Schedules

What are Schedules?

Schedules attach a cron expression to a function and trigger it automatically.

Every scheduled run executes the target function in a fresh isolated microVM, just like a manual invocation.

Create a schedule

First deploy a function, then attach a schedule to it:

from pandastack import Client

client = Client()

fn = client.functions.deploy(name="daily-report", runtime="python", path="handler.py")
schedule = client.schedules.create("daily-report", fn["id"], "0 9 * * *")
print(schedule["id"])

import { Client } from "@pandastack/sdk";
import { readFileSync } from "node:fs";

const client = new Client();

const fn = await client.functions.create("daily-report", "python", readFileSync("handler.py"), {
  entrypoint: "handler.py",
});
const schedule = await client.schedules.create("daily-report", fn.id, "0 9 * * *");
console.log(schedule.id);

pandastack function deploy handler.py --name daily-report --runtime python
pandastack schedule create --name daily-report --fn <function-id> --cron "0 9 * * *"

curl -X POST https://api.pandastack.ai/v1/schedules \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"name": "daily-report", "function_id": "<function-id>", "cron": "0 9 * * *"}'

The schedule stores:

function_id
name
cron
paused
last_run_at
created_at
updated_at

Cron syntax

Schedules use standard 5-field cron expressions:

┌ minute (0 - 59)
│ ┌ hour (0 - 23)
│ │ ┌ day of month (1 - 31)
│ │ │ ┌ month (1 - 12)
│ │ │ │ ┌ day of week (0 - 6)
│ │ │ │ │
* * * * *

Examples:

*/5 * * * * — every 5 minutes
0 * * * * — every hour
0 9 * * * — every day at 09:00 UTC
0 0 * * 1 — every Monday at midnight UTC

Pause and resume

client.schedules.update("<schedule-id>", paused=True)   # pause
client.schedules.update("<schedule-id>", paused=False)  # resume

await client.schedules.update("<schedule-id>", { paused: true });   // pause
await client.schedules.update("<schedule-id>", { paused: false });  // resume

pandastack schedule pause <schedule-id>
pandastack schedule resume <schedule-id>

# Pause
curl -X PATCH https://api.pandastack.ai/v1/schedules/<schedule-id> \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"paused": true}'

# Resume
curl -X PATCH https://api.pandastack.ai/v1/schedules/<schedule-id> \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"paused": false}'

Pausing keeps the schedule definition but stops future automatic invocations until you resume it.

Trigger manually

run = client.schedules.trigger("<schedule-id>")
print(client.schedules.runs("<schedule-id>"))

const run = await client.schedules.trigger("<schedule-id>");
console.log(await client.schedules.runs("<schedule-id>"));

pandastack schedule trigger <schedule-id>
pandastack schedule runs <schedule-id>

curl -X POST https://api.pandastack.ai/v1/schedules/<schedule-id>/trigger \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{}'

curl https://api.pandastack.ai/v1/schedules/<schedule-id>/runs \
  -H "Authorization: Bearer $PANDASTACK_API_KEY"

Manual triggers are useful for testing a cron-backed workflow immediately without waiting for the next scheduled window.

Update a schedule

client.schedules.update("<schedule-id>", cron="0 */6 * * *")

await client.schedules.update("<schedule-id>", { cron: "0 */6 * * *" });

pandastack schedule update <schedule-id> --cron "0 */6 * * *"

curl -X PATCH https://api.pandastack.ai/v1/schedules/<schedule-id> \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"cron": "0 */6 * * *"}'

Use updates when you need to change cadence without redeploying the underlying function.