A Public Scraping API as an Experimental Layer for Market Data Exploration
This working paper investigates how a centralized, API-based scraping service can be used as an experimental layer for accessing and exploring large-scale e-commerce data without exposing end users to the operational complexity of scraping itself. Rather than focusing on scraping techniques or reverse engineering, the paper examines the architectural and design implications of wrapping scraping logic behind a controlled HTTP interface.
The investigation is applied and exploratory in nature. It uses the eBay Scraper API as a concrete case to reflect on how concerns such as authentication, concurrency control, retries, and error normalization can be abstracted away from consumers, enabling faster experimentation and prototyping. The paper does not aim to evaluate scraping legality, long-term robustness, or competitive performance against official APIs.
As a working paper, this document does not present finalized results or generalized claims. Instead, it frames a set of design decisions, constraints, and observed behaviors that emerge when scraping is treated as a shared infrastructure component rather than an ad-hoc script. The intent is to stimulate reflection on scraping-as-a-service as a pedagogical and research-oriented construct, particularly in contexts where official APIs are limited, unavailable, or insufficient for exploratory analysis.
General Information
Motivation
Scraping remains a common but fragile technique in data engineering and market analysis. In practice, many teams rely on isolated scripts with inconsistent error handling, duplicated logic, and little observability. The motivation behind this investigation is to explore whether centralizing scraping behind a thin API layer can reduce this fragmentation and make exploratory access to market data more systematic and reusable.
The eBay Scraper API was designed as a public utility rather than a production-grade service. Its primary goal is to support experiments, prototypes, and research workflows that require access to product, seller, and pricing information without embedding scraping logic directly into each consumer application.
Scope and assumptions
This work focuses on HTTP-based scraping of publicly accessible eBay product and seller pages, exposed through a REST API with API key enforcement. It assumes non-adversarial usage, moderate traffic, and consumers who are aware that data completeness and stability are not guaranteed.
The API is treated as a black box from the client perspective. The internal scraping mechanics are not analyzed in detail, as the investigation centers on interface design, control boundaries, and usage patterns rather than scraping internals.
Non-goals
This paper does not aim to benchmark scraping performance, ensure long-term availability, or compare results against official eBay APIs. It does not address legal, ethical, or contractual considerations of scraping beyond acknowledging their existence. Real-time guarantees, strict SLAs, and high-availability architectures are explicitly out of scope.
Status of the investigation
The system is considered experimental and best-effort. Endpoints, payload shapes, and behavior may change without notice. Findings reflect observations from the current version of the API rather than a stable or finalized design.
