I’m in a bit of a jam and could really use some help from anyone who’s had a similar problem. So, here’s what happened: I was working on my Jupyter notebook on Ubuntu, and in a moment of complete distraction, I ended up overwriting it. The last version I saved was from a few days ago, and I’ve made a lot of progress since then—like, A LOT. It’s super frustrating to think about all that work potentially going to waste!
I’ve been trying to figure out if there’s any way to recover the lost version of my notebook. I’ve done some basic digging online, but I don’t want to risk making things worse. Jupyter has this autosave feature, and I just want to know if there’s any chance it’s saved a backup somewhere that I’m just not seeing. I’ve searched the `~/.jupyter` folder and other places in my home directory, but no luck so far.
Is there a hidden cache or something that might be holding onto an older version? I’d love to hear if anyone has ever experienced this and managed to pull a rabbit out of the hat.
Also, if you’ve got any tips or tricks for future-proofing my Jupyter notebooks to prevent this kind of thing from happening again, I’m all ears. Should I be using version control or saving my notebooks in a different way? I know there are some cloud options out there, but I guess that depends on my internet speed and how critical that data is.
I’d really appreciate any advice, even if it’s just “that sucks, good luck,” at least I know someone else has been here before. If you have any common pitfalls to avoid too, that could save me some future heartache. Thanks in advance for any insight you’ve got!
Sounds like a tough situation! I’ve been there before, and it’s really frustrating to lose work like that. When it comes to Jupyter notebooks, there are a few things you can try to recover your lost version.
First off, Jupyter sometimes saves checkpoints automatically. You might want to check the following:
.ipynb_checkpoints
. You can access it by runningls -la
in your terminal.If that doesn’t work, sometimes your operating system might have backed up files. For example, some systems have a trash or recycle bin where deleted files might land. You can also check your system’s autosave or backup features, depending on how your Ubuntu is set up.
If none of this works, and you’ve been saving your work in a .ipynb file format, it’s a bit trickier. Unfortunately, if the autosave didn’t catch it and no checkpoints exist, it might be lost. But don’t lose hope just yet!
For the future, you might want to consider a few tips to avoid similar problems:
Hope this helps! It’s always a bummer when these things happen, but take it as a learning experience. Good luck, and I hope you get your work back!
It’s unfortunate to hear about your experience with the Jupyter notebook. While Jupyter does have an autosave feature, it typically saves the notebook state every few minutes and may not keep older versions of the files once they are overwritten. However, there are a couple of avenues worth exploring for recovery. Check the directory where your Jupyter notebooks are stored; often, Jupyter creates hidden checkpoints. Look for files named like `.ipynb_checkpoints` and see if there’s a backup version available in that folder. Additionally, if you have been running the notebook in a Jupyter server environment, you might find temporary files in the `~/.local/share/jupyter/` directory or similar locations on your filesystem. If you can’t find anything there, a tool like `extundelete` can be used to recover deleted files from ext filesystems, provided you haven’t written much new data after the overwrite.
For future-proofing your work, consider using version control systems like Git to manage your notebooks. You can utilize GitHub to store your notebook repositories, enabling you to track changes and revert to earlier versions easily. Another option is to save periodic backups of your notebooks manually or use automation scripts to handle this for you. Also, consider exploring cloud services, such as Google Colab or cloud storage with automatic sync features. These allow you to access and save your work without the risk of local data loss. Finally, if you are still working locally, make a habit of using the “Save As” feature to create dated copies at regular intervals. This will allow you to maintain a history of your work and reduce the stress of losing significant progress in the future.