# durable-rust
Lightweight durable job execution engine backed by Postgres.
No external services, no replay log, no orchestrator. Just checkpointed steps in plain Rust.
## Quick example
```rust
use durable::{Ctx, DurableError};
async fn ingest(db: &DatabaseConnection) -> Result<(), DurableError> {
let ctx = Ctx::start(db, "ingest", None).await?;
// Step 1 — runs once, result saved to Postgres
let shards: Vec<u32> = ctx.step("resolve_shards", || async {
Ok(vec![0, 1, 2, 3])
}).await?;
// Step 2..N — skips already-completed shards on resume
for shard in shards {
ctx.step(&format!("shard_{shard}"), || async move {
process_shard(shard).await
}).await?;
}
// Child workflow with its own steps
let child = ctx.child("post_process", None).await?;
child.step("notify", || async { send_slack("done").await }).await?;
child.complete(&"ok").await?;
ctx.complete(&"finished").await?;
Ok(())
}
```
If the process crashes at shard 2, on restart it skips shards 0-1 (results saved) and resumes from 2.
## Schema
Two tables in a `durable` schema:
- **`task`** -- unified row for workflows, steps, and child workflows. Self-referential via `parent_id`. Idempotent creation via `UNIQUE(parent_id, name)`.
- **`task_queue`** -- optional concurrency and rate-limit controls.
See [doc/schema.md](doc/schema.md) for the full DDL, indexes, and status lifecycle.
## Getting started
1. Start Postgres:
```sh
docker compose -f compose.db.yml up -d
```
2. Add the dependency:
```toml
[dependencies]
durable = { package = "durable-rust", version = "0.1" }
```
3. Initialize in your app -- connects and runs migrations automatically:
```rust
let db = durable::init("postgres://durable:durable@localhost:5432/durable").await?;
```
4. Write workflows using `Ctx`:
- `Ctx::start(&db, name, input)` -- create or resume a root workflow
- `ctx.step(name, closure)` -- run-once step with saved output
- `ctx.child(name, input)` -- spawn a nested child workflow
- `ctx.complete(output)` -- mark workflow done
- `Ctx::pause(&db, task_id)` -- pause a running workflow (cascades to children)
- `Ctx::resume(&db, task_id)` -- resume a paused workflow
- `Ctx::cancel(&db, task_id)` -- cancel a workflow permanently (cascades to children)
## Pause, resume, and cancel
Workflows can be paused, resumed, or cancelled by task ID -- useful for admin tooling or HTTP handlers:
```rust
// Pause a running workflow — all pending/running children are paused too
Ctx::pause(&db, task_id).await?;
// Resume — workflow goes back to RUNNING, children reset to PENDING
Ctx::resume(&db, task_id).await?;
// Cancel permanently — sets CANCELLED on the workflow and all non-terminal children
Ctx::cancel(&db, task_id).await?;
```
When a workflow is paused, any in-progress step will complete, but the next `step()`, `child()`, or `transaction()` call returns `DurableError::Paused`. After `resume()`, execution continues from where it left off.
Cancellation is terminal — a cancelled workflow cannot be resumed.
## Crate structure
| `durable-rust` | `crates/durable` | SDK -- `Ctx`, `DurableError`, `Executor`, proc-macro re-exports. The only crate users add. |
| `durable-db` | `crates/durable-db` | SeaORM migrations for the `durable` schema (pulled in transitively) |
| `durable-macros` | `crates/durable-macros` | `#[durable::workflow]` and `#[durable::step]` proc macros (pulled in transitively) |
## Run the example
```sh
docker compose -f compose.db.yml up -d
cargo run -p nested-etl
```
The `nested-etl` example runs a parent ETL workflow that spawns child workflows per data source, then demonstrates crash recovery by resuming mid-run.
## Run tests
```sh
cargo test --workspace
```
## Multi-node setup
Multiple workers can share one Postgres database. Each worker sets a unique `executor_id`:
```
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
│ Worker A │ │ Worker B │ │ Worker C │
│ executor_id │ │ executor_id │ │ executor_id │
│ = "a1b2" │ │ = "c3d4" │ │ = "e5f6" │
└──────┬───────┘ └──────┬───────┘ └──────┬───────┘
│ │ │
└────────┬────────┴────────┬────────┘
│ │
▼ ▼
┌─────────────────────────────────┐
│ Postgres │
│ durable.task (all state) │
│ durable.task_queue (limits) │
└─────────────────────────────────┘
```
**How it works:**
- Workers dequeue tasks with `FOR UPDATE SKIP LOCKED` -- no double-processing
- Each task's `executor_id` column tracks which worker owns it
- On startup, a worker resets its own stale `RUNNING` tasks to `PENDING` (single-worker recovery)
- For cross-worker recovery (worker A detects worker B crashed), enable the executor heartbeat (see [#7](https://github.com/code-salad/durable-rust/issues/7))
**Queue concurrency control:**
```sql
-- task_queue limits how many tasks run concurrently per queue
INSERT INTO durable.task_queue (name, max_concurrency) VALUES ('ingest', 4);
-- Workers respect the limit across all nodes
-- If 4 ingest tasks are RUNNING, the 5th worker waits
```
## Design docs
- [doc/api.md](doc/api.md) -- API design with proc macros (`#[durable::workflow]`, `#[durable::step]`)
- [doc/dataflow.md](doc/dataflow.md) -- dataflow diagrams for direct, queued, scheduled, and nested execution
- [doc/schema.md](doc/schema.md) -- full schema DDL and status lifecycle
## Design principles
1. **Postgres is the source of truth** -- no WAL, no event log, no separate replay mechanism
2. **Steps are idempotent by design** -- if a step completed, its saved result is returned; the closure is never re-executed
3. **No orchestrator** -- the job runner is just your application code calling `ctx.step()`
4. **No serialization framework** -- uses `serde_json` for input/output
5. **Crash safe** -- incomplete steps are detected on resume; completed steps replay from saved output
6. **Observable** -- query the `durable.task` table directly for monitoring and debugging