Python developers frequently utilize Streamlit to rapidly develop interactive web applications, particularly when paired with InfluxDB 3 Core, a time series database optimized for high-ingest, time-stamped data. This combination offers a Python-friendly alternative to traditional visualization tools like Grafana or Power BI, enabling advanced customization and domain-specific functionality. Streamlit allows quick prototyping of bespoke applications, while InfluxDB 3's Python client simplifies data querying and analysis. A sample project demonstrates integrating these tools by storing and visualizing stock and cryptocurrency prices in real-time, providing a foundation for extending applications to financial use cases such as real-time tracking and technical analysis. This approach empowers developers to create tailored applications for various fields, such as IoT monitoring, financial analytics, or devops observability, offering complete control over data pipelines and user interfaces.