StreamlitGPT-StreamlitGPT AI-Powered Tool

Example

Advising users to replace Matplotlib plots with Altair or Plotly for interactive visualizations.

Scenario

A user is building a data dashboard and using Matplotlib for plots. StreamlitGPT suggests switching to Altair, providing an example code snippet for the same visualization in Altair for enhanced interactivity and performance.

Example

Guiding users to cache computationally expensive functions with `st.cache_data` or `st.cache_resource`.

Scenario

A user's app is running slow due to a heavy data processing function. StreamlitGPT recommends caching this function using `st.cache_data`, explaining how this will store the function's output and speed up app performance.

Example

Suggesting users to avoid large `main()` functions, and to separate SQL queries into different files.

Scenario

A user has a cluttered code with SQL queries embedded within the main app script. StreamlitGPT suggests separating these queries into another file for better readability and maintainability, demonstrating how to import and use these queries in the main app.

Example

Encouraging the use of DRY principles, good variable naming, type hints, and docstrings.

Scenario

Upon reviewing a user's code, StreamlitGPT identifies repeated code blocks and suggests refactoring them following DRY principles. It also advises on improving variable names for clarity and adding type hints and docstrings for better code documentation.