- webapp.py: FastAPI serving the continuous map (port 8973) with /api/preview, /api/generate and /api/status; tiles are downloaded from IGN and processed in a logged subprocess, tracked live in a side "File de génération" panel that survives page reloads - fetch_ign.py: download missing 1 km LiDAR HD tiles from the IGN geoplateforme before processing - index.py: tile thumbnails and 500 m subtiles are now invalidated by mtime so regenerating a tile refreshes its cached images; progress logging per tile - dtm.py: back to the historical gap handling (small gaps filled by fillnodata only, larger holes left as nodata rendered black); lowest-return floor only via --bare-earth, IGN class selection via --ign-classes - cli.py: positional input now optional (--rebuild-index works alone) - docker-compose.yml: serve (GPU, port 8973) and process services; launch via docker compose only (documented in AGENTS.md/AGENTS.md) - tests: 131 passing, incl. regressions for thumbnail staleness, --rebuild-index without input, and nodata rendering
3.8 KiB
3.8 KiB
Workflow
- install:
docker build -t lidar-lidar .(deps baked into image) - build:
docker build -t lidar-lidar . - test all:
./run.sh --test - test file:
docker run --rm lidar-lidar python3 -m pytest -v --pyargs lidar_pipeline.tests.<module> - test case:
docker run --rm lidar-lidar python3 -m pytest -v --pyargs lidar_pipeline.tests.<module>::<TestClass>::<test_method> - lint: not configured
- format: not configured
- after every edit:
./run.sh --test - RÈGLE 1 — toujours lancer via docker compose (jamais
docker rundirect) : carte/API →docker compose up -d serve(port 8973) ; traitement ponctuel →docker compose run --rm process [options]; logs →docker compose logs -f serve; arrêt →docker compose down. - RÈGLE 2 — après chaque édition de code : rebuild de l'image puis relance du conteneur. Le code est baké dans l'image (jamais monté) : sans
docker compose buildsuivi d'undocker compose up -d serve(recrée le conteneur), l'ANCIEN code continue de tourner. Toujours reconstruire avant de faire tester/valider une modif par l'utilisateur. - test rapide sans rebuild (code monté par-dessus l'image):
docker run --rm -e PYTHONPATH=/app -v $(pwd)/lidar_pipeline:/app/lidar_pipeline lidar-lidar python3 -m pytest --pyargs lidar_pipeline.tests - debug:
./run.sh --debug(file:line logging); container shell:docker run --rm -it -v $(pwd)/input:/data/input -v $(pwd)/output:/data/output --entrypoint bash lidar-lidar
Conventions
- Bilingual naming: all code identifiers are English; every user-facing string, log message, argparse help, and comment is French.
- Adding a visualization requires 3 edits: (1)
generate_X()invisualizations.py, (2) entry inVIZ_STEPSinpipeline.py, (3) entry inCOLORMAPSinrendering.py. Missing any one breaks the pipeline. generate_*signature is strict:(dem_file, basename, vis_dir, resolution, shared=None)returningPathon success,Noneon failure. IGN overlays (ortho,topo) omitshared.- Return
Noneon failure, never raise:dtm.py,visualizations.py, andign.pyall returnNoneto let the pipeline continue. Raising aborts the entire file. - Logger is always
logging.getLogger("lidar"), never__name__. All modules route through this single logger so worker processes can configure it. - Filename special-cases in
_expected_output_path():pos_open→positive_openness,neg_open→negative_openness,hillshade→hillshade_multi. - Default output is AVIF, not WebP. Use
--format webpfor WebP. Quality default is 98. - Tests use lazy imports inside each test function, never at module top, to avoid importing CuPy/GDAL at import time.
_-prefixed names are critical private:_create_ground_pipeline,_fallback_to_smrf,_fill_nans,_init_gpu,_process_file_standalone— do not call from outside their module.build_index()writes 3 files:output/index.html(data shell,const TILESembedded),output/assets/app.cssandoutput/assets/app.js(source:_APP_CSS/_APP_JSconstants inindex.py).webapp.pyserves/assetswith no-cache headers. Each tile carriesmeta— ground method read fromDTM/*_dtm{_rXpY}_method.txt(falls back to the primary-resolution sidecar) + per-viz dates/sizes.
Commit & Pull Request Guidelines
Commits use imperative tense, short single-line subjects (~60–80 chars), no prefixes or scopes. Compound commits are common — multiple related changes joined by commas or "and". Examples: Fix multi-GPU with lazy CuPy init + rendering improvements, Add multi-resolution support and remove PDF generation, Fix corrupted COPC detection, add CSF→SMRF fallback, improve MSRM colormap, add SVF and anisotropic openness.
No PR template, no CI pipeline, no issue tracker. This is a standalone Docker project with no formal PR process.