* <p>A high-quality hash function strives for some subset of the following virtues:
 *
 * <ul>
 *   <li><b>collision-resistant:</b> while the definition above requires making at least <i>some</i>
 *       token attempt, one measure of the quality of a hash function is <i>how well</i> it succeeds
 *       at this goal. Important note: it may be easy to achieve the theoretical minimum collision

to do with this creature when I get it home?' when it grunted
again, so violently, that she looked down into its face in some
alarm.  This time there could be NO mistake about it:  it was
neither more nor less than a pig, and she felt that it would be
quite absurd for her to carry it further.

  So she set the little creature down, and felt quite relieved to

 * may cause corruption or runtime errors if not. It may however be shared amongst multiple OkHttpClient
 * instances.
 *
 * ## Cache Optimization
 *
 * To measure cache effectiveness, this class tracks three statistics:
 *
 *  * **[Request Count:][requestCount]** the number of HTTP requests issued since this cache was
 *    created.

In almost any framework handling the security becomes a rather complex subject quite quickly.

Many packages that simplify it a lot have to make many compromises with the data model, database, and available features. And some of these packages that simplify things too much actually have security flaws underneath.

---

**FastAPI** doesn't make any compromise with any database, data model or tool.

The same way as with Pydantic models, you declare class attributes with type annotations, and possibly default values.

You can use all the same validation features and tools you use for Pydantic models, like different data types and additional validations with `Field()`.

//// tab | Pydantic v2

```Python hl_lines="2  5-8  11"
{!> ../../docs_src/settings/tutorial001.py!}
```

import com.google.common.collect.testing.TestStringMapGenerator;
import com.google.common.collect.testing.features.CollectionFeature;
import com.google.common.collect.testing.features.CollectionSize;
import com.google.common.collect.testing.features.MapFeature;
import com.google.common.testing.FakeTicker;
import com.google.common.testing.NullPointerTester;
import com.google.common.testing.SerializableTester;

import com.google.common.collect.testing.TestStringMapGenerator;
import com.google.common.collect.testing.features.CollectionFeature;
import com.google.common.collect.testing.features.CollectionSize;
import com.google.common.collect.testing.features.MapFeature;
import com.google.common.testing.FakeTicker;
import com.google.common.testing.NullPointerTester;
import com.google.common.testing.SerializableTester;

import com.google.common.collect.testing.ListTestSuiteBuilder;
import com.google.common.collect.testing.NavigableSetTestSuiteBuilder;
import com.google.common.collect.testing.features.CollectionFeature;
import com.google.common.collect.testing.features.CollectionSize;
import com.google.common.collect.testing.google.SetGenerators.ImmutableSortedSetAsListGenerator;

such as MinIO. MapReduce workloads typically interact with object stores in the same way they do with HDFS. These workloads rely on HDFS atomic rename functionality to complete writing data to the datastore. Object storage operations are atomic by nature and they do not require/implement rename API. The default S3A committer emulates renames through copy and delete APIs. This interaction pattern causes significant loss of performance because of the write amplification. _Netflix_, for example, developed...

		class="org.codelibs.fess.crawler.extractor.impl.HtmlExtractor">
		<property name="featureMap">
			<component class="java.util.LinkedHashMap">
				<postConstruct name="put">
					<arg>"http://xml.org/sax/features/namespaces"</arg>
					<arg>"false"</arg>
				</postConstruct>
			</component>
		</property>
		<property name="propertyMap">
			<component class="java.util.LinkedHashMap">
			</component>
		</property>