🛠️ DevUtils

A collection of simple automation tools for developers and data scientists

Lightweight command-line tools that automate repetitive tasks in machine learning and file management workflows.

Explore Tools
HFPusher
DropSync
NbClean
DBignore

🚀 Projects

1️⃣

HFPusher

Push your ML models to Hugging Face in one command.

Store credentials in .env file
Upload entire model folder
Auto-create repos

Perfect for: Quickly sharing trained models without manual uploads.

2️⃣

DropSync

Automatically backup folders to Dropbox, skip the junk.

Set source and destination once
Skip cache and temp files
Schedule runs

Perfect for: Keeping important project files backed up without filling Dropbox with garbage.

3️⃣

NbClean

Shrink Jupyter notebooks by removing outputs and metadata.

Clean single notebook or folder
Remove outputs & exec counts
Show space saved

Perfect for: Sharing notebooks on GitHub or with teammates without messy diffs.

4️⃣

DBignore

Stop Dropbox from syncing files you want to keep local.

Mark files as ignored
Doesn't delete anything
Easy undo

Perfect for: Keeping datasets, models, or sensitive files local without Dropbox trying to upload them.

💡 Why These Tools?

Built by a data scientist who got tired of:

Manually uploading models
Dropbox syncing 50GB datasets
Massive notebook files clogging git repos
Repetitive file management tasks

Simple, scriptable, and actually useful.

terminal
$ hfpusher my-model/
✓ Model uploaded to huggingface.co/models/username/my-model
$ nbclean notebook.ipynb
✓ Cleaned notebook.ipynb (saved 2.3MB)

📦 Getting Started

1

Pick Your Tool

Choose the tool that best fits your workflow and requirements.

2

Configure Once

Each tool has its own folder with setup instructions. Follow the README.

3

Forget About It

Set it up once and let it work in the background. Simple, scriptable, and useful.

🌟 Discover More Projects

Enjoyed these tools?
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