subProjectTestClassTimes: List<SubprojectTestClassTime>,
        testCoverage: TestCoverage,
        parallelization: (Int) -> ParallelizationMethod,
    ): List<SmallSubprojectBucket> {
        // splitIntoBuckets() method expects us to split large element into N elements,
        // but we want to have a single bucket with N batches.
        // As a workaround, we repeat the bucket N times, and deduplicate the result at the end

Dann können wir das „Dependable“ `common_parameters` der Abhängigkeit von oben in die Klasse `CommonQueryParams` ändern:

{* ../../docs_src/dependencies/tutorial002_an_py310.py hl[11:15] *}

Achten Sie auf die Methode `__init__`, die zum Erstellen der Instanz der Klasse verwendet wird:

{* ../../docs_src/dependencies/tutorial002_an_py310.py hl[12] *}

... sie hat die gleichen Parameter wie unsere vorherige `common_parameters`:

* `@app.post()`
* `@app.put()`
* `@app.delete()`
* usw.

{* ../../docs_src/response_status_code/tutorial001.py hl[6] *}

/// note | Hinweis

Beachten Sie, dass `status_code` ein Parameter der „Dekorator“-Methode ist (`get`, `post`, usw.). Nicht der *Pfadoperation-Funktion*, so wie die anderen Parameter und der Body.

///

Dem `status_code`-Parameter wird eine Zahl mit dem HTTP-Statuscode übergeben.

/// info

        StackTraceElement[] stackTrace = exception.getStackTrace();
        assertNotNull(stackTrace);
        assertTrue(stackTrace.length > 0);

        // Verify the top of the stack trace contains this test method
        boolean foundTestMethod = false;
        for (StackTraceElement element : stackTrace) {
            if (element.getMethodName().equals("test_stackTracePresence")) {
                foundTestMethod = true;

      } else {
        oldCell.merge(value, merger);
      }
    }

    /*
     * While the current implementation returns `this`, that's not something we mean to guarantee.
     * Anyway, the purpose of this method is to implement a BinaryOperator combiner for a Collector,
     * so its return value will get used naturally.
     */
    @SuppressWarnings("CanIgnoreReturnValueSuggester")
    ImmutableTableCollectorState<R, C, V> combine(

			t.Fatalf("Test %d: got %v expected %v", i+1, actual, tc)
		}
	}
}

// TestRestoreObjOnDisk tests restoreObjStatus' OnDisk method
func TestRestoreObjOnDisk(t *testing.T) {
	testCases := []struct {
		restoreStatus restoreObjStatus
		ondisk        bool
	}{
		{
			// restore in progress
			restoreStatus: ongoingRestoreObj(),

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

            StackOverflowError.class,
            e -> e instanceof StackOverflowError);
      }
    };

    // used under GWT, etc., since the override of this method does not exist there
    ImmutableMap<Class<? extends Throwable>, Predicate<Throwable>> exceptions() {
      return ImmutableMap.of();
    }
  }

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

labels.purgeJobLogDay=Delete old job logs
labels.purgeUserInfoDay=Delete old user logs
labels.reading=Reading
labels.roleTypeIds=Role IDs
labels.scriptData=Script
labels.scriptResult=Result
labels.scriptType=Execution Method
labels.segmentation=Segmentation
labels.startTime=Start Time
labels.target=Target
labels.token=Token
labels.synonymFile=Synonym File
labels.stopwordsFile=Stopwords File