from sqlalchemy.orm import Session

from . import models, schemas


def get_user(db: Session, user_id: int):
    return db.query(models.User).filter(models.User.id == user_id).first()


def get_user_by_email(db: Session, email: str):
    return db.query(models.User).filter(models.User.email == email).first()


def get_users(db: Session, skip: int = 0, limit: int = 100):
    return db.query(models.User).offset(skip).limit(limit).all()

    return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {

from sqlalchemy.orm import Session

from . import models, schemas


def get_user(db: Session, user_id: int):
    return db.query(models.User).filter(models.User.id == user_id).first()


def get_user_by_email(db: Session, email: str):
    return db.query(models.User).filter(models.User.email == email).first()


def get_users(db: Session, skip: int = 0, limit: int = 100):
    return db.query(models.User).offset(skip).limit(limit).all()

only a placeholder to enable test cases to run. The TensorFlow build replaces
this file with a file generated from [`api_template.__init__.py`](https://www.github.com/tensorflow/tensorflow/blob/master/tensorflow/api_template.__init__.py)
"""
# pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top

import distutils as _distutils
import importlib
import inspect as _inspect
import os as _os

    if response.status_code != 200:
        logging.error(
            f"Response was not 200, after: {after}, category_id: {category_id}"
        )
        logging.error(response.text)
        raise RuntimeError(response.text)
    data = response.json()
    if "errors" in data:
        logging.error(f"Errors in response, after: {after}, category_id: {category_id}")
        logging.error(data["errors"])

    return [pet1, pet2]


client = TestClient(app)


def test_filter_top_level_model():
    response = client.post(
        "/users", json={"email": "******@****.***", "password": "secret"}
    )
    assert response.json() == {"email": "******@****.***"}


def test_filter_second_level_model():
    response = client.get("/pets/1")
    assert response.json() == {

        return {"name": name, "description": "model-a-desc", "foo": model_c}

    client = TestClient(app)
    return client


@needs_pydanticv2
def test_filter_sub_model(client: TestClient):
    response = client.get("/model/modelA")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "modelA",
        "description": "model-a-desc",

_CONTRIB_WARNING = """
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
"""

from ..utils import needs_pydanticv1


@pytest.fixture(name="client")
def get_client():
    from .app_pv1 import app

    client = TestClient(app)
    return client


@needs_pydanticv1
def test_filter_sub_model(client: TestClient):
    response = client.get("/model/modelA")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "modelA",
        "description": "model-a-desc",