from docs_src.query_params.tutorial005 import app

client = TestClient(app)


def test_foo_needy_very():
    response = client.get("/items/foo?needy=very")
    assert response.status_code == 200
    assert response.json() == {"item_id": "foo", "needy": "very"}


def test_foo_no_needy():
    response = client.get("/items/foo")
    assert response.status_code == 422
    assert response.json() == IsDict(
        {

// PolicyRule maps requests based off metadata to an audit Level.
// Requests must match the rules of every field (an intersection of rules).
message PolicyRule {
  // The Level that requests matching this rule are recorded at.
  optional string level = 1;

  // The users (by authenticated user name) this rule applies to.
  // An empty list implies every user.
  // +optional
  // +listType=atomic
  repeated string users = 2;

    * Although it's probably not very problematic here with the way `SQLAlchemy` works.
    * But if you added more code to the middleware that had a lot of <abbr title="input and output">I/O</abbr> waiting, it could then be problematic.
* A middleware is run for *every* request.
    * So, a connection will be created for every request.

## Composition by architecture modules

Each [architecture module and platform](platforms.md) can contribute code to any of the runtimes.
Not every module contributes to every runtime.

The core-runtime module defines each runtime:

- The target JVM for the runtime. Each runtime has its own JVM compatibility constraints.

# Dependencies

**FastAPI** has a very powerful but intuitive **<abbr title="also known as components, resources, providers, services, injectables">Dependency Injection</abbr>** system.

It is designed to be very simple to use, and to make it very easy for any developer to integrate other components with **FastAPI**.

## What is "Dependency Injection"

    return client


@needs_pydanticv1
def test_post_body_example(client: TestClient):
    response = client.put(
        "/items/5",
        json={
            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,
        },
    )
    assert response.status_code == 200


@needs_pydanticv1
def test_openapi_schema(client: TestClient):

// flushing the buffer.
//
// TODO: A "go:nosplitrec" annotation would be perfect for this.
//
//go:nowritebarrierrec
//go:nosplit
func wbBufFlush() {
	// Note: Every possible return from this function must reset
	// the buffer's next pointer to prevent buffer overflow.

	if getg().m.dying > 0 {
		// We're going down. Not much point in write barriers

 * Dependency resolution consistency configuration for
 * the Java derived plugins.
 *
 * @since 6.8
 */
@Incubating
public interface JavaResolutionConsistency {
    /**
     * Configures the runtime classpath of every source set to be consistent
     * with the compile classpath. For dependencies which are common between
     * the compile classpath and the runtime classpath, the version from the
     * compile classpath is going to be used.

    return client


@needs_pydanticv2
def test_post_body_example(client: TestClient):
    response = client.put(
        "/items/5",
        json={
            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,
        },
    )
    assert response.status_code == 200


@needs_pydanticv2
def test_openapi_schema(client: TestClient):

@needs_py310
@needs_pydanticv1
def test_post_body_example(client: TestClient):
    response = client.put(
        "/items/5",
        json={
            "name": "Foo",
            "description": "A very nice Item",
            "price": 35.4,
            "tax": 3.2,
        },
    )
    assert response.status_code == 200


@needs_py310
@needs_pydanticv1
def test_openapi_schema(client: TestClient):