Columns: []clause.Column{{Name: "role"}},
				Having:  []clause.Expression{clause.Eq{"role", "admin"}},
			}},
			"SELECT * FROM `users` GROUP BY `role` HAVING `role` = ?",
			[]interface{}{"admin"},
		},
		{
			[]clause.Interface{clause.Select{}, clause.From{}, clause.GroupBy{
				Columns: []clause.Column{{Name: "role"}},
				Having:  []clause.Expression{clause.Eq{"role", "admin"}},
			}, clause.GroupBy{

		builder.WriteString(" HAVING ")
		Where{Exprs: groupBy.Having}.Build(builder)
	}
}

// MergeClause merge group by clause
func (groupBy GroupBy) MergeClause(clause *Clause) {
	if v, ok := clause.Expression.(GroupBy); ok {
		copiedColumns := make([]Column, len(v.Columns))
		copy(copiedColumns, v.Columns)
		groupBy.Columns = append(copiedColumns, groupBy.Columns...)

		copiedHaving := make([]Expression, len(v.Having))

		t.Errorf("name should be groupby, but got %v, total should be 60, but got %v", name, total)
	}

	if err := DB.Model(&User{}).Select("name, sum(age) as total").Where("name LIKE ?", "groupby%").Group("name").Having("name = ?", "groupby1").Row().Scan(&name, &total); err != nil {
		t.Errorf("no error should happen, but got %v", err)
	}

	if name != "groupby1" || total != 660 {

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.

import org.junit.jupiter.params.provider.ArgumentsProvider
import org.junit.jupiter.params.provider.ArgumentsSource
import org.junit.jupiter.params.support.ParameterDeclarations

/**
 * This enforces us having the params classes on the classpath to workaround
 * https://github.com/graalvm/native-build-tools/issues/745
 */
class WithArgumentSourceTest {
  @ParameterizedTest
  @ArgumentsSource(FakeArgumentsProvider::class)

   * the result is chosen uniformly at random in [0, numBits), and then the result is chosen in that
   * range uniformly at random. Zero is treated as having log2 == 0.
   */
  static BigInteger randomNonNegativeBigInteger(int numBits) {
    int digits = RANDOM_SOURCE.nextInt(numBits);
    if (digits == 0) {
      return new BigInteger(1, RANDOM_SOURCE);
    } else {

## Date

2024-12-20

## Context

### Embedding a Java runtime in the Gradle distribution

There have been discussions on embedding a Java runtime in the Gradle distribution.
This would allow users to run Gradle without having to install a Java runtime beforehand.
This capability could help increase Gradle adoption outside of the JVM ecosystem.

Gradle can be invoked in different ways:

For now we just have this global repository of ADRs.
If we see fit, we can break these out to per-platform ones, or keep a hybrid approach to having global and platform-specific ADSs.

Our aim is to keep the process lightweight and approachable.

   *       expression involving {@code view} will throw)
   *   <li>{@code hashCode()} does not throw
   *   <li>if {@code node} is re-added to the graph after having been removed, {@code view}'s
   *       behavior is undefined
   * </ul>
   *
   * @throws IllegalArgumentException if {@code node} is not an element of this graph
   */
  Set<N> adjacentNodes(N node);

  /**

## Parameterized dependencies { #parameterized-dependencies }

All the dependencies we have seen are a fixed function or class.

But there could be cases where you want to be able to set parameters on the dependency, without having to declare many different functions or classes.

Let's imagine that we want to have a dependency that checks if the query parameter `q` contains some fixed content.

But we want to be able to parameterize that fixed content.