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adora-project

dora-rs/dora/.claude/skills/adora-project/SKILL.md

Dora project architecture, conventions, and patterns. Auto-activate when working in this repository. Keywords: dora, dataflow, node, operator, daemon, coordinator, shared memory, zero-copy, Arrow, YAML, DaemonRequest, DaemonReply, DoraNode, DoraOperator, DataflowId, NodeId, RuntimeConfig

Skill4k starsChanged 44 days ago

What's in it

  1. Dora Project Patterns
  2. Architecture Overview
  3. Message Protocol
  4. Node Lifecycle
  5. Key Abstractions
  6. Data Format
  7. Dataflow YAML Schema
  8. Communication Patterns
  9. Topic (Default)
  10. Service (Request/Reply)
  11. Action (Goal/Feedback/Result)
  12. State & Parameters
  13. ID Conventions
  14. Error Handling Patterns
  15. Testing Conventions
  16. Build Commands (Quick Reference)
  17. PyO3 Bindings
  18. Key Conventions
---
description: "Dora project architecture, conventions, and patterns. Auto-activate when working in this repository. Keywords: dora, dataflow, node, operator, daemon, coordinator, shared memory, zero-copy, Arrow, YAML, DaemonRequest, DaemonReply, DoraNode, DoraOperator, DataflowId, NodeId, RuntimeConfig"
triggers:
  - dataflow
  - node
  - operator
  - daemon
  - coordinator
  - shared memory
  - DaemonRequest
  - DoraNode
  - RuntimeConfig
  - DataflowId
---

# Dora Project Patterns

## Architecture Overview

```
CLI (WS:6013) --> Coordinator --> Daemon(s) --> Nodes / Operators
                  (orchestrate)   (per machine)  (user code)
```

- **Coordinator**: Single orchestrator, persistent state (in-memory or redb), label-based node scheduling
- **Daemon**: Per-machine process manager, owns shared memory regions, TCP/Unix sockets to nodes
- **Node**: Separate OS process, communicates via shared memory (>4KB) or TCP (small msgs)
- **Operator**: In-process (runtime), no IPC overhead

## Message Protocol

All inter-component messages are in `libraries/message/src/`. Key types:

| Message | Direction | File | Purpose |
|---------|-----------|------|---------|
| `DaemonRequest` / `DaemonReply` | Node <-> Daemon | `node_to_daemon.rs` / `daemon_to_node.rs` | Data send/recv, subscribe, register |
| `DaemonCoordinatorEvent` | Coordinator -> Daemon | `coordinator_to_daemon.rs` | Spawn/stop nodes, reload |
| `CoordinatorRequest` | Daemon -> Coordinator | `daemon_to_coordinator.rs` | Status, logs, node results |
| `InterDaemonEvent` | Daemon <-> Daemon | `daemon_to_daemon.rs` | Cross-machine message routing |

Messages are versioned. Version check happens at connection init.

## Node Lifecycle

1. Coordinator sends `SpawnNode` to target Daemon (selected by labels)
2. Daemon creates `RunningNode` with `RuntimeConfig` passed as env var (JSON)
3. Node process starts, connects back to Daemon via TCP/Unix socket
4. Node registers inputs/outputs, subscribes to data channels
5. Data flows via bounded `flume` channels internally, shared memory for large payloads
6. On stop: soft kill (SIGTERM) -> grace period -> hard kill (SIGKILL)

## Key Abstractions

```rust
// Node API (apis/rust/node/src/node/mod.rs)
pub struct DoraNode { /* ... */ }
impl DoraNode {
    pub fn init(node_config: NodeConfig) -> NodeResult<(Self, EventStream)>;
    pub fn init_from_env() -> NodeResult<(Self, EventStream)>;
    pub fn init_from_node_id(node_id: NodeId) -> NodeResult<(Self, EventStream)>;
    pub fn init_flexible(node_id: NodeId) -> NodeResult<(Self, EventStream)>;
    pub fn init_interactive() -> NodeResult<(Self, EventStream)>;

    pub fn send_output(&mut self, output_id: DataId, parameters: MetadataParameters, data: impl Array) -> NodeResult<()>;
    pub fn send_service_request(&mut self, output_id: DataId, parameters: MetadataParameters, data: impl Array) -> NodeResult<String>;  // returns auto-generated request_id
    pub fn send_service_response(&mut self, output_id: DataId, parameters: MetadataParameters, data: impl Array) -> NodeResult<()>;
}

// Operator API (apis/rust/operator/src/lib.rs)
pub trait DoraOperator: Default {
    fn on_event(&mut self, event: &Event, output_sender: &mut DoraOutputSender) -> Result<DoraStatus, String>;
}
```

## Data Format

- **Apache Arrow** columnar format throughout (zero serialization)
- Messages >4KB use shared memory (4 named regions per node)
- Messages <4KB use TCP directly
- Python bindings use `arrow::pyarrow` for zero-copy across FFI

## Dataflow YAML Schema

```yaml
nodes:
  my-node:
    path: path/to/executable        # or "shell:" or Python script
    inputs:
      input_name: other-node/output  # Simple form
      input_with_opts:               # Extended form
        source: other-node/output
        queue_size: 10
        queue_policy: drop_oldest    # drop_oldest (default) | backpressure
    outputs:
      - output_name
    env:
      KEY: value
    args: "-v --some-flag foo"       # String, not a list
    restart_policy: on-failure       # never | on-failure | always
    health_check_timeout: 2.0        # seconds (per node)
    deploy:                # unstable, may change
      machine: gpu-server
```

Top-level descriptor fields:
```yaml
health_check_interval: 5.0           # seconds (global)
```

**Virtual inputs** (daemon-generated):
- `dora/timer/secs/<N>` or `dora/timer/millis/<N>`
- `dora/logs`, `dora/logs/<level>`, `dora/logs/<level>/<node>`

## Communication Patterns

### Topic (Default)
Standard pub/sub. Node sends output, all subscribers receive.

### Service (Request/Reply)
```rust
// Client: request_id is auto-generated and returned
let request_id = node.send_service_request(
    "service_output".into(),
    MetadataParameters::default(),
    data,
)?;

// Server: pass through request_id from incoming metadata
if let Some(req_id) = metadata.get(dora_message::metadata::REQUEST_ID) {
    let mut params = MetadataParameters::default();
    params.insert(REQUEST_ID.to_string(), req_id.clone());
    node.send_service_response("response_output".into(), params, result)?;
}
```

### Action (Goal/Feedback/Result)
Uses `goal_id` and `goal_status` metadata keys. Supports cancellation.

## State & Parameters

- **Coordinator Store**: Persistent state via `CoordinatorStore` trait (in-memory or redb backend)
- **Parameters**: Key-value per dataflow, propagated via `SetParam`/`GetParam`/`DeleteParam`
- **Distributed state**: UHLC (hybrid logical clock) for distributed causality
- **Node state**: `restart_count`, `last_activity` (atomic), `pid`
- **Fault tolerance**: `FaultToleranceStats` with atomic counters

## ID Conventions

- **DataflowId**: UUID v7 (sortable, timestamp-based)
- **NodeId**: String identifier from YAML
- **Timestamps**: UHLC for cross-machine ordering
- Metadata keys defined in `libraries/message/`: `REQUEST_ID`, `GOAL_ID`, `GOAL_STATUS`, `SESSION_ID`

## Error Handling Patterns

- `eyre::Result` for application errors (with `.context()` chains)
- `NodeErrorCause` enum: `GraceDuration`, `Cascading`, `FailedToSpawn`, `Other`
- Restart policies with exponential backoff (configurable window)
- Cascading error tracking: which node caused which failure

## Testing Conventions

| Change Type | Test Tier | Location |
|------------|-----------|----------|
| Library function | Unit `#[cfg(test)]` | Same file |
| Coordinator/Daemon behavior | Integration | `binaries/coordinator/tests/` |
| CLI command | Smoke (networked) | `tests/example-smoke.rs` |
| Dataflow feature | Smoke (both modes) | `tests/example-smoke.rs` |
| Bug fix | Regression | Whichever tier reproduces it |

**Smoke test helpers**:
- `run_smoke_test(name, yaml, timeout)` -- networked mode (up/start/poll/stop/down)
- `run_smoke_test_local(name, yaml, stop_after_secs)` -- local mode (run --stop-after)

**Integration test setup**: `setup_integration_testing()` with JSON inputs via `DORA_TEST_WITH_INPUTS` env var.

## Build Commands (Quick Reference)

```bash
# Build (exclude Python)
cargo build --all --exclude dora-node-api-python --exclude dora-operator-api-python --exclude dora-ros2-bridge-python

# Test (exclude Python + examples)
cargo test --all --exclude dora-node-api-python --exclude dora-operator-api-python --exclude dora-ros2-bridge-python --exclude dora-runtime-python --exclude dora-cli-api-python --exclude dora-examples

# Single crate
cargo test -p dora-core

# Pre-commit (mandatory)
cargo fmt --all -- --check
cargo clippy --all --exclude dora-node-api-python --exclude dora-operator-api-python --exclude dora-ros2-bridge-python -- -D warnings
```

## PyO3 Bindings

- Python Node API: `apis/python/node/` -- `#[pyclass] Node` with iterator protocol
- Python Operator API: `apis/python/operator/` -- type conversion utilities
- Python CLI API: `apis/python/cli/` -- `build()`, `run()`, `start_runtime()`
- Uses PyO3 0.29 with `eyre`, `abi3-py311`, `multiple-pymethods` features
- Arrow arrays passed zero-copy via `arrow::pyarrow` FFI
- GIL released during blocking Rust ops (`py.detach()`)

## Key Conventions

- Rust edition 2024, MSRV 1.85.0
- Workspace version 0.2.0 (all crates share it)
- `flume` bounded MPSC for internal event routing
- `tokio` async runtime with full features
- `Zenoh` for distributed cross-machine pub/sub
- Zero-copy threshold: 4KB
- Fire-and-forget for logging/metrics (never block data path)

More agent context in dora-rs/dora

2 other files this repository gives its agents.

AGENTS.md

CLAUDE.md

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