### Est-ce que la concurrence est mieux que le parallélisme ?

Nope ! C'est ça la morale de l'histoire.

import importlib

import pytest
from fastapi.testclient import TestClient


@pytest.fixture(
    name="client",
    params=[
        "app_py39.main",
        "app_an_py39.main",
    ],
)
def get_client(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.bigger_applications.{request.param}")

    client = TestClient(mod.app)
    return client


def test_users_token_jessica(client: TestClient):

from typing import Annotated

import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot


@pytest.fixture(name="client")
def get_client():
    from pydantic import (
        BaseModel,
        ConfigDict,
        PlainSerializer,
        TypeAdapter,
        WithJsonSchema,
    )

    class FakeNumpyArray:
        def __init__(self):

* `datetime.timedelta`:
    * 파이썬의 `datetime.timedelta`.
    * 요청과 응답에서 전체 초(seconds)의 `float`로 표현됩니다.
    * Pydantic은 "ISO 8601 시차 인코딩"으로 표현하는 것 또한 허용합니다. <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">더 많은 정보는 이 문서에서 확인하십시오.</a>.
* `frozenset`:
    * 요청과 응답에서 `set`와 동일하게 취급됩니다:
        * 요청 시, 리스트를 읽어 중복을 제거하고 `set`로 변환합니다.

### GNU/Linux and macOS

```sh
docker-compose pull
docker-compose up
```

or

```sh
docker stack deploy --compose-file docker-compose.yaml minio
```

# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=us-docker.pkg.dev/ml-oss-artifacts-published/ml-public-container/ml-build-arm64:latest
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/ml_build_arm64"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1

typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.10.0.dev
tb-nightly ~= 2.20.0.a

name: 'Dependency Review'
on: [pull_request]

permissions:
  contents: read

jobs:
  dependency-review:
    runs-on: ubuntu-latest
    steps:
      - name: 'Checkout Repository'
        uses: actions/checkout@v4
      - name: 'Dependency Review'

from typing import Annotated

import pytest
from fastapi import FastAPI, Form
from fastapi.exceptions import FastAPIDeprecationWarning
from fastapi.testclient import TestClient
from inline_snapshot import snapshot

from .utils import needs_py310


def get_client():
    app = FastAPI()
    with pytest.warns(FastAPIDeprecationWarning):

        @app.post("/items/")
        async def read_items(

# @format

name: Issue Workflow

on:
  issues:
    types:
      - opened

jobs:
  add-to-project:
    name: Add issue to project
    runs-on: ubuntu-latest
    steps:
      - uses: actions/add-to-project@v0.5.0
        with:
          project-url: https://github.com/orgs/miniohq/projects/2