Kaggle Auto-Deploy

A tool for automatically deploying multi-file Python projects to Kaggle.

Sample: https://www.kaggle.com/datasets/quochungcyou/housing-price-predictor-files https://www.kaggle.com/code/quochungcyou/multi-local-module-project-python-run-sample

Overview

This solution automatically converts any multi-file Python project into a Kaggle-compatible format by:

• Analyzing your project structure and dependencies
• Creating a Kaggle dataset containing all your project files
• Generating a Kaggle notebook that automatically downloads and runs your project
• Uploading everything to Kaggle via API

Guide

You can try command below to try deploy the sample housing price predictor project:

python kaggle_deploy.py ./housing_price_predictor

If you modify the code and redeploy again, you may need use Check Update option to update the dataset and notebook.

Prerequisites

1. Install Kaggle API

pip install kaggle

2. Configure Kaggle Credentials

   • Option A: API Token File
     • Go to https://www.kaggle.com/account
     • Click "Create New API Token"
     • Download kaggle.json
     • Place it in:
       • Linux/Mac: ~/.kaggle/kaggle.json
       • Windows: C:\Users{username}.kaggle\kaggle.json
   • Option B: Environment Variables

     export KAGGLE_USERNAME="your-username"
     export KAGGLE_KEY="your-api-key"

3. Set Permissions (Linux/Mac)

chmod 600 ~/.kaggle/kaggle.json

Installation & Setup

1. Download the Deployer Script

git clone https://github.com/yourusername/kaggle-auto-deploy.git
cd kaggle-auto-deploy

2. Make it Executable (Linux/Mac)

chmod +x kaggle_deployer.py

3. Optional: Add to PATH (Linux/Mac)

# Add to ~/.bashrc or ~/.zshrc
export PATH="$PATH:/path/to/kaggle_deployer"

Usage

Basic Usage

python kaggle_deployer.py /path/to/your/project

Sample Project

This repository includes a sample project called housing_price_predictor that demonstrates how to structure a multi-file Python project for deployment to Kaggle.

python kaggle_deploy.py ./housing_price_predictor

Project Structure

housing_price_predictor/
├── main.py          # Entry point
├── data_loader.py   # Data loading and preprocessing
├── model.py         # Model training and evaluation
├── utils/
│   └── helpers.py   # Utility functions
├── data/
│   └── housing.csv  # Sample data
└── requirements.txt # Dependencies

Running the Sample Project

# Run locally
cd housing_price_predictor
python main.py

# Deploy to Kaggle
python kaggle_deployer.py ./housing_price_predictor

License

MIT