rendercv/tests/conftest.py

import pathlib
from typing import Type

import jinja2
import pytest

from rendercv import data_models as dm
import rendercv.renderer as r


@pytest.fixture
def publication_entry() -> dict[str, str | list[str]]:
    return {
        "title": "My Title",
        "authors": ["John Doe", "Jane Doe"],
        "doi": "10.1109/TASC.2023.3340648",
        "date": "2023-12-08",
    }


@pytest.fixture
def experience_entry() -> dict[str, str]:
    return {
        "company": "CERN",
        "position": "Researcher",
    }


@pytest.fixture
def education_entry() -> dict[str, str]:
    return {
        "institution": "Boğaziçi University",
        "area": "Mechanical Engineering",
    }


@pytest.fixture
def normal_entry() -> dict[str, str]:
    return {
        "name": "My Entry",
    }


@pytest.fixture
def one_line_entry() -> dict[str, str]:
    return {
        "name": "My One Line Entry",
        "details": "My Details",
    }


@pytest.fixture
def text_entry() -> str:
    return "My Text Entry"


@pytest.fixture
def invalid_entries() -> dict[
    Type[dm.EducationEntry]
    | Type[dm.ExperienceEntry]
    | Type[dm.PublicationEntry]
    | Type[dm.OneLineEntry]
    | Type[dm.NormalEntry],
    list[dict[str, str]],
]:
    invalid_entries = dict()
    invalid_entries[dm.EducationEntry] = [
        {
            "institution": "Boğaziçi University",
            "area": "Mechanical Engineering",
            "degree": "BS",
            "date": "2028-12-08",
        },
        {
            "area": "Mechanical Engineering",
        },
    ]
    invalid_entries[dm.ExperienceEntry] = [
        {
            "company": "CERN",
        },
        {
            "position": "Researcher",
        },
    ]
    invalid_entries[dm.PublicationEntry] = [
        {
            "doi": "10.1109/TASC.2023.3340648",
        },
        {
            "authors": ["John Doe", "Jane Doe"],
        },
    ]
    invalid_entries[dm.OneLineEntry] = [
        {
            "name": "My One Line Entry",
        },
    ]
    invalid_entries[dm.NormalEntry] = [
        {
            "name": "My Entry",
        },
    ]

    return invalid_entries


@pytest.fixture
def rendercv_data_model(
    education_entry,
    experience_entry,
    normal_entry,
    publication_entry,
    one_line_entry,
    text_entry,
) -> dm.RenderCVDataModel:
    return dm.RenderCVDataModel(
        cv=dm.CurriculumVitae(
            name="John Doe",
            sections={
                "Section 1": [
                    dm.NormalEntry(**normal_entry),
                ],
                "Section 2": [
                    dm.OneLineEntry(**one_line_entry),
                    dm.OneLineEntry(**one_line_entry),
                    dm.OneLineEntry(**one_line_entry),
                    dm.OneLineEntry(**one_line_entry),
                ],
                "Section 3": [
                    dm.PublicationEntry(**publication_entry),
                ],
                "Section 4": [
                    dm.ExperienceEntry(**experience_entry),
                    dm.ExperienceEntry(**experience_entry),
                ],
                "Section 5": [
                    dm.EducationEntry(**education_entry),
                ],
                "Section 6": [text_entry],
            },
        ),
    )


@pytest.fixture
def jinja2_environment() -> jinja2.Environment:
    return r.setup_jinja2_environment()


@pytest.fixture
def tests_directory_path() -> pathlib.Path:
    return pathlib.Path(__file__).parent


@pytest.fixture
def root_directory_path(tests_directory_path) -> pathlib.Path:
    return tests_directory_path.parent


@pytest.fixture
def reference_files_directory_path(tests_directory_path) -> pathlib.Path:
    return tests_directory_path / "reference_files"


@pytest.fixture
def input_file_path(reference_files_directory_path) -> pathlib.Path:
    return reference_files_directory_path / "John_Doe_CV.yaml"