graph LR
d3py_Figure_API["d3py.Figure API"]
Data_Spec_Processor["Data & Spec Processor"]
Geometric_Scale_Definitions["Geometric & Scale Definitions"]
Web_Asset_Generator["Web Asset Generator"]
Local_Server_Browser_Renderer["Local Server & Browser Renderer"]
d3py_Figure_API -- "Initiates Data Transformation & Spec Generation" --> Data_Spec_Processor
d3py_Figure_API -- "Incorporates Visual Definitions" --> Geometric_Scale_Definitions
d3py_Figure_API -- "Orchestrates Asset Generation" --> Web_Asset_Generator
Data_Spec_Processor -- "Provides Data & Vega Specs" --> Web_Asset_Generator
Geometric_Scale_Definitions -- "Contributes JS/CSS Snippets" --> Web_Asset_Generator
Web_Asset_Generator -- "Outputs Renderable Assets" --> Local_Server_Browser_Renderer
d3py_Figure_API -- "Initiates Local Serving" --> Local_Server_Browser_Renderer
click d3py_Figure_API href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/d3py/d3py_Figure_API.md" "Details"
click Data_Spec_Processor href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/d3py/Data_Spec_Processor.md" "Details"
click Geometric_Scale_Definitions href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/d3py/Geometric_Scale_Definitions.md" "Details"
The d3py architecture is centered around a Python-driven pipeline for generating interactive D3.js or Vega visualizations. The d3py.Figure API serves as the user's primary interaction point, orchestrating the entire visualization creation process. It delegates data preparation to the Data & Spec Processor, which transforms Python data into JSON and can generate Vega specifications. Concurrently, the API integrates visual definitions from Geometric & Scale Definitions, which define the plot's visual elements and their scaling. All these components feed into the Web Asset Generator, responsible for compiling the final HTML, JavaScript, and CSS files. These self-contained web assets are then either saved to disk or served by the Local Server & Browser Renderer, enabling the interactive visualization to be displayed in a web browser. This architecture emphasizes a clear separation between the Python backend's data processing and code generation, and the client-side browser's rendering capabilities.
d3py.Figure API [Expand]
The primary interface for users to define, configure, and initiate the visualization build process. It acts as the central orchestrator for the entire visualization pipeline.
Related Classes/Methods:
d3py.figure.Figure.__init__d3py.figure.Figure.showd3py.figure.Figure.saved3py.figure.Figure._build
Data & Spec Processor [Expand]
Responsible for ingesting raw Python data (e.g., Pandas DataFrames), transforming it into JSON, and generating declarative Vega specifications.
Related Classes/Methods:
d3py.pandas_figure.PandasFigure._data_to_jsond3py.figure.Figure._save_datad3py.vega.Vega.tabular_datad3py.vega.Vega.build_vega
Geometric & Scale Definitions [Expand]
Defines the visual components (geoms like bars, lines, axes) and their associated D3.js/CSS properties, including data-to-visual scale mappings. These are the building blocks of the visualization.
Related Classes/Methods:
Aggregates and formats all necessary client-side assets (JavaScript, CSS, HTML) into a self-contained web page, ready for display.
Related Classes/Methods:
Provides a temporary HTTP server to serve the generated web assets and represents the external web browser environment where D3.js/Vega executes to render the interactive visualization.
Related Classes/Methods: