Streamlit is ideal for data scientists, analysts, and developers looking to rapidly prototype and deploy data-driven applications. It is recommended for those who prioritize simplicity, quick deployment, and seamless integration with Python code. Individuals or teams interested in building dashboards, ML model sharing platforms, or interactive reports will find Streamlit particularly useful.
Based on our record, Streamlit seems to be a lot more popular than Chart.js. While we know about 210 links to Streamlit, we've tracked only 1 mention of Chart.js. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Https://chartjs.org works well, but you have to call the update function yourself if you want to do some reactive updates. Source: about 4 years ago
Use Streamlit to visualize and test predictions interactively:. - Source: dev.to / 2 days ago
The only thing left to do then was to build something that could showcase the power of code ingestion within a vector database, and it immediately clicked in my mind: "Why don't I ingest my entire codebase of solved Go exercises from Exercism?" That's how I created Code-RAGent, your friendly coding assistant based on your personal codebases and grounded in web search. It is built on top of GPT-4.1, powered by... - Source: dev.to / about 1 month ago
Streamlit.io: Great documentation and reusable components to integrate with your AI application for rapid python front-end AI development. - Source: dev.to / about 1 month ago
The agent uses MCP to translate this into a DynamoDB query. Then, using Streamlit UI, results are returned in a structured format, making it easy to use. - Source: dev.to / 3 months ago
It's powered by something called "Streamlit" (https://streamlit.io). > A faster way to build and share data apps Website doesn't even load for me. I don't even know what to say...welcome to web dev 2025 edition. - Source: Hacker News / 3 months ago
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