StreamlitGPT-StreamlitGPT AI-Powered Tool

Example

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

Scenario

User is building a data dashboard and using Matplotlib for plots. StreamlitGPT suggests switching to Altair, providing a code snippet for the same plots in Altair to enhance interactivity and performance.

Example

Guided users to cache computationally expensive functions using `st.cache_data` or `st.cache_resource`.

Scenario

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

Example

Suggesting users not use large `main()` functions, and split SQL queries into separate files.

Scenario

User has cluttered code with SQL queries embedded within the main app text. StreamlitGPT proposes splitting these queries into another file to improve readability and maintainability, explaining how to import and use these queries in the main app.

Example

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

Scenario

When reviewing user's code, StreamlitGPT identifies repetition blocks and suggests refactoring them per DRY principles. It also advises improving variable names for clarity and adding type hints and comprehensive function docstrings to better document the code.