chainladder-python/conftest.py at main · casact/chainladder-python · GitHub

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from __future__ import annotations

import chainladder as cl
import functools
import pytest

from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from collections.abc import Iterator
    from chainladder import Triangle
    from typing import (
        Any,
        Callable,
    )


def pytest_generate_tests(metafunc):
    if "raa" in metafunc.fixturenames:
        metafunc.parametrize("raa", ["normal_run", "sparse_only_run"], indirect=True)
    if "qtr" in metafunc.fixturenames:
        metafunc.parametrize("qtr", ["normal_run", "sparse_only_run"], indirect=True)
    if "clrd" in metafunc.fixturenames:
        metafunc.parametrize("clrd", ["normal_run", "sparse_only_run"], indirect=True)
    if "genins" in metafunc.fixturenames:
        metafunc.parametrize("genins", ["normal_run", "sparse_only_run"], indirect=True)
    if "monthly" in metafunc.fixturenames:
        metafunc.parametrize(
            "monthly", ["normal_run", "sparse_only_run"], indirect=True
        )
    if "prism" in metafunc.fixturenames:
        metafunc.parametrize("prism", ["sparse_only_run"], indirect=True)
    if "tail_sample" in metafunc.fixturenames:
        metafunc.parametrize(
            "tail_sample", ["normal_run", "sparse_only_run"], indirect=True
        )
    if "xyz" in metafunc.fixturenames:
        metafunc.parametrize("xyz", ["normal_run", "sparse_only_run"], indirect=True)


@functools.lru_cache(maxsize=None)
def _cached_load_sample(sample: str) -> Triangle:
    """
    Create a cache of the requested sample Triangle when called initially,
    then load the cache when called again.

    The cache is preserved throughout the test session.

    Parameters
    ----------
    sample: str
        The requested triangle, e.g., "clrd", "raa", etc.

    Returns
    -------
    Triangle
        The cached triangle.
    """
    return cl.load_sample(sample)


def _sample_fixture(
    request: Any,
    sample: str,
    transform: Callable[[Triangle], Triangle] | None = None,
) -> Iterator[Triangle]:
    """
    Common template fixture for using sample data in unit tests.

    Parameters
    ----------
    request:Any
        The pytest request built-in.
    sample: str
        The name of the sample data set to be loaded, e.g., raa, clrd, etc.
    transform: Callable[[Triangle], Triangle] | None
        An optional transformation to be applied to the triangle supplied as a lambda function.

    Yields
    -------
    A Triangle, with backend set according to request.param.

    """

    # Load a copy of cached sample data.
    tri = _cached_load_sample(sample).copy()
    # Apply a transformation if supplied
    tri = transform(tri) if transform else tri
    # Set the backend to sparse for a sparse-only-run, then yield the triangle to the test.
    yield tri.set_backend("sparse" if request.param == "sparse_only_run" else "numpy")


@pytest.fixture
def raa(request):
    yield from _sample_fixture(request, "raa")


@pytest.fixture
def qtr(request):
    yield from _sample_fixture(request, "quarterly")


@pytest.fixture
def clrd(request):
    yield from _sample_fixture(request, "clrd")


@pytest.fixture
def genins(request):
    yield from _sample_fixture(request, "genins")


@pytest.fixture
def prism(request):
    yield from _sample_fixture(request, "prism")


@pytest.fixture
def monthly(request):
    yield from _sample_fixture(request, "prism", transform=lambda t: t.sum())


@pytest.fixture
def tail_sample(request):
    yield from _sample_fixture(request, "tail_sample")


@pytest.fixture
def xyz(request):
    yield from _sample_fixture(request, "xyz")


@pytest.fixture
def atol():
    return 1e-4


@pytest.fixture
def empty_triangle():
    return cl.Triangle()