firstException = expected;
    // Second time should also fail, with a cached causal chain.
    expected = assertThrows(PotentialDeadlockException.class, () -> lockA.lock());
    checkMessage(expected, "LockB -> LockA", "LockA -> LockB");
    // The causal chain should be cached.
    assertSame(firstException.getCause(), expected.getCause());
    // lockA should work after lockB is released.

    firstException = expected;
    // Second time should also fail, with a cached causal chain.
    expected = assertThrows(PotentialDeadlockException.class, () -> lockA.lock());
    checkMessage(expected, "LockB -> LockA", "LockA -> LockB");
    // The causal chain should be cached.
    assertSame(firstException.getCause(), expected.getCause());
    // lockA should work after lockB is released.

That way, your application won't have to generate the schema every time a user opens your API docs.

It will be generated only once, and then the same cached schema will be used for the next requests.

{* ../../docs_src/extending_openapi/tutorial001.py hl[13:14,25:26] *}

### Override the method { #override-the-method }

		// value is cached we should attempt to invalidate it if such calls
		// were attempted. This can lead to false success under certain conditions
		// - this change attempts to avoid stale information if the underlying
		// transport is already down.
		return "", errDiskNotFound
	}

	// This call should never be over the network, this is always
	// a cached value - caller should make sure to use this

        out.write(b[i]);
      }
    } else {
      out.write(b, off, len);
    }
    out.flush(); // for coverage
  }

  // TODO(chrisn): only works if we ensure we have crossed file threshold

  public void testWriteErrorAfterClose() throws Exception {
    byte[] data = newPreFilledByteArray(100);
    FileBackedOutputStream out = new FileBackedOutputStream(50);

		if len(dui.BucketsUsage) > 0 {
			internalLogOnceIf(GlobalContext, fmt.Errorf("unable to retrieve usage information for bucket: %s, relying on older value cached in-memory: err(%v)", bucket, err), "bucket-usage-cache-"+bucket)
		} else {

        return String.format("BufferCache: queued=%d, max=%d, utilization=%.1f%%", queueSize.get(), MAX_BUFFERS,
                (queueSize.get() * 100.0 / MAX_BUFFERS));
    }

    /**
     * Clear all cached buffers (for testing or cleanup)
     */
    public static void clearCache() {
        bufferQueue.clear();
        queueSize.set(0);
    }

    protected static final String GROOVY_MATCHER = "groovy:";

    /** Map of path mappings by process type. */
    protected final Map<String, List<PathMapping>> pathMappingMap = new HashMap<>();

    /** Cached list of path mappings. */
    protected volatile List<PathMapping> cachedPathMappingList = null;

    /**
     * Initializes the path mapping helper.
     */
    @PostConstruct
    public void init() {

            });
        } catch (final ExecutionException e) {
            logger.warn("Failed to load popular words.", e);
        }
        return Collections.emptyList();
    }

    /**
     * Clears all cached popular word lists.
     */
    public void clearCache() {
        cache.invalidateAll();
    }

    /**
     * Generates a cache key based on the provided parameters.
     *

		// observations. This is to test the channel based
		// synchronization used internally.
		<-ticker.C
		ttfbHist.With(prometheus.Labels{"api": obs.label}).Observe(obs.val)
	}

	// Accumulate regular-cased API label metrics for 'PutObject' for deeper verification
	metrics := getHistogramMetrics(ttfbHist, getBucketTTFBDistributionMD(), false, false)
	capitalPutObjects := make([]MetricV2, 0, len(histBuckets)+1)