seismometer.configuration.model.OtherInfo

class seismometer.configuration.model.OtherInfo(*, template=None, info_dir=None, event_definition=None, prediction_definition=None, usage_config=None, automation_config=None, data_dir=None, prediction_path='scores.parquet', event_path='events.parquet', metadata_path='metadata.json')

Locations of configuration and data files.

Parameters:

• template (str | None)

• info_dir (str | Path | None)

• event_definition (str | Path | None)

• prediction_definition (str | Path | None)

• usage_config (str | Path | None)

• automation_config (str | Path | None)

• data_dir (str | Path | None)

• prediction_path (str | Path)

• event_path (str | Path)

• metadata_path (str | Path)

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
template	Descriptor of the template; not used.
info_dir	Writable directors for output; used during run.
event_definition	The location of the event dictionary.
prediction_definition	The location of the prediction dictionary.
usage_config	The location of the usage configuration; used during run.
automation_config	The location of the automation configuration; used during run if automated metric export is desired.
data_dir	The parent location of data files; primarily used during run.
prediction_path	The location of the prediction data within data_dir.
event_path	The location of the event data within data_dir.
metadata_path	The location of the metadata file within data_dir.