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Settings editor

As explained in Build Python Web Apps with Streamlit

A settings editor is a user-interface pattern for viewing and changing configurable application options.

A settings editor gives users a visible place to view and change application options. In Streamlit, an editable dataframe provides a spreadsheet-like interface for choices such as quizmaster and difficulty. section 9.7.1

A practical settings editor:

  • Uses fixed rows when each setting should have exactly one value. section 9.7.1
  • Keeps edited values across Streamlit reruns through widget and session-state handling. section 9.7.1

Game settings

A Fact Frenzy app places the editor inside a Settings popover, offering Quizmaster and Difficulty choices. The returned settings update the running Game object, which uses them when generating questions.

How Build Python Web Apps with Streamlit covers it

How deep it goes
Implements editable dataframes, fixed rows, constrained columns, widget keys, and rerun state, stopping at in-session persistence.
Examples
Uses Quizmaster and Difficulty fields, selectbox options, a Settings popover, and a Fact Frenzy game.
What it assumes
Assumes familiarity with Streamlit and pandas dataframes while introducing editable dataframe widgets through a concrete application.
What you can do after
Build an editable Streamlit settings panel and pass its returned values into application logic.
How it connects
Connects Streamlit, pandas dataframes, session state, popovers, and application settings.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Build Python Web Apps with Streamlit. The section links point to the parts of the book it draws on.