| | |
| | | from __future__ import annotations |
| | | |
| | | import importlib.util |
| | | import io |
| | | import sys |
| | | import tempfile |
| | | import unittest |
| | | import json |
| | | from urllib.parse import quote |
| | | from pathlib import Path |
| | | |
| | | |
| | |
| | | Path(handler.translate_path("/shared/data/raw/01-object-detection/sample.jpeg")), |
| | | ROOT / "shared" / "data" / "raw" / "01-object-detection" / "sample.jpeg", |
| | | ) |
| | | self.assertEqual( |
| | | Path(handler.translate_path("/shared/data/raw/02-semantic-mapping/sample.tif")), |
| | | ROOT / "shared" / "data" / "raw" / "02-semantic-mapping" / "sample.tif", |
| | | ) |
| | | self.assertEqual( |
| | | Path(handler.translate_path("/shared/data/raw/00-change-detection/sample.jpg")), |
| | | ROOT / "shared" / "data" / "raw" / "00-change-detection" / "sample.jpg", |
| | | ) |
| | | self.assertEqual( |
| | | Path(handler.translate_path("/shared/data/raw/09-anomaly-detection/sample.tif")), |
| | | ROOT / "shared" / "data" / "raw" / "09-anomaly-detection" / "sample.tif", |
| | | ) |
| | | self.assertEqual( |
| | | Path(handler.translate_path("/shared/data/processed/09-anomaly-detection/sample.tif")), |
| | | ROOT / ".console-forbidden", |
| | | ) |
| | | |
| | | def test_upload_name_is_sanitized_and_extension_is_allowlisted(self) -> None: |
| | | self.assertEqual(MODULE.safe_file_name("../../unsafe name.JPG", {".jpg"}), "unsafe_name.jpg") |
| | | self.assertEqual(MODULE.safe_file_name("../正常参考图.JPG", {".jpg"}), "正常参考图.jpg") |
| | | with self.assertRaises(MODULE.ApiError): |
| | | MODULE.safe_file_name("image.exe", {".jpg", ".png"}) |
| | | |
| | | def test_oversized_request_is_rejected_before_reading_body(self) -> None: |
| | | handler = self.make_handler() |
| | | handler.headers = {"Content-Length": str(MODULE.MAX_REQUEST_BYTES + 1), "Content-Type": "application/json"} |
| | | handler.rfile = io.BytesIO(b"") |
| | | with self.assertRaises(MODULE.ApiError): |
| | | handler.read_json_body() |
| | | |
| | | def test_large_tiff_upload_limits_allow_one_gibibyte_files(self) -> None: |
| | | self.assertEqual(MODULE.MAX_FILE_BYTES, 1024 * 1024 * 1024) |
| | | self.assertEqual(MODULE.MAX_REQUEST_BYTES, 3072 * 1024 * 1024) |
| | | |
| | | def test_binary_change_upload_preserves_original_bytes(self) -> None: |
| | | with tempfile.TemporaryDirectory() as temp_dir: |
| | | handler = object.__new__(MODULE.WorkbenchConsoleHandler) |
| | | handler.directory = temp_dir |
| | | handler.path = "/api/change-detection/uploads/0123456789abcdef0123456789abcdef?role=before" |
| | | handler.headers = {"Content-Length": "13", "X-Upload-Name": "../1.tif"} |
| | | handler.rfile = io.BytesIO(b"raw-tif-bytes") |
| | | result = handler.receive_change_upload("/api/change-detection/uploads/0123456789abcdef0123456789abcdef") |
| | | staged = Path(temp_dir) / "shared" / "data" / "raw" / "00-change-detection" / "uploads" / result["uploadId"] / "before.tif" |
| | | self.assertEqual(staged.read_bytes(), b"raw-tif-bytes") |
| | | self.assertEqual(result["name"], "1.tif") |
| | | |
| | | def test_binary_anomaly_upload_preserves_bytes_and_checksum(self) -> None: |
| | | with tempfile.TemporaryDirectory() as temp_dir: |
| | | handler = object.__new__(MODULE.WorkbenchConsoleHandler) |
| | | handler.directory = temp_dir |
| | | handler.path = "/api/anomaly-detection/uploads/1123456789abcdef0123456789abcdef?role=reference" |
| | | handler.headers = {"Content-Length": "15", "X-Upload-Name": "../normal.JPG"} |
| | | handler.rfile = io.BytesIO(b"reference-bytes") |
| | | result = handler.receive_anomaly_upload("/api/anomaly-detection/uploads/1123456789abcdef0123456789abcdef") |
| | | staged = Path(temp_dir) / "shared" / "data" / "raw" / "09-anomaly-detection" / "uploads" / result["uploadId"] / "reference.jpg" |
| | | self.assertEqual(staged.read_bytes(), b"reference-bytes") |
| | | self.assertEqual(result["sha256"], MODULE.file_sha256(staged)) |
| | | |
| | | def test_binary_anomaly_upload_decodes_chinese_file_name(self) -> None: |
| | | with tempfile.TemporaryDirectory() as temp_dir: |
| | | handler = object.__new__(MODULE.WorkbenchConsoleHandler) |
| | | handler.directory = temp_dir |
| | | handler.path = "/api/anomaly-detection/uploads/3123456789abcdef0123456789abcdef?role=input" |
| | | handler.headers = {"Content-Length": "11", "X-Upload-Name": quote("异常测试图.JPG", safe="")} |
| | | handler.rfile = io.BytesIO(b"image-bytes") |
| | | result = handler.receive_anomaly_upload("/api/anomaly-detection/uploads/3123456789abcdef0123456789abcdef") |
| | | staged = Path(temp_dir) / "shared" / "data" / "raw" / "09-anomaly-detection" / "uploads" / result["uploadId"] / "input.jpg" |
| | | self.assertEqual(result["name"], "异常测试图.jpg") |
| | | self.assertEqual(staged.read_bytes(), b"image-bytes") |
| | | |
| | | def test_interrupted_anomaly_upload_removes_partial_file(self) -> None: |
| | | with tempfile.TemporaryDirectory() as temp_dir: |
| | | handler = object.__new__(MODULE.WorkbenchConsoleHandler) |
| | | handler.directory = temp_dir |
| | | handler.path = "/api/anomaly-detection/uploads/2123456789abcdef0123456789abcdef?role=input" |
| | | handler.headers = {"Content-Length": "20", "X-Upload-Name": "target.tif"} |
| | | handler.rfile = io.BytesIO(b"short") |
| | | with self.assertRaisesRegex(MODULE.ApiError, "ended before"): |
| | | handler.receive_anomaly_upload("/api/anomaly-detection/uploads/2123456789abcdef0123456789abcdef") |
| | | staging = Path(temp_dir) / "shared" / "data" / "raw" / "09-anomaly-detection" / "uploads" / "2123456789abcdef0123456789abcdef" |
| | | self.assertFalse(any(staging.glob("*.part"))) |
| | | |
| | | def test_anomaly_parameters_are_bounded(self) -> None: |
| | | self.assertEqual(MODULE.validate_anomaly_parameters({}), (256, 128, 0.995, 42)) |
| | | with self.assertRaisesRegex(MODULE.ApiError, "Stride"): |
| | | MODULE.validate_anomaly_parameters({"tileSize": 128, "stride": 256}) |
| | | with self.assertRaisesRegex(MODULE.ApiError, "quantile"): |
| | | MODULE.validate_anomaly_parameters({"thresholdQuantile": 1.0}) |
| | | |
| | | def test_anomaly_run_discovery_requires_exposed_raw_sources(self) -> None: |
| | | with tempfile.TemporaryDirectory() as temp_dir: |
| | | root = Path(temp_dir) |
| | | artifact = root / "shared" / "outputs" / "09-anomaly-detection" / "runs" / "anomaly-test" |
| | | raw_input = root / "shared" / "data" / "raw" / "09-anomaly-detection" / "runs" / "anomaly-test" / "input" |
| | | raw_reference = raw_input.parent / "reference" |
| | | artifact.mkdir(parents=True) |
| | | raw_input.mkdir(parents=True) |
| | | raw_reference.mkdir(parents=True) |
| | | (artifact / "target.comparison.overlay.png").write_bytes(b"png") |
| | | metadata = {"capability": "09-anomaly-detection", "created_at": "2026-08-18", "display_name": "五参考图边界案例", "case_note": "保留真实漏检结果。", "raw_input_dir": raw_input.relative_to(root).as_posix(), "raw_reference_dir": raw_reference.relative_to(root).as_posix(), "images": [{"overlay_file": "target.comparison.overlay.png"}]} |
| | | (artifact / "run_metadata.json").write_text(json.dumps(metadata), encoding="utf-8") |
| | | runs = MODULE.anomaly_runs(root) |
| | | self.assertEqual(runs[0]["id"], "anomaly-test") |
| | | self.assertEqual(runs[0]["label"], "五参考图边界案例") |
| | | self.assertEqual(runs[0]["note"], "保留真实漏检结果。") |
| | | |
| | | def test_script_failure_becomes_a_useful_api_error(self) -> None: |
| | | handler = self.make_handler() |
| | | with self.assertRaisesRegex(MODULE.ApiError, "Processing failed"): |
| | | handler.run_command([sys.executable, "-c", "raise SystemExit(2)"], timeout=10) |
| | | |
| | | def test_semantic_validation_run_is_discovered(self) -> None: |
| | | runs = MODULE.semantic_runs(ROOT) |
| | | self.assertTrue(any(item["id"] == "validation-20260817" for item in runs)) |
| | | |
| | | def test_spatial_measurement_run_is_discovered(self) -> None: |
| | | runs = MODULE.measurement_runs(ROOT) |
| | | validation = next(item for item in runs if item["id"] == "validation-normal-20260817-v4") |
| | | self.assertTrue(validation["artifactRoot"].startswith("shared/outputs/04-spatial-measurement/")) |
| | | |
| | | def test_change_run_requires_both_allowlisted_images(self) -> None: |
| | | handler = self.make_handler() |
| | | with self.assertRaisesRegex(MODULE.ApiError, "name and Base64"): |
| | | handler.create_change_run({"files": {"before": {"name": "before.jpg", "content": "eA=="}}}) |
| | | |
| | | def test_change_threshold_is_validated(self) -> None: |
| | | handler = self.make_handler() |
| | | payload = {"files": {"before": {"name": "before.jpg", "content": "eA=="}, "after": {"name": "after.jpg", "content": "eA=="}}} |
| | | with self.assertRaisesRegex(MODULE.ApiError, "between 0.01 and 0.99"): |
| | | handler.create_change_run({**payload, "threshold": 1.0}) |
| | | with self.assertRaisesRegex(MODULE.ApiError, "must be a number"): |
| | | handler.create_change_run({**payload, "threshold": "0.5"}) |
| | | |
| | | def test_change_resolution_is_validated(self) -> None: |
| | | handler = self.make_handler() |
| | | payload = {"files": {"before": {"name": "before.jpg", "content": "eA=="}, "after": {"name": "after.jpg", "content": "eA=="}}} |
| | | with self.assertRaisesRegex(MODULE.ApiError, "between 512 and 4096"): |
| | | handler.create_change_run({**payload, "maxDimension": 256}) |
| | | with self.assertRaisesRegex(MODULE.ApiError, "must be an integer"): |
| | | handler.create_change_run({**payload, "maxDimension": "2048"}) |
| | | |
| | | def test_change_processing_mode_is_validated(self) -> None: |
| | | handler = self.make_handler() |
| | | payload = {"files": {"before": {"name": "before.jpg", "content": "eA=="}, "after": {"name": "after.jpg", "content": "eA=="}}} |
| | | with self.assertRaisesRegex(MODULE.ApiError, "auto, image, or geotiff"): |
| | | handler.create_change_run({**payload, "processingMode": "wrong"}) |
| | | |
| | | def test_change_validation_run_is_discovered_without_fake_crs(self) -> None: |
| | | runs = MODULE.change_runs(ROOT) |
| | | self.assertTrue(any(item["id"].startswith("validation-real-") for item in runs)) |
| | | |
| | | def test_semantic_task_catalog_only_enables_verified_baseline(self) -> None: |
| | | tasks = MODULE.semantic_tasks(ROOT) |
| | | self.assertEqual(len(tasks), 5) |
| | | selectable = [item["id"] for item in tasks if item.get("selectable") is True] |
| | | self.assertEqual(selectable, ["color_baseline"]) |
| | | handler = self.make_handler() |
| | | with self.assertRaisesRegex(MODULE.ApiError, "not runnable yet"): |
| | | handler.create_semantic_run({"taskId": "drainage_blockage", "images": []}) |
| | | |
| | | def test_blocks_repository_files_and_encoded_traversal(self) -> None: |
| | | handler = self.make_handler() |