Session management

Executing workflows is achieved with the OpenProtein session object

# Use environment variables to store your username and password
# If using Jupyter, you can use the %env magic command
# %env OPENPROTEIN_USERNAME=username
# %env OPENPROTEIN_PASSWORD=password

session = openprotein.connect()

# Alternatively, just provide them as arguments.
# session = openprotein.connect(username="username", password="password")

You then have access to all the workflows:

For example, upload your dataset with

session.data.create

or create an MSA using homology search with

session.align.create_msa()

Job System

The OpenProtein.AI platform operates with an asynchronous framework. When initiating a task using our Python client, the system schedules the job, returning a prompt response with a unique Job ID. This mechanism ensures that tasks requiring longer processing times do not necessitate immediate waiting.

When you submit a task, such as using the method

session.align.create_msa()

a Future object is returned for results tracking and access. You can check a job’s status using the refresh() and done() methods on this object. If you wish to wait for the results, you can use the wait() method, or the get() method if the results are already completed.

In addition, you can resume a workflow using the session.jobs.get function along with the unique job ID obtained during task execution. This method will return a Future Class, allowing you to continue from where you left off.