Source code for coincidence.utils

#!/usr/bin/env python
#
#  utils.py
"""
Test helper utilities.
"""
#
#  Copyright © 2020-2021 Dominic Davis-Foster <dominic@davis-foster.co.uk>
#
#  Permission is hereby granted, free of charge, to any person obtaining a copy
#  of this software and associated documentation files (the "Software"), to deal
#  in the Software without restriction, including without limitation the rights
#  to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
#  copies of the Software, and to permit persons to whom the Software is
#  furnished to do so, subject to the following conditions:
#
#  The above copyright notice and this permission notice shall be included in all
#  copies or substantial portions of the Software.
#
#  THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
#  EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
#  MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
#  IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
#  DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
#  OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
#  OR OTHER DEALINGS IN THE SOFTWARE.
#
#  is_docker based on https://github.com/jaraco/jaraco.docker
#  Copyright Jason R. Coombs
#  MIT Licensed
#

# stdlib
import datetime
import os
import random
from contextlib import contextmanager
from functools import lru_cache
from itertools import chain, permutations
from typing import Any, Iterable, Iterator, List, Optional, Sequence, TypeVar, Union

# 3rd party
import pytest
from domdf_python_tools.compat import PYPY
from domdf_python_tools.iterative import Len
from domdf_python_tools.paths import PathPlus

__all__ = (
		"generate_truthy_values",
		"generate_falsy_values",
		"is_docker",
		"with_fixed_datetime",
		"whitespace",
		"whitespace_perms_list",
		)

_T = TypeVar("_T")

_cgroup = PathPlus("/proc/self/cgroup")
_dockerenv = "/.dockerenv"


[docs]def is_docker() -> bool: """ Returns whether the current Python instance is running in Docker. """ if os.path.exists(_dockerenv): return True if _cgroup.is_file(): try: return any("docker" in line for line in _cgroup.read_lines()) except FileNotFoundError: return False return False
class _DateMeta(type): # pragma: no cover (PyPy) _date = datetime.date def __instancecheck__(self, instance: Any): # noqa: MAN002 return isinstance(instance, self._date) class _DatetimeMeta(type): # pragma: no cover (PyPy) _datetime = datetime.datetime def __instancecheck__(self, instance: Any) -> bool: return isinstance(instance, self._datetime)
[docs]@contextmanager def with_fixed_datetime(fixed_datetime: datetime.datetime) -> Iterator: """ Context manager to set a fixed datetime for the duration of the ``with`` block. :param fixed_datetime: .. seealso:: The :fixture:`~.fixed_datetime` fixture. .. attention:: The monkeypatching only works when datetime is used and imported like: .. code-block:: python import datetime print(datetime.datetime.now()) Using ``from datetime import datetime`` won't work. """ if PYPY: # pragma: no cover (!PyPy) with pytest.MonkeyPatch.context() as monkeypatch: monkeypatch.setattr( datetime.date, "today", lambda *args: datetime.date( fixed_datetime.year, fixed_datetime.month, fixed_datetime.day, ) ) monkeypatch.setattr( datetime.datetime, "today", lambda *args: datetime.datetime( fixed_datetime.year, fixed_datetime.month, fixed_datetime.day, ) ) monkeypatch.setattr(datetime.datetime, "now", lambda *args: fixed_datetime) yield else: # pragma: no cover (PyPy) class D(datetime.date, metaclass=_DateMeta): @classmethod def today(cls) -> datetime.date: # type: ignore[override] return datetime.date( fixed_datetime.year, fixed_datetime.month, fixed_datetime.day, ) class DT(datetime.datetime, metaclass=_DatetimeMeta): @classmethod def today(cls) -> datetime.datetime: # type: ignore[override] return datetime.datetime( fixed_datetime.year, fixed_datetime.month, fixed_datetime.day, ) @classmethod def now(cls, tz: Optional[datetime.tzinfo] = None) -> datetime.datetime: # type: ignore[override] return datetime.datetime.fromtimestamp(fixed_datetime.timestamp()) D.__name__ = "date" D.__qualname__ = "date" DT.__qualname__ = "datetime" DT.__name__ = "datetime" D.__module__ = "datetime" DT.__module__ = "datetime" with pytest.MonkeyPatch.context() as monkeypatch: monkeypatch.setattr(datetime, "date", D) monkeypatch.setattr(datetime, "datetime", DT) yield
[docs]def generate_truthy_values( extra_truthy: Iterable[Union[str, int, _T]] = (), ratio: float = 1, ) -> Iterator[Union[str, int, _T]]: """ Returns an iterator of strings, integers and booleans which should be considered :py:obj:`True`. Optionally, a random selection of the values can be returned using the ``ratio`` argument. :param extra_truthy: Additional values which should be considered :py:obj:`True`. :param ratio: The ratio of the number of values to select to the total number of values. """ truthy_values: Sequence[Union[str, int, _T]] = [ True, "True", "true", "tRUe", 'y', 'Y', "YES", "yes", "Yes", "yEs", "ON", "on", '1', 1, *extra_truthy, ] if ratio < 1: truthy_values = random.sample(truthy_values, int(len(truthy_values) * ratio)) yield from truthy_values
[docs]def generate_falsy_values( extra_falsy: Iterable[Union[str, int, _T]] = (), ratio: float = 1, ) -> Iterator[Union[str, int, _T]]: """ Returns an iterator of strings, integers and booleans which should be considered :py:obj:`False`. Optionally, a random selection of the values can be returned using the ``ratio`` argument. :param extra_falsy: Additional values which should be considered :py:obj:`True`. :param ratio: The ratio of the number of values to select to the total number of values. """ falsy_values: Sequence[Union[str, int, _T]] = [ False, "False", "false", "falSE", 'n', 'N', "NO", "no", "nO", "OFF", "off", "oFF", '0', 0, *extra_falsy, ] if ratio < 1: falsy_values = random.sample(falsy_values, int(len(falsy_values) * ratio)) yield from falsy_values
whitespace = " \t\n\r" @lru_cache(1) def whitespace_perms_list() -> List[str]: # noqa: D103 perms = chain.from_iterable(permutations(whitespace, n) for n in Len(whitespace)) return list(''.join(x) for x in perms)