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()

              <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
              <version>2.0.0</version>
              <models>
                <model>src/main/mdo/plugin.mdo</model>
              </models>
              <templates>
                <template>model.vm</template>
              </templates>
              <params>
                <param>packageModelV4=org.apache.maven.api.plugin.descriptor</param>

from . import models, schemas


def get_user(user_id: int):
    return models.User.filter(models.User.id == user_id).first()


def get_user_by_email(email: str):
    return models.User.filter(models.User.email == email).first()


def get_users(skip: int = 0, limit: int = 100):
    return list(models.User.select().offset(skip).limit(limit))


def create_user(user: schemas.UserCreate):

        List<ToolchainModel> models = session.getRequest().getToolchains().get(type);

        return selectToolchains(models, type, requirements);
    }

    private List<Toolchain> selectToolchains(
            List<ToolchainModel> models, String type, Map<String, String> requirements) {
        List<Toolchain> toolchains = new ArrayList<>();

        if (models != null) {

        "info": {"title": "FastAPI", "version": "0.1.0"},
        "paths": {
            "/models/{model_name}": {
                "get": {
                    "summary": "Get Model",
                    "operationId": "get_model_models__model_name__get",
                    "parameters": [
                        {
                            "required": True,

                        },
                    },
                }
            },
            "/tuple-of-models/": {
                "post": {
                    "summary": "Post Tuple Of Models",
                    "operationId": "post_tuple_of_models_tuple_of_models__post",
                    "requestBody": {
                        "content": {
                            "application/json": {

from docs_src.events.tutorial003 import (
    app,
    fake_answer_to_everything_ml_model,
    ml_models,
)


def test_events():
    assert not ml_models, "ml_models should be empty"
    with TestClient(app) as client:
        assert ml_models["answer_to_everything"] == fake_answer_to_everything_ml_model
        response = client.get("/predict", params={"x": 2})
        assert response.status_code == 200, response.text

## Create the Pydantic models

Now let's check the file `sql_app/schemas.py`.

!!! tip
    To avoid confusion between the SQLAlchemy *models* and the Pydantic *models*, we will have the file `models.py` with the SQLAlchemy models, and the file `schemas.py` with the Pydantic models.

    These Pydantic models define more or less a "schema" (a valid data shape).

Does nothing. false true false false false true generate-sources org.apache.maven.plugin.coreit.CMojo java per-lookup once-per-session models java.lang.String[] false true version java.lang.String false true ${version} xpp3-writer Does nothing. false true false false false true generate-sources org.apache.maven.plugin.coreit.BMojo java per-lookup once-per-session models java.lang.String[] false true version java.lang.String false true ${version} org.apache.maven maven-plugin-api jar 2.0 org/apache/m...

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.