FastHTML vs. Streamlit - The Dashboarding Face Off
PyCon DE
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FastHTML vs. Streamlit - The Dashboarding Face Off
532 просмотра · 1 г. назад
PyCon DE
5,31 тыс. подписчиков
532 просмотра · 1 г. назад
🔊 Recorded at PyCon DE & PyData 2025, April 25, 2025
https://2025.pycon.de/program/WCDPLP/
🎓 A hands-on comparison of FastHTML and Streamlit reveals how dashboard framework choices impact development complexity and maintainability at different scales.
Speakers:
Tilman Krokotsch
Description:
In this technical comparison, Tilman Krokotsch examines two Python frameworks for building interactive data dashboards: FastHTML and Streamlit. Through live demonstrations and code examples, he illustrates the key differences in implementation approaches, performance characteristics, and developer experience. The presentation explores fundamental aspects including data loading, interactive visualizations, authentication systems, and multi-page navigation. While Streamlit excels in rapid prototyping with its straightforward top-down execution model and rich ecosystem of integrations, FastHTML offers more granular control through its route-based architecture and HTMX foundation. Krokotsch demonstrates how Streamlit's simplicity can become a limitation when implementing more complex features like custom layouts or state management, whereas FastHTML's web-standard approach provides greater flexibility despite requiring more initial setup. The comparison culminates in a practical recommendation: Streamlit is optimal for quick, disposable dashboards, while FastHTML proves more suitable for maintainable, production-grade applications. Notably, FastHTML's adherence to web fundamentals offers developers transferable knowledge of HTML, CSS, and modern web architecture patterns.
⭐️ About PyCon DE & PyData:
The PyCon DE & PyData conference unite the Python, AI, and data science communities, offering a unique platform for collaboration and innovation. The PyCon DE & PyData 2025 conference, provided an exceptional experience, fostering deeper connections within the Python community while showcasing advancements in AI and data science. Attendees enjoyed a diverse and engaging program, solidifying the event as a highlight for Python and AI enthusiasts nationwide.
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Acknowledgements:
Special thanks to all the volunteers and sponsors who made this event possible.
About:
Python Softwareverband e.V.:
PySV is a non-profit that promotes the use and development of Python in Germany through events, education, and advocacy, fostering an open Python community.
NumFOCUS Inc.
supports open-source scientific computing by providing financial and logistical support to key projects like NumPy and Jupyter, promoting sustainable development and collaboration.
Pioneers Hub gemeinnützige GmbH:
is a non-profit fostering innovation in AI and tech by connecting experts and promoting knowledge exchange through events and collaborative initiatives.