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Static API fixtures are useful for rendering a known state, but they cannot show how your app behaves across different requests and network outcomes. If a test fulfills a request with fixed JSON, it can verify the resulting UI without calling the API at all. Use fixtures for focused UI checks; use request-aware handlers, response modification, or recorded traffic when the question requires more varied request behavior—and keep a separate check against the live service when you need to test that service itself.
What static API mocks test—and what they skip
A fixed fixture gives a page predictable input: for example, a known list, an empty result, or a stable sample record. That is valuable when the goal is to check rendering without depending on a live service. In Playwright’s documented example, a route fulfills the request with a custom fruit array and the test checks that the value appears on the page. Playwright notes that the API was never called. Playwright’s API-mocking guide therefore illustrates both the strength and the boundary of this approach: the UI state is testable, but the endpoint is not exercised.
A mock test passing means the client behaved as expected under the request and response conditions encoded in that mock. It does not establish that a production API returns the same data or behaves the same way. Treat the fixture as a controlled test input, not evidence that the live service conforms to it.
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Frontend code often takes different paths depending on request details and response conditions. A single happy-path payload cannot, by itself, show what the client does when authorization fails, a response sets cookies, the server returns an error or redirect, or the response arrives after a delay. A set of fixtures can represent several states, but request-aware handlers make it possible to select outcomes based on the request and define the behavior at the network boundary.
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MSW’s documentation describes handlers for varied response behavior, including errors, redirects, cookies, and timing. These cases let tests check client behavior under explicit conditions. They remain mocked outcomes: adding more scenarios does not prove that the live service produces them.
Choose a mocking approach for the question you need to answer
| Approach | Useful when | What it does not establish |
|---|---|---|
| Static JSON or fixed response | You need predictable data for a focused rendering or UI-state check. | If the mock fulfills the request, the real API is not called. |
| Request-aware handlers | You need to match requests and model multiple response outcomes. | The handlers test only the behavior they encode; they do not verify the live service. |
| Fetch, then modify | You want data from a real API but need a controlled variation for a reproducible scenario. | The modified response is not the unmodified API response. |
| HAR record and replay | You want to capture network exchanges and replay them in a test. | Replay depends on matching requests; changed requests may not match the recording. |
| Real-service integration check | You need to check behavior against the service itself. | A mock-based test cannot substitute for this check. |
These are choices by test purpose, not a performance ranking. Playwright documents both fulfilling a request with a modified response and recording and replaying traffic. For HAR replay, the URL and HTTP method must match; POST payloads must match strictly. If the application changes the request, the stored exchange may no longer be suitable.
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How to cover loading, error, and empty states without a live API
- List the client states that matter. Include the normal result as well as relevant empty, authorization-failure, error, redirect, cookie, or delayed-response cases.
- Use the smallest boundary that answers the question. For a static rendering check, fulfill the request with a fixture. To check how the app issues requests and responds to different outcomes, use request-aware handlers or browser routing.
- Give each scenario an explicit response. Define the request match and the status, headers, body, or timing needed for the state you want the client to handle.
- Assert the user-visible behavior. Check the rendered result or error handling for that scenario; do not treat the presence of a mock as proof that the service behaves the same way.
This keeps outcomes repeatable while making clear which client branches the test actually covers. The mock should be as specific as the question, rather than an all-purpose stand-in for the backend.
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Fetch and modify when real data matters
Playwright documents a pattern that fetches a real response, alters it, then fulfills the request with the modified result. This preserves a real API call while allowing a controlled variation—for example, changing returned data to reproduce a client state. Because the test sees the altered result, it does not validate the original response unchanged.
Use HAR replay when a captured exchange is the useful input
A HAR records requests and responses for replay. It can make a recorded exchange available without depending on a fresh live response, but matching is strict: URL and method must match, and POST bodies must match strictly. When requests evolve, update or recapture the recording rather than assuming an old entry will still match.
Can you reuse API mocks in development and end-to-end tests?
MSW presents its network behavior layer for reuse across local development, integration and end-to-end tests, Storybook, and demos. In a browser, it uses a Service Worker to intercept requests at the network level. Shared handlers can keep scenarios consistent across those settings, though the behavior they encode still needs maintenance as the app and service change.
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There is an important interaction when combining MSW with Playwright routing. Playwright’s network guide warns that MSW’s Service Worker can make requests invisible to Playwright’s built-in page and browser-context routing. Do not assume both interception layers automatically see the same traffic. Choose the interception mechanism for the test, or configure Service Workers and routing deliberately so the test observes the intended request path.
Keep mock tests and service checks distinct
Use mocks to test how the frontend responds to defined conditions. Use a real-service integration check when the question is whether the service itself returns the expected response. The two layers answer different questions: a passing mock test covers the client’s behavior under its encoded conditions, while a live check exercises the actual service path. Keeping that distinction explicit makes test results easier to interpret and prevents a simulated response from being mistaken for a verified backend behavior.
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