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Yuzviak
2dd60a0e37
7 structured documents covering stack, integrations, architecture, structure, conventions, testing, and concerns. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
120 lines
5.3 KiB
Markdown
120 lines
5.3 KiB
Markdown
# Technology Stack
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**Analysis Date:** 2026-04-01
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## Languages
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**Primary:**
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- Python 3.11+ — entire application (enforced in `pyproject.toml` via `requires-python = ">=3.11"`)
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## Runtime
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**Environment:**
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- Target hardware: NVIDIA Jetson Orin Nano Super 8GB (ARM64/aarch64)
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- Target OS: JetPack 6.2.2 (L4T / Ubuntu 22.04)
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- CUDA 12.6.10, TensorRT 10.3.0, cuDNN 9.3 (all JetPack-bundled, not in pyproject.toml)
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- Development/CI: x86_64 Linux with Docker+CUDA (cuVSLAM and TensorRT mocked)
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**Package Manager:**
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- pip / setuptools >=75
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- Lockfile: not present (no `requirements.txt`, no lock file)
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## Frameworks
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**Core:**
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- FastAPI (unpinned, >=0.115 per docs) — REST API framework with auto-generated OpenAPI docs
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- Uvicorn (`uvicorn[standard]`, unpinned) — ASGI server
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- sse-starlette >=2.0 — Server-Sent Events streaming (`EventSourceResponse` actively used in `src/gps_denied/api/routers/flights.py`)
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**Data Validation / Settings:**
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- Pydantic >=2 — schema definitions across all `src/gps_denied/schemas/*.py`
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- pydantic-settings >=2 — env/YAML configuration in `src/gps_denied/config.py`
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**Database:**
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- SQLAlchemy >=2 (async) — ORM and query layer (`src/gps_denied/db/engine.py`, `src/gps_denied/db/models.py`)
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- Alembic >=1.14 — database migrations
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- aiosqlite >=0.20 — async SQLite driver (default DB URL: `sqlite+aiosqlite:///./flight_data.db`)
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**Testing:**
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- pytest >=8.0 — test runner (config in `pyproject.toml`, `testpaths = ["tests"]`)
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- pytest-asyncio >=0.24 — async test support (`asyncio_mode = "auto"`)
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- httpx >=0.28 (dev) — HTTP client for integration tests
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**Linting / Formatting:**
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- ruff >=0.9 — linting and formatting (`target-version = "py311"`, `line-length = 100`)
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## Key Dependencies
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**HTTP Client:**
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- httpx >=0.27 — async HTTP client used in `src/gps_denied/core/satellite.py` for tile fetching
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**Computer Vision:**
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- opencv-python-headless >=4.9 — image decode/encode, feature detection/matching, resize
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- Actively imported in `src/gps_denied/core/satellite.py` and `src/gps_denied/core/vo.py`
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- Note: docs specify a CUDA-enabled build must be compiled from source (`CUDA_ARCH_BIN=8.7`) on Jetson; pyproject.toml installs the headless CPU build as default
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- numpy >=1.26 — array operations, ESKF math, image buffer handling (used throughout core modules)
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**Tile Caching:**
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- diskcache >=5.6 — disk-based tile cache with size limit in `src/gps_denied/core/satellite.py`
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**Factor Graph Optimization:**
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- gtsam >=4.3a0 — factor graph optimizer (`src/gps_denied/core/graph.py`)
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- Import is wrapped in a try/except (`HAS_GTSAM` flag); the module degrades gracefully if not installed
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**Multipart Upload:**
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- python-multipart >=0.0.9 — required for FastAPI `UploadFile` in flight frame ingestion
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## Dependencies Planned-but-Not-in-pyproject.toml
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These appear in `_docs/01_solution/tech_stack.md` but are NOT listed in `pyproject.toml` or `requires.txt`:
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| Package | Planned Purpose | Status |
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|---------|----------------|--------|
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| PyCuVSLAM v15.0.0 (aarch64 wheel) | Primary visual odometry engine | Planned — local wheel install from `bin/aarch64/` |
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| scipy | Rotation matrices, ESKF spatial transforms | Planned — not yet in deps |
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| torch (JetPack-compatible aarch64) | LiteSAM / XFeat model loading | Conditional — depends on day-1 benchmark |
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| tensorrt 10.3.0 | TensorRT FP16 inference engine | JetPack-bundled, not pip-installed |
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| pycuda | CUDA stream management | Planned, not yet added |
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| geojson | GeoJSON output formatting | Planned, not yet added |
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| pygeohash | GeoHash tile indexing | Planned, not yet added |
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| filterpy v1.4.5 | ESKF reference/fallback | Planned, not yet added |
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The VO interface in `src/gps_denied/core/vo.py` is written against an abstract `ISequentialVisualOdometry` — PyCuVSLAM implementation is a planned concrete subclass. Current `ModelManager` in `src/gps_denied/core/models.py` uses `MockInferenceEngine` stubs (SuperPoint/LightGlue mock returning random keypoints).
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## ML Models (Planned)
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| Model | Format | Purpose |
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|-------|--------|---------|
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| SuperPoint | TensorRT FP16 / ONNX | Frame keypoint extraction (VO) |
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| LightGlue | TensorRT FP16 / ONNX | Keypoint matching (VO) |
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| LiteSAM (opt) OR XFeat semi-dense | TensorRT FP16 | Satellite image matching — selection via day-1 benchmark at 480px |
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Weights expected at paths configured in `ModelPaths` settings (`src/gps_denied/config.py`): `weights/superpoint.pt`, `weights/lightglue.pt`, `weights/litesam.pt`.
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## Configuration
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**Environment:**
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- Loaded from `.env` file (root) via pydantic-settings `AppSettings` in `src/gps_denied/config.py`
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- Nested delimiter: `__` (e.g., `DB__URL=...`)
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- Key env prefix groups: `DB_`, `API_`, `TILES_`, `MODEL_`, `AREA_`, `RECOVERY_`, `ROTATION_`
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**Build:**
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- `pyproject.toml` — project metadata, dependencies, ruff and pytest config
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- No Dockerfile present in scanned directories
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## Platform Requirements
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**Development:**
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- Python 3.11+, pip
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- x86_64 Linux with GPU (Docker+CUDA) for model export and unit tests
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- cuVSLAM and TensorRT mocked in unit tests (per documented strategy)
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**Production:**
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- NVIDIA Jetson Orin Nano Super 8GB, JetPack 6.2.2
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- No internet connectivity during flight (all tiles pre-fetched)
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- OpenCV must be compiled from source with `CUDA_ARCH_BIN=8.7` for GPU preprocessing
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---
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*Stack analysis: 2026-04-01*
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