triggers {
            val triggerHour = branch.determineNightlyPromotionTriggerHour() ?: return@triggers
            // for master/release branch, we trigger them on midnight (with pending change only, i.e. if there is no change, don't rigger it)
            // for old release branches, we trigger them on midnight if there is change, or unconditionally on weekends
            when {
                branch.isMaster || branch.isRelease ->

test:rbe_base --test_env=USER=anon

# TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu.
common:rbe_linux --config=rbe_base
common:rbe_linux --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"
# Non-rbe settings we should include because we do not run configure
common:rbe_linux --config=avx_linux
# TODO(gunan): Check why we need this specified in rbe, but not in other builds.

            }
            metadataSources {
                artifact()
            }
            content {
                includeModule('gradle', 'gradle')
            }
        }
    }
}

// We support multiple accepted public api changes JSON files, but "accepted-public-api-changes.json"
// is the "main" one that is also shown in HTML report

        }
    }
)


class User(BaseModel):
    username: str


# Here we use string annotations to test them
def get_current_user(oauth_header: "str" = Security(reusable_oauth2)):
    user = User(username=oauth_header)
    return user


@app.post("/login")
# Here we use string annotations to test them
def login(form_data: "OAuth2PasswordRequestFormStrict" = Depends()):
    return form_data

// Here you should declare versions which should be shared by the different modules of buildSrc itself
val javaParserVersion = "3.18.0"
// Note: this currently still contains 3/4 logic as we will temporarily have Groovy 3 for the build itself until we move to a Gradle built with Groovy 4
// It can be removed or changed to 4/5 logic (if necessary) at that point.
val groovyVersion = GroovySystem.getVersion()

1. Should avoid using simplified Chinese characters and terms. Always examine if the translation can be easily comprehended by the Traditional Chinese readers.
2. For some Python-specific terms like "pickle", "list", "dict" etc, we don't have to translate them.
3. Use the following preferred translations when they apply in documentation prose:

- request (HTTP): 請求
- response (HTTP): 回應
- path operation: 路徑操作
- path operation function: 路徑操作函式

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. We still import `field` from standard `dataclasses`.

2. `pydantic.dataclasses` is a drop-in replacement for `dataclasses`.

3. The `Author` dataclass includes a list of `Item` dataclasses.

            "city": "Anytown",
            "state_province": "CA",
        },
    }


def test_openapi_schema(client: TestClient):
    """
    Sanity check to ensure our app's openapi schema renders as we expect
    """
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text
    assert response.json() == snapshot(
        {
            "components": {
                "schemas": {

            # Pydantic >= 2.12.0 warns about field specific metadata that is unused
            # (e.g. `TypeAdapter(Annotated[int, Field(alias='b')])`). In some cases, we
            # end up building the type adapter from a model field annotation so we
            # need to ignore the warning:
            if shared.PYDANTIC_VERSION_MINOR_TUPLE >= (2, 12):
                from pydantic.warnings import UnsupportedFieldAttributeWarning