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Apheris CLI Python API Reference🔗

apheris🔗

Convenience namespace containing some common Apheris functions.

login(username=None, password=None, login_mode='sso') 🔗

Authenticate a user, either through their Apheris account or using their company account. Programmatic login can be achieved by supplying the apheris username/passwords directly. Alternatively the user can jump right through to using their company login by setting the login mode to "sso"

logout() 🔗

Logs the user out.

list_datasets(n=None, to_table=True) 🔗

List the n most recently updated remote datasets.

Parameters:

Name Type Description Default
n Optional[int]

number of remote datasets to list. If None, list all. Default: None

 None
to_table bool

If True, a prettytable.PrettyTable is returned. If False, a list of Dictionaries will be returned.

 True

Returns:

Type Description
Union[PrettyTable, List[dict]]
  • If to_table is True, a prettytable.PrettyTable is returned. The datasets are sorted by their updated_at time, starting from the most recent one. most recently updated remote datasets is returned. If n is provided, will return the n most recent rows.
Union[PrettyTable, List[dict]]
  • If to_table is False, a list of Dictionaries is returned. The datasets are sorted by their updated_at time, starting from the most recent one. most recently updated remote datasets is returned. If n is provided, will return the n most recent rows.

list_models(to_table=True) 🔗

Convenience function to query the model list and parse the response in one call.

Parameters:

Name Type Description Default
to_table bool

If True, a prettytable.PrettyTable is returned. If False, a list of Dictionaries will be returned.

 True

Returns:

Type Description
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is True, a prettytable.PrettyTable is returned.
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is False, a list of Dictionaries is returned.

list_compute_specs(limit=10, to_table=True, verbose=False) 🔗

Convenience function to list the limit most recent compute specs and optionally output as a table.

Parameters:

Name Type Description Default
limit Optional[int]

The number of most recent compute specs to list. If None, all compute specs are listed. Defaults to 10.

 10
to_table bool

Whether to output the results as a pretty table. Defaults to True.

 True
verbose bool

Whether to include all details in the table. Defaults to False.

 False

Returns:

Type Description
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is True, a prettytable.PrettyTable is returned.
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is False, a list of Dictionaries is returned. In future versions this will return a list of ComputeSpec objects.

list_jobs(compute_spec_id=None) 🔗

List all jobs of a certain compute spec

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None

Returns: list: List of all jobs on the specified compute spec

aphcli.api.compute🔗

Functions related to the handling of Compute Specs (creation, activation, list, etc.).

set_ignore_limits(ignore) 🔗

Limits have been set on

create_from_args(dataset_ids=None, client_n_cpu=None, client_n_gpu=None, client_memory=None, server_n_cpu=None, server_n_gpu=None, server_memory=None, model=None, model_id=None, model_version=None) 🔗

Create a compute specification from raw arguments.

To describe the model, the user can supply either a dictionary with id and version fields, or provide them as individual arguments.

get(compute_spec_id=None) 🔗

Get a compute spec ID.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

Compute spec ID that shall be fetched. If None, use the most recently used compute spec ID.

 None

Returns:

Name Type Description
ComputeSpec ComputeSpec

definition of a compute spec

activate(compute_spec_id=None, verbose=False) 🔗

Activate a compute spec ID.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

Compute spec ID that shall be activated. If None, use the most recently used compute spec ID.

 None
verbose bool

If True, print more detailed information.

 False

deactivate(compute_spec_id=None, verbose=False) 🔗

Deactivate a compute spec ID.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

Compute spec ID that shall be de-activated. If None, use the most recently used compute spec ID.

 None
verbose bool

If True, print more detailed information.

 False

get_activation_status(compute_spec_id=None) 🔗

Get the activation status of a compute spec.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

ID of the compute spec that shall be queried. If None, use the most recently used compute spec ID.

 None

get_status(compute_spec_id=None) 🔗

Get the detailed status of a compute spec.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

ID of the compute spec that shall be queried. If None, use the most recently used compute spec ID.

 None

Returns:

Name Type Description
dict Dict[str, str]

A dict with keys status and message. The ´statusshows the activation status, e.g.creatingorrunning. Themessage` contains detail information. For example, if the compute spec isn't activating, the message might show that there is not enough hardware resource of a certain type.

wait_until_running(compute_spec_id, check_interval=10, timeout=600) 🔗

Wait until a Compute Spec's activation status is running.

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

ID of the compute spec that we want to observe. If None, use the most recently used compute spec id.

 required
check_interval float

Interval to check the status in seconds

 10
timeout Optional[float]

Timeout in seconds. If the target status is not reached within this time a TimeoutError is raised. If set to None, the function will not time out.

 600

aphcli.api.job🔗

Functions related to the handling of jobs (run, abort, list, status, etc.).

list_jobs(compute_spec_id=None) 🔗

List all jobs of a certain compute spec

Parameters:

Name Type Description Default
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None

Returns: list: List of all jobs on the specified compute spec

get(job_id=None, compute_spec_id=None, verbose=True) 🔗

Get details on a job

Parameters:

Name Type Description Default
job_id Optional[UUID]

The ID of the job whose details shall be fetched

 None
compute_spec_id Optional[UUID]

deprecated, stays to prevent breaking changes

 None
verbose

If True, provide more detailed information.

 True

Returns: dict: A dictionary with information on the job

status(job_id=None, compute_spec_id=None, verbose=True) 🔗

Get the status of a job

Parameters:

Name Type Description Default
job_id Optional[UUID]

The ID of the job whose status shall be fetched

 None
compute_spec_id Optional[UUID]

This argument is deprecated and

 None
verbose

If True, provide more detailed information.

 True

Returns: str: A string with details on the job's status

submit(job_args, compute_spec_id=None, verbose=False) 🔗

Submit a job

Parameters:

Name Type Description Default
job_args dict

Arguments for the job that you want to submit.

 required
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None
verbose bool

If True, provide more detailed information.

 False

Returns: UUID: This UUID is your reference to the submitted job

abort(job_id=None, compute_spec_id=None) 🔗

Abort a job

Parameters:

Name Type Description Default
job_id Optional[UUID]

The ID of the job that shall be aborted

 None
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None

download_results(download_path, job_id=None, compute_spec_id=None) 🔗

Download the results of a job

Parameters:

Name Type Description Default
download_path Union[str, Path]

File path to download the results to

 required
job_id Optional[UUID]

The ID of the job

 None
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None

logs(job_id=None, compute_spec_id=None) 🔗

Get the logs of a job

Parameters:

Name Type Description Default
job_id Optional[UUID]

The ID of the job whose logs shall be fetched

 None
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None

Returns:

Name Type Description
str str

A string that contains the logs

wait_until_job_finished(job_id=None, compute_spec_id=None, check_interval=3, timeout=100, warn_time=None) 🔗

Wait until a job is finished

Parameters:

Name Type Description Default
job_id Optional[UUID]

The ID of the job

 None
compute_spec_id Optional[UUID]

The ID of the compute spec. If None, use the most recently used compute spec id.

 None
check_interval float

Interval between http-requests that query the status in seconds.

 3
timeout Optional[float]

Maximum time to wait in seconds before a TimeoutError is raised.

 100
warn_time Optional[float]

After this time in seconds, a warning is fired.

 None

aphcli.api.models🔗

Functions related to the Apheris Model Registry.

get_models() 🔗

Returns a dictionary with detailed information on models available in the model registry.

models_from_response(response) 🔗

Parses the raw data from the models response and extracts the list of models and available versions.

list_models(to_table=True) 🔗

Convenience function to query the model list and parse the response in one call.

Parameters:

Name Type Description Default
to_table bool

If True, a prettytable.PrettyTable is returned. If False, a list of Dictionaries will be returned.

 True

Returns:

Type Description
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is True, a prettytable.PrettyTable is returned.
Union[PrettyTable, List[Dict[str, str]]]
  • If to_table is False, a list of Dictionaries is returned.

indexed_model_list(models) 🔗

Convert the list of models to a tabular format for interaction

add_model_version(model_id, version, digest, commit_hash, engine_version=None) 🔗

Adds a new version to an existing model in the Model Registry.

Parameters:

Name Type Description Default
model_id str

The ID of the model to add a version to.

 required
version str

The version tag for the new model version.

 required
digest str

The digest of the model.

 required
commit_hash str

The commit hash associated with this model version.

 required
engine_version Optional[str]

Optional EngineVersion string.

 None

Returns:

Type Description
Dict[str, Any]

A dictionary containing the response from the API.

Raises:

Type Description
ComputeSpecException

If there's an error in adding the model version.