tidy3d.web.Job#

class tidy3d.web.Job(*, type: Literal['Job'] = 'Job', simulation: tidy3d.components.simulation.Simulation, task_name: str, folder_name: str = 'default', callback_url: str = None, solver_version: str = None, verbose: bool = True, simulation_type: str = 'tidy3d', parent_tasks: Tuple[str, ...] = None, task_id: str = None)#

Bases: tidy3d.web.container.WebContainer

Interface for managing the running of a Simulation on server.

Parameters
  • simulation (Simulation) – Simulation to run as a ‘task’.

  • task_name (str) – Unique name of the task.

  • folder_name (str = default) – Name of folder to store task on web UI.

  • callback_url (Optional[str] = None) – Http PUT url to receive simulation finish event. The body content is a json file with fields {'id', 'status', 'name', 'workUnit', 'solverVersion'}.

  • solver_version (Optional[str] = None) – verbose : bool = True Whether to print info messages and progressbars.

  • simulation_type (str = tidy3d) – Type of simulation, used internally only.

  • parent_tasks (Optional[Tuple[str, ...]] = None) – Tuple of parent task ids, used internally only.

  • task_id (Optional[str] = None) – Task ID number, set when the task is uploaded, leave as None.

__init__(**kwargs)#

Init method, includes post-init validators.

Methods

__init__(**kwargs)

Init method, includes post-init validators.

add_type_field()

Automatically place "type" field with model name in the model field dictionary.

construct([_fields_set])

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

copy(**kwargs)

Copy a Tidy3dBaseModel.

delete()

Delete server-side data associated with Job.

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

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

dict_from_file(fname[, group_path])

Loads a dictionary containing the model from a .yaml, .json, .hdf5, or .hdf5.gz file.

dict_from_hdf5(fname[, group_path, ...])

Loads a dictionary containing the model contents from a .hdf5 file.

dict_from_hdf5_gz(fname[, group_path, ...])

Loads a dictionary containing the model contents from a .hdf5.gz file.

dict_from_json(fname)

Load dictionary of the model from a .json file.

dict_from_yaml(fname)

Load dictionary of the model from a .yaml file.

download([path])

Download results of simulation.

estimate_cost()

Compute the maximum FlexCredit charge for a given Job.

from_file(fname[, group_path])

Loads a Tidy3dBaseModel from .yaml, .json, .hdf5, or .hdf5.gz file.

from_hdf5(fname[, group_path, custom_decoders])

Loads Tidy3dBaseModel instance to .hdf5 file.

from_hdf5_gz(fname[, group_path, ...])

Loads Tidy3dBaseModel instance to .hdf5.gz file.

from_json(fname, **parse_obj_kwargs)

Load a Tidy3dBaseModel from .json file.

from_orm(obj)

from_yaml(fname, **parse_obj_kwargs)

Loads Tidy3dBaseModel from .yaml file.

generate_docstring()

Generates a docstring for a Tidy3D mode and saves it to the __doc__ of the class.

get_info()

Return information about a Job.

get_run_info()

Return information about the running Job.

get_sub_model(group_path, model_dict)

Get the sub model for a given group path.

get_submodels_by_hash()

Return a dictionary of this object's sub-models indexed by their hash values.

get_tuple_group_name(index)

Get the group name of a tuple element.

get_tuple_index(key_name)

Get the index into the tuple based on its group name.

help([methods])

Prints message describing the fields and methods of a Tidy3dBaseModel.

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

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

load([path])

Download results from simulation (if not already) and load them into SimulationData object.

monitor()

Monitor progress of running Job.

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

parse_obj(obj)

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

real_cost()

Get the billed cost for the task associated with this job.

run([path])

run Job all the way through and return data.

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

start()

Start running a Job.

to_file(fname)

Exports Tidy3dBaseModel instance to .yaml, .json, or .hdf5 file

to_hdf5(fname[, custom_encoders])

Exports Tidy3dBaseModel instance to .hdf5 file.

to_hdf5_gz(fname[, custom_encoders])

Exports Tidy3dBaseModel instance to .hdf5.gz file.

to_json(fname)

Exports Tidy3dBaseModel instance to .json file

to_yaml(fname)

Exports Tidy3dBaseModel instance to .yaml file.

tuple_to_dict(tuple_values)

How we generate a dictionary mapping new keys to tuple values for hdf5.

update_forward_refs(**localns)

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

updated_copy(**kwargs)

Make copy of a component instance with **kwargs indicating updated field values.

validate(value)

Attributes

status

Return current status of Job.

simulation

task_name

folder_name

callback_url

solver_version

verbose

simulation_type

parent_tasks

task_id

class Config#

Bases: object

Sets config for all Tidy3dBaseModel objects.

allow_population_by_field_namebool = True

Allow properties to stand in for fields(?).

arbitrary_types_allowedbool = True

Allow types like numpy arrays.

extrastr = ‘forbid’

Forbid extra kwargs not specified in model.

json_encodersDict[type, Callable]

Defines how to encode type in json file.

validate_allbool = True

Validate default values just to be safe.

validate_assignmentbool

Re-validate after re-assignment of field in model.

__eq__(other)#

Define == for two Tidy3DBaseModels.

__ge__(other)#

define >= for getting unique indices based on hash.

__gt__(other)#

define > for getting unique indices based on hash.

__hash__() int#

Hash method.

classmethod __init_subclass__() None#

Things that are done to each of the models.

__iter__() TupleGenerator#

so dict(model) works

__le__(other)#

define <= for getting unique indices based on hash.

__lt__(other)#

define < for getting unique indices based on hash.

__pretty__(fmt: Callable[[Any], Any], **kwargs: Any) Generator[Any, None, None]#

Used by devtools (https://python-devtools.helpmanual.io/) to provide a human readable representations of objects

__repr_name__() str#

Name of the instance’s class, used in __repr__.

__rich_repr__() RichReprResult#

Get fields for Rich library

classmethod __try_update_forward_refs__(**localns: Any) None#

Same as update_forward_refs but will not raise exception when forward references are not defined.

classmethod add_type_field() None#

Automatically place “type” field with model name in the model field dictionary.

classmethod construct(_fields_set: Optional[SetStr] = 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(**kwargs) tidy3d.components.base.Tidy3dBaseModel#

Copy a Tidy3dBaseModel. With deep=True as default.

delete() None#

Delete server-side data associated with Job.

dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = 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.

classmethod dict_from_file(fname: str, group_path: Optional[str] = None) dict#

Loads a dictionary containing the model from a .yaml, .json, .hdf5, or .hdf5.gz file.

Parameters
  • fname (str) – Full path to the file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to use as the base level.

Returns

A dictionary containing the model.

Return type

dict

Example

>>> simulation = Simulation.from_file(fname='folder/sim.json') 
classmethod dict_from_hdf5(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None) dict#

Loads a dictionary containing the model contents from a .hdf5 file.

Parameters
  • fname (str) – Full path to the .hdf5 file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only.

  • custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.

Returns

Dictionary containing the model.

Return type

dict

Example

>>> sim_dict = Simulation.dict_from_hdf5(fname='folder/sim.hdf5') 
classmethod dict_from_hdf5_gz(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None) dict#

Loads a dictionary containing the model contents from a .hdf5.gz file.

Parameters
  • fname (str) – Full path to the .hdf5.gz file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only.

  • custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.

Returns

Dictionary containing the model.

Return type

dict

Example

>>> sim_dict = Simulation.dict_from_hdf5(fname='folder/sim.hdf5.gz') 
classmethod dict_from_json(fname: str) dict#

Load dictionary of the model from a .json file.

Parameters

fname (str) – Full path to the .json file to load the Tidy3dBaseModel from.

Returns

A dictionary containing the model.

Return type

dict

Example

>>> sim_dict = Simulation.dict_from_json(fname='folder/sim.json') 
classmethod dict_from_yaml(fname: str) dict#

Load dictionary of the model from a .yaml file.

Parameters

fname (str) – Full path to the .yaml file to load the Tidy3dBaseModel from.

Returns

A dictionary containing the model.

Return type

dict

Example

>>> sim_dict = Simulation.dict_from_yaml(fname='folder/sim.yaml') 
download(path: str = 'simulation_data.hdf5') None#

Download results of simulation.

Parameters

path (str = "./simulation_data.hdf5") – Path to download data as .hdf5 file (including filename).

Note

To load the data into SimulationData`objets, can call :meth:`Job.load.

estimate_cost() float#

Compute the maximum FlexCredit charge for a given Job.

Returns

Estimated maximum cost for Simulation associated with given Job.

Return type

float

Note

Cost is calculated assuming the simulation runs for the full run_time. If early shut-off is triggered, the cost is adjusted proporionately.

Returns

Estimated cost of the task in FlexCredits.

Return type

float

classmethod from_file(fname: str, group_path: Optional[str] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#

Loads a Tidy3dBaseModel from .yaml, .json, .hdf5, or .hdf5.gz file.

Parameters
  • fname (str) – Full path to the file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to use as the base level. Only for hdf5 files. Starting / is optional.

  • **parse_obj_kwargs – Keyword arguments passed to either pydantic’s parse_obj function when loading model.

Returns

An instance of the component class calling load.

Return type

Tidy3dBaseModel

Example

>>> simulation = Simulation.from_file(fname='folder/sim.json') 
classmethod from_hdf5(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#

Loads Tidy3dBaseModel instance to .hdf5 file.

Parameters
  • fname (str) – Full path to the .hdf5 file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only. Starting / is optional.

  • custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Example

>>> simulation = Simulation.from_hdf5(fname='folder/sim.hdf5') 
classmethod from_hdf5_gz(fname: str, group_path: str = '', custom_decoders: Optional[List[Callable]] = None, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#

Loads Tidy3dBaseModel instance to .hdf5.gz file.

Parameters
  • fname (str) – Full path to the .hdf5.gz file to load the Tidy3dBaseModel from.

  • group_path (str, optional) – Path to a group inside the file to selectively load a sub-element of the model only. Starting / is optional.

  • custom_decoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, model_dict: dict, key: str, value: Any) that store the value in the model dict after a custom decoding.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Example

>>> simulation = Simulation.from_hdf5_gz(fname='folder/sim.hdf5.gz') 
classmethod from_json(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#

Load a Tidy3dBaseModel from .json file.

Parameters

fname (str) – Full path to the .json file to load the Tidy3dBaseModel from.

Returns

  • Tidy3dBaseModel – An instance of the component class calling load.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Example

>>> simulation = Simulation.from_json(fname='folder/sim.json') 
classmethod from_yaml(fname: str, **parse_obj_kwargs) tidy3d.components.base.Tidy3dBaseModel#

Loads Tidy3dBaseModel from .yaml file.

Parameters
  • fname (str) – Full path to the .yaml file to load the Tidy3dBaseModel from.

  • **parse_obj_kwargs – Keyword arguments passed to pydantic’s parse_obj method.

Returns

An instance of the component class calling from_yaml.

Return type

Tidy3dBaseModel

Example

>>> simulation = Simulation.from_yaml(fname='folder/sim.yaml') 
classmethod generate_docstring() str#

Generates a docstring for a Tidy3D mode and saves it to the __doc__ of the class.

get_info() tidy3d.web.task.TaskInfo#

Return information about a Job.

Returns

TaskInfo object containing info about status, size, credits of task and others.

Return type

TaskInfo

get_run_info() tidy3d.web.task.RunInfo#

Return information about the running Job.

Returns

Task run information.

Return type

RunInfo

classmethod get_sub_model(group_path: str, model_dict: dict | list) dict#

Get the sub model for a given group path.

get_submodels_by_hash() Dict[int, List[Union[str, Tuple[str, int]]]]#

Return a dictionary of this object’s sub-models indexed by their hash values.

static get_tuple_group_name(index: int) str#

Get the group name of a tuple element.

static get_tuple_index(key_name: str) int#

Get the index into the tuple based on its group name.

help(methods: bool = False) None#

Prints message describing the fields and methods of a Tidy3dBaseModel.

Parameters

methods (bool = False) – Whether to also print out information about object’s methods.

Example

>>> simulation.help(methods=True) 
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) str#

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().

load(path: str = 'simulation_data.hdf5') tidy3d.components.data.sim_data.SimulationData#

Download results from simulation (if not already) and load them into SimulationData object.

Parameters

path (str = "./simulation_data.hdf5") – Path to download data as .hdf5 file (including filename).

Returns

Object containing data about simulation.

Return type

SimulationData

monitor() None#

Monitor progress of running Job.

Note

To load the output of completed simulation into SimulationData`objets, call :meth:`Job.load.

real_cost() float#

Get the billed cost for the task associated with this job.

run(path: str = 'simulation_data.hdf5') tidy3d.components.data.sim_data.SimulationData#

run Job all the way through and return data.

Parameters

path_dir (str = "./simulation_data.hdf5") – Base directory where data will be downloaded, by default current working directory.

Returns

Dict[str – Dictionary mapping task name to SimulationData for Job.

Return type

SimulationData]

start() None#

Start running a Job.

Note

To monitor progress of the Job, call Job.monitor() after started.

property status#

Return current status of Job.

to_file(fname: str) None#

Exports Tidy3dBaseModel instance to .yaml, .json, or .hdf5 file

Parameters

fname (str) – Full path to the .yaml or .json file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_file(fname='folder/sim.json') 
to_hdf5(fname: str, custom_encoders: Optional[List[Callable]] = None) None#

Exports Tidy3dBaseModel instance to .hdf5 file.

Parameters
  • fname (str) – Full path to the .hdf5 file to save the Tidy3dBaseModel to.

  • custom_encoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, value: Any) that take the value supplied and write it to the hdf5 fname at group_path.

Example

>>> simulation.to_hdf5(fname='folder/sim.hdf5') 
to_hdf5_gz(fname: str, custom_encoders: Optional[List[Callable]] = None) None#

Exports Tidy3dBaseModel instance to .hdf5.gz file.

Parameters
  • fname (str) – Full path to the .hdf5.gz file to save the Tidy3dBaseModel to.

  • custom_encoders (List[Callable]) – List of functions accepting (fname: str, group_path: str, value: Any) that take the value supplied and write it to the hdf5 fname at group_path.

Example

>>> simulation.to_hdf5_gz(fname='folder/sim.hdf5.gz') 
to_json(fname: str) None#

Exports Tidy3dBaseModel instance to .json file

Parameters

fname (str) – Full path to the .json file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_json(fname='folder/sim.json') 
to_yaml(fname: str) None#

Exports Tidy3dBaseModel instance to .yaml file.

Parameters

fname (str) – Full path to the .yaml file to save the Tidy3dBaseModel to.

Example

>>> simulation.to_yaml(fname='folder/sim.yaml') 
classmethod tuple_to_dict(tuple_values: tuple) dict#

How we generate a dictionary mapping new keys to tuple values for hdf5.

classmethod update_forward_refs(**localns: Any) None#

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

updated_copy(**kwargs) tidy3d.components.base.Tidy3dBaseModel#

Make copy of a component instance with **kwargs indicating updated field values.