# Path Operation Advanced Configuration

## OpenAPI operationId

!!! warning
    If you are not an "expert" in OpenAPI, you probably don't need this.

You can set the OpenAPI `operationId` to be used in your *path operation* with the parameter `operation_id`.

You would have to make sure that it is unique for each operation.

```Python hl_lines="6"
{!../../../docs_src/path_operation_advanced_configuration/tutorial001.py!}
```

	shardSize := int(e.ShardSize())
	if cap(b) < len(readers)*shardSize {
		// We should always have enough capacity, but older objects may be bigger.
		globalBytePoolCap.Load().Put(b)
		b = nil
	} else {
		// Seed the buffers.
		for i := range bufs {
			bufs[i] = b[i*shardSize : (i+1)*shardSize]
		}
	}

	return &parallelReader{
		readers:       readers,
		orgReaders:    readers,
		dataBlocks:    e.dataBlocks,

  chmod +x "/usr/local/bin/bazel"
fi

# "TFCI_MACOS_UPGRADE_PYENV_ENABLE" is used to decide if we need to upgrade the
# Pyenv version. We enable this for macOS x86 builds as the default Pyenv on
# those VMs does not support installing Python 3.12 and above which we need
# for running smoke tests in nightly/release wheel builds.
if [[ "${TFCI_MACOS_UPGRADE_PYENV_ENABLE}" == 1 ]]; then

	}
	// For forward compatibility reasons, we need to add this code.
	if len(dataUsageInfo.BucketsUsage) == 0 {
		dataUsageInfo.BucketsUsage = make(map[string]BucketUsageInfo, len(dataUsageInfo.BucketSizes))
		for bucket, size := range dataUsageInfo.BucketSizes {
			dataUsageInfo.BucketsUsage[bucket] = BucketUsageInfo{Size: size}
		}
	}

	// For backward compatibility reasons, we need to add this code.

   * the implementation will need to be revisited to support a more flexible rule.
   */
  private fun assertWildcardRule(rule: String) {
    check(rule.startsWith(WILDCARD_CHAR)) {
      """Wildcard Assertion Failure: '$rule'
A wildcard rule was added with a wildcard that is not in leftmost position! We'll need to change the ${PublicSuffixDatabase::class.java.name} to handle this."""
    }

    }

    public List<String> getWordList(final SearchRequestType searchRequestType, final String seed, final String[] tags, final String[] roles,
            final String[] fields, final String[] excludes) {
        final String baseSeed = seed != null ? seed : fessConfig.getSuggestPopularWordSeed();
        final String[] baseTags = tags != null ? tags : fessConfig.getSuggestPopularWordTagsAsArray();

            println("CACHE_MISS in task $taskPath")
            cacheMiss.set(true)
        }
    }
}


/**
 *  We monitor some tasks in non-seed builds. If a task executed in a non-seed build, we think it as "CACHE_MISS".
 */
fun isCacheMissMonitoredTask(task: Task) = task.isCompileCacheMissMonitoredTask() || task.project.isAsciidoctorCacheMissTask()

This can be very useful for setting up **resources** that you need to use for the whole app, and that are **shared** among requests, and/or that you need to **clean up** afterwards. For example, a database connection pool, or loading a shared machine learning model.

## Use Case

# ADR-0002 - Avoid using Java serialization

## Date

2012-12-01

## Context

In Gradle, we often need to serialize in-memory objects for caching or transmitting them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

            throw new IllegalStateException();
        }
        values.remove(0);
    }

    public <T> void seed(Class<T> clazz, Provider<T> value) {
        getScopeState().seed(clazz, value);
    }

    public <T> void seed(Class<T> clazz, final T value) {
        seed(clazz, (Provider<T>) () -> value);
    }

    public <T> Provider<T> scope(final Key<T> key, final Provider<T> unscoped) {