punctual
The reliability layer cron never had. One long-running process, zero
infrastructure, a config file that reads like a crontab — plus the five things
every team ends up bolting onto cron by hand:
cron |
punctual |
|
|---|---|---|
| Retries / backoff | ✗ | ✓ |
| Catch-up after downtime | ✗ (silently skips) | ✓ (per-job policy) |
| Dependencies between jobs | ✗ | ✓ (after = [...], no DAG file) |
| "Did the 3am job run?" | ✗ | ✓ (durable run history, metrics, traces) |
| Exactly-once under overlap/restart | ✗ | ✓ (claim-before-run) |
Not Airflow. Airflow (and Dagster, Temporal, …) assume a database, a scheduler
process, a web server, a worker pool, and that you'll rewrite your jobs as DAGs.
That's right at 500 jobs and 12 engineers. punctual is for the machine with
6 scripts on it — which is most machines.
Status: alpha. The full M0–M6 roadmap is built (scheduling, retries, dependencies, observability, clustering, Python jobs). See
docs/DESIGN.mdfor every decision and why.
The shape of it
# punctual.toml
[job.scrape]
schedule = "*/10 * * * *"
command = "python -m sniper.scrape"
on_missed = "skip" # skip | run_latest | run_each
[job.retrain]
command = "python -m sniper.retrain"
after = ["scrape"] # runs when scrape succeeds (no clock)
timeout = "45m"
retries = { max = 3, backoff = "exponential" }
on_fail = "ntfy://my-topic" # page after retries are exhausted
$ punctual run # start the daemon (put this under systemd/launchd)
$ punctual plan # what runs next: catch-up + annotated fire list
$ punctual status # one line per job: health, quarantine
$ punctual history retrain # every run: when, how long, exit code, output
$ punctual why retrain # health, last run, pending retry, next fire
$ punctual why retrain 412 # explain one run: trigger, attempts, what happened next
$ punctual graph # the `after` dependency tree (--format dot for graphviz)
$ punctual trigger backup # run a job now (ignore schedule / after / quarantine)
$ punctual resume retrain # take a job out of quarantine
$ punctual reload # apply added / removed jobs without a restart
$ punctual stop --kill # drain (or hard-kill) the running daemon
$ punctual metrics # Prometheus text; also GET /metrics if a port is set
$ punctual tui # read-only dashboard (pip install punctual-scheduler[tui])
Set [observability] metrics_port = 9095 in punctual.toml and the daemon
serves GET /metrics (per-job counters, run-duration histogram,
punctual_time_since_last_success_seconds — the SLO gauge) and GET /healthz
on 127.0.0.1:9095.
Python jobs
A job can be a Python function instead of a command:
# myapp/jobs.py
from punctual import job, step
@job("reindex", schedule="0 * * * *", retries={"max": 2}, timeout="30m")
def reindex():
docs = step("export", lambda: db.dump()) # runs once per fire; on a retry
step("index", lambda: search.load(docs)) # a completed step is replayed,
# not re-run
# punctual.toml
[python]
modules = ["myapp.jobs"] # the daemon imports these; decorators register the jobs
The function runs in its own subprocess (python -m punctual._inproc …), so it
gets the same process-group kill, timeout, output capture and crash recovery as
a shell command. TOML [job.*] tables and @job functions mix freely.
step(name, fn) checkpoints work inside a fire (keyed by the fire's timestamp);
results must be JSON-serialisable.
Quickstart
$ uv tool install --prerelease=allow punctual-scheduler # or: pipx install --pre punctual-scheduler
$ mkdir -p ~/.config/punctual && cat > ~/.config/punctual/punctual.toml <<'EOF'
[job.heartbeat]
schedule = "* * * * * */30" # every 30s — 6-field cron: seconds go LAST
command = "date -u +%FT%TZ"
[job.backup]
schedule = "0 3 * * *" # 03:00 daily
command = "restic backup /home/me"
EOF
$ punctual -c ~/.config/punctual/punctual.toml validate
$ punctual -c ~/.config/punctual/punctual.toml run # Ctrl-C drains, then exits
# ...in another shell:
$ punctual -c ~/.config/punctual/punctual.toml history
09-01 14:30 heartbeat succeeded 0.0s exit 0
09-01 14:30 backup succeeded 12.4s exit 0
State lives in ~/.local/state/punctual/punctual.db (override with $PUNCTUAL_DB).
To keep it running, install a service — see packaging/.
High availability
Run two daemons against one shared store and pass --cluster:
$ punctual -c punctual.toml run --cluster # host A — becomes leader
$ punctual -c punctual.toml run --cluster # host B — hot standby
One daemon holds a 30 s lease and does all the scheduling; the other idles until
that lease expires, then takes over (failover ≈ 30–40 s). Every node's control
socket stays live, so ping / healthz / metrics work on both;
healthz reports standby on the follower.
A cluster on one SQLite file is only as available as that host, so point it at Postgres:
$ pip install "punctual-scheduler[postgres]"
# punctual.toml
[store]
url = "postgresql://punctual:secret@db.internal:5432/punctual"
[store] url also takes sqlite://<path>; unset means the default XDG file.
$PUNCTUAL_STORE_URL overrides the config.
What works today (M1–M5): scheduling,
afterdependencies (trigger-driven, fan-in, upstream-failure policy,wait_timeout),punctual triggerfor an ad-hoc run, subprocess exec with output capture + timeouts, durable history, restart recovery + catch-up, retries with backoff, a quarantine circuit-breaker, failure/recovery notifications (ntfy/slack/discord/exec/ webhook / plugins),why/status/ annotatedplan/graph, a control socket (drain/stop/reload), Prometheus/metrics+/healthz, structured JSON logs (--log-format json), a read-only TUI, lease-based leader election (run --cluster), a Postgres store,@punctual.jobPython jobs, and durable in-jobstep()checkpoints. That's M0–M6 — the whole roadmap. Seedocs/DESIGN.md.
Design principles
- A missed run is an incident, not a shrug. cron's original sin is silence.
- Zero infra to start. Embedded SQLite. No server, no broker, no web app.
- Crontab-shaped. If you can write a crontab you can write a
punctual.toml. - Exactly-once is at-least-once + idempotency. We're honest about that and build the idempotency in.
- Grows, doesn't bloat. Single node → leader-elected cluster → durable in-process steps, same core.
License
Apache-2.0.
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