Instruction file imported from Esbern/Lecture-5-exercise (.github/instructions/20-osm-workflow-recommendation.instructions.md). Copyright stays with the author.

OSM Workflow Recommendation

Recommended

• Prefer OSMnx as the default OSM acquisition path for Python-based analysis.
• Configure OSMnx to cache into the project .cache/ folder: ox.settings.cache_folder = ".cache/".
• Let library defaults choose the Overpass endpoint unless there is a documented reason to override.
• Use direct curl + raw Overpass queries primarily as fallback or for reproducible low-level debugging.
• Keep OSM workflows split into stage scripts where practical:
  • fetch/download
  • analysis/modeling
  • visualisation/export
• Deliver OSM workflows stage-by-stage by default, not as a pre-authored full pipeline.

Required

• Store raw binaries in 00_Binary/raw/ first.
• Keep 03_Sanctuary/ logical-only (manifests, lineage, descriptors), with no binary payloads.
• Log provenance in 03_Sanctuary/raw/_manifest.md and lineage in 03_Sanctuary/Sanctuary_Index.md.
• Do not generate downstream OSM stage scripts before the prior stage has completed and been validated.
• Wait for user confirmation between OSM stages unless the user explicitly requests full pipeline creation.
• After each OSM stage, emit a user validation checkpoint including output paths and at least one sanity metric.
• Document OSM task logic in user-facing terms, including:
  • key tag filters or query scope
  • network type assumptions (walk, bike, drive)
  • geometry/boundary clipping rules
  • where this logic is implemented in script files

Fallback

• If OSMnx retrieval fails or rate limits persist, retry with an alternative endpoint and capture the rationale in Design_Rationale.md.