How to backup Google Colab notebooks (without losing work)

Google Colab is amazing for quick experiments – until it suddenly disconnects, your runtime resets, and you realise you’ve just lost hours of work.

In this guide, we’ll walk through a simple way to protect your Colab projects so that even if the runtime dies, your notebook and project state are safe – and how NoteCapsule can give you an extra layer of safety beyond “just download the notebook”.

What can go wrong in Google Colab

• Idle timeouts shut down your runtime if you leave it for too long.
• Long training jobs can hit runtime limits and restart the machine.
• Temporary files in /content disappear when the runtime resets.
• Notebook revisions don’t always capture the state your results depended on.

A basic backup workflow (without any tools)

Before we bring NoteCapsule into the picture, here’s a simple baseline you can use today:

1. Keep your data in Google Drive or a mounted GCS bucket, not only in /content.
2. Regularly “Save a copy in Drive” or download your notebook after major changes.
3. Use clear file names like projectname_YYYYMMDD_stage.ipynb, not final2.ipynb.
4. Copy important outputs (plots, metrics, tables) to Drive as well.

This is better than doing nothing, but it still has gaps: no record of dependencies, no explicit data layout, and it’s hard to know which version produced your final results.

Adding NoteCapsule as a project snapshot layer

NoteCapsule is a small Python package that creates Capsules – project snapshots – from within your Colab notebook. Each Capsule is a folder with:

• a copy of your notebook,
• a suggested requirements_suggested.txt from your imports,
• a data_manifest.json describing the files you’re using,
• a README_template.md with run instructions.

!pip install notebookcapsule -q

from notebookcapsule import create_capsule

create_capsule(
    name="baseline_cnn",
    data_dirs=["./data"]   # or any paths you use in your notebook
)

This creates a timestamped folder under ./capsules/ (in your Drive-mounted project, for example) that you can zip, upload, or share later.

Where to store your Capsules

In Colab, a good pattern is:

/content/drive/MyDrive/your-project/
  notebook.ipynb
  data/...
  capsules/
    2025-11-23_baseline_cnn/
    2025-11-24_resnet_augment/

Because this lives in your Google Drive, your Capsules survive runtime resets and you can revisit specific project states months later.

When to create a Capsule

• After you get a first “baseline” model working end-to-end.
• After a big change (new model, new preprocessing, new dataset).
• Before refactoring or large code clean-up.
• Right before you share the project with a friend, guide, or recruiter.

Summary: Colab backups that don’t suck

• Don’t trust the runtime – store data and Capsules in Drive.
• Use clear notebook names and occasional manual downloads as a minimum.
• Add NoteCapsule as a project-level snapshot tool so you capture code, deps, and data layout together.