assert response.status_code == 422, response.text
    assert response.json() == {
        "detail": [
            {
                "loc": ["body", 0, "url"],
                "input": "not a valid url",
                "msg": "Input should be a valid URL, relative URL without a base",
                "type": "url_parsing",
                "ctx": {"error": "relative URL without a base"},
            },
        ]
    }

        }

        @Test
        @DisplayName("Should encode input parameters correctly")
        void testEncodeIn() throws NdrException {
            // Given: Close handle message
            samr.SamrCloseHandle message = new samr.SamrCloseHandle(mockPolicyHandle);

            // When: Encoding input
            message.encode_in(mockNdrBuffer);

            // Then: Should encode handle

        assertEquals(0, exception.getErrorCode(), "Error code should be 0 for message and cause constructor.");
        assertEquals(message, exception.getMessage(), "Message should match the input.");
        assertEquals(cause, exception.getCause(), "Cause should match the input.");
        assertEquals(cause, exception.getRootCause(), "getRootCause() should return the same cause as getCause().");
    }

    /**
     * Test getErrorCode() method.
     */

    /**
     * Processes and saves an image from the input stream to the output file as a thumbnail.
     *
     * <p>This method reads image data, validates dimensions, applies subsampling and scaling
     * transformations based on configuration settings, and writes the processed thumbnail
     * to the specified output file.</p>
     *
     * @param input the image input stream containing the source image data

from pydantic import BaseModel


def forwardref_method(input: "ForwardRefModel") -> "ForwardRefModel":
    return ForwardRefModel(x=input.x + 1)


class ForwardRefModel(BaseModel):

  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

  TF_Output inputs[] = {{feed, 0}};
  TF_Output outputs[] = {{neg, 0}};
  *func = TF_GraphToFunction(func_graph.get(), name, append_hash, -1,
                             /*opers=*/nullptr, 1, inputs, 1, outputs,
                             /*output_names=*/nullptr,
                             /*opts=*/nullptr, description, s.get());

                "loc": ["query", "token"],
                "msg": "Field required",
                "input": None,
            },
            {
                "type": "missing",
                "loc": ["header", "x-token"],
                "msg": "Field required",
                "input": None,
            },
        ]
    }


def test_put_invalid_header(client: TestClient):

    public LhaExtractor() {
        super();
    }

    /**
     * Extracts text content from an LHA archive input stream.
     *
     * @param in the input stream containing the LHA archive
     * @param params extraction parameters
     * @return the extracted text data
     * @throws CrawlerSystemException if the input stream is null
     * @throws ExtractException if an error occurs during extraction

	}
}

// NewLexer returns a lexer for the named file and the given link context.
func NewLexer(name string) TokenReader {
	input := NewInput(name)
	fd, err := os.Open(name)
	if err != nil {
		log.Fatalf("%s\n", err)
	}
	input.Push(NewTokenizer(name, fd, fd))
	return input
}

// The other files in this directory each contain an implementation of TokenReader.

    assert response.json() == {
        "detail": [
            {
                "type": "missing",
                "loc": IsOneOf(["body"], ["body", "p"]),
                "msg": "Field required",
                "input": IsOneOf(None, {}),
            }
        ]
    }


@pytest.mark.parametrize(
    "path",
    ["/required-str", "/model-required-str"],
)
def test_required_str(path: str):
    client = TestClient(app)