README.md

Quantum Challenge Grader

Grading client for the IBM Quantum Challenge grading service.

Run locally

Pre-requisites:

• IBM Quantum account
• Python (3.10 or later) environment with
  • Classic Jupyter Notebook interface or JupyterLab
  • Qiskit

To install the grader locally:

1. In the Python environment, install the grading client

   pip install git+https://github.com/qiskit-community/Quantum-Challenge-Grader.git
   

   Alternatively, if you also need to install JupyterLab and Qiskit along with the grader you can instead run:

   pip install 'qc-grader[qiskit,jupyter] @ git+https://github.com/qiskit-community/Quantum-Challenge-Grader.git'
   

2. Configure the QXToken environment variables

   From a terminal (before launching your JupyterLab environment), enter

   export QXToken=your_quantum_api_token
   

   where your_quantum_api_token is your IBM Quantum API Token found in your Account Profile.

   Alternatively, if you prefer you can instead run the following at the top cell of a notebook cell (whenever you start/restart the kernel)

   %set_env QXToken=your_quantum_api_token
   

   Note: you can check if the environment variable has been set by running the following in a notebook cell:

   import os
   print(os.getenv('QXToken'))

Usage

1. Open an exercise notebook

   • In IBM Quantum Lab, the notebooks can be found in the quantum-challenge folder in the Lab files panel
   • For local install, download the notebooks (from IBM Quantum Lab or specific challenge repo) and import into local Jupyter environment

2. Run the notebook cells, answering the exercises and submitting solution for grading. For example

   from qc_grader.challenges.challenge_2021 import grade_lab1_ex1 
   
   grade_lab1_ex1(qc_1)

   from qc_grader.challenges.challenge_2021 import grade_lab1_ex2 
   
   grade_lab1_ex2(qc_2)