* href="http://portal.acm.org/citation.cfm?id=6621">min-max heap</a> developed by Atkinson, et al.
 * Unlike many other double-ended priority queues, it stores elements in a single array, as compact
 * as the traditional heap data structure used in {@link PriorityQueue}.
 *
 * <p>This class is not thread-safe, and does not accept null elements.
 *
 * <p><i>Performance notes:</i>
 *
 * <ul>

   * any other start node, such as a tree or forest.
   *
   * <p>{@code forTree()} is especially useful (versus {@code forGraph()}) in cases where the data
   * structure being traversed is, in addition to being a tree/forest, also defined <a
   * href="https://github.com/google/guava/wiki/GraphsExplained#non-recursiveness">recursively</a>.

 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code
 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for

import org.jetbrains.kotlin.analysis.low.level.api.fir.api.getOrBuildFirFile
import org.jetbrains.kotlin.analysis.low.level.api.fir.api.getOrBuildFirOfType
import org.jetbrains.kotlin.analysis.project.structure.KtSourceModule
import org.jetbrains.kotlin.backend.jvm.JvmBackendExtension
import org.jetbrains.kotlin.codegen.ClassBuilderMode
import org.jetbrains.kotlin.codegen.generateLanguageVersionSettingsBasedMetadataFlags

				relValue = joinSchema.ReflectValueOf(db.Statement.Context, currentReflectValue)
				if relValue.Kind() == reflect.Ptr {
					fullRelsName := utils.JoinNestedRelationNames(fullRels)
					// same nested structure
					if _, ok := joinedNestedSchemaMap[fullRelsName]; !ok {
						if value := reflect.ValueOf(values[idx]).Elem(); value.Kind() == reflect.Ptr && value.IsNil() {
							isNilPtrValue = true
							break
						}

 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>As compared with {@link java.util.LinkedHashMap}, this structure places significantly reduced
 * load on the garbage collector by only using a constant number of internal objects.
 *
 * <p>This class should not be assumed to be universally superior to {@code

So, we are going to focus only on the differences.

## File structure

Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```

This is almost the same structure as we had for the SQLAlchemy tutorial.

 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code
 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for

import com.google.common.primitives.Booleans;
import java.io.Serializable;
import java.util.NoSuchElementException;
import javax.annotation.CheckForNull;

/**
 * Implementation detail for the internal structure of {@link Range} instances. Represents a unique
 * way of "cutting" a "number line" (actually of instances of type {@code C}, not necessarily

 *
 * There is no benefit to invoking multiple `close()` methods for the same response body.
 *
 * For synchronous calls, the easiest way to make sure a response body is closed is with a `try`
 * block. With this structure the compiler inserts an implicit `finally` clause that calls
 * [close()][Response.close] for you.
 *
 * ```java
 * Call call = client.newCall(request);
 * try (Response response = call.execute()) {