Quick Start

This walkthrough covers the fastest path from installation to a working grading run.

1. Install InstantGrade

python3 -m pip install instantgrade

2. Launch the UI

instantgrade launch

Open the printed URL in your browser. If 8501 is unavailable, InstantGrade automatically uses the next free port.

3. Prepare your grading inputs

For notebook grading, gather:

  • one instructor solution notebook

  • one or more student notebooks

  • any supporting files required by the notebooks, such as .csv, .json, .txt, or spreadsheets

You can upload files directly in the UI or point to existing server paths.

4. Choose execution mode

  • Use local mode when Docker is not installed or not running

  • Use Docker mode only when Docker is installed and available

5. Start grading

In the UI:

  • upload the instructor notebook

  • upload the student notebooks

  • upload any additional data files if needed

  • choose local or Docker execution

  • run grading

When grading finishes, the UI shows the report and saves the run to the local InstantGrade runs directory.

6. Review and download results

From the UI you can:

  • open the generated HTML report

  • download the HTML report

  • download the PDF report when available

  • download the execution log

  • reopen earlier saved runs from run history

7. Generate a student notebook template

The UI can generate a student-facing notebook from an instructor solution notebook.

Use this when you want:

  • function stubs instead of instructor implementations

  • assertions removed from the student copy

  • a quick distribution-ready notebook template

Python API example

from instantgrade import InstantGrader

grader = InstantGrader(
    solution_file_path="data/python_example/sample_solutions.ipynb",
    submission_folder_path="data/python_example/submissions",
    use_docker=False,
)

report = grader.run()
report.to_html("reports/report.html")