*
 * Both this class and [Response] implement [Closeable]. Closing a response simply
 * closes its response body. If you invoke [Call.execute] or implement [Callback.onResponse] you
 * must close this body by calling any of the following methods:
 *
 * * `Response.close()`
 * * `Response.body().close()`
 * * `Response.body().source().close()`
 * * `Response.body().charStream().close()`
 * * `Response.body().byteStream().close()`

   * method.
   */
  public void callAndAssertWaits(String methodName, Object conditionLikeObject) throws Exception {
    checkNotNull(methodName);
    checkNotNull(conditionLikeObject);
    // TODO: Restore the following line when Monitor.hasWaiters() no longer acquires the lock.
    // assertEquals(false, invokeMethod("hasWaiters", conditionLikeObject));
    sendRequest(methodName, conditionLikeObject);
    Thread.sleep(DUE_DILIGENCE_MILLIS);

import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * Tests for {@link Queues}.
 *
 * @author Dimitris Andreou
 */
public class QueuesTest extends TestCase {
  /*
   * All the following tests relate to BlockingQueue methods in Queues.
   */

  public static List<BlockingQueue<Object>> blockingQueues() {
    return ImmutableList.<BlockingQueue<Object>>of(
        new LinkedBlockingQueue<Object>(),

     * or
     * proto:server[key1=val1,key2=val2]
     * or
     * proto:[key1=val1,key2=val2]
     *
     * If a key is absent it is assumed to be 'endpoint'. Thus the
     * following are equivalent:
     * proto:\\ts0.win.net[endpoint=\pipe\srvsvc]
     * proto:ts0.win.net[\pipe\srvsvc]
     *
     * If the server is absent it is set to "127.0.0.1"
     */

        Path topDirectory = requireNonNull(context.cwd);
        boolean isAltFile = false;
        for (String arg : context.parserRequest.args()) {
            if (isAltFile) {
                // this is the argument following -f/--file
                Path path = topDirectory.resolve(stripLeadingAndTrailingQuotes(arg));
                if (Files.isDirectory(path)) {
                    topDirectory = path;

////

**FastAPI** provides a shortcut for these cases, in where the dependency is *specifically* a class that **FastAPI** will "call" to create an instance of the class itself.

For those specific cases, you can do the following:

Instead of writing:

//// tab | Python 3.8+

```Python
commons: Annotated[CommonQueryParams, Depends(CommonQueryParams)]
```

////

//// tab | Python 3.8+ non-Annotated

## Set default rootUser, rootPassword ## AccessKey and secretKey is generated when not set ## Distributed MinIO ref: https://docs.minio.io/docs/distributed-minio-quickstart-guide ## rootUser: "" rootPassword: "" ## Use existing Secret that store following variables: ## ## | Chart var | .data.<key> in Secret | ## |:-------- ## | rootUser | rootUser | ## | rootPassword | rootPassword | ## ## All mentioned variables will be ignored in values file. ## .data.rootUser and .data.rootPassword are mandatory,...

)

func (f fatalMsg) pretty(msg string, args ...interface{}) {
	// Build the passed error message
	errMsg := fmt.Sprintf(msg, args...)

	tagPrinted := false

	// Print the error message: the following code takes care
	// of splitting error text and always pretty printing the
	// red banner along with the error message. Since the error
	// message itself contains some colored text, we needed

   * each given element has increased by one since the test collection was created, and the number
   * of occurrences of all other elements has not changed.
   *
   * <p>Note: This means that a test like the following will fail if {@code collection} is a {@code
   * Set}:
   *
   * <pre>
   * collection.add(existingElement);
   * expectAdded(existingElement);</pre>
   *

    TF_ShapeAndTypeList** shape_list_array, int num_items);

// Infer shapes for the given `op`. The arguments mimic the arguments of the
// `shape_inference::InferenceContext` constructor. Note the following:
//   - The inputs of the `op` are not used for shape inference. So, it is
//     OK to not have the inputs properly set in `op`. See `input_tensors`
//     if you want shape inference to consider the input tensors of the