Getting Started with OpenProtein.AI’s API

Step 2: Install our python client

You can install the package via pip or conda as below:

pip

pip install openprotein-python

conda

conda install -c openprotein openprotein-python

Github
The source code is available here.

Want to start with the web version?

Visit Get started with no code

Step 3: Authenticate your session

Use your username and password credentials generated at sign-up to authenticate your connection to OpenProtein backend.

import openprotein

with open('secrets.config', 'r') as f:
    config = json.load(f)

session = openprotein.connect(username= config['username'], password= config['password'])

OpenProtein Job System

The OpenProtein.AI platform uses a job system to support asynchronous task execution. Upon initiating a task, the system will schedule a job with a unique Job ID so you can return at a later time for tasks with long processing times.

OpenProtein API session

Executing workflows is achieved with the OpenProtein APISession object (see openprotein.APISession())

session = openprotein.connect(username="username", password="password")

You then have access to all the workflows:
For example

session.data.create()

session.poet.create_msa()

Step 4: Get started with our Python API docs

Quick start tips

Do you want to…

Make sequence predictions or designs without using any data?
Get started with PoET which uses evolutionary information to generate protein sequences

Analyze your experimental data for library design?
Create your first project and deploy machine learning models trained on your data
Learn more about OP Models Get started uploading your data

Explore your protein’s structure?
Use our Structure Prediction tool to view and download high quality images