package projects

import configurations.PerformanceTest
import jetbrains.buildServer.configs.kotlin.Project
import model.CIBuildModel
import model.PerformanceTestBucketProvider
import model.PerformanceTestCoverage
import model.PerformanceTestProjectSpec
import model.Stage

abstract class PerformanceTestProject(
    model: CIBuildModel,
    val spec: PerformanceTestProjectSpec,
    val performanceTests: List<PerformanceTest>,
) : Project({

     */
    @Deprecated
    Model interpolate(Model project, Map<String, ?> context) throws ModelInterpolationException;

    /**
     * @deprecated Use {@link ModelInterpolator#interpolate(Model, File, ProjectBuilderConfiguration, boolean)} instead.
     */
    @Deprecated

	DB.Find(&user2, "id = ?", user.ID)
	DB.Model(&user2).Association("Pets").Find(&user2.Pets)
	CheckUser(t, user2, user)

	var pets []Pet
	DB.Model(&user).Where("name = ?", user.Pets[0].Name).Association("Pets").Find(&pets)

	if len(pets) != 1 {
		t.Fatalf("should only find one pets, but got %v", len(pets))
	}

	CheckPet(t, pets[0], *user.Pets[0])

Here we are simulating the expensive *startup* operation of loading the model by putting the (fake) model function in the dictionary with machine learning models before the `yield`. This code will be executed **before** the application **starts taking requests**, during the *startup*.

    model = ModelWithDefault(foo="foo", bar="bar")
    assert jsonable_encoder(model) == {"foo": "foo", "bar": "bar", "bla": "bla"}
    assert jsonable_encoder(model, exclude_unset=True) == {"foo": "foo", "bar": "bar"}
    assert jsonable_encoder(model, exclude_defaults=True) == {"foo": "foo"}
    assert jsonable_encoder(model, exclude_unset=True, exclude_defaults=True) == {
        "foo": "foo"
    }

 * under the License.
 */
package org.apache.maven.plugin.prefix;

import java.util.Collections;
import java.util.List;

import org.apache.maven.execution.MavenSession;
import org.apache.maven.model.Model;
import org.apache.maven.project.MavenProject;
import org.eclipse.aether.RepositorySystemSession;
import org.eclipse.aether.repository.RemoteRepository;

/**
 * Collects settings required to resolve a plugin prefix.

        if (!Features.consumerPom(session.getConfigProperties())) {
            try {
                Model model = read(project.getFile().toPath());
                String version = model.getVersion();
                if (version == null && model.getParent() != null) {
                    version = model.getParent().getVersion();
                }
                String newVersion;
                if (version != null) {

                if annotation_is_pydantic_v1(model):
                    raise PydanticV1NotSupportedError(
                        "pydantic.v1 models are no longer supported by FastAPI."
                        f" In responses={{}}, please update {model}."
                    )
                response_field = create_model_field(
                    name=response_name, type_=model, mode="serialization"
                )

import org.apache.maven.model.PluginContainer;
import org.apache.maven.model.ReportPlugin;
import org.apache.maven.model.Reporting;
import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;
import org.apache.maven.model.merge.MavenModelMerger;
import org.codehaus.plexus.util.StringUtils;

/**
 * Handles inheritance of model values.
 *

    }

    /**
     * Converts this compat model InputSource to an API model InputSource.
     * This method is used for converting between the compat model and the API model.
     *
     * @return the equivalent API model InputSource
     */
    public org.apache.maven.api.model.InputSource toApiSource() {
        return org.apache.maven.api.model.InputSource.of(modelId, location);
    }