"""
This module provides decorator functions which can be applied to test objects
in order to skip those objects when certain conditions occur. A sample use case
is to detect if the platform is missing ``matplotlib``. If so, any test objects
which require ``matplotlib`` and decorated with ``@td.skip_if_no_mpl`` will be
skipped by ``pytest`` during the execution of the test suite.

To illustrate, after importing this module:

import pandas.util._test_decorators as td

The decorators can be applied to classes:

@td.skip_if_some_reason
class Foo:
    ...

Or individual functions:

@td.skip_if_some_reason
def test_foo():
    ...

For more information, refer to the ``pytest`` documentation on ``skipif``.
"""
from __future__ import annotations

import locale
from typing import (
    TYPE_CHECKING,
    Callable,
)

import numpy as np
import pytest

from pandas._config import get_option

if TYPE_CHECKING:
    from pandas._typing import F

from pandas.compat import (
    IS64,
    is_platform_windows,
)

from pandas.core.computation.expressions import (
    NUMEXPR_INSTALLED,
    USE_NUMEXPR,
)
from pandas.util.version import Version


def safe_import(mod_name: str, min_version: str | None = None):
    """
    Parameters
    ----------
    mod_name : str
        Name of the module to be imported
    min_version : str, default None
        Minimum required version of the specified mod_name

    Returns
    -------
    object
        The imported module if successful, or False
    """
    try:
        mod = __import__(mod_name)
    except ImportError:
        return False

    if not min_version:
        return mod
    else:
        import sys

        version = getattr(sys.modules[mod_name], "__version__")
        if version and Version(version) >= Version(min_version):
            return mod

    return False


def _skip_if_not_us_locale() -> bool:
    lang, _ = locale.getlocale()
    if lang != "en_US":
        return True
    return False


def _skip_if_no_scipy() -> bool:
    return not (
        safe_import("scipy.stats")
        and safe_import("scipy.sparse")
        and safe_import("scipy.interpolate")
        and safe_import("scipy.signal")
    )


def skip_if_installed(package: str) -> pytest.MarkDecorator:
    """
    Skip a test if a package is installed.

    Parameters
    ----------
    package : str
        The name of the package.

    Returns
    -------
    pytest.MarkDecorator
        a pytest.mark.skipif to use as either a test decorator or a
        parametrization mark.
    """
    return pytest.mark.skipif(
        safe_import(package), reason=f"Skipping because {package} is installed."
    )


def skip_if_no(package: str, min_version: str | None = None) -> pytest.MarkDecorator:
    """
    Generic function to help skip tests when required packages are not
    present on the testing system.

    This function returns a pytest mark with a skip condition that will be
    evaluated during test collection. An attempt will be made to import the
    specified ``package`` and optionally ensure it meets the ``min_version``

    The mark can be used as either a decorator for a test class or to be
    applied to parameters in pytest.mark.parametrize calls or parametrized
    fixtures. Use pytest.importorskip if an imported moduled is later needed
    or for test functions.

    If the import and version check are unsuccessful, then the test function
    (or test case when used in conjunction with parametrization) will be
    skipped.

    Parameters
    ----------
    package: str
        The name of the required package.
    min_version: str or None, default None
        Optional minimum version of the package.

    Returns
    -------
    pytest.MarkDecorator
        a pytest.mark.skipif to use as either a test decorator or a
        parametrization mark.
    """
    msg = f"Could not import '{package}'"
    if min_version:
        msg += f" satisfying a min_version of {min_version}"
    return pytest.mark.skipif(
        not safe_import(package, min_version=min_version), reason=msg
    )


skip_if_mpl = pytest.mark.skipif(
    bool(safe_import("matplotlib")), reason="matplotlib is present"
)
skip_if_32bit = pytest.mark.skipif(not IS64, reason="skipping for 32 bit")
skip_if_windows = pytest.mark.skipif(is_platform_windows(), reason="Running on Windows")
skip_if_not_us_locale = pytest.mark.skipif(
    _skip_if_not_us_locale(),
    reason=f"Specific locale is set {locale.getlocale()[0]}",
)
skip_if_no_scipy = pytest.mark.skipif(
    _skip_if_no_scipy(), reason="Missing SciPy requirement"
)
skip_if_no_ne = pytest.mark.skipif(
    not USE_NUMEXPR,
    reason=f"numexpr enabled->{USE_NUMEXPR}, installed->{NUMEXPR_INSTALLED}",
)


def skip_if_np_lt(
    ver_str: str, *args, reason: str | None = None
) -> pytest.MarkDecorator:
    if reason is None:
        reason = f"NumPy {ver_str} or greater required"
    return pytest.mark.skipif(
        Version(np.__version__) < Version(ver_str),
        *args,
        reason=reason,
    )


def parametrize_fixture_doc(*args) -> Callable[[F], F]:
    """
    Intended for use as a decorator for parametrized fixture,
    this function will wrap the decorated function with a pytest
    ``parametrize_fixture_doc`` mark. That mark will format
    initial fixture docstring by replacing placeholders {0}, {1} etc
    with parameters passed as arguments.

    Parameters
    ----------
    args: iterable
        Positional arguments for docstring.

    Returns
    -------
    function
        The decorated function wrapped within a pytest
        ``parametrize_fixture_doc`` mark
    """

    def documented_fixture(fixture):
        fixture.__doc__ = fixture.__doc__.format(*args)
        return fixture

    return documented_fixture


def mark_array_manager_not_yet_implemented(request) -> None:
    mark = pytest.mark.xfail(reason="Not yet implemented for ArrayManager")
    request.node.add_marker(mark)


skip_array_manager_not_yet_implemented = pytest.mark.xfail(
    get_option("mode.data_manager") == "array",
    reason="Not yet implemented for ArrayManager",
)

skip_array_manager_invalid_test = pytest.mark.skipif(
    get_option("mode.data_manager") == "array",
    reason="Test that relies on BlockManager internals or specific behaviour",
)

skip_copy_on_write_not_yet_implemented = pytest.mark.xfail(
    get_option("mode.copy_on_write"),
    reason="Not yet implemented/adapted for Copy-on-Write mode",
)

skip_copy_on_write_invalid_test = pytest.mark.skipif(
    get_option("mode.copy_on_write"),
    reason="Test not valid for Copy-on-Write mode",
)