ButlerLogRecords

class lsst.daf.butler.ButlerLogRecords(*, __root__: list[lsst.daf.butler.core.logging.ButlerLogRecord])

Bases: _ButlerLogRecords

Class representing a collection of ButlerLogRecord.

Attributes Summary

log_format

model_fields

root

Methods Summary

append(value)

clear()

construct([_fields_set])

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.

copy(*[, include, exclude, update, deep])

Duplicate a model, optionally choose which fields to include, exclude and change.

dict(*[, include, exclude, by_alias, ...])

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

extend(records)

from_file(filename)

Read records from file.

from_orm(obj)

from_raw(serialized)

Parse raw serialized form and return records.

from_records(records)

Create collection from iterable.

from_stream(stream)

Read records from I/O stream.

insert(index, value)

json(*[, include, exclude, by_alias, ...])

Generate a JSON representation of the model, include and exclude arguments as per dict().

model_construct([_fields_set])

model_dump(*[, mode, include, exclude, ...])

model_dump_json(*[, indent, include, ...])

model_rebuild(*[, force, raise_errors, ...])

model_validate(obj, *[, strict, ...])

model_validate_json(json_data, *[, strict, ...])

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

pop([index])

reverse()

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

set_log_format(format)

Set the log format string for these records.

update_forward_refs(**localns)

Try to update ForwardRefs on fields based on this Model, globalns and localns.

validate(value)

Attributes Documentation

log_format
model_fields = {'__root__': ModelField(name='__root__', type=List[ButlerLogRecord], required=True)}
root: list[lsst.daf.butler.core.logging.ButlerLogRecord]

Methods Documentation

append(value: LogRecord | ButlerLogRecord) None
clear() None
classmethod construct(_fields_set: SetStr | None = None, **values: Any) Model

Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = 'allow' was set since it adds all passed values

copy(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, update: DictStrAny | None = None, deep: bool = False) Model

Duplicate a model, optionally choose which fields to include, exclude and change.

Parameters:
  • include – fields to include in new model

  • exclude – fields to exclude from new model, as with values this takes precedence over include

  • update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data

  • deep – set to True to make a deep copy of the model

Returns:

new model instance

dict(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) DictStrAny

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

extend(records: Iterable[LogRecord | ButlerLogRecord]) None
classmethod from_file(filename: str) ButlerLogRecords

Read records from file.

Parameters:
filenamestr

Name of file containing the JSON records.

Notes

Works with one-record-per-line format JSON files and a direct serialization of the Pydantic model.

classmethod from_orm(obj: Any) Model
classmethod from_raw(serialized: str | bytes) ButlerLogRecords

Parse raw serialized form and return records.

Parameters:
serializedbytes or str

Either the serialized JSON of the model created using .model_dump_json() or a streaming format of one JSON ButlerLogRecord per line. This can also support a zero-length string.

classmethod from_records(records: Iterable[ButlerLogRecord]) ButlerLogRecords

Create collection from iterable.

Parameters:
recordsiterable of ButlerLogRecord

The records to seed this class with.

classmethod from_stream(stream: IO) ButlerLogRecords

Read records from I/O stream.

Parameters:
streamtyping.IO

Stream from which to read JSON records.

Notes

Works with one-record-per-line format JSON files and a direct serialization of the Pydantic model.

insert(index: int, value: LogRecord | ButlerLogRecord) None
json(*, include: AbstractSetIntStr | MappingIntStrAny | None = None, exclude: AbstractSetIntStr | MappingIntStrAny | None = None, by_alias: bool = False, skip_defaults: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = None, models_as_dict: bool = True, **dumps_kwargs: Any) unicode

Generate a JSON representation of the model, include and exclude arguments as per dict().

encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) Self
model_dump(*, mode: Literal['json', 'python'] | str = 'python', include: set[int] | set[str] | dict[int, Any] | dict[str, Any] | None = None, exclude: set[int] | set[str] | dict[int, Any] | dict[str, Any] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool = True) dict[str, Any]
model_dump_json(*, indent: int | None = None, include: set[int] | set[str] | dict[int, Any] | dict[str, Any] | None = None, exclude: set[int] | set[str] | dict[int, Any] | dict[str, Any] | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, round_trip: bool = False, warnings: bool = True) str
classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: dict[str, Any] | None = None) bool | None
classmethod model_validate(obj: Any, *, strict: bool | None = None, from_attributes: bool | None = None, context: dict[str, Any] | None = None) Self
classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, context: dict[str, Any] | None = None) Self
classmethod parse_file(path: str | Path, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
classmethod parse_obj(obj: Any) Model
classmethod parse_raw(b: str | bytes, *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) Model
pop(index: int = -1) ButlerLogRecord
reverse() None
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) unicode
set_log_format(format: str | None) str | None

Set the log format string for these records.

Parameters:
formatstr, optional

The new format string to use for converting this collection of records into a string. If None the default format will be used.

Returns:
old_formatstr, optional

The previous log format.

classmethod update_forward_refs(**localns: Any) None

Try to update ForwardRefs on fields based on this Model, globalns and localns.

classmethod validate(value: Any) Model