"""
Backports of fixes for joblib dependencies
"""
import os
import re
import time

from os.path import basename
from multiprocessing import util

# Prior to joblib 1.2, joblib used to import LooseVersion from
# distutils.version. This import had a side-effect with setuptools that was
# implicitly required in sklearn.show_versions() to work without raising an
# exception for scikit-learn 1.0 and earlier. This has been fixed in
# scikit-learn 1.1 (not yet released at the time of writing), see:
# https://github.com/scikit-learn/scikit-learn/issues/22614
#
# To avoid unnecessary disruption for users who might update to joblib 1.2
# prior to a release of scikit-learn that includes the fix, let's keep on
# importing distutils here. TODO: Remove this for a future release of joblib,
# e.g. 6 months after the release of scikit-learn 1.1.
import distutils  # noqa


class Version:
    """Backport from deprecated distutils

    We maintain this backport to avoid introducing a new dependency on
    `packaging`.

    We might rexplore this choice in the future if all major Python projects
    introduce a dependency on packaging anyway.
    """

    def __init__(self, vstring=None):
        if vstring:
            self.parse(vstring)

    def __repr__(self):
        return "%s ('%s')" % (self.__class__.__name__, str(self))

    def __eq__(self, other):
        c = self._cmp(other)
        if c is NotImplemented:
            return c
        return c == 0

    def __lt__(self, other):
        c = self._cmp(other)
        if c is NotImplemented:
            return c
        return c < 0

    def __le__(self, other):
        c = self._cmp(other)
        if c is NotImplemented:
            return c
        return c <= 0

    def __gt__(self, other):
        c = self._cmp(other)
        if c is NotImplemented:
            return c
        return c > 0

    def __ge__(self, other):
        c = self._cmp(other)
        if c is NotImplemented:
            return c
        return c >= 0


class LooseVersion(Version):
    """Backport from deprecated distutils

    We maintain this backport to avoid introducing a new dependency on
    `packaging`.

    We might rexplore this choice in the future if all major Python projects
    introduce a dependency on packaging anyway.
    """

    component_re = re.compile(r'(\d+ | [a-z]+ | \.)', re.VERBOSE)

    def __init__(self, vstring=None):
        if vstring:
            self.parse(vstring)

    def parse(self, vstring):
        # I've given up on thinking I can reconstruct the version string
        # from the parsed tuple -- so I just store the string here for
        # use by __str__
        self.vstring = vstring
        components = [x for x in self.component_re.split(vstring)
                      if x and x != '.']
        for i, obj in enumerate(components):
            try:
                components[i] = int(obj)
            except ValueError:
                pass

        self.version = components

    def __str__(self):
        return self.vstring

    def __repr__(self):
        return "LooseVersion ('%s')" % str(self)

    def _cmp(self, other):
        if isinstance(other, str):
            other = LooseVersion(other)
        elif not isinstance(other, LooseVersion):
            return NotImplemented

        if self.version == other.version:
            return 0
        if self.version < other.version:
            return -1
        if self.version > other.version:
            return 1


try:
    import numpy as np

    def make_memmap(filename, dtype='uint8', mode='r+', offset=0,
                    shape=None, order='C', unlink_on_gc_collect=False):
        """Custom memmap constructor compatible with numpy.memmap.

        This function:
        - is a backport the numpy memmap offset fix (See
          https://github.com/numpy/numpy/pull/8443 for more details.
          The numpy fix is available starting numpy 1.13)
        - adds ``unlink_on_gc_collect``, which specifies  explicitly whether
          the process re-constructing the memmap owns a reference to the
          underlying file. If set to True, it adds a finalizer to the
          newly-created memmap that sends a maybe_unlink request for the
          memmaped file to resource_tracker.
        """
        util.debug(
            "[MEMMAP READ] creating a memmap (shape {}, filename {}, "
            "pid {})".format(shape, basename(filename), os.getpid())
        )

        mm = np.memmap(filename, dtype=dtype, mode=mode, offset=offset,
                       shape=shape, order=order)
        if LooseVersion(np.__version__) < '1.13':
            mm.offset = offset
        if unlink_on_gc_collect:
            from ._memmapping_reducer import add_maybe_unlink_finalizer
            add_maybe_unlink_finalizer(mm)
        return mm
except ImportError:
    def make_memmap(filename, dtype='uint8', mode='r+', offset=0,
                    shape=None, order='C', unlink_on_gc_collect=False):
        raise NotImplementedError(
            "'joblib.backports.make_memmap' should not be used "
            'if numpy is not installed.')


if os.name == 'nt':
    # https://github.com/joblib/joblib/issues/540
    access_denied_errors = (5, 13)
    from os import replace

    def concurrency_safe_rename(src, dst):
        """Renames ``src`` into ``dst`` overwriting ``dst`` if it exists.

        On Windows os.replace can yield permission errors if executed by two
        different processes.
        """
        max_sleep_time = 1
        total_sleep_time = 0
        sleep_time = 0.001
        while total_sleep_time < max_sleep_time:
            try:
                replace(src, dst)
                break
            except Exception as exc:
                if getattr(exc, 'winerror', None) in access_denied_errors:
                    time.sleep(sleep_time)
                    total_sleep_time += sleep_time
                    sleep_time *= 2
                else:
                    raise
        else:
            raise
else:
    from os import replace as concurrency_safe_rename  # noqa