"""Tests du serveur web de génération de zones (webapp).""" def test_bbox_to_cells_single_km_cell(): """Une bbox couvrant ~1 km² retourne la cellule L93 correspondante.""" from lidar_pipeline.webapp import bbox_to_cells # Cellule 1054,6882 : X∈[1054000,1055000], Y∈[6881000,6882000] (L93) from rasterio.warp import transform as warp_transform lons, lats = warp_transform('EPSG:2154', 'EPSG:4326', [1054100, 1054900], [6881100, 6881900]) cells = bbox_to_cells(min(lons), min(lats), max(lons), max(lats)) assert (1054, 6882) in cells # La sélection reste locale : pas de cellule lointaine for (c, r) in cells: assert abs(c - 1054) <= 1 and abs(r - 6882) <= 1 def test_bbox_to_cells_empty_for_tiny_bbox(): """Une bbox quasi ponctuelle ne sélectionne rien (rétrécie sous 1 m).""" from lidar_pipeline.webapp import bbox_to_cells assert bbox_to_cells(7.850000, 48.930000, 7.850001, 48.930001) == [] def test_processed_cells(tmp_path): """processed_cells lit les dossiers de visualisations.""" from lidar_pipeline.webapp import processed_cells vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_r0p2" vis.mkdir(parents=True) (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x") assert processed_cells(tmp_path) == {(1054, 6882)} def test_missing_cells_filters_processed(tmp_path): """Les cellules déjà traitées sont exclues, les autres gardent leurs coins.""" from lidar_pipeline.webapp import missing_cells_with_corners vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69" vis.mkdir(parents=True) (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x") todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path) assert len(todo) == 1 assert todo[0]['col'] == 1055 and todo[0]['row'] == 6882 assert len(todo[0]['corners']) == 4 # SW, SE, NE, NW def test_missing_cells_include_done(tmp_path): """include_done=True conserve les cellules déjà traitées (régénération).""" from lidar_pipeline.webapp import missing_cells_with_corners vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69" vis.mkdir(parents=True) (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x") todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path, include_done=True) assert {(t['col'], t['row']) for t in todo} == {(1054, 6882), (1055, 6882)} def _make_tile(tmp_path, col, row, viz_keys, resolutions=(0.5, 0.2)): """Crée les dossiers de visualisations d'une tuile (une entrée par résolution). Le suffixe de résolution n'est que sur le DOSSIER : les fichiers gardent le basename nu (cf. _expected_output_path dans le pipeline). """ base = f"LHD_FXX_{col:04d}_{row:04d}_PTS_LAMB93_IGN69" for res in resolutions: suffix = "" if res == 0.5 else "_r" + str(res).replace('.', 'p') vis = tmp_path / "visualisations" / (base + suffix) vis.mkdir(parents=True, exist_ok=True) for key in viz_keys: (vis / f"{base}_{key}.avif").write_bytes(b"x") def test_missing_cells_includes_incomplete_tile(tmp_path): """Une tuile existante mais incomplète reste incluse (visualisation manquante).""" from lidar_pipeline.webapp import missing_cells_with_corners _make_tile(tmp_path, 1054, 6882, ["aspect"]) # aspect aux deux résolutions → complète pour ['aspect'] assert missing_cells_with_corners([(1054, 6882)], tmp_path, viz=["aspect"]) == [] # slope manquante → la tuile est incluse pour être complétée todo = missing_cells_with_corners([(1054, 6882)], tmp_path, viz=["aspect", "slope"]) assert [(t['col'], t['row']) for t in todo] == [(1054, 6882)] def test_missing_cells_requires_both_resolutions(tmp_path): """Une tuile complète à 0.5 mais sans 0.2 reste à traiter.""" from lidar_pipeline.webapp import missing_cells_with_corners _make_tile(tmp_path, 1054, 6882, ["aspect"], resolutions=(0.5,)) assert len(missing_cells_with_corners([(1054, 6882)], tmp_path, viz=["aspect"])) == 1 _make_tile(tmp_path, 1054, 6882, ["aspect"], resolutions=(0.2,)) assert missing_cells_with_corners([(1054, 6882)], tmp_path, viz=["aspect"]) == [] def test_complete_cells_maps_step_names(tmp_path): """Les noms d'étapes sont convertis en mots-clés de fichiers (hillshade → hillshade_multi).""" from lidar_pipeline.webapp import complete_cells _make_tile(tmp_path, 1054, 6882, ["hillshade_multi"]) assert complete_cells(tmp_path, ["hillshade"]) == {(1054, 6882)} # 'pos_open' → 'positive_openness' : absent → tuile non complète assert complete_cells(tmp_path, ["pos_open"]) == set() def test_preview_rejects_unknown_viz(): """/api/preview refuse un nom de visualisation inconnu (HTTPException 400).""" from fastapi import HTTPException from lidar_pipeline.webapp import preview, PreviewRequest req = PreviewRequest(bbox=[7.85, 48.93, 7.86, 48.94], viz=["inconnu"]) try: preview(req) assert False, "une HTTPException était attendue" except HTTPException as e: assert e.status_code == 400 assert "inconnu" in e.detail def test_build_command_resolutions_match_completeness(): """La commande -r et la détection de complétude utilisent les mêmes résolutions.""" from lidar_pipeline.webapp import GENERATE_RESOLUTIONS, _build_command cmd = _build_command([(1054, 6882)]) i = cmd.index("-r") assert cmd[i + 1] == ",".join(str(r) for r in GENERATE_RESOLUTIONS) def test_job_state_persisted_across_reload(tmp_path, monkeypatch): """L'état du job survit au redémarrage du serveur (file .generation.job.json).""" import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "JOB_FILE", tmp_path / "job.json") saved = {k: webapp._job.get(k) for k in ("proc", "started", "returncode", "cmd", "finished")} try: webapp._job.update({"started": 123.0, "returncode": 0, "cmd": ["python", "-m", "lidar_pipeline"], "finished": 456.0}) webapp._save_job_state() assert (tmp_path / "job.json").exists() # Simulation du redémarrage : état mémoire vide, rechargé depuis disque webapp._job.update({"proc": None, "started": None, "returncode": None, "cmd": None, "finished": None}) webapp._load_job_state() assert webapp._job["started"] == 123.0 assert webapp._job["returncode"] == 0 assert webapp._job["finished"] == 456.0 finally: webapp._job.update(saved) def test_laz_cells_parses_input(tmp_path): """laz_cells repère les dalles LHD présentes dans input/ (les autres ignorés).""" from lidar_pipeline.webapp import laz_cells (tmp_path / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69.copc.laz").write_bytes(b"x") (tmp_path / "LHD_FXX_1055_6881_PTS_LAMB93_IGN69.laz").write_bytes(b"x") (tmp_path / "LHD_FXX_1056_6880_PTS_LAMB93_IGN69.copc.las").write_bytes(b"x") (tmp_path / "autre_fichier.laz").write_bytes(b"x") assert laz_cells(tmp_path) == [(1054, 6882), (1055, 6881), (1056, 6880)] def test_preview_all_missing(tmp_path, monkeypatch): """all_missing: seulement les dalles présentes dans input/ et incomplètes.""" import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "INPUT_DIR", tmp_path) monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) (tmp_path / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69.copc.laz").write_bytes(b"x") (tmp_path / "LHD_FXX_1055_6881_PTS_LAMB93_IGN69.copc.laz").write_bytes(b"x") # 1054,6882 : aspect aux deux résolutions → complète pour ['aspect'] base = "LHD_FXX_1054_6882_PTS_LAMB93_IGN69" for suffix in ("", "_r0p2"): vis = tmp_path / "visualisations" / (base + suffix) vis.mkdir(parents=True) (vis / f"{base}_aspect.avif").write_bytes(b"x") d = webapp.preview(webapp.PreviewRequest(all_missing=True, viz=["aspect"])) assert d["count"] == 1 assert d["cells"][0]["col"] == 1055 and d["cells"][0]["row"] == 6881 def test_generate_all_missing(tmp_path, monkeypatch): """all_missing: traite toutes les dalles présentes (au-delà de la limite 400).""" import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "INPUT_DIR", tmp_path) monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) for i in range(1054, 1455): # 401 dalles → au-delà de MAX_CELLS (tmp_path / f"LHD_FXX_{i:04d}_6882_PTS_LAMB93_IGN69.copc.laz").write_bytes(b"x") captured = {} def fake_popen(cmd, **kwargs): captured["cmd"] = cmd class _P: def wait(self): return 0 def poll(self): return 0 return _P() # Stub du module subprocess : patcher le vrai module global casserait ses # autres usages (matplotlib l'appelle à l'import, ex. fc-list) et la # restauration serait un no-op (valeur déjà falsifiée). import subprocess as _real_subprocess class _SubprocessStub: Popen = staticmethod(fake_popen) run = staticmethod(_real_subprocess.run) STDOUT = _real_subprocess.STDOUT monkeypatch.setattr(webapp, "subprocess", _SubprocessStub) req = webapp.GenerateRequest(tiles=[], all_missing=True, viz=["aspect"]) result = webapp.generate(req) assert result["demarré"] is True and result["tuiles"] == 401 i = captured["cmd"].index("--file") assert len(captured["cmd"][i + 1:]) == 401 assert "LHD_FXX_1054_6882_PTS_LAMB93_IGN69.copc.laz" in captured["cmd"] def test_generate_all_missing_empty(tmp_path, monkeypatch): """all_missing sans dalle présente → 400.""" from fastapi import HTTPException import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "INPUT_DIR", tmp_path) monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) try: webapp.generate(webapp.GenerateRequest(tiles=[], all_missing=True)) assert False, "une HTTPException était attendue" except HTTPException as e: assert e.status_code == 400 def test_build_command_regenerate(): """regenerate=True ajoute --force --force-classification à la commande.""" from lidar_pipeline.webapp import _build_command cmd = " ".join(_build_command([(1054, 6882)], regenerate=True)) assert "--force" in cmd assert "--force-classification" in cmd cmd = " ".join(_build_command([(1054, 6882)])) assert "--force" not in cmd assert "--force-classification" not in cmd def test_build_command_ground_classification(): """La commande utilise la méthode de classification demandée (défaut : ign).""" from lidar_pipeline.webapp import _build_command, GROUND_CLASS_METHODS # Défaut : ign (pré-classification) cmd = _build_command([(1054, 6882)]) i = cmd.index("--ground-classification") assert cmd[i + 1] == "ign" # Chaque méthode valide est transmise telle quelle, avec ou sans régénération for method in GROUND_CLASS_METHODS: for regenerate in (False, True): cmd = _build_command([(1054, 6882)], regenerate=regenerate, ground_class=method) i = cmd.index("--ground-classification") assert cmd[i + 1] == method assert ("--force" in cmd) == regenerate assert ("--force-classification" in cmd) == regenerate def test_build_command_default_viz_aspect(): """Sans choix de visualisation, la commande génère uniquement aspect.""" from lidar_pipeline.webapp import _build_command cmd = _build_command([(1054, 6882)]) i = cmd.index("--only") assert cmd[i + 1] == "aspect" def test_build_command_custom_viz(): """Les visualisations demandées sont passées à --only dans l'ordre.""" from lidar_pipeline.webapp import _build_command cmd = _build_command([(1054, 6882)], viz=["aspect", "wavelet", "slope"]) i = cmd.index("--only") assert cmd[i + 1:i + 4] == ["aspect", "wavelet", "slope"] def test_build_command_incremental_index(): """La génération web reconstruit l'index après chaque tuile (affichage en direct).""" from lidar_pipeline.webapp import _build_command cmd = _build_command([(1054, 6882)]) assert "--incremental-index" in cmd def test_tiles_endpoint_stamp_diffing(tmp_path, monkeypatch): """/api/tiles sert index_tiles.json, allégé quand le stamp correspond.""" import json import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) # Fichier absent (aucune tuile encore indexée) → réponse vide assert webapp.tiles_data() == {"stamp": None, "tiles": None} # Fichier présent → données complètes puis réponse allégée au stamp (tmp_path / "index_tiles.json").write_text( json.dumps({"tiles": [{"col": 1054, "corners": []}], "viz_meta": {}, "stats": {}}), encoding="utf-8") full = webapp.tiles_data() assert full["tiles"][0]["col"] == 1054 light = webapp.tiles_data(stamp=full["stamp"]) assert light["tiles"] is None and light["stamp"] == full["stamp"] # Un stamp périmé redonne les données complètes assert webapp.tiles_data(stamp=full["stamp"] - 10)["tiles"] is not None def test_viz_step_names_match_pipeline(): """Les noms acceptés par l'API sont exactement les étapes VIZ_STEPS du pipeline.""" from lidar_pipeline.webapp import _viz_step_names from lidar_pipeline.pipeline import VIZ_STEPS assert _viz_step_names() == [n for n, _ in VIZ_STEPS] def test_generate_rejects_unknown_viz(): """L'API refuse un nom de visualisation inconnu (HTTPException 400).""" from fastapi import HTTPException from lidar_pipeline.webapp import generate, GenerateRequest req = GenerateRequest(tiles=[[1054, 6882]], viz=["wavelet", "inconnu"]) try: generate(req) assert False, "une HTTPException était attendue" except HTTPException as e: assert e.status_code == 400 assert "inconnu" in e.detail def test_generate_accepts_wavelet_and_slope(monkeypatch): """L'API accepte wavelet + slope et les transmet à --only.""" import lidar_pipeline.webapp as webapp captured = {} def fake_popen(cmd, **kwargs): captured["cmd"] = cmd class _P: def wait(self): return 0 def poll(self): return 0 return _P() # Stub du module subprocess (voir test_generate_all_missing) : ne pas # patcher le vrai module global. import subprocess as _real_subprocess class _SubprocessStub: Popen = staticmethod(fake_popen) run = staticmethod(_real_subprocess.run) STDOUT = _real_subprocess.STDOUT monkeypatch.setattr(webapp, "subprocess", _SubprocessStub) req = webapp.GenerateRequest(tiles=[[1054, 6882]], viz=["wavelet", "slope"]) result = webapp.generate(req) assert result["demarré"] is True i = captured["cmd"].index("--only") assert captured["cmd"][i + 1:i + 3] == ["wavelet", "slope"] def test_available_layers_scans_disk(tmp_path, monkeypatch): """/api/layers retourne les couches présentes (clé → label).""" import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69" vis.mkdir(parents=True) (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_wavelet.avif").write_bytes(b"x") layers = webapp.available_layers() assert layers.get("wavelet") assert "aspect" not in layers def test_rebuild_index_background(tmp_path, monkeypatch): """POST /api/rebuild lance build_index en arrière-plan puis termine.""" import time as _time import lidar_pipeline.webapp as webapp import lidar_pipeline.index as index_mod calls = [] monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out)) assert webapp.rebuild_index()["demarré"] is True for _ in range(100): if not webapp.rebuild_status()["running"]: break _time.sleep(0.05) assert calls # build_index a bien été appelé assert webapp.rebuild_status()["running"] is False assert webapp.rebuild_status()["done"] is not None def test_status_exposes_tiles_from_events(tmp_path, monkeypatch): """/api/status agrège les événements en tuiles (nom court + étapes).""" import lidar_pipeline.webapp as webapp from lidar_pipeline.progress import report_event, reset_events monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) reset_events(tmp_path) report_event(tmp_path, "LHD_FXX_1054_6882_PTS_LAMB93_IGN69", "viz", "start", "aspect", res=0.5) s = webapp.status() match = [t for t in s["tiles"] if t["short"] == "1054-6882"] assert len(match) == 1 assert match[0]["state"] == "running" assert any(step["label"] == "Aspect" for step in match[0]["steps"]) def test_generate_resets_progress_events(tmp_path, monkeypatch): """Un nouveau run repart d'un journal d'événements vide.""" import lidar_pipeline.webapp as webapp from lidar_pipeline.progress import read_events, report_event def fake_popen(cmd, **kwargs): class _P: def wait(self): return 0 def poll(self): return 0 return _P() import subprocess as _real_subprocess class _SubprocessStub: Popen = staticmethod(fake_popen) run = staticmethod(_real_subprocess.run) STDOUT = _real_subprocess.STDOUT monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path) monkeypatch.setattr(webapp, "subprocess", _SubprocessStub) report_event(tmp_path, "ancienne_tuile", "tile", "ok") req = webapp.GenerateRequest(tiles=[[1054, 6882]]) assert webapp.generate(req)["demarré"] is True assert read_events(tmp_path) == [] # ============================================================ # Mode webapp légère (Raspberry Pi) : génération déléguée à une # machine de traitement distante via LIDAR_GENERATION_URL. # ============================================================ def test_generate_forwards_to_remote(monkeypatch): """/api/generate transmet la demande à la machine de traitement.""" import lidar_pipeline.webapp as webapp calls = [] def fake_proxy(method, path, payload=None, timeout=30): calls.append((method, path, payload)) return {"demarré": True, "tuiles": 1} monkeypatch.setattr(webapp, "GENERATION_URL", "http://distant:8973") monkeypatch.setattr(webapp, "_proxy_api", fake_proxy) req = webapp.GenerateRequest(tiles=[[1054, 6882]], viz=["aspect"]) result = webapp.generate(req) assert result["demarré"] is True and result["distant"] is True assert calls == [("POST", "/api/generate", {"tiles": [[1054, 6882]], "regenerate": False, "ground_class": "ign", "ign_classes": "sol", "bare_earth": False, "viz": ["aspect"], "all_missing": False})] def test_status_proxies_remote(monkeypatch): """/api/status rapporte l'état du job distant (file de génération).""" import lidar_pipeline.webapp as webapp calls = [] def fake_proxy(method, path, payload=None, timeout=30): calls.append((method, path, timeout)) return {"running": True, "tiles": []} monkeypatch.setattr(webapp, "GENERATION_URL", "http://distant:8973") monkeypatch.setattr(webapp, "_proxy_api", fake_proxy) data = webapp.status() assert data["running"] is True and data["distant"] is True assert calls == [("GET", "/api/status", 10)] # timeout court : sondage UI def test_preview_forwards_to_remote(monkeypatch): """/api/preview interroge le distant (il seul connaît input/ complet).""" import lidar_pipeline.webapp as webapp calls = [] def fake_proxy(method, path, payload=None, timeout=30): calls.append((method, path, payload)) return {"count": 0, "cells": []} monkeypatch.setattr(webapp, "GENERATION_URL", "http://distant:8973") monkeypatch.setattr(webapp, "_proxy_api", fake_proxy) req = webapp.PreviewRequest(bbox=[7.85, 48.93, 7.86, 48.94], viz=["aspect"]) assert webapp.preview(req)["count"] == 0 assert calls[0][0] == "POST" and calls[0][1] == "/api/preview" assert calls[0][2]["bbox"] == [7.85, 48.93, 7.86, 48.94] def test_proxy_translates_unreachable_host(monkeypatch): """Une machine de traitement injoignable devient un 503 explicite.""" from fastapi import HTTPException import lidar_pipeline.webapp as webapp monkeypatch.setattr(webapp, "GENERATION_URL", "http://localhost:1") try: webapp._proxy_api("GET", "/api/status", timeout=1) assert False, "une HTTPException était attendue" except HTTPException as e: assert e.status_code == 503 assert "injoignable" in e.detail def test_fallback_viz_step_names_match_pipeline(): """Le repli léger (sans pipeline) liste les mêmes étapes, même ordre.""" from lidar_pipeline.pipeline import VIZ_STEPS from lidar_pipeline.webapp import _fallback_viz_step_names assert _fallback_viz_step_names() == [name for name, _ in VIZ_STEPS] def test_viz_step_labels_without_pipeline(): """Les libellés d'étapes restent corrects même sans importer le pipeline.""" import lidar_pipeline.webapp as webapp labels = webapp._viz_step_labels() assert labels["hillshade"] == "Hillshade multidirectionnel" assert labels["pos_open"] == "Openness positive" def test_sync_runs_command_then_rebuild(tmp_path, monkeypatch): """POST /api/sync exécute LIDAR_SYNC_CMD puis build_index en arrière-plan.""" import time as _time import lidar_pipeline.webapp as webapp import lidar_pipeline.index as index_mod calls = [] monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out)) monkeypatch.setattr(webapp, "SYNC_CMD", "exit 0") webapp._rebuild["done"] = None # ignore l'état d'un test précédent assert webapp.sync_and_rebuild()["sync"] is True for _ in range(200): s = webapp.rebuild_status() if s["done"] is not None and not s["running"]: break _time.sleep(0.05) assert calls # l'index a été reconstruit après la synchronisation assert webapp.rebuild_status()["error"] is None assert webapp.rebuild_status()["done"] is not None def test_sync_failure_reported_but_index_rebuilt(tmp_path, monkeypatch): """Un rsync en échec est remonté dans l'état sans bloquer le rebuild.""" import time as _time import lidar_pipeline.webapp as webapp import lidar_pipeline.index as index_mod calls = [] monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out)) monkeypatch.setattr(webapp, "SYNC_CMD", "exit 3") webapp._rebuild["done"] = None webapp.sync_and_rebuild() for _ in range(200): s = webapp.rebuild_status() if s["done"] is not None and not s["running"]: break _time.sleep(0.05) assert calls # rebuild quand même (données locales éventuelles) assert "rc=3" in webapp.rebuild_status()["error"] def test_sync_without_cmd_is_rebuild_only(monkeypatch): """Sans LIDAR_SYNC_CMD (machine locale), /api/sync = simple rebuild.""" import time as _time import lidar_pipeline.webapp as webapp import lidar_pipeline.index as index_mod calls = [] monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out)) monkeypatch.setattr(webapp, "SYNC_CMD", None) webapp._rebuild["done"] = None assert webapp.sync_and_rebuild()["sync"] is False for _ in range(200): s = webapp.rebuild_status() if s["done"] is not None and not s["running"]: break _time.sleep(0.05) assert calls and webapp.rebuild_status()["error"] is None def test_require_token(): """Le jeton (si défini) bloque les appels sans ou avec mauvais mauvais header.""" from fastapi import HTTPException import lidar_pipeline.webapp as webapp old = webapp.API_TOKEN webapp.API_TOKEN = "secret" try: for bad in (None, "faux"): try: webapp._require_token(bad) assert False, "une HTTPException était attendue" except HTTPException as e: assert e.status_code == 401 assert webapp._require_token("secret") is None finally: webapp.API_TOKEN = old # Sans jeton configuré : tout passe (LAN de confiance) webapp.API_TOKEN = None assert webapp._require_token(None) is None