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graph LR
    riko_bado_sux["riko.bado.sux"]
    riko_bado_microdom["riko.bado.microdom"]
    riko_dotdict["riko.dotdict"]
    riko_bado_sux -- "dispatches parsing events to" --> riko_bado_microdom
    riko_bado_microdom -- "provides structured data to" --> riko_dotdict
    riko_dotdict -- "accesses and manipulates data from" --> riko_bado_microdom
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Details

The Data Structuring & Parsing Utilities subsystem encompasses the core functionalities for ingesting raw data (XML, HTML, plain text), parsing it into an event stream, constructing an in-memory hierarchical representation, and providing a user-friendly interface for accessing and manipulating this structured data. This subsystem acts as the initial data transformation layer within the riko project, preparing raw input for further processing by other components.

riko.bado.sux

This component is the primary entry point for raw, unstructured data. It efficiently performs low-level parsing and tokenization of various structured text formats (e.g., XML, HTML). Its core responsibility is to transform the raw input into a stream of parsing events, adhering to the "Stream Processing Engine" and "Iterator Pattern" architectural biases by emitting events as data flows.

Related Classes/Methods:

riko.bado.microdom

Acting as an intermediary, this component consumes the parsing events generated by riko.bado.sux. It then constructs a lightweight, hierarchical in-memory Document Object Model (DOM) tree. This micro-DOM provides a structured, traversable representation of the parsed data, embodying the "Data Model" aspect of the project's expected components. It's crucial for transforming event streams into a coherent data structure.

Related Classes/Methods:

riko.dotdict

This component offers a convenient and Pythonic DotDict interface. Its purpose is to simplify programmatic access and manipulation of nested data structures, typically the micro-DOM tree produced by riko.bado.microdom. It enhances the usability of the parsed data, aligning with the "Modular and Composable" and "Separation of Concerns" architectural patterns by providing a clean abstraction over the underlying data structure.

Related Classes/Methods: