Quantum Challenge Grader

Grading client for the IBM Quantum Challenge grading service.

Installation

Follow one of these steps to install the grading client.

• Run in IBM Quantum Lab
• Run in Docker
• Run locally

Run in IBM Quantum Lab

Pre-requisites:

• IBM Quantum account

The grader comes pre-installed in Quantum Lab and does not need to be installed.

Run in Docker

Pre-requisites:

• IBM Quantum account
• Docker installed

To install the dockerized grader client environment:

1. Create an env setting the following parameters. All parameters are optional and can be changed later

   • QXToken - IBM Quantum API Token (can be found in Account Details)
   • QC_GH_REPO - the org/repo name where exercise notebooks can be downloaded (e.g., qiskit-community/ibm-quantum-challenge-2021)
   • QC_GH_BRANCH - the branch in the repo to download notebooks (e.g., main)

   Note: All parameters are optional and can be updated later

   Example env file:

   QC_GH_REPO=qiskit-community/ibm-quantum-challenge-2021
   QC_GH_BRANCH=main
   QXToken=1df75f29d97a46caa689bae3e3f05f477376c81b7a1157b7fe413811f6cb13c0c032f3
   

2. From a command prompt, run

   docker run -it -p 8888:8888 --env-file=<env_file> qiskitcommunity/qc-grader
   

   where <env_file> is the path to the env created in step (1).

Once running open a browser and go to http://localhost:8888/lab to access the Jupyter environment. Additional information is available in the README.md in the Jupyter environment.

Run locally

Pre-requisites:

• IBM Quantum account
• Python (3.7 or later) environment with
  • Classic Jupyter Notebook interface or JupyterLab
  • Qiskit
    • pip install qiskit[all]
  • qiskit_textbook package
    • pip install git+https://github.com/qiskit-community/qiskit-textbook.git#subdirectory=qiskit-textbook-src

To install the grader locally:

1. In the Python environment, install the grading client

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

2. Configure the following environment variables

   • QC_GRADING_ENDPOINT - the URL to the grading server
   • QXAuthURL - IBM Quantum Authentication API URL
   • QXToken - IBM Quantum API Token (can be found in Account Details)

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 import grade_lab1_ex1 
   
   grade_lab1_ex1(qc_1)

   from qc_grader import grade_lab1_ex2 
   
   grade_lab1_ex2(qc_2)