Code
How plotly/dash is laid out, and where to start for common changes.
There is no import map for this report yet.
Where to start reading
- Repository root
- Repository root
- Likely public API
- Likely public API
- Likely start-up file
- Suggested starting pointAI
- Suggested starting pointAI
- Suggested starting pointAI
Find files for a task
AIAdd a New Callback
- Use the @app.callback() decorator to bind component properties to Python functions
- The callback system automatically serializes/deserializes JSON payloads via websocket
Add a New Component Type
- Run component generation to auto-create Python wrapper classes
- Generated class inherits from base_component.Component and registers props/callbacks
Add a Multi-Page Application
- Register pages using @page decorator or register_page() call
- Use dcc.Location component to capture current pathname and conditionally render layouts
Configure Persistent Storage
- Choose storage backend: Redis, diskcache, or local memory in _shared_storage/
- Pass storage instance to dcc.Store or use dcc.Store with persistence=True flag
- Storage layer automatically syncs data across browser tabs via websocket polling
Change the public API
Trace runtime behavior
Add or update tests
Change build or automation
RepoPilot lists up to 500 files, so a file missing here may still exist.
- Files marked “likely” are guessed from their names.