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I've always had a keen interest in both graffiti and computers.
When I was first getting into designing graffiti pieces and making street art, I found it difficult to find a centralized database for inspiration or to quickly check if certain names or styles were overused.
This personal challenge was the driving force behind creating this platform.
Contribute anonymously to a worldwide street art database – Discover art from across the globe, or easily find pieces nearest to your location to explore local scenes.
I have been actively developing this project since early January 2025. This entire endeavor has been an incredibly insightful journey, truly guiding me through learning a multitude of modern development concepts and practices. Building this application from the ground up served as a practical bootcamp, pushing me to understand how different components integrate to deliver a functional and interactive platform. Teaching me better than any tutorial.
This project is built predominantly with Python and features a dynamic web-based interface crafted using Streamlit. Interactive elements and application structure are developed within the Streamlit framework for web application functionality.
For crucial interactive map functionality, streamlit-folium is utilized, seamlessly integrating Folium maps. Folium leverages underlying technologies like Leaflet.js and OpenStreetMap data to render engaging geographical visualizations, facilitating spatial data representation and web mapping.
On the backend, a robust data management system is implemented using PostgreSQL. This involves database design, persistence, and the execution of various SQL requests, enabling data insertions and complex queries for effective information retrieval and management.
Beyond the main components, the project incorporates API interactions and web requests for communication with outside services. Python's requests library is used to send specific GET requests for precise geocoding (e.g., Nominatim API integration). Cloudflare R2 is integrated for efficient storage and serving of media assets (e.g., graffiti images), leveraging its S3-compatible API for cost-effective, global content delivery. This includes handling HTTP headers and managing network errors, with JSON data processing for application use.
Foundational web styling is achieved with HTML and CSS, directly tweaking Streamlit's user interface aesthetics using st.markdown.
Thanks to all the contributors behind these amazing open-source tools and libraries! ❤nbsp;❤
To install all requirements at once run pip install -r requirements.txt
(I recommend you do this in a new virtual environment.)
- Python 3.13:
- Streamlit (Version 1.45.1): (Python package) Install via pip:
pip install streamlit==1.45.1 - Pillow: (Python package) Install via pip:
pip install Pillow - requests: (Python package) Install via pip:
pip install requests - folium: (Python package) Install via pip:
pip install folium - streamlit-folium: (Python package) Install via pip:
pip install streamlit-folium - bcrypt: (Python package) Install via pip:
pip install bcrypt - captcha: (Python package) Install via pip:
pip install captcha
- Streamlit (Version 1.45.1): (Python package) Install via pip:
This software is licensed under the MIT License.
See the LICENSE.txt file for detailss