*/

package com.google.common.math;

import java.math.BigInteger;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying

  final Collection<? extends Throwable> exceptions;

  private ClusterException(Collection<? extends Throwable> exceptions) {
    super(
        exceptions.size() + " exceptions were thrown. The first exception is listed as a cause.",
        exceptions.iterator().next());
    ArrayList<? extends Throwable> temp = new ArrayList<>(exceptions);
    this.exceptions = Collections.unmodifiableCollection(temp);
  }

You can combine normal FastAPI *path operations* with GraphQL on the same application.

/// tip

**GraphQL** solves some very specific use cases.

It has **advantages** and **disadvantages** when compared to common **web APIs**.

Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

///

## GraphQL Libraries { #graphql-libraries }

	. "bytes"
	"syscall"
	"testing"
)

// This file tests the situation where byte operations are checking
// data very near to a page boundary. We want to make sure those
// operations do not read across the boundary and cause a page
// fault where they shouldn't.

// These tests run only on linux. The code being tested is
// not OS-specific, so it does not need to be tested on all
// operating systems.

        long result = (long) a + (long) b;
        if (result > Integer.MAX_VALUE || result < Integer.MIN_VALUE) {
            throw new ArithmeticException(operation + " would cause integer overflow: " + a + " + " + b);
        }
    }

    /**
     * Validates integer multiplication for safe arithmetic
     *
     * @param a first operand
     * @param b second operand

  final Collection<? extends Throwable> exceptions;

  private ClusterException(Collection<? extends Throwable> exceptions) {
    super(
        exceptions.size() + " exceptions were thrown. The first exception is listed as a cause.",
        exceptions.iterator().next());
    ArrayList<? extends Throwable> temp = new ArrayList<>(exceptions);
    this.exceptions = Collections.unmodifiableCollection(temp);
  }

# OpenAPI Webhooks { #openapi-webhooks }

There are cases where you want to tell your API **users** that your app could call *their* app (sending a request) with some data, normally to **notify** of some type of **event**.

This means that instead of the normal process of your users sending requests to your API, it's **your API** (or your app) that could **send requests to their system** (to their API, their app).

This is normally called a **webhook**.

For example, you cannot put a Pydantic model in a `JSONResponse` without first converting it to a `dict` with all the data types (like `datetime`, `UUID`, etc) converted to JSON-compatible types.

For those cases, you can use the `jsonable_encoder` to convert your data before passing it to a response:

{* ../../docs_src/response_directly/tutorial001.py hl[6:7,21:22] *}

/// note | Technical Details

        if (cause != null) {
          initCause(cause)
        }
      }

    @Throws(IOException::class)
    fun exitAndThrowIfTimedOut() {
      if (exit()) throw newTimeoutException(null)
    }
  }

   * {@link Long#MAX_VALUE} or {@link Long#MIN_VALUE}. This behavior can be useful when decomposing
   * a duration in order to call a legacy API which requires a {@code long, TimeUnit} pair.
   */
  // We use this method only for cases in which we need to decompose to primitives.
  @SuppressWarnings({"GoodTime-ApiWithNumericTimeUnit", "GoodTime-DecomposeToPrimitive"})
  @IgnoreJRERequirement
  static long toNanosSaturated(Duration duration) {