Review a geospatial Python module
Overview
This question evaluates proficiency in geospatial data processing and Python code review, including detection of correctness bugs, numerical stability issues, CRS handling, performance optimization, refactoring, testing strategy, and security considerations when working with CSV/GeoJSON datasets.
You receive a Python module that processes geospatial datasets (CSV/GeoJSON) to compute distances, cluster nearby points, and write summaries. Perform a code review: identify correctness bugs, numerical issues, and edge cases (CRS mismatches, missing/invalid coordinates). Propose performance improvements (vectorization, spatial indexing such as R-tree, batching I/O), refactorings (modularization, type hints, docstrings), and security considerations (input validation, dependency pinning). Outline unit/integration tests with fixture data, estimate time/space complexity of critical paths, and suggest library choices (e.g., pandas, shapely, pyproj) with trade-offs.