Reproducible Python Research Workflow for Financial Data

Reproducible Python research for financial data The problem Research runs can blur source data, assumptions, simulation results, and conclusions. I built a deterministic Python workflow that keeps those stages distinct and makes decisions traceable. The work The public repository shows data adapters, preflight checks, scenario simulation, diagnostics, evidence classification, decision records, and repeatable outputs. Tests and logs support review of how a result was produced. What this demonstrates Hands-on Python, data validation, reproducible analysis, and clear boundaries between observed inputs and modeled outputs. The repository is a research prototype; I make no claim of trading returns or production deployment.