Python client

Python client

cortex

client

client(env: Optional[str] = None) -> Client

Initialize a client based on the specified environment. If no environment is specified, it will attempt to use the default environment.

Arguments:

  • env - Name of the environment to use.

Returns:

Cortex client that can be used to deploy and manage APIs in the specified environment.

new_client

new_client(name: str, operator_endpoint: str) -> Client

Create a new environment to connect to an existing cluster, and initialize a client to deploy and manage APIs on that cluster.

Arguments:

  • name - Name of the environment to create.

  • operator_endpoint - The endpoint for the operator of your Cortex cluster. You can get this endpoint by running the CLI command cortex cluster info.

Returns:

Cortex client that can be used to deploy and manage APIs on a cluster.

env_list

env_list() -> list

List all environments configured on this machine.

env_delete

env_delete(name: str)

Delete an environment configured on this machine.

Arguments:

  • name - Name of the environment to delete.

cortex.client.Client

create_api

 | create_api(api_spec: dict, predictor=None, task=None, requirements=[], conda_packages=[], project_dir: Optional[str] = None, force: bool = True, wait: bool = False) -> list

Deploy an API.

Arguments:

  • api_spec - A dictionary defining a single Cortex API. See https://docs.cortex.dev/v/0.32/ for schema.

  • predictor - A Cortex Predictor class implementation. Not required for TaskAPI/TrafficSplitter kinds.

  • task - A callable class/function implementation. Not required for RealtimeAPI/BatchAPI/TrafficSplitter kinds.

  • requirements - A list of PyPI dependencies that will be installed before the predictor class implementation is invoked.

  • conda_packages - A list of Conda dependencies that will be installed before the predictor class implementation is invoked.

  • project_dir - Path to a python project.

  • force - Override any in-progress api updates.

  • wait - Streams logs until the APIs are ready.

Returns:

Deployment status, API specification, and endpoint for each API.

get_api

 | get_api(api_name: str) -> dict

Get information about an API.

Arguments:

  • api_name - Name of the API.

Returns:

Information about the API, including the API specification, endpoint, status, and metrics (if applicable).

list_apis

 | list_apis() -> list

List all APIs in the environment.

Returns:

List of APIs, including information such as the API specification, endpoint, status, and metrics (if applicable).

get_job

 | get_job(api_name: str, job_id: str) -> dict

Get information about a submitted job.

Arguments:

  • api_name - Name of the Batch/Task API.

  • job_id - Job ID.

Returns:

Information about the job, including the job status, worker status, and job progress.

refresh

 | refresh(api_name: str, force: bool = False)

Restart all of the replicas for a Realtime API without downtime.

Arguments:

  • api_name - Name of the API to refresh.

  • force - Override an already in-progress API update.

patch

 | patch(api_spec: dict, force: bool = False) -> dict

Update the api specification for an API that has already been deployed.

Arguments:

  • api_spec - The new api specification to apply

  • force - Override an already in-progress API update.

delete_api

 | delete_api(api_name: str, keep_cache: bool = False)

Delete an API.

Arguments:

  • api_name - Name of the API to delete.

  • keep_cache - Whether to retain the cached data for this API.

stop_job

 | stop_job(api_name: str, job_id: str, keep_cache: bool = False)

Stop a running job.

Arguments:

  • api_name - Name of the Batch/Task API.

  • job_id - ID of the Job to stop.

stream_api_logs

 | stream_api_logs(api_name: str)

Stream the logs of an API.

Arguments:

  • api_name - Name of the API.

stream_job_logs

 | stream_job_logs(api_name: str, job_id: str)

Stream the logs of a Job.

Arguments:

  • api_name - Name of the Batch API.

  • job_id - Job ID.

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