model-platform/DEVELOP.md

# DEVELOP.md — Developer Guide

This guide is for engineers working on the model platform codebase. For
high-level design see `ARCHITECTURE.md`; for the current state of in-flight
refactors see `HANDOVER.md`.

## Code layout

All Python packages use the `src/<pkg>/` layout; `uv` workspace glues them into
one `.venv`. Always invoke via `uv run [--package <pkg>] <cmd>` (see "Local
development" for the gotcha).

```
common/src/common/                Pure-Python shared library
  config.py                       Settings (pydantic-settings, lru_cache singleton)
  db/                             SQLAlchemy 2.0 async engine, session_scope, Base
  db/models/                      26 tables in 9 domain files (zero FK, zero relationship)
  auth/                           JWT / bcrypt / workspace membership helpers
  scheduler/                      APScheduler trigger helpers (delayed import)
  storage/                        AsyncStorageBackend abstraction + Pydantic schemas
    base.py                       Abstract interface
    factory.py                    create_storage + build_storage_config + PURPOSE_BUCKETS
    schemas.py                    CreateUploadRequest / ServerObjectRequest
    backends/local.py            Local filesystem impl
    backends/s3.py                S3-compatible impl (boto3)
    registry.py                   Bucket registry
  eventing.py                     add_outbox_event / utcnow / event_time
  service_app.py                  /health/ready TCP probe, /api/v1/health
  logging.py                      loguru config (LOG_LEVEL)
  schemas.py                      StrictModel base
  ids.py                          ULID generation helpers
  utils.py                        get_free_port, start_process

backend/src/backend/              Public FastAPI service
  main.py                         lifespan + route registration
  audit.py                        HTTP access log middleware (loguru sink)
  api/                            HTTP route handlers (one module per bounded context)
    auth.py                       /api/v1/auth/* (login / me / jupyter)
    jupyter.py                    /api/v1/auth/jupyter — the ONLY auth entry
    dependencies.py               request_context, database_session
    platform.py                   /api/v1/platform/* (system admin)
    admin.py                      /api/v1/admin/* (workspace-internal admin)
    scripts.py                    /api/v1/scripts/* + /api/v1/workspace-directories
    resources.py                  /api/v1/data-resources/*
    schedules/schedules.py        DAG CRUD
    schedules/runs.py             Run lifecycle
    storage.py                    /internal/v1/objects — single token-guarded endpoint (P0-1)
  services/                       Pure-Python business logic (no HTTP / no DI)
    scripts.py                    create_workspace_directory, visibility-filtered queries
    resources.py                  owner-scoped resource listing helpers
    jupyter.py                    jupyter_path / lock helpers
    storage.py                    object store helpers
    schedules.py                  DAG validation (cycle / orphan detection)
  schemas/                        Pydantic request / response models
    auth.py / common.py / jupyter.py / platform.py / resources.py / schedules.py / scripts.py
  clients/                        Outbound HTTP / RPC clients
    runtime.py                    Self-contained httpx wrapper for the runtime
    scheduler.py                  Backend → Schedule HTTP client (callback / dispatch)
    rclone.py                     rclone RC API client (FUSE cache invalidation)

schedule/src/schedule/            Schedule Executor (DAG worker)
  main.py                         Lifespan + FastAPI app
  notebook_runner.py              Subprocess entry point (nbclient) — DO NOT RENAME
  domain/                         Pure-Python domain types
    execution.py                  ExecutionResult (frozen dataclass) + state enums
    context.py                    Constants + naive_utc
  scheduling/                     Time-based trigger
    scheduler.py                  CronScheduler (APScheduler + 5s sync loop)
  application/                    Facades / orchestrators
    service.py                    SchedulerService (composes the three)
    orchestrator.py               DispatchOrchestrator (Outbox poll + DAG advance)
  execution/                      DAG node execution
    executor.py                   NodeExecutor (notebook / python dispatch)
    worker.py                     asyncio entry, schedule-spawned task boundary
    runners/notebook.py           nbclient subprocess path (6-line `notebook_runner` shim re-exports `main`)
  infrastructure/                 External-system adapters
    storage/client.py             SchedulerStorageClient — talks to backend /internal/v1/objects

runtime/src/runtime/              Jupyter Runtime
  main.py                         FastAPI entry: jupyter action endpoints
  process.py                      Per-workspace subprocess pool + asyncio locks
  mount.py                        rclone FUSE mount lifecycle

frontend/                         React Router SPA (vite build → nginx)
  app/                            features/ routes/ services/ components/

migrations/                       Alembic schema versions
docker-compose.yml                4 services (gateway / backend / schedule / runtime)
default.conf                      Nginx template
scripts/nginx-entrypoint.sh
.env.example                      All 26 config.py keys documented
```

## Configuration system

All env vars go through one place: `common/src/common/config.py`.

```python
from common.config import settings

# Auth / runtime
settings.database_url          # str — SQLAlchemy async URL (mysql+asyncmy, charset utf8mb4)
settings.jwt_secret             # HS256 secret for the auth_request handler
settings.cookie_force_secure    # bool — write Secure flag even on plain HTTP (TLS-terminating proxy)
settings.service_name          # surfaced in /health
settings.schedule_event_namespace  # APScheduler JobStore namespace + Outbox scope prefix
settings.readiness_targets     # CSV host:port list for /health/ready

# HTTP clients (intra-cluster URLs)
settings.runtime_api_url       # backend → runtime HTTP base
settings.public_base_url       # runtime public base URL (browser-facing /jupyter/)
settings.backend_api_url       # schedule → backend HTTP base
settings.rclone_rc_url         # backend → rclone RC control API
settings.internal_service_token  # Backend ↔ Schedule shared secret (X-Internal-Service-Token)

# Logging / audit
settings.log_level             # DEBUG / INFO / WARNING / ERROR / CRITICAL (lowercase → fallback INFO)
settings.audit_log_dir         # dir for daily audit logs (relative to cwd; "" disables file sink)
settings.audit_log_retention_days  # 0 disables cleanup
settings.audit_excluded_paths  # list[str] — paths skipped from audit (health probes, etc.)

# Storage
settings.storage_backend       # "s3" (default) or "local"
settings.local_storage_base_dir  # root dir for storage data (default "/data")
settings.s3_endpoint            # str (s3 mode only)
settings.s3_access_key          # str (s3 mode only)
settings.s3_secret_key          # str (s3 mode only)
settings.s3_workspace_bucket    # str (s3 mode only)
settings.s3_version_bucket      # str (s3 mode only)
settings.s3_run_log_bucket      # str (s3 mode only)
settings.s3_trash_bucket        # str (s3 mode only)
settings.s3_trash_retention_days  # int (s3 mode only)

# Schedule
settings.schedule_execution_concurrency  # int — max concurrent notebook subprocesses
```

`Settings` reads from process env first, then from a `.env` file at CWD
if present. `pydantic-settings` auto-loads. `case_sensitive=False` so
`DATABASE_URL` / `database_url` both work. The full list of 26 fields
is in `common/src/common/config.py`.

### Adding a new env var

1. Add the field to `Settings`:
   ```python
   new_var: str = Field(default="x", description="...")
   ```
2. Add the line to `.env.example` with a comment (keep it synced — every
   field in config.py must have a matching `.env.example` entry).
3. Use `settings.new_var` at the call site.

Do **not** call `os.environ["NEW_VAR"]` or `os.getenv("NEW_VAR")` in
application code. The grep below should return zero hits:

```bash
grep -rnE 'os\.(environ\[?["\x27][A-Z_]+|getenv\(["\x27][A-Z_]+)' --include="*.py" \
  backend/src/ schedule/src/ runtime/src/ common/src/
```

## Conventions

### Database / SQLAlchemy

- **No foreign keys, no `relationship`** — every join is explicit.
- Every table has `is_deleted TINYINT(1) NOT NULL DEFAULT 0` and
  `deleted_at DATETIME(3) NULL`; queries must filter `is_deleted == 0`
  (or `deleted_at.is_(None)`) to avoid logical-deleted rows.
- Domain files under `common/src/common/db/models/` are split by
  bounded context: `audit` / `events` / `experiments` / `identity` /
  `runtime` / `schedules` / `scripts` / `storage` / `workspaces`.
- All models are `class X(Base)` SQLAlchemy 2.0 declarative-mapped.
- The full schema is in `migrations/versions/`. Apply with:
  ```bash
  uv run --frozen --package backend alembic upgrade head
  ```

### Storage

- All object bytes go through `common.storage.AsyncStorageBackend`,
  created by `create_storage(config)` from `common.storage.factory`.
- Two backends are registered: `local` (filesystem, local mode) and
  `s3` (S3-compatible service, s3 mode). Selection is per-deployment
  via `settings.storage_backend` (`"s3"` default, `"local"` for
  dev / single-node / air-gapped).
- The factory helper `build_storage_config(bucket_name)` returns the
  right `create_storage` kwargs for each of the 4 purpose buckets
  (`workspace`, `version`, `run_log`, `trash`). Use it in lifespan code;
  route handlers don't see the difference.
- Bucket resolution from `usage_type` is in **one place**
  (`backend/storage_api.py:resolve_bucket`); route handlers only know
  about `app.state.object_stores[bucket_name]`.
- The runtime's view of the workspace bucket on disk is exposed by
  `common.storage.workspaces_root()`:
  - `s3` mode: `${settings.local_storage_base_dir}/workspace`
    (default `/data/workspace`, the rclone FUSE mount target).
  - `local` mode: `${settings.local_storage_base_dir}/workspace`
    (default `/data/workspace`, a subdir of the shared local-storage
    volume).
  `settings.local_storage_base_dir` is the **only** path setting; the
  helper handles the per-mode suffix. Don't read `settings.workspaces_root`
  or any other path setting directly in runtime code — use this helper.
- The pre-2026 abstraction (`RustFSObjectStore` / `common.storage.client`
  / `StorageClient` HTTP wrapper) is gone. Don't reintroduce it.

### Auth

- Browser → `/jupyter/{workspace_id}/...` → Nginx `auth_request` →
  `GET /api/v1/auth/jupyter` (Backend).
- The handler:
  1. Parses cookie / Bearer JWT (HS256 + `settings.jwt_secret`).
  2. Verifies `WorkspaceMembers` for the workspace.
  3. Verifies `Scripts.is_locked` for the requested notebook path
     (owner / unlocked → allow; otherwise 403).
  4. Calls `RuntimeClient.get_workspace` / `start_workspace`.
  5. Returns `x-upstream-addr` + `x-jupyter-internal-token` response
     headers. **Browser never holds the runtime token.**

### Service-to-service auth (P0-1 fix)

- Schedule → Backend single endpoint ``POST /internal/v1/objects`` is
  guarded by ``require_internal_service`` in ``backend.api.storage``.
- The token header is ``X-Internal-Service-Token`` (case-insensitive
  on the wire because FastAPI ``Header`` lowercase-matches the name
  ``x-internal-service-token``); the secret value comes from
  ``settings.internal_service_token`` / env ``INTERNAL_SERVICE_TOKEN``.
- Comparison uses ``secrets.compare_digest`` — never equality.
- Backend and schedule must be configured with the same value; a
  mismatch fails fast at the first notebook run (``401``) which is
  intentional. ``.env.example`` ships a placeholder
  ``change-me-internal-service-token`` and the docker-compose
  ``${INTERNAL_SERVICE_TOKEN:?...}`` reference forces production
  deployments to set a real value.
- Removing the legacy backend / runtime host-port mappings
  (``8891:8000`` / ``8892:8000``) is part of the same fix — no service
  is reachable from the host except Nginx anymore.
- Nginx captures the headers via `auth_request_set` and proxies to the
  upstream sub-process with `Authorization: token $jupyter_token`.

### Permission gates

- For write operations on a script/notebook, call
  `require_script_modify_access(script, user_id=..., is_admin=...)`
  from `backend/src/backend/services/scripts.py`. It enforces:
  - admin or owner → allow
  - non-owner, `is_locked == 0` → allow
  - non-owner, `is_locked == 1` → 403
- Read endpoints (`list_scripts`, `get_script`) intentionally do **not**
  check `is_locked` — workspace members can see the script list.

### Owner-scoping + visibility (cross-owner browsing)

`GET /api/v1/scripts`, `GET /api/v1/data-resources`, and
`GET /api/v1/workspace-directories` all accept an optional
`owner_user_id` query param and follow the same model:

- `owner_user_id` 缺省 = 当前请求者本人(scope to `workspace/{me}/...`).
- 传值时 scope 到 `workspace/{owner_user_id}/...`,用于前端"点开其他成员
  分组"的懒加载(见 §3.4 of `API.md`).
- `visibility` 过滤(非 admin):`owner_user_id == me OR visibility IN
  (workspace, public)` — 自己可见自己全部(含 private),他人只见其
  workspace/public,排除他人 private.
- 系统管理员跳过 visibility 过滤.
- 目录行默认 `visibility='public'`(由 `create_workspace_directory` 写入),
  不施加 visibility 过滤,使跨 owner 目录树可见.

实现 helper 在 `backend/src/backend/services/scripts.py`
(`_build_list_scripts_owner_descendant_prefix`) 和
`backend/src/backend/api/resources.py` 中按相同模式分别构造 owner-scoped
LIKE 前缀。

### Outbox events

- The platform's only async-messaging fabric is the MySQL
  `OutboxEvents` table. Producers (Backend) write rows in the same
  transaction as the business state. Consumers (Schedule Executor)
  poll every 250 ms and update `event_status` to `published` or
  `failed` (with retry).
- Use `common.eventing.add_outbox_event` to write.
- `event_type` values currently in use:
  - `schedule.run.requested` — produced by `schedule_runs.py` / cron post-back
  - `job.node.execute`       — produced by orchestrator when a node is ready
  - `job.node.finished`      — produced by worker after node execution
- `consumer_inbox` provides exactly-once delivery per
  `(consumer_name, event_id)` (with `process_status: processing →
  succeeded` lifecycle).

### Async / sync signatures

- `SchedulerService.start()` and `SchedulerService.close()` are
  `async def` (so the FastAPI lifespan can `await` them).
- `CronScheduler.start()`, `DispatchOrchestrator.start()` are
  **`def` (sync)** — they only `create_task(...)` and return. Don't
  `await` them.
- `cron.start()`, `orchestrator.start()`, `worker.handle_node_execute`
  are wired together in `SchedulerService.__init__`; their lifetime
  is owned by the facade.

## Local development

### One-time setup

```bash
# Python workspace (monorepo via uv workspaces)
uv sync --all-packages

# Frontend deps
cd frontend && pnpm install && cd ..
```

### Per-service dev

Always go through `uv run` so the workspace `.venv` is used — bare
`uvicorn` / `python` resolves to system Python and `from backend.X`
imports fail with ModuleNotFoundError.

```bash
# Backend (terminal 1)
export DATABASE_URL="mysql+asyncmy://model_platform:model_platform@127.0.0.1:3306/model_platform?charset=utf8mb4"
export STORAGE_BACKEND=s3
export S3_ACCESS_KEY=modelplatform
export S3_SECRET_KEY=modelplatformsecret
export S3_ENDPOINT=http://127.0.0.1:9000
# Or for local mode:
# export STORAGE_BACKEND=local
# export LOCAL_STORAGE_BASE_DIR=/data
uv run --package backend uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload

# Schedule Executor (terminal 2)
uv run --package schedule uvicorn schedule.main:app --host 0.0.0.0 --port 8001 --reload

# Runtime (terminal 3 — needs SYS_ADMIN, FUSE, devmode)
uv run --package runtime python -m runtime.main
```

### Frontend dev

```bash
cd frontend
pnpm dev          # http://localhost:5173, proxies /api to backend
pnpm typecheck
pnpm build
```

### Static checks

```bash
# Python compile
uv run --frozen --package backend python -m compileall -q backend/src common/src
uv run --frozen --package schedule python -m compileall -q schedule/src
uv run --frozen --package runtime python -m compileall -q runtime/src

# Type check (frontend)
cd frontend && pnpm typecheck && cd ..

# Docker compose config
docker compose config --quiet
```

### Smoke test

```bash
# Run the full ORM import + Settings smoke test
PYTHONPATH="backend/src:common/src" uv run --frozen --package backend python -c "
from backend.main import app
from common.config import settings
print('backend:', len(app.routes), 'routes')
print('settings ok:', settings.s3_endpoint)
"
```

## Common tasks

### Add a new DAG endpoint

1. Add the route handler in `backend/schedules.py` (DAG template) or
   `backend/schedule_runs.py` (run lifecycle).
2. Validate request via `backend/schedule_schemas.py`.
3. For mutations on nodes/edges/versions: route through
   `create_script_record` / `get_script_row` and apply
   `require_script_modify_access` if it touches a script.
4. If it produces an outbox event, use
   `add_outbox_event(session, event_type="...", producer="...", ...)`.

### Add a new env var

See "Adding a new env var" above.

### Add a new MySQL table

1. Add a model class in `common/src/common/db/models/<domain>.py`.
   Include `is_deleted TINYINT(1) NOT NULL DEFAULT 0` and
   `deleted_at DATETIME(3) NULL`.
2. Export it from `common/src/common/db/models/__init__.py`.
3. Generate the migration:
   ```bash
   uv run --frozen --package backend alembic revision --autogenerate -m "add <feature>"
   ```
4. Review the generated `migrations/versions/*.py` — Alembic may
   miss comments / server defaults. Manually fix the migration.
5. Apply locally:
   ```bash
   uv run --frozen --package backend alembic upgrade head
   ```

### Wire a new storage bucket

The current 4 buckets are wired in `backend/storage_api.py:resolve_bucket`:

```python
BUCKET_FOR_USAGE: dict[str, str] = {
    "working_copy":     settings.s3_workspace_bucket,
    "public_script":    settings.s3_workspace_bucket,
    "data_resource":    settings.s3_workspace_bucket,
    "snapshot":         settings.s3_workspace_bucket,
    "version_artifact": settings.s3_version_bucket,
    "run_log":          settings.s3_run_log_bucket,
    "run_result":       settings.s3_run_log_bucket,
}
```

The constant `PURPOSE_BUCKETS = ("workspace", "version", "run_log", "trash")`
in `common.storage.factory` enumerates the four backends built in the
backend lifespan. To add a fifth bucket:

1. Add the env var to `Settings` (s3 mode only):
   ```python
   s3_<feature>_bucket: str = Field(default="<feature>", description="...")
   ```
2. Add to `.env.example` with a one-line comment.
3. Append `"<feature>"` to the `PURPOSE_BUCKETS` tuple in
   `common/storage/factory.py`. `build_storage_config("<feature>")`
   will then automatically read `settings.s3_<feature>_bucket` (s3
   mode) or use `<local_storage_base_dir>/<feature>` (local mode).
4. Extend the `Literal` in `common/storage/schemas.py` (in
   `CreateUploadRequest.usage_type`, `ServerObjectRequest.usage_type`)
   to include the new value.
5. Add an entry in `BUCKET_FOR_USAGE` mapping the new `usage_type` to
   the new bucket env var.
6. Pre-create the bucket (s3 mode) or subdirectory (local mode) in the
   deployment. The backend no longer auto-creates buckets.

A workspace's `artifact_bucket` column (when non-null) overrides the
default for that workspace, regardless of `usage_type`.

### Add a new schedule node type

`schedule/execution.py` dispatches on `script_type` in
`execute_artifact`. Add a new branch + a new `_<type>` function.
`worker.py` does not need to change — the dispatch happens inside
`execute_artifact`.

## Tests

There is **no formal test suite yet** (see HANDOVER §Pending Tasks
P1). A reasonable first test surface:

- `require_script_modify_access` (admin / owner / non-owner-unlock /
  non-owner-lock): pure-function unit test, no DB.
- `validate_dag` (cycle detection + orphan detection) in
  `backend/schedules.py`.
- `execute_artifact` end-to-end with mocked `content_hash` and a
  real `tempfile.TemporaryDirectory`.

Test convention: pytest with `pytest-asyncio` for `async def`
handlers. Use SQLite in-memory (or a MySQL test container) for DB
integration. Use moto for S3.

## Troubleshooting

### "the greenlet library is required"

SQLAlchemy 2.0 needs `greenlet` for `engine.dispose()` in async
contexts. Add `greenlet>=3.0.0` to `common/pyproject.toml` and
`uv sync --all-packages`. (Already present in this repo.)

### "Can't connect to MySQL server"

Either MySQL isn't running, or the network namespace doesn't allow
`mysql:3306` resolution. Inside the Docker network, services reach
each other by service name (`mysql`, `backend`, `runtime`,
`schedule`, `s3`).

### Jupyter routing 401s

Inspect `docker compose logs backend` — `jupyter.py:check_notebook_is_locked`
or `load_active_membership` will return an explicit reason. Then
check the JWT (use `JWT_SECRET` from `.env`).

### Schedule run never advances

`schedule_runs.run_status` is stuck at `queued`. Two likely causes:
- `outbox_events` is empty (Backend's `add_outbox_event` failed —
  check `add_outbox_event` in `schedule_runs.py`).
- The orchestrator's polling loop is dead. Check
  `docker compose logs schedule` and look for "database event loop
  failed" exceptions.

### "AttributeError: 'SchedulerService' object has no attribute 'worker'"

`worker` must be constructed before `orchestrator` in
`SchedulerService.__init__`, because orchestrator's dispatch table
captures `self.worker.handle_node_execute` at construction time.
See `service.py` — the order is load-bearing.

## Style

- Type hints everywhere (this repo uses `from __future__ import
  annotations`).
- 4-space indent, double quotes, no trailing whitespace.
- Comments are technical (explain *why*, not *what*).
- Module docstrings document non-obvious invariants. Don't add
  docstrings to functions whose behavior is self-evident from the
  name.
- 4 levels of indentation = "this function is doing too much; split
  it". (Project convention; see e.g. `execute_artifact`.)

## See also

- `ARCHITECTURE.md` — design diagrams
- `HANDOVER.md` — current refactor state and pending work
- `CLAUDE.md` — agent-facing conventions for the repo
- `models / __init__.py` — exhaustive list of all 26 tables
- `common/config.py` — all env vars in one place