Here we'll see an example using <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">SQLModel</a>.

**SQLModel** is built on top of <a href="https://www.sqlalchemy.org/" class="external-link" target="_blank">SQLAlchemy</a> and Pydantic. It was made by the same author of **FastAPI** to be the perfect match for FastAPI applications that need to use **SQL databases**.

You could have a proxy that adds a path prefix to your application.

In these cases you can use `root_path` to configure your application.

The `root_path` is a mechanism provided by the ASGI specification (that FastAPI is built on, through Starlette).

The `root_path` is used to handle these specific cases.

And it's also used internally when mounting sub-applications.

    executor.setThreadFactory(
        new ThreadFactoryBuilder()
            .setDaemon(true)
            .setThreadFactory(executor.getThreadFactory())
            .build());
  }

  /**
   * Creates an executor service that runs each task in the thread that invokes {@code
   * execute/submit}, as in {@link CallerRunsPolicy} This applies both to individually submitted

        supportedLanguages = fessConfig.getSupportedLanguagesAsArray();
        langItemsCache = CacheBuilder.newBuilder()
                .maximumSize(20)
                .expireAfterAccess(1, TimeUnit.HOURS)
                .build(new CacheLoader<String, List<Map<String, String>>>() {
                    @Override
                    public List<Map<String, String>> load(final String key) throws Exception {

* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

      return "CharSource.wrap(" + Ascii.truncate(seq, 30, "...") + ")";
    }
  }

  /**
   * Subclass specialized for string instances.
   *
   * <p>Since Strings are immutable and built into the jdk we can optimize some operations
   *
   * <ul>
   *   <li>use {@link StringReader} instead of {@link CharSequenceReader}. It is faster since it can

      return "CharSource.wrap(" + Ascii.truncate(seq, 30, "...") + ")";
    }
  }

  /**
   * Subclass specialized for string instances.
   *
   * <p>Since Strings are immutable and built into the jdk we can optimize some operations
   *
   * <ul>
   *   <li>use {@link StringReader} instead of {@link CharSequenceReader}. It is faster since it can

import com.google.common.primitives.Longs;
import junit.framework.TestCase;
import org.jspecify.annotations.NullUnmarked;

/**
 * Tests for {@link StatsAccumulator}. This tests the stats methods for instances built with {@link
 * StatsAccumulator#add} and {@link StatsAccumulator#addAll}, and various error cases of the {@link
 * StatsAccumulator#add} and {@link StatsAccumulator#addAll} methods. For tests of the {@link

    /** The sequence number of the most recently committed edit to this entry. */
    internal var sequenceNumber: Long = 0

    init {
      // The names are repetitive so re-use the same builder to avoid allocations.
      val fileBuilder = StringBuilder(key).append('.')
      val truncateTo = fileBuilder.length
      for (i in 0 until valueCount) {
        fileBuilder.append(i)

   */
  private void ensureCapacity(int minCapacity) {
    if (nextInBucketKToV.length < minCapacity) {
      int oldCapacity = nextInBucketKToV.length;
      int newCapacity = ImmutableCollection.Builder.expandedCapacity(oldCapacity, minCapacity);

      keys = Arrays.copyOf(keys, newCapacity);
      values = Arrays.copyOf(values, newCapacity);
      nextInBucketKToV = expandAndFillWithAbsent(nextInBucketKToV, newCapacity);