers that correspond to nodes in the graph. If specified, only these nodes will be loaded. Defaults to None, in which case all nodes will be loaded.
graphIDstr or None: If specified this ID is verified against the loaded graph prior to loading any Nodes. This defaults to None in which case no validation is done.
minimumVersionint: Minimum version of a save file to load. Set to -1 to load all versions. Older versions may need to be loaded, and re-saved to upgrade them to the latest format before they can be used in production.

Returns:

graphQuantumGraph: Resulting QuantumGraph instance.

Raises:

TypeError: Raised if pickle contains instance of a type other than QuantumGraph.
ValueError: Raised if one or more of the nodes requested is not in the QuantumGraph or if graphID parameter does not match the graph being loaded or if the supplied uri does not point at a valid QuantumGraph save file.

Notes

Reading Quanta from pickle requires existence of singleton DimensionUniverse which is usually instantiated during Registry initialization. To make sure that DimensionUniverse exists this method accepts dummy DimensionUniverse argument.

classmethod loadUri(uri: Union[str, ParseResult, ResourcePath, Path], universe: Optional[DimensionUniverse] = None, nodes: Optional[Iterable[UUID]] = None, graphID: Optional[BuildId] = None, minimumVersion: int = 3) → QuantumGraph¶

Read QuantumGraph from a URI.

Parameters:

uriconvertible to ResourcePath: URI from where to load the graph.
universe: `~lsst.daf.butler.DimensionUniverse` optional: DimensionUniverse instance, not used by the method itself but needed to ensure that registry data structures are initialized. If None it is loaded from the QuantumGraph saved structure. If supplied, the DimensionUniverse from the loaded QuantumGraph will be validated against the supplied argument for compatibility.
nodes: iterable of `int` or None: Numbers that correspond to nodes in the graph. If specified, only these nodes will be loaded. Defaults to None, in which case all nodes will be loaded.
graphIDstr or None: If specified this ID is verified against the loaded graph prior to loading any Nodes. This defaults to None in which case no validation is done.
minimumVersionint: Minimum version of a save file to load. Set to -1 to load all versions. Older versions may need to be loaded, and re-saved to upgrade them to the latest format before they can be used in production.

Returns:

graphQuantumGraph: Resulting QuantumGraph instance.

Raises:

TypeError: Raised if pickle contains instance of a type other than QuantumGraph.
ValueError: Raised if one or more of the nodes requested is not in the QuantumGraph or if graphID parameter does not match the graph being loaded or if the supplied uri does not point at a valid QuantumGraph save file.
RuntimeError: Raise if Supplied DimensionUniverse is not compatible with the DimensionUniverse saved in the graph

Notes

Reading Quanta from pickle requires existence of singleton DimensionUniverse which is usually instantiated during Registry initialization. To make sure that DimensionUniverse exists this method accepts dummy DimensionUniverse argument.

pruneGraphFromRefs(refs: Iterable[DatasetRef]) → _T¶

Return a graph pruned of input DatasetRefs and nodes which depend on them.

Parameters:

refsIterable of DatasetRef: Refs which should be removed from resulting graph

Returns:

graphQuantumGraph: A graph that has been pruned of specified refs and the nodes that depend on them.

classmethod readHeader(uri: Union[str, ParseResult, ResourcePath, Path], minimumVersion: int = 3) → Optional[str]¶

Read the header of a QuantumGraph pointed to by the uri parameter and return it as a string.

Parameters:

uriconvertible to ResourcePath: The location of the QuantumGraph to load. If the argument is a string, it must correspond to a valid ResourcePath path.
minimumVersionint: Minimum version of a save file to load. Set to -1 to load all versions. Older versions may need to be loaded, and re-saved to upgrade them to the latest format before they can be used in production.

Returns:

headerstr or None: The header associated with the specified QuantumGraph it there is one, else None.

Raises:

ValueError: Raised if QuantuGraph was saved as a pickle. Raised if the extention of the file specified by uri is not a QuantumGraph extention.

save(file: BinaryIO) → None¶

Save QuantumGraph to a file.

Parameters:

fileio.BufferedIOBase: File to write pickle data open in binary mode.

saveUri(uri: Union[str, ParseResult, ResourcePath, Path]) → None¶

Save QuantumGraph to the specified URI.

Parameters:

uriconvertible to ResourcePath: URI to where the graph should be saved.

subset(nodes: Union[QuantumNode, Iterable[QuantumNode]]) → _T¶

Create a new graph object that contains the subset of the nodes specified as input. Node number is preserved.

Parameters:

nodesQuantumNode or iterable of QuantumNode

Returns:

graphinstance of graph type: An instance of the type from which the subset was created

subsetToConnected() → Tuple[_T, ...]¶

Generate a list of subgraphs where each is connected.

Returns:

resultlist of QuantumGraph: A list of graphs that are each connected

tasksWithDSType(datasetTypeName: DatasetTypeName) → Iterable[TaskDef]¶

Find all tasks that are associated with the specified dataset type name.

Parameters:

datasetTypeNamestr: A string representing the name of a dataset type to be queried, can also accept a DatasetTypeName which is a NewType of str for type safety in static type checking.

Returns:

resultiterable of TaskDef: TaskDef objects that are associated with the specified DatasetTypeName

Raises:

KeyError: Raised if the DatasetTypeName is not part of the QuantumGraph

writeDotGraph(output: Union[str, BufferedIOBase]) → None¶

Write out the graph as a dot graph.

Parameters:

outputstr or io.BufferedIOBase: Either a filesystem path to write to, or a file handle object

Navigation

QuantumGraph¶