README.md

metadata

title: Travel Prophet Forecaster
emoji: ✈️
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.32.0
python_version: '3.10'
app_file: app.py
pinned: false

✈️ Travel Demand Forecaster — Prophet + Streamlit

A time series forecasting app for travel demand using Facebook Prophet, deployed via CI/CD to Hugging Face Spaces.

---

🚀 CI/CD Pipeline

Push code to GitHub
        ↓
GitHub Actions triggers
        ↓
🧪 Run all tests (CI)
        ↓
✅ Tests pass?
        ↓
🤗 Auto deploy to Hugging Face (CD)
        ↓
🌐 App is live!

---

🛠️ Setup Instructions

Step 1 — Fork or clone this repo

git clone https://github.com/YOUR_USERNAME/travel-prophet.git
cd travel-prophet

Step 2 — Create Hugging Face Space

1. Go to https://huggingface.co/spaces
2. Click Create new Space
3. Choose Streamlit as SDK
4. Name it e.g. travel-prophet-forecaster

Step 3 — Add HF Token to GitHub Secrets

1. Go to https://huggingface.co/settings/tokens
2. Create a new token with write access
3. Go to your GitHub repo → Settings → Secrets and variables → Actions
4. Click New repository secret
5. Name: HF_TOKEN, Value: (paste your token)

Step 4 — Update deploy.yml

In .github/workflows/deploy.yml, replace:

YOUR_HF_USERNAME  →  your Hugging Face username
YOUR_SPACE_NAME   →  your Space name

Step 5 — Push to GitHub

git add .
git commit -m "Initial commit"
git push origin main

Step 6 — Watch it deploy! 🎉

Go to your GitHub repo → Actions tab to watch the pipeline run.

---

📁 Project Structure

travel-prophet/
├── app.py                          # Main Streamlit app
├── requirements.txt                # Dependencies
├── tests/
│   └── test_app.py                 # All tests (CI runs these)
├── .github/
│   └── workflows/
│       └── deploy.yml              # CI/CD pipeline definition
└── README.md

---

🧪 Run Tests Locally

pip install -r requirements.txt
pip install pytest
pytest tests/ -v

---

📊 Features

• Upload your own CSV travel data
• Sample data included for demo
• Adjustable forecast period (30–365 days)
• Yearly and weekly seasonality
• Confidence intervals
• Downloadable forecast CSV
• Interactive Plotly charts

---

🔄 How CI/CD Works

Travel Prophet Forecaster

Event	What Happens
Push to main	Tests run → if pass → deploy to HF
Pull Request	Tests run only → no deployment
Tests fail	Pipeline stops → no deployment
Tests pass	Auto deploys to Hugging Face Spaces