*
     * @param phase
     * @return
     */
    public Lifecycle get(String phase) {
        return getPhaseToLifecycleMap().get(phase);
    }

    /**
     * We use this to map all phases to the lifecycle that contains it. This is used so that a user can specify the
     * phase they want to execute, and we can easily determine what lifecycle we need to run.
     *
     * @return A map of lifecycles, indexed on id

  platforms = json.load(meta)
  meta.close()
  aliases = platforms['aliases']
  api_levels = sorted(list(set([aliases[i] for i in aliases])))

  android_ndk_api_level = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_NDK_API_LEVEL',
      var_default='21',  # 21 is required for ARM64 support.
      ask_for_var=(
          'Please specify the (min) Android NDK API level to use. '

from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/optional-str", operation_id="optional_str")
async def read_optional_str(p: Annotated[str | None, Form()] = None):
    return {"p": p}


class FormModelOptionalStr(BaseModel):

from inline_snapshot import snapshot
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/required-str")
async def read_required_str(p: str):
    return {"p": p}


class QueryModelRequiredStr(BaseModel):
    p: str


@app.get("/model-required-str")

from inline_snapshot import snapshot
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/optional-str")
async def read_optional_str(p: Annotated[str | None, Header()] = None):
    return {"p": p}


class HeaderModelOptionalStr(BaseModel):
    p: str | None = None

from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/optional-list-str", operation_id="optional_list_str")
async def read_optional_list_str(
    p: Annotated[list[str] | None, Form()] = None,
):
    return {"p": p}

Um desses sistemas de gerenciamento de contêineres distribuídos como o Kubernetes normalmente tem alguma maneira integrada de lidar com a **replicação de contêineres** enquanto ainda oferece **balanceamento de carga** para as solicitações recebidas. Tudo no **nível do cluster**.

from fastapi.testclient import TestClient

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/optional-bytes", operation_id="optional_bytes")
async def read_optional_bytes(p: Annotated[bytes | None, File()] = None):
    return {"file_size": len(p) if p else None}

from pydantic import BaseModel, Field

from .utils import get_body_model_name

app = FastAPI()

# =====================================================================================
# Without aliases


@app.post("/required-str", operation_id="required_str")
async def read_required_str(p: Annotated[str, Form()]):
    return {"p": p}


class FormModelRequiredStr(BaseModel):
    p: str

from inline_snapshot import snapshot
from pydantic import BaseModel, Field

app = FastAPI()

# =====================================================================================
# Without aliases


@app.get("/optional-list-str")
async def read_optional_list_str(
    p: Annotated[list[str] | None, Query()] = None,
):
    return {"p": p}


class QueryModelOptionalListStr(BaseModel):