ButlerLogRecords

class lsst.daf.butler.logging.ButlerLogRecords(*, __root__: list[lsst.daf.butler.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_copy(*[, update, deep])
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.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_copy(*, update: dict[str, Any] | None = None, deep: bool = False) → 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