Report Playwright results as they run

@plune-ai/playwright is a Playwright reporter: it sends results to the Plune platform while the suite runs, instead of parsing a report afterwards.

v0.2.2no runtime depsNode ≥ 20

Reporter or import — which one

Both land runs in Plune, and neither is a lesser version of the other.

• This reporter — when the suite is Playwright. Results stream during the run, shards merge into one run, and ids resolve through annotations rather than titles.
• plune run import — when the suite is anything else, or when the report already exists and you do not want to touch the config. Reads JUnit XML from any runner, and Playwright’s own JSON.

Setup

1. Install it beside the Playwright you already have:

   npm install --save-dev @plune-ai/playwright
   npx plune login          # from @plune-ai/cli — saves your API token

2. Add it as a reporter:

   playwright.config.ts

   import { defineConfig } from "@playwright/test";
   
   export default defineConfig({
     reporter: [["list"], ["@plune-ai/playwright"]],
   });

That is the whole setup. Everything below is for cases the default does not cover.

In CI, without editing the config

A committed config cannot know the run key of a job that does not exist yet, so the environment fills in what the file left out — and anything set in the file wins.

env:
  PLUNE_TOKEN: ${{ secrets.PLUNE_TOKEN }}
  PLUNE_RUN: ${{ github.run_id }}-${{ github.run_attempt }}
  PLUNE_ENV: staging
  PLUNE_LABELS: smoke,nightly

Variable	What it does
PLUNE_TOKEN	the API token, so a CI job need not run plune login
PLUNE_RUN	the shared run key — every process with the same value lands in one run
PLUNE_API_URL	which deployment to report to
PLUNE_SHARED_RUN	this process is one of several — do not close the run
PLUNE_PROCEED	the job closes the run itself, later
PLUNE_BATCH_SIZE	results per request (default 100, max 500)
PLUNE_RUN_TITLE · PLUNE_ENV · PLUNE_LABELS	what the run is called, where it ran, how it is marked
PLUNE_CREATE	offer tests Plune has no case for to the review queue

Flags are read by value, not by presence: PLUNE_PROCEED=0 in a matrix cell means off, not on.

Sharding

Give every shard the same key and they land in one run rather than one run each:

env:
  PLUNE_RUN: ${{ github.run_id }}-${{ github.run_attempt }}
  PLUNE_SHARED_RUN: "1"

The Playwright test id is stable across shards and merges, which is what makes the same test in shard 3 of 8 resolve to the same case it resolved to yesterday.

How a result finds its case

First match wins:

1. A PluneId annotation — names the case outright.

   test("rejects a negative quantity",
     { annotation: { type: "PluneId", description: "tc-1a2b" } },
     async ({ page }) => { /* … */ });

2. A @P<id> token in the title — the same statement, where you can read it in the report. No space after @P: @Ptc-1a2b.

3. An application/plune.metadata+json attachment — for a fixture that knows the id, or a key from another tool: {"keys": [{"kind": "qase", "value": "Q-9"}]}.

4. The Playwright test id — stable across shards.

5. File and title path — cart.spec.ts#cart#rejects a negative quantity.

A result that matches no case is not sent and not invented. A made-up id would write into some other test’s history, which is worse than a gap; the run summary counts them instead. To turn those into proposals, set PLUNE_CREATE=1 — they reach the review queue and wait for a person.

When Plune is unreachable

Nothing is lost and nothing fails. An unreachable platform, a refused token or an already-closed run all append the batch to .plune/pending-results.jsonl, print one line saying so, and let your suite exit with its own code. Your tests do not depend on our uptime.

What it deliberately does not decide

The status. Playwright’s own word — passed, failed, timedOut, interrupted, skipped — goes to Plune as-is, and the project maps it. So your team can decide a timeout counts as broken (the default) or as something else, and change its mind, without waiting for a release of this package.

Platform — Getting started Mint a token, send your first run, and work the review queue.