RawIngestTask¶
-
class
lsst.obs.base.
RawIngestTask
(config: Optional[lsst.obs.base.ingest.RawIngestConfig] = None, *, butler: lsst.daf.butler.butler.Butler, **kwds: Any)¶ Bases:
lsst.pipe.base.Task
Driver Task for ingesting raw data into Gen3 Butler repositories.
This Task is intended to be runnable from the command-line, but it doesn’t meet the other requirements of CmdLineTask or PipelineTask, and wouldn’t gain much from being one. It also wouldn’t really be appropriate as a subtask of a CmdLineTask or PipelineTask; it’s a Task essentially just to leverage the logging and configurability functionality that provides.
Each instance of
RawIngestTask
writes to the same Butler. Each invocation ofRawIngestTask.run
ingests a list of files.- Parameters
- config
RawIngestConfig
Configuration for the task.
- butler
Butler
Butler instance. Ingested Datasets will be created as part of
butler.run
and associated with its Collection.- kwds
Additional keyword arguments are forwarded to the
lsst.pipe.base.Task
constructor.- Other keyword arguments are forwarded to the Task base class constructor.
- config
Methods Summary
collectDimensionRecords
(exposure)Collect the
DimensionRecord
instances that must be inserted into theRegistry
before an exposure’s raw files may be.Empty (clear) the metadata for this Task and all sub-Tasks.
expandDataIds
(data)Expand the data IDs associated with a raw exposure to include additional metadata records.
extractMetadata
(filename)Extract and process metadata from a single raw file.
Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
Return the DatasetType of the Datasets ingested by this Task.
Get metadata for all tasks.
Get the task name as a hierarchical name including parent task names.
getName
()Get the name of the task.
Get the schemas generated by this task.
Get a dictionary of all tasks as a shallow copy.
groupByExposure
(files)Group an iterable of
RawFileData
by exposure.ingestExposureDatasets
(exposure[, butler])Ingest all raw files in one exposure.
insertDimensionData
(records)Insert dimension records for one or more exposures.
makeField
(doc)Make a
lsst.pex.config.ConfigurableField
for this task.makeSubtask
(name, **keyArgs)Create a subtask as a new instance as the
name
attribute of this task.prep
(files[, pool, processes])Perform all ingest preprocessing steps that do not involve actually modifying the database.
run
(files[, pool, processes])Ingest files into a Butler data repository.
timer
(name[, logLevel])Context manager to log performance data for an arbitrary block of code.
Methods Documentation
-
collectDimensionRecords
(exposure: lsst.obs.base.ingest.RawExposureData) → lsst.obs.base.ingest.RawExposureData¶ Collect the
DimensionRecord
instances that must be inserted into theRegistry
before an exposure’s raw files may be.- Parameters
- exposure
RawExposureData
A structure containing information about the exposure to be ingested. Should be considered consumed upon return.
- exposure
- Returns
- exposure
RawExposureData
An updated version of the input structure, with
RawExposureData.records
populated.
- exposure
-
emptyMetadata
()¶ Empty (clear) the metadata for this Task and all sub-Tasks.
-
expandDataIds
(data: lsst.obs.base.ingest.RawExposureData) → lsst.obs.base.ingest.RawExposureData¶ Expand the data IDs associated with a raw exposure to include additional metadata records.
- Parameters
- exposure
RawExposureData
A structure containing information about the exposure to be ingested. Must have
RawExposureData.records
populated. Should be considered consumed upon return.
- exposure
- Returns
- exposure
RawExposureData
An updated version of the input structure, with
RawExposureData.dataId
and nestedRawFileData.dataId
attributes containingExpandedDataCoordinate
instances.
- exposure
-
extractMetadata
(filename: str) → lsst.obs.base.ingest.RawFileData¶ Extract and process metadata from a single raw file.
- Parameters
- filename
str
Path to the file.
- filename
- Returns
- data
RawFileData
A structure containing the metadata extracted from the file, as well as the original filename. All fields will be populated, but the
RawFileData.dataId
attribute will be a minimal (unexpanded)DataCoordinate
instance.
- data
-
getAllSchemaCatalogs
()¶ Get schema catalogs for all tasks in the hierarchy, combining the results into a single dict.
- Returns
- schemacatalogs
dict
Keys are butler dataset type, values are a empty catalog (an instance of the appropriate lsst.afw.table Catalog type) for all tasks in the hierarchy, from the top-level task down through all subtasks.
- schemacatalogs
Notes
This method may be called on any task in the hierarchy; it will return the same answer, regardless.
The default implementation should always suffice. If your subtask uses schemas the override
Task.getSchemaCatalogs
, not this method.
-
getDatasetType
()¶ Return the DatasetType of the Datasets ingested by this Task.
-
getFullMetadata
()¶ Get metadata for all tasks.
- Returns
- metadata
lsst.daf.base.PropertySet
The
PropertySet
keys are the full task name. Values are metadata for the top-level task and all subtasks, sub-subtasks, etc..
- metadata
Notes
The returned metadata includes timing information (if
@timer.timeMethod
is used) and any metadata set by the task. The name of each item consists of the full task name with.
replaced by:
, followed by.
and the name of the item, e.g.:topLevelTaskName:subtaskName:subsubtaskName.itemName
using
:
in the full task name disambiguates the rare situation that a task has a subtask and a metadata item with the same name.
-
getFullName
()¶ Get the task name as a hierarchical name including parent task names.
- Returns
- fullName
str
The full name consists of the name of the parent task and each subtask separated by periods. For example:
The full name of top-level task “top” is simply “top”.
The full name of subtask “sub” of top-level task “top” is “top.sub”.
The full name of subtask “sub2” of subtask “sub” of top-level task “top” is “top.sub.sub2”.
- fullName
-
getSchemaCatalogs
()¶ Get the schemas generated by this task.
- Returns
- schemaCatalogs
dict
Keys are butler dataset type, values are an empty catalog (an instance of the appropriate
lsst.afw.table
Catalog type) for this task.
- schemaCatalogs
See also
Task.getAllSchemaCatalogs
Notes
Warning
Subclasses that use schemas must override this method. The default implemenation returns an empty dict.
This method may be called at any time after the Task is constructed, which means that all task schemas should be computed at construction time, not when data is actually processed. This reflects the philosophy that the schema should not depend on the data.
Returning catalogs rather than just schemas allows us to save e.g. slots for SourceCatalog as well.
-
getTaskDict
()¶ Get a dictionary of all tasks as a shallow copy.
- Returns
- taskDict
dict
Dictionary containing full task name: task object for the top-level task and all subtasks, sub-subtasks, etc..
- taskDict
-
groupByExposure
(files: Iterable[lsst.obs.base.ingest.RawFileData]) → List[lsst.obs.base.ingest.RawExposureData]¶ Group an iterable of
RawFileData
by exposure.- Parameters
- filesiterable of
RawFileData
File-level information to group.
- filesiterable of
- Returns
- exposures
list
ofRawExposureData
A list of structures that group the file-level information by exposure. The
RawExposureData.records
attributes of elements will beNone
, but all other fields will be populated. TheRawExposureData.dataId
attributes will be minimal (unexpanded)DataCoordinate
instances.
- exposures
-
ingestExposureDatasets
(exposure: lsst.obs.base.ingest.RawExposureData, butler: Optional[lsst.daf.butler.butler.Butler] = None) → List[lsst.daf.butler.core.datasets.DatasetRef]¶ Ingest all raw files in one exposure.
- Parameters
- exposure
RawExposureData
A structure containing information about the exposure to be ingested. Must have
RawExposureData.records
populated and all data ID attributes expanded.- butler
lsst.daf.butler.Butler
, optional Butler to use for ingest. If not provided,
self.butler
will be used.
- exposure
- Returns
- refs
list
oflsst.daf.butler.DatasetRef
Dataset references for ingested raws.
- refs
-
insertDimensionData
(records: Mapping[str, List[lsst.daf.butler.core.dimensions.records.DimensionRecord]])¶ Insert dimension records for one or more exposures.
- Parameters
- records
dict
mappingstr
tolist
Dimension records to be inserted, organized as a mapping from dimension name to a list of records for that dimension. This may be a single
RawExposureData.records
dict, or an aggregate for multiple exposures created by concatenating the value lists of those dictionaries.
- records
- Returns
- refs
list
oflsst.daf.butler.DatasetRef
Dataset references for ingested raws.
- refs
-
classmethod
makeField
(doc)¶ Make a
lsst.pex.config.ConfigurableField
for this task.- Parameters
- doc
str
Help text for the field.
- doc
- Returns
- configurableField
lsst.pex.config.ConfigurableField
A
ConfigurableField
for this task.
- configurableField
Examples
Provides a convenient way to specify this task is a subtask of another task.
Here is an example of use:
class OtherTaskConfig(lsst.pex.config.Config) aSubtask = ATaskClass.makeField("a brief description of what this task does")
-
makeSubtask
(name, **keyArgs)¶ Create a subtask as a new instance as the
name
attribute of this task.- Parameters
- name
str
Brief name of the subtask.
- keyArgs
Extra keyword arguments used to construct the task. The following arguments are automatically provided and cannot be overridden:
“config”.
“parentTask”.
- name
Notes
The subtask must be defined by
Task.config.name
, an instance of pex_config ConfigurableField or RegistryField.
-
prep
(files, pool: Optional[multiprocessing.context.BaseContext.Pool] = None, processes: int = 1) → Iterator[lsst.obs.base.ingest.RawExposureData]¶ Perform all ingest preprocessing steps that do not involve actually modifying the database.
- Parameters
- filesiterable over
str
or path-like objects Paths to the files to be ingested. Will be made absolute if they are not already.
- pool
multiprocessing.Pool
, optional If not
None
, a process pool with which to parallelize some operations.- processes
int
, optional The number of processes to use. Ignored if
pool
is notNone
.
- filesiterable over
- Yields
- exposure
RawExposureData
Data structures containing dimension records, filenames, and data IDs to be ingested (one structure for each exposure).
- exposure
-
run
(files, pool: Optional[multiprocessing.context.BaseContext.Pool] = None, processes: int = 1)¶ Ingest files into a Butler data repository.
This creates any new exposure or visit Dimension entries needed to identify the ingested files, creates new Dataset entries in the Registry and finally ingests the files themselves into the Datastore. Any needed instrument, detector, and physical_filter Dimension entries must exist in the Registry before
run
is called.- Parameters
- filesiterable over
str
or path-like objects Paths to the files to be ingested. Will be made absolute if they are not already.
- pool
multiprocessing.Pool
, optional If not
None
, a process pool with which to parallelize some operations.- processes
int
, optional The number of processes to use. Ignored if
pool
is notNone
.
- filesiterable over
- Returns
- refs
list
oflsst.daf.butler.DatasetRef
Dataset references for ingested raws.
- refs
Notes
This method inserts all records (dimensions and datasets) for an exposure within a transaction, guaranteeing that partial exposures are never ingested.
-
timer
(name, logLevel=10000)¶ Context manager to log performance data for an arbitrary block of code.
- Parameters
- name
str
Name of code being timed; data will be logged using item name:
Start
andEnd
.- logLevel
A
lsst.log
level constant.
- name
See also
timer.logInfo
Examples
Creating a timer context:
with self.timer("someCodeToTime"): pass # code to time