///

### What is "Mounting" { #what-is-mounting }

"Mounting" means adding a complete "independent" application in a specific path, that then takes care of handling all the sub-paths.

This is different from using an `APIRouter` as a mounted application is completely independent. The OpenAPI and docs from your main application won't include anything from the mounted application, etc.

## Mounting a **FastAPI** application { #mounting-a-fastapi-application }

"Mounting" means adding a completely "independent" application in a specific path, that then takes care of handling everything under that path, with the _path operations_ declared in that sub-application.

### Top-level application { #top-level-application }

        "https://github.com/bazelbuild/rules_shell/releases/download/v0.4.1/rules_shell-v0.4.1.tar.gz",
    ),
)

# Initialize toolchains for ML projects.
#
# A hermetic build system is designed to produce completely reproducible builds for C++.
# Details: https://github.com/google-ml-infra/rules_ml_toolchain
tf_http_archive(
    name = "rules_ml_toolchain",
    sha256 = "f2c924e85a22ba2eaa0c08657e5f5467fedbc3d0506f9cc0c69dd97ed9fbaf28",

And it should have an `access_token`, with a string containing our access token.

For this simple example, we are going to just be completely insecure and return the same `username` as the token.

/// tip

In the next chapter, you will see a real secure implementation, with password hashing and <abbr title="JSON Web Tokens">JWT</abbr> tokens.

For example, to set it to be served at `/api/v1/openapi.json`:

{* ../../docs_src/metadata/tutorial002_py310.py hl[3] *}

If you want to disable the OpenAPI schema completely you can set `openapi_url=None`, that will also disable the documentation user interfaces that use it.

## Docs URLs { #docs-urls }

You can configure the two documentation user interfaces included:

        }
    }

    /**
     * Creates a permissive filter that allows all classes to be deserialized.
     * <p>
     * WARNING: Use this only when you completely trust the data source and have
     * other security measures in place. Unrestricted deserialization can lead to
     * remote code execution vulnerabilities.
     * </p>
     *

        assertFalse(result3.isPresent());
    }

    // Test selectList method with empty file
    @Test
    public void test_selectList_emptyFile() throws Exception {
        // Write completely empty file
        try (java.io.FileWriter fw = new java.io.FileWriter(testFile)) {
            // Write nothing
        }

        // Create a new CharMappingFile instance to ensure clean state

			for {
				select {
				case <-done:
					return
				case <-ticker.C:
					res.deleteExpired()
				}
			}
		}(res.done)
	}
	return &res
}

// Purge clears the cache completely.
// onEvict is called for each evicted key.
func (c *LRU[K, V]) Purge() {
	c.mu.Lock()
	defer c.mu.Unlock()
	for k, v := range c.items {
		if c.onEvict != nil {
			c.onEvict(k, v.Value)
		}

The client will get a **500 Internal Server Error** for that request, but the application will continue working for the next requests instead of just crashing completely.

### Bigger Errors - Crashes { #bigger-errors-crashes }

Nevertheless, there might be cases where we write some code that **crashes the entire application** making Uvicorn and Python crash. 💥

# instead depend on the dummy plugins in //tensorflow/compiler/xla/tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.
check_deps(
    name = "cuda_plugins_check_deps",
    disallowed_deps = if_static(
        [],