navi/backend/pyproject.toml
Matt 9d684bef43 feat(offroute): numba A* with anisotropic Tobler, exponentially-inflated cost grid (combined #17+#18)
Replace MCP_Geometric in _pathfind_wilderness with a numba-jit anisotropic A* (new
astar.py): signed-slope speed (climbing != descending; tobler peaks at -0.05), hard
cliff, per-edge avg context multiplier, trail-takes-both via 256-entry lookup, per-edge
barriers (strict/pragmatic/emergency), multi-goal A* (first popped wins) with admissible
distance/base-speed heuristic. New compute_cost_multiplier_grid (slope-free context
multiplier) + exponential inflation (sigma=1.8; inf->HARD=50*p95 for blur, inf re-imposed).
numba>=0.59 added (numba 0.65.1).

fix: wilderness leg is always foot effort; mode parameter reserved for future flexibility.
_pathfind_wilderness keeps the mode param (threaded from _route_A/B/C) but hardcodes
cost_mode=foot for the cost grid, trail friction, speed function, base speed, and max
grade. Off-trail math for MTB/ATV/vehicle is not well-grounded and real-world wilderness
traversal is foot regardless (push the bike, walk past where the vehicle stops). User mode
still drives entry-point eligibility (query_radius highway filter) and Valhalla network
costing. Matches the original pre-#17 design: wilderness ALWAYS uses foot.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-25 15:15:36 +00:00

42 lines
1.7 KiB
TOML

[build-system]
requires = ["setuptools>=68"]
build-backend = "setuptools.build_meta"
[project]
name = "navi-backend"
version = "0.1.0"
description = "Echo6 navi-backend monorepo — Navi API services extracted from recon (decoupling project)."
requires-python = ">=3.10"
# Single workspace, single .venv. pytest is included so `pip install -e .` is the
# only setup step needed before running the test suite.
dependencies = [
"Flask>=3.0",
"gunicorn>=21",
"requests>=2.31",
"PyYAML>=6",
"psycopg2-binary>=2.9",
"pytest>=8",
# navi-geo (extraction #6): geocode engine + reverse bundle.
"usaddress>=0.5", # address parsing / intent classification
"rapidfuzz>=3", # reranker fuzzy string scoring
"cachetools>=5", # reverse-bundle TTLCache
"shapely>=2", # timezone point-in-polygon
"numpy>=1.24", # planet-DEM tile decode
"Pillow>=10", # planet-DEM Terrarium WebP decode
"pmtiles>=3", # planet-DEM PMTiles reader
# navi-offroute (extraction #8): off-network router + readers.
"scikit-image>=0.22", # MCP_Geometric least-cost pathfinding (router.py)
"numba>=0.59", # navi-offroute anisotropic A* JIT pathfinder (astar.py)
"rasterio>=1.3", # barriers/wilderness/trails/friction raster readers
"psutil>=5.9", # MEMORY_LIMIT_GB enforcement in router.py
# scripts/overture_import.py: Overture Places ETL (S3 Parquet -> overture PG).
"duckdb>=1.5", # S3 Parquet read for the overture import script
]
[tool.setuptools.packages.find]
where = ["."]
include = ["shared*", "services*"]
namespaces = true
[tool.pytest.ini_options]
testpaths = ["services", "shared"]