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Assess your internal programmers on a regular basis using Jupyter notebooks - A probable way to enrich and baseline developers

 

  1. Install Jupyter: To build a Jupyter notebook environment, you will first need to install Jupyter on your computer. You can do this by installing Anaconda, which includes Jupyter, or by installing Jupyter separately.

  2. Install nbgrader: nbgrader is a tool that allows instructors to create and grade assignments in Jupyter notebooks. You can install nbgrader by running the command “pip install nbgrader” in your command prompt.

  3. Create assignments: Once nbgrader is installed, you can create assignments using Jupyter notebooks. nbgrader provides several commands that allow you to create assignments, add test cases, and grade them.

  4. Create a JupyterHub server: JupyterHub is a tool that allows multiple users to access Jupyter notebooks on a single server. This can be useful for a programming class, where multiple students need to access the same assignments. You can create a JupyterHub server by installing JupyterHub and configuring it to work with nbgrader.

  5. Integrate with a Learning Management System (LMS): Integrating JupyterHub with a LMS such as Canvas, Blackboard, or Moodle allows students to access the assignments and submit their work. It also allows instructors to easily grade and provide feedback on the assignments.

  6. Add a test runner: To add test cases to the assignments and run them automatically, you can use test runners such as nose or pytest. This allows students to automatically check their code against test cases and get instant feedback.

  7. Provide feedback and grades: Finally, you can use the nbgrader commands to grade the assignments and provide feedback to students. You can also use the JupyterHub server to track student progress and access the graded assignments.

It's important to note that this process might require some technical knowledge and experience in order to set it up correctly. If you need additional help or support, you can reach out to the Jupyter community or consider hiring a professional developer.

What are the options available other than say mbgrader, a quick check on google provides a gamut of projects that help in achieving this goal

  1. nbgrader: nbgrader is an open-source tool that allows instructors to create and grade assignments in Jupyter notebooks. It supports multiple programming languages and can be easily integrated with other tools such as JupyterHub and GitHub.

  2. Jupyter Notebook Evaluator: Jupyter Notebook Evaluator (JNE) is another open-source tool that allows instructors to create and grade assignments in Jupyter notebooks. It has a built-in test execution engine and supports multiple programming languages.

  3. Autograder: Autograder is a cloud-based tool that allows instructors to create and grade assignments in Jupyter notebooks. It supports multiple programming languages and can be easily integrated with other tools such as GitHub and Canvas.

  4. JupyterLab-grading-extension: JupyterLab-grading-extension is a JupyterLab extension that allows instructors to grade Jupyter notebooks in-place. It supports multiple programming languages and can be used in conjunction with other tools such as GitHub.

  5. Gradescope: Gradescope is a cloud-based tool that allows instructors to create and grade assignments in Jupyter notebooks. It supports multiple programming languages and can be easily integrated with other tools such as Canvas and Blackboard.

  6. Jupyter Notebook Checker: Jupyter Notebook Checker (Jupyter nbchecker) is a command-line tool that checks the quality of Jupyter notebooks. It can be used to check the code, markdown, and outputs of the notebooks, and it supports multiple programming languages.

  7. Jupyter Test: Jupyter Test is a command-line tool that allows instructors to run test cases on Jupyter notebooks. It supports multiple programming languages and can be easily integrated with other tools such as GitHub and Travis CI.


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