learning-lab_submission

To prepare and validate lab assignments for Brightspace, you can use an automated script to check required files, ensure proper naming conventions, and generate a clean zip package. This reduces submission errors and potential point deductions by verifying all requirements are met.

The best way to package a programming lab submission is to use an automated validation script that verifies the presence of source code, notebooks, and documentation, then automatically archives them into a single organized zip file for upload.

Yes, you can automatically check if your Python script and Jupyter notebook meet lab submission requirements by running a validation script that scans your directory for missing files and incorrect naming conventions before packaging.

The lab submission validation script supports PDF reports and Word documents by utilizing pdfplumber and pypdf dependencies to process files, ensuring your documentation is correctly identified and packaged into the final zip archive.

Lab submission validation fails when packaging files into a zip archive if required files are missing from the directory or if the files do not follow the strict naming conventions expected by the automated checking script.

Limitations of using a Python script to automate assignment preparation include its dependency on specific directory structures and predefined file names, meaning it cannot dynamically adapt to custom submission requirements outside its configured validation rules.