Use Playwright’s retry-aware result model when you need trustworthy counts: a test is passed if its first run passes, flaky if the first run fails but a retry passes, and failed if the first run and every retry fail. For people, run the list or dot reporter. For CI, write a JSON report or aggregate results in a custom reporter.
What Playwright means by passed, flaky, and failed
Playwright counts logical tests rather than treating every attempt as a separate test. Its retry definitions are:
- Passed: the first run passed.
- Flaky: the first run failed, but a retry passed.
- Failed: the first run failed and all retries failed.
Retries are disabled by default. Enable them with the --retries=N command-line option or the retries setting in your Playwright configuration. Without retries, a first-run failure cannot be classified as flaky.
These definitions differ from attempt totals. If one test runs once and then twice more as retries, Playwright has made three attempts but there is still one logical test. Decide which number your dashboard needs before aggregating results.
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Choose the right way to get counts
| Method | Best for | What it provides | Main caution |
|---|---|---|---|
list reporter |
Detailed human review | One readable line per test and a final summary | Terminal text is not a stable machine-readable interface |
dot reporter |
Compact CI logs | Symbols for pass, failure, retry, flaky, timeout and skip | Symbols are useful to people but awkward to parse reliably |
| JSON reporter | CI files and scripts | A comprehensive report written to an output file | Inspect the generated shape for your installed Playwright version |
| Custom Reporter | Exact, retry-aware aggregation | Access to complete TestResult objects in onTestEnd |
You must define identity, scope and handling for nonstandard statuses |
See counts in a human-readable terminal report
Use the list reporter
Run:
npx playwright test --reporter=listThe list reporter prints individual test results and a summary that includes categories such as passed and flaky. It is the easiest choice when a developer is reading a local run and does not need to feed the output into another program.
Use the dot reporter for compact output
npx playwright test --reporter=dotThe dot reporter maps common outcomes to symbols: · for passed, F for failed, × for a retrying run, ± for a test that ultimately passed on retry (flaky), T for timed out, and ° for skipped. Treat the final summary as the count source; do not count every symbol as a separate logical test when retries are enabled.
A three-test run can legitimately finish with one flaky and two passed. That is an example of the classification, not a general performance statistic.
Write a JSON report for CI
Configure a readable terminal reporter and the JSON reporter together so people can watch the run while automation consumes a file:
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export default defineConfig({
reporter: [
['list'],
['json', { outputFile: 'test-results.json' }],
],
});Run your normal command:
npx playwright testAfter completion, read test-results.json in the CI workspace and archive it as an artifact. The JSON reporter is a better automation input than scraping list or dot output because it is intended to describe the run, not merely display it.
Do not hard-code an assumed JSON shape
The nesting and field layout can vary between Playwright versions and reporter consumers. Generate a report with the exact version installed in your project, inspect its top-level projects, suites, specs and tests, and then pin your parser to the fields you actually use. Keep the Playwright version and parser changes in the same review when possible.
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If you aggregate multiple projects, shards or repeat-each runs, include those dimensions in your data model. A raw sum of every result node may count the same logical test several times.
Count logical tests with a custom Reporter
For a stable in-process count, implement the Reporter interface and aggregate in onTestEnd(test, result). Playwright calls this method after the run for that attempt has finished, so the TestResult is complete. The result exposes a status and a sequential retry number.
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Illustrative reporter aggregation
type Attempt = { status: string; retry: number };
const attempts = new Map<string, Attempt[]>();
function record(testId: string, result: Attempt) {
const list = attempts.get(testId) ?? [];
list.push(result);
attempts.set(testId, list);
}
function classify(list: Attempt[]) {
const first = list.find(a => a.retry === 0) ?? list[0];
const retriedPass = list.some(a => a.retry > 0 && a.status === 'passed');
if (first?.status === 'passed') return 'passed';
if (first?.status === 'failed' && retriedPass) return 'flaky';
if (first?.status === 'failed' && list.every(a => a.status === 'failed')) return 'failed';
return 'other';
}In a real reporter, call record from onTestEnd(test, result), using a test identity that remains the same across retries. Depending on your version and project setup, that identity can be derived from the test’s stable identifier and its project context. Do not use a changing attempt number as the map key.
Why grouping is necessary
onTestEnd runs once for each attempt. With retries enabled, counting callback invocations directly inflates the number of tests. Store all attempts for one logical test, select the attempt with retry === 0 as the first run, and then apply the three classifications above.
Handle statuses beyond the three headline categories
The result status can also represent timed-out, skipped, interrupted, expected-failure and version-specific states. Keep an explicit other, skipped or timedOut bucket instead of silently labeling those outcomes as failed. Decide whether expected failures belong in a separate total before publishing a CI metric.
Emit the final totals
Print or write totals from the reporter’s completion hook, after all onTestEnd callbacks have arrived. A minimal output shape is:
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{
"passed": 42,
"flaky": 3,
"failed": 2,
"other": 1
}The values above are only an output example. Your reporter should calculate them from the current run.
Make the scope explicit in CI
Projects
Chromium, Firefox and WebKit projects can execute the same test independently. Report per project when browser-specific health matters, or merge by a stable logical identity when you want one cross-browser test total. Document which interpretation your dashboard uses.
Shards
Each shard sees only part of the suite. Upload one report per shard and merge them using a stable test identity. Never compare a single shard’s counts with the full-suite total.
Retries
Retries add attempts, not logical tests. A first-run failure followed by a passing retry contributes one flaky test, not one failed plus one passed test.
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repeatEach intentionally runs a test multiple times. Decide whether your metric counts each repetition as a separately evaluated case or collapses repetitions into one logical test, and include that choice in the metric name.
Common counting problems and fixes
Every retry appears as a failure
Cause: the script counts attempts or reads an intermediate status. Fix: group by test identity, select retry zero as the first run, and classify only after all attempts finish.
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No tests are marked flaky
Cause: retries are still disabled, or the parser ignores retry records. Fix: set retries in configuration or pass --retries=N, then verify that retry attempts and their numbers are present in the report.
JSON parsing breaks after an upgrade
Cause: the parser assumed an undocumented nesting or field name. Fix: save a fixture generated by the installed version, inspect it during upgrades, and keep parsing limited to fields your version documents or consistently emits.
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Totals differ between local and CI
Cause: different projects, shards, repeat counts, workers or retry settings. Fix: record those settings with the report and compare the same scope. Merge shard files before calculating a suite-wide total.
Timeouts are reported as ordinary failures
Cause: the aggregation collapses every non-passed status into failed. Fix: preserve the status field and publish a separate timed-out count when that distinction matters.
Skipped tests disappear from the dashboard
Cause: only passed, flaky and failed buckets were implemented. Fix: add an explicit skipped bucket and decide whether skipped tests belong in the denominator.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Performance and reliability considerations
- Use the dot reporter for low-noise logs and JSON for machine processing; avoid parsing terminal decoration.
- Write reports to a workspace location that survives the CI step that uploads artifacts.
- Keep reporter aggregation in memory keyed by test identity, then emit once at completion; this avoids double-counting while keeping per-attempt details available.
- For large suites, stream or archive raw JSON and compute derived totals in a separate job, but preserve project and shard metadata.
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Frequently Asked Questions
Are flaky tests included in the failed count?
No. Under Playwright’s retry model, a test that fails first and passes on retry is flaky, not failed. Define any combined “non-green” metric separately.
Can I get counts without enabling retries?
Yes, you can count passed and failed first attempts. You cannot identify flaky tests unless a failed first attempt is retried.
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No. Use the JSON reporter or a custom Reporter. Dot output is intended for compact human-readable logs.
Why do my totals exceed the number of test cases?
Retries, projects, shards or repeat-each may be adding attempts. State the scope and group attempts by logical test identity before counting.
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