This working paper investigates how a minimal API dedicated to XML and JSON conversion can function as an experimental layer for studying data interoperability in modern systems. Rather than focusing on performance optimization or comprehensive schema management, the paper explores the role of simple, stateless format transformation services in contemporary data pipelines.
The investigation is applied and conceptual in nature. It examines a FastAPI-based utility that exposes basic endpoints for converting XML to JSON and JSON to XML, alongside a status endpoint for observability. The goal is not to propose a universal solution for data serialization, but to reflect on how constrained utilities can support experimentation, learning, and integration across heterogeneous systems where legacy and modern formats coexist.
As a working paper, this document does not claim general applicability or production readiness. It presents observations derived from the current implementation, emphasizing design simplicity, explicit error handling, and ease of use. The paper aims to prepare the reader to think about format conversion not as a solved problem, but as a recurring interface challenge that reveals deeper questions about data structure, validation, and semantic loss across representations.
General Information
Motivation
Despite the widespread adoption of JSON as a dominant data interchange format, XML remains deeply embedded in legacy systems, enterprise integrations, and standardized protocols. Engineers frequently encounter scenarios where XML and JSON must coexist, requiring reliable conversion between formats. The motivation behind this investigation is to explore whether a deliberately simple API can reduce friction in these scenarios while making the limitations of format conversion more visible.
The XML/JSON Utility API was conceived as a public utility rather than a full-featured transformation engine. Its primary intent is to offer a lightweight interface for experimentation, prototyping, and educational use.
Scope and assumptions
This work focuses exclusively on syntactic conversion between XML and JSON representations. It assumes well-formed input and does not enforce schemas, namespaces, or semantic validation beyond basic parsing. The API operates in a stateless manner and assumes non-adversarial usage.
The service is positioned as an auxiliary tool rather than a core integration platform, and it is expected that consumers understand the potential ambiguity involved in mapping hierarchical XML structures to JSON objects and back.
Non-goals
This paper does not aim to address schema inference, XML namespaces, attribute preservation strategies, or round-trip fidelity guarantees. It does not attempt to standardize XML-to-JSON mappings or compare alternative serialization formats. Performance benchmarking, security hardening, and large-payload handling are explicitly out of scope.
Status of the investigation
The system is experimental and subject to change. Endpoints, behavior, and implementation details may evolve without notice. Observations reflect the current state of the API rather than a finalized or stabilized design.
Sections
Background and related context
Data interchange formats have evolved alongside computing paradigms. XML emerged as a flexible, self-describing format suited for document-oriented and enterprise workflows, while JSON gained prominence through its alignment with web applications and lightweight data exchange. Conversion between these formats is often treated as a mechanical task, yet practical experience shows that such transformations can introduce ambiguity and information loss.
Utility APIs that expose conversion functionality provide an opportunity to examine these issues explicitly, rather than hiding them within libraries or monolithic integration systems.
Conceptual model
The XML/JSON Utility API follows a straightforward conceptual model. Clients submit raw XML or JSON payloads to dedicated endpoints, and the service returns the corresponding transformed representation. The API does not persist state, enforce authentication, or apply schema constraints, reinforcing its role as a transient transformation layer.
A /status endpoint provides minimal operational insight, separating service liveness from functional correctness. CORS is enabled to facilitate experimentation across environments, further emphasizing accessibility over restriction.
Observations on transformation behavior
One observation arising from the implementation is that structural clarity in input data strongly influences the quality of the output. Simple, well-nested XML structures map cleanly to JSON, while more complex constructs—such as attributes, mixed content, or repeated elements—highlight the inherent subjectivity of conversion rules.
Error handling plays a critical role in this context. By returning explicit parsing errors and details, the API exposes failure modes that might otherwise remain implicit, encouraging users to reason about data quality rather than assuming seamless interoperability.
Trade-offs and limitations
The simplicity of the API is both its strength and its limitation. While it lowers the barrier to entry and supports rapid experimentation, it deliberately avoids addressing deeper concerns such as semantic preservation or schema alignment. This trade-off reinforces the idea that format conversion alone does not resolve interoperability challenges; it merely surfaces them.
Status & Next Steps
This work is currently exploratory and applied. Open questions include how users interpret lossy conversions, how schema-aware extensions could alter behavior, and whether explicit conversion policies improve or hinder usability.
Possible future directions involve experimenting with schema validation, namespace handling, configurable mapping strategies, and comparative studies between utility APIs and embedded library approaches. These questions remain intentionally open, reinforcing the role of this API as a laboratory rather than a definitive solution.
Bibliographic References
Fielding, R. Architectural Styles and the Design of Network-based Software Architectures. Doctoral Dissertation, 2000.
Bray, T. et al. Extensible Markup Language (XML) 1.0. W3C Recommendation, 2008.
ECMA International. The JSON Data Interchange Syntax. ECMA-404, 2017.
Kleppmann, M. Designing Data-Intensive Applications. O’Reilly Media, 2017.
Python Software Foundation. xmltodict and dicttoxml Documentation., 2023.