tasi.io.orm.TrafficParticipantORM#

class tasi.io.orm.TrafficParticipantORM(*, id=None, start_time=None, end_time=None, id_object, id_dimension=None, id_classification=None)[source]#

__init__(**data)[source]#

Methods

`__init__`(**data)
`as_dataframe`()
`as_dict`()
`as_flat_dict`([drop, replace])
`as_series`([name])
`by_id_object`(id_object, session, **kwargs)
`construct`([_fields_set])
`copy`(*[, include, exclude, update, deep])	Returns a copy of the model.
`dict`(*[, include, exclude, by_alias, ...])
`from_dataframe`(df, **kwargs)
`from_orm`(obj[, update])
`from_series`(se)
`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`(args, *kwargs)	!!! abstract "Usage Documentation"
`model_dump_json`(*[, indent, include, ...])	!!! 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, ...])	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[, update])
`parse_raw`(b, *[, content_type, encoding, ...])
`schema`([by_alias, ref_template])
`schema_json`(*[, by_alias, ref_template])
`sqlmodel_update`(obj, *[, update])
`update_forward_refs`(**localns)
`validate`(value)

Attributes

`classifications`
`dimension`
`end_time`	The last time the traffic participant was within the measurement site
`geotrajectory`
`id`
`id_classification`
`id_dimension`
`id_object`	A unique identifier
`metadata`
`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.
`start_time`	The first time the traffic participant was within the measurement site
`trajectory`