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by mckinsey
CLAUDE.md1.86 kB
# CLAUDE.md for `vizro-core` folder `vizro-core` contains all code for the core Vizro framework. ## Development ### Working Directory **Important**: All Hatch commands must be run from the `vizro-core/` directory. ### Additional Hatch Commands for vizro-core only - `hatch run example` - Run the scratch dev example on port 8050 (hot-reloads) - `hatch run example scratch_dev/yaml_version` - Run the scratch_dev yaml example on port 8050 (hot-reloads) - `hatch run example dev` - Run the feature example dashboard on port 8050 (hot-reloads) ## Project Architecture ### Key concepts - Vizro is based on Pydantic models to create a config driven dashboard framework. - The Pydantic driven config layer abstract away the underlying plotly/dash implementation. ### Core Vizro usage example ```python import vizro.plotly.express as px from vizro import Vizro import vizro.models as vm df = px.data.iris() page = vm.Page( title="My first dashboard", components=[ vm.Graph(figure=px.scatter(df, x="sepal_length", y="petal_width", color="species")), vm.Graph(figure=px.histogram(df, x="sepal_width", color="species")), ], controls=[ vm.Filter(column="species"), ], ) dashboard = vm.Dashboard(pages=[page]) Vizro().build(dashboard).run() ``` ### Important implementation notes - Add Vizro model must be derived from `VizroBaseModel` - Anything Dash related must only appear in the `build` method of a model ### Main folders - Source code: `src/vizro/` - Vizro models: `src/vizro/models/` - Tests: `tests/` - Documentation: `docs/` - Examples: `examples/` - Changelog: `changelog.d/` and `CHANGELOG.md` ## Workspace structure - `pyproject.toml`: Package configuration for vizro-core with dependencies - `hatch.toml`: Hatch configuration for the vizro-core folder, with all commands for task automation

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