RateFlow

RateFlow is a lightweight, end-to-end data pipeline built with Python.
It automatically fetches live currency exchange rates from free APIs, stores them locally, and visualizes historical trends in an interactive Streamlit dashboard.

🚀 Features

• Automated ETL: Extracts, transforms, and loads daily exchange rate data.
• Open APIs: Uses Frankfurter API.
• Local Storage: Saves data in a SQLite database for persistence and analysis.
• Interactive Dashboard: Explore and visualize currency trends over time with Streamlit.

🏗️ Tech Stack

• Python 3
• Pandas – data processing
• SQLAlchemy + SQLite – local database
• Streamlit – dashboard and visualization
• Requests – API data fetching
• Altair – Interactive data visualization

📦 Project Structure

RateFlow/ ├── dashboard/ │ └── app.py ├── etl/ │ ├── extract.py │ ├── load.py │ └── scheduler.py ├── data/ │ └── exchange_rates.db ├── requirements.txt ├── .gitignore └── README.md

🧭 Getting Started

1. Clone the repo

git clone https://github.com/<your-username>/rateflow.git
cd rateflow

2. Set up env

Option A: Create a virtual environment

python -m venv venv
source venv/bin/activate   # macOS/Linux
venv\Scripts\activate      # Windows

Option B: Create a conda environment

conda create -n rateflow python=3.11
conda activate rateflow

3. Install dependencies

pip install -r requirements.txt

4. Run ETL pipeline

python etl/load.py

5. Launch dashboard

streamlit run dashboard/app.py