SparkyBudget
Open-source personal finance web app for tracking accounts and budgets
117 stars 7 forks last commit first released
Actively maintained
Last commit 18 Jul 2026.
SparkyBudget is an open-source personal finance web application that helps users track accounts (Checking, Credit Card, Loan), manage budgets and recurring items, and analyze historical spending and net cash over time. It is delivered as a Flask-based web app with a dark-themed UI and is prepared for Docker-based deployment.
Key Features
- Account tracking for multiple account types (checking, credit, loan) and transaction history.
- Budget creation and recurring budget/transaction support for monitoring periodic expenses.
- Spending analysis and historical views to evaluate net cash and trends.
- Local SQLite database shipped as demo/sample DB for testing and import (demo DB included in repository).
- Implementation details: Flask backend, gunicorn WSGI server, Python 3.10-compatible code, and Docker/Docker Compose deployment files for easy local hosting.
Use Cases
- Personal finance tracking for individuals who prefer a self-hosted, privacy-focused budget tool.
- Testing and development: reviewers or contributors can run the included demo SQLite DB to explore features without connecting bank APIs.
- Home server / local Docker deployment for small households wanting historical spending analysis and simple budgeting.
Limitations and Considerations
- Integrations: the project references a third-party SimpleFin token flow for importing transactions; token handling is single-use and requires manual reset steps described in the repository README.
- Feature maturity: repository is focused on core budgeting and analysis — advanced features like multi-user accounts, real-time bank integrations, or mobile apps are not present in the source repository.
SparkyBudget provides a concise, self-hostable budgeting web app suitable for individuals who want a straightforward Flask-based solution for tracking accounts and budgets. The repository includes Docker Compose, an example .env, and a demo SQLite database to get started quickly.
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