#Run your own scripts

Keep the test scripts you already have. A recipe step runs your script with exec. The script publishes what it measured as channels, and the recipe judges them. Instrument SDKs, vendor tools and SSH sessions all work as they are.

Copyrecipe("unit_accept", setup="load_test", unit="serial")

ch = channels()
reading = ch["/dut/reading"]

level = value("reading_at_rest")
require(level.below(0.5))

step("read", exec("python3 read.py --source running", timeout="60s"),
             measure(level, reading))

plan(steps=["read"])

#What exec does

The exit code decides nothing. A script can exit 0 after failing to do its job. The verdict comes from measurements taken afterwards, from an independent read of the unit.

Your script gets the run's details as environment variables:

Read fields from the environment, not the command line. exec splits at spaces, so "python3 cfg.py --batch " + field("batch") breaks on a batch called Batch 7, while os.environ["PHLOEM_FIELD_BATCH"] always holds the whole value.

#Publishing readings from the script

Your script publishes channels like any input, by POSTing readings to the device's push endpoint. See Send your own data for the address, body and responses.

Set up once:

Declare the same cadence in the setup that reads it:

Copych.read("/dut/output_v", unit="V", cadence="episodic")

A setup arms only after it has seen every channel it reads. Your script's channel has no data before the first step. Without cadence="episodic", Start run stays blocked on "waiting for first data" until someone enters the value by hand.

Declared episodic, the setup arms without it and never calls it stale. The recipe judges it with measure() in the step that produced it. An episodic channel can't carry checks= or an interlock, since nothing watches it between steps. Both declarations must agree: a setup that calls a stream episodic is refused at deploy.

A minimal reader:

Copyimport json, subprocess, time, urllib.request

def read_unit():
    out = subprocess.run(["my-tool", "status"], capture_output=True, text=True).stdout
    try:
        return float(out.split("reading=", 1)[1].split()[0])
    except (IndexError, ValueError):
        return None          # could not read it — publish nothing

def publish(readings):
    t_us = time.time_ns() // 1000
    body = [{"path": p, "samples": [{"t_us": t_us, "value": {"f64": v}}]}
            for p, v in readings.items() if v is not None]
    if not body:
        return
    req = urllib.request.Request(PUSH_URL, data=json.dumps(body).encode(),
                                 headers={"Content-Type": "application/json"})
    urllib.request.urlopen(req).read()

publish({"/dut/reading": read_unit()})

PUSH_URL is the endpoint on Send your own data.

#See the shape first

Before you write a recipe for a script, run the script once and read what it prints (its describe verb, or a --dry-run read). Probing scripts, on Settings → Document scripts, lets the assistant do this for you. It runs a file in the script folder once, never as a test run. While probing it can read anywhere, write only a scratch folder, reach no network, and start only the script or python. It is off by default; a refusal names the switch.

#Rules that keep a verdict honest

Updated November 6, 2026