`@lru_cache` is part of `functools` which is part of Python's standard library, you can read more about it in the <a href="https://docs.python.org/3/library/functools.html#functools.lru_cache" class="external-link" target="_blank">Python docs for `@lru_cache`</a>.

## Recap { #recap }

### 10.1 Handle Caching Strategy
```java
public class HandleCache {
    private final int maxHandles = 1000;
    private final LinkedHashMap<String, HandleInfo> lruCache;
    
    public HandleCache() {
        this.lruCache = new LinkedHashMap<String, HandleInfo>(maxHandles, 0.75f, true) {
            @Override
            protected boolean removeEldestEntry(Map.Entry<String, HandleInfo> eldest) {

String last = CollectionsUtil.getLast(sequenced);
SequencedCollection<String> reversed = CollectionsUtil.reversed(sequenced);

// Specialized collections
LruHashMap<String, Object> lruCache = new LruHashMap<>(100); // LRU cache with max 100 entries
CaseInsensitiveMap<String> configMap = new CaseInsensitiveMap<>();
```

### Resource Management
```java
import org.codelibs.core.io.*;

* Start Portuguese translations. PR [#1210](https://github.com/tiangolo/fastapi/pull/1210) by [@cassiobotaro](https://github.com/cassiobotaro).
* Update docs for Pydantic's `Settings` using a dependency with `@lru_cache()`. PR [#1214](https://github.com/tiangolo/fastapi/pull/1214).