Keep Python coursework environments separate

Start from the module instructions

Record the Python version, package requirements and editor or notebook environment the course expects. Check whether the department provides a setup file or a hosted service. Follow that route before adding a separate collection of tools from online tutorials. Similar-looking examples can depend on different versions or assumptions.

Create a project folder for the module or assignment in the approved storage location. Put the brief and a short setup note there, keeping restricted data in the university's required location. Avoid scattering scripts between downloads and the desktop. A clear folder gives commands and relative file paths a predictable starting point.

Create the environment deliberately

Use the documented environment command or the course's supported tool from the intended project location. Check which Python interpreter creates the environment. The name of an environment folder alone does not establish which version it contains. Keep the creation method in the setup note so you can reproduce it later.

Activate or select the environment as the course instructions require, then confirm the interpreter used by your editor or notebook. A terminal and an editor can otherwise point at different installations. If an import works in one place but fails in another, compare those interpreter selections before repeatedly installing the same package.

Install only what the task requires

Use the module's requirements file or named packages from the intended official package source. Avoid copying installation commands without understanding which environment they affect. Read unexpected prompts or errors and ask for help when they conflict with the course guide. More packages do not automatically make a student setup more capable or reliable.

After installation, run a small exercise provided by the course and save the result. Note the working versions or retain the supplied environment specification. If a later task requires a change, record the reason. This creates an explanation for the setup rather than an accumulation of commands nobody can reconstruct.

Diagnose before rebuilding

When a script fails, save the exact error and identify whether it concerns a missing package, a missing file, an incorrect path or the code itself. Check that you are running the expected project and interpreter. A file-not-found error does not usually become clearer by reinstalling the entire programming language.

If you need help, provide a minimal permitted example and the environment details, removing credentials and restricted data. Explain what you expected and what happened. Keep your original coursework safe before experimenting with a fix. A short, reproducible problem helps a tutor identify the issue without reviewing your whole computer.

Prepare a reproducible submission

Read the assessment instructions for what to submit: source files, notebook, dependency information, data or a report. Do not include an entire virtual-environment folder unless explicitly required. Preserve the source and the information needed to recreate its dependencies through the supported process. Check any data-sharing restrictions separately.

Test the submission in the course's intended way, ideally from a clean permitted copy of the project. Confirm that paths do not depend on an unexplained folder elsewhere on your laptop. New hardware is rarely the first answer to a package mismatch; choose related products only if a demonstrated course requirement exceeds the device you already have.

Your next steps

• Follow the module’s environment method.
• Confirm the interpreter in each application.
• Retain the working dependency specification.
• Test the submission from a clean permitted project copy.

Keep planning

• Keep coursework backed up and practise getting it back
• Make spreadsheet coursework easy to check and reproduce
• Package code coursework so it runs beyond your own laptop
• Build a keyboard workflow for reading and editing coursework