openprotein.embeddings.EmbeddingsResultFuture#

class openprotein.embeddings.EmbeddingsResultFuture(session, job, sequences=None, max_workers=10)[source]#

Future for manipulating results for embeddings-related requests.

Parameters:

__init__(session, job, sequences=None, max_workers=10)[source]#

Initialize the MappedFuture.

Parameters:

session (APISession) – The session for API interactions.
job (Job) – The job to retrieve results from.
max_workers (int, optional) – The number of workers for concurrent result retrieval. Defaults to config.MAX_CONCURRENT_WORKERS.
sequences (list[bytes] | list[str] | None)

Notes

Use max_workers > 0 to enable concurrent retrieval.

Methods

`__init__`(session, job[, sequences, max_workers])	Initialize the MappedFuture.
`cancelled`()	Check if the job has been cancelled.
`create`(session[, job_id, job, response])	Create an instance of the appropriate Future class based on the job type.
`done`()	Check if the job has completed.
`get`([verbose])	Return all results from the job by consuming the stream.
`get_item`(sequence)	Get embedding results for specified sequence.
`refresh`()	Refresh the job status and internal job object.
`stream`()	Retrieve results for this job as a stream.
`stream_parallel`()	Stream the results in parallel using a thread pool.
`stream_sync`()	Stream the results synchronously.
`wait`([interval, timeout, verbose])	Wait for the job to complete, then fetch results.
`wait_until_done`([interval, timeout, verbose])	Wait for the job to complete.

Attributes

`created_date`	The creation timestamp of the job.
`end_date`	The end timestamp of the job.
`id`	The unique identifier of the job.
`job_id`	The unique identifier of the job.
`job_type`	The type of the job.
`progress_counter`	The progress counter of the job.
`sequences`
`start_date`	The start timestamp of the job.
`status`	The current status of the job.
`job`
`session`