Streamlit Sage-Streamlit UI Enhancer

Example

Streamlit Sage provides code snippets for integrating various chart libraries like Matplotlib, Plotly, and Altair into Streamlit apps, enabling rich, interactive data visualizations.

Scenario

A data scientist wants to visualize sales data over the past year with interactive charts that allow users to filter by product category. Streamlit Sage can offer guidance on creating these visualizations seamlessly within a Streamlit app.

Example

Guidance on creating sliders, buttons, text inputs, and other interactive elements to capture user input and dynamically update app content.

Scenario

Building a mortgage calculator that allows users to adjust interest rates, loan amount, and term to see how these variables affect monthly payments. Streamlit Sage would provide examples of how to implement these UI elements.

Example

Instructions on how to use CSS and HTML to customize the appearance of Streamlit apps, enhancing the user interface beyond the default styling options.

Scenario

A developer needs to align the company branding with their Streamlit app's design, requiring custom fonts, colors, and layouts. Streamlit Sage would assist by demonstrating how to apply these styles.

Example

Techniques for managing large datasets efficiently, including caching to speed up data loading and processing within the app.

Scenario

An app that processes and displays real-time streaming data from IoT devices. Streamlit Sage can provide advice on optimizing data handling to ensure the app remains responsive.

Example

Streamlit Sage can offer insights into deploying machine learning models within Streamlit apps, including real-time predictions and incorporating user feedback to improve model accuracy over time.

Scenario

A machine learning engineer wants to deploy a text classification model and use active learning to refine the model based on user feedback. Streamlit Sage would guide the integration of these components.