assertEquals("BoostQuery", boostQueryCommand.getQueryClassName());
    }

    public void test_execute_withTermQuery() {
        // Test executing BoostQuery with a TermQuery inside
        Term term = new Term("field", "value");
        TermQuery termQuery = new TermQuery(term);
        BoostQuery boostQuery = new BoostQuery(termQuery, 2.5f);

	// if object upload fails stop the test.
	if err != nil {
		t.Fatalf("Error uploading object: <ERROR> %v", err)
	}

	// initialize httptest Recorder, this records any mutations to response writer inside the handler.
	rec := httptest.NewRecorder()
	// construct HTTP request for DELETE bucket.

{* ../../docs_src/query_params_str_validations/tutorial002_an_py310.py hl[9] *}

Notice that the default value is still `None`, so the parameter is still optional.

	for i, testCase := range testCases {
		// obtain the put bucket policy request body.
		// initialize HTTP NewRecorder, this records any mutations to response writer inside the handler.
		recV4 := httptest.NewRecorder()
		// construct HTTP request for PUT bucket policy endpoint.
		reqV4, err := newTestSignedRequestV4(http.MethodPut, getPutPolicyURL("", testCase.bucketName),

The `TestClient` does some magic inside to call the asynchronous FastAPI application in your normal `def` test functions, using standard pytest. But that magic doesn't work anymore when we're using it inside asynchronous functions. By running our tests asynchronously, we can no longer use the `TestClient` inside our test functions.

///

If you used to rely on this behavior, now you should create the resources for background tasks inside the background task itself, and use internally only data that doesn't depend on the resources of dependencies with `yield`.

* Use the `templates` you created to render and return a `TemplateResponse`, pass the name of the template, the request object, and a "context" dictionary with key-value pairs to be used inside of the Jinja2 template.

{* ../../docs_src/templates/tutorial001.py hl[4,11,15:18] *}

/// note

Before FastAPI 0.108.0, Starlette 0.29.0, the `name` was the first parameter.

        /** The URL of the zip file. */
        protected final URL zipUrl;

        /** Prefix of entries inside the zip. */
        protected final String prefix;

        /** Set of entry names inside the zip. */
        protected final Set<String> entryNames = newHashSet();

        /**
         * Constructs an instance.
         *
         * @param url

        verify(mockDeferredNdrBuffer).advance(4 * sidArray.num_sids);
        verify(sidArray.sids[0]).encode(any(NdrBuffer.class)); // Buffer reassignment happens inside encode
        verify(sidArray.sids[1]).encode(any(NdrBuffer.class)); // Buffer reassignment happens inside encode
    }

    @Test
    void testLsarSidArrayEncodeNullSids() throws NdrException {
        lsarpc.LsarSidArray sidArray = new lsarpc.LsarSidArray();

# to PyPI.
if [[ "$TFCI_MACOS_TWINE_INSTALL_ENABLE" == 1 ]]; then
  pip install twine==3.6.0
fi

# When cross-compiling with RBE, we need to copy the macOS sysroot to be
# inside the TensorFlow root directory. We then define them as a filegroup
# target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel
# can register it as an input to compile/link actions and send it to the remote
# VMs when needed.