yaltik_odoo_custom/yaltik_dsl/tests/__coconut__.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# type: ignore

# Compiled with Coconut version 2.1.1 [The Spanish Inquisition]

"""Built-in Coconut utilities."""

# Coconut Header: -------------------------------------------------------------

from __future__ import generator_stop, annotations
import sys as _coconut_sys
from builtins import chr, hex, input, int, map, object, oct, open, print, range, str, super, zip, filter, reversed, enumerate, repr
py_chr, py_hex, py_input, py_int, py_map, py_object, py_oct, py_open, py_print, py_range, py_str, py_super, py_zip, py_filter, py_reversed, py_enumerate, py_repr = chr, hex, input, int, map, object, oct, open, print, range, str, super, zip, filter, reversed, enumerate, repr
_coconut_py_str, _coconut_py_super = str, super
from functools import wraps as _coconut_wraps
exec("_coconut_exec = exec")
py_breakpoint = breakpoint
@_coconut_wraps(_coconut_py_super)
def _coconut_super(type=None, object_or_type=None):
    if type is None:
        if object_or_type is not None:
            raise _coconut.TypeError("invalid use of super()")
        frame = _coconut_sys._getframe(1)
        try:
            cls = frame.f_locals["__class__"]
        except _coconut.AttributeError:
            raise _coconut.RuntimeError("super(): __class__ cell not found")
        self = frame.f_locals[frame.f_code.co_varnames[0]]
        return _coconut_py_super(cls, self)
    return _coconut_py_super(type, object_or_type)
super = _coconut_super
class _coconut:
    import collections, copy, functools, types, itertools, operator, threading, os, warnings, contextlib, traceback, weakref, multiprocessing, math
    from multiprocessing import dummy as multiprocessing_dummy
    import copyreg
    import asyncio
    import pickle
    OrderedDict = collections.OrderedDict
    import collections.abc as abc
    import typing
    if _coconut_sys.version_info < (3, 10):
        try:
            from typing_extensions import TypeAlias, ParamSpec, Concatenate
        except ImportError:
            class you_need_to_install_typing_extensions:
                __slots__ = ()
            TypeAlias = ParamSpec = Concatenate = you_need_to_install_typing_extensions()
        typing.TypeAlias = TypeAlias
        typing.ParamSpec = ParamSpec
        typing.Concatenate = Concatenate
    if _coconut_sys.version_info < (3, 11):
        try:
            from typing_extensions import TypeVarTuple, Unpack
        except ImportError:
            class you_need_to_install_typing_extensions:
                __slots__ = ()
            TypeVarTuple = Unpack = you_need_to_install_typing_extensions()
        typing.TypeVarTuple = TypeVarTuple
        typing.Unpack = Unpack
    zip_longest = itertools.zip_longest
    try:
        import numpy
    except ImportError:
        class you_need_to_install_numpy:
            __slots__ = ()
        numpy = you_need_to_install_numpy()
    else:
        abc.Sequence.register(numpy.ndarray)
    numpy_modules = ('numpy', 'pandas', 'jaxlib.xla_extension')
    jax_numpy_modules = ('jaxlib.xla_extension',)
    abc.Sequence.register(collections.deque)
    Ellipsis, NotImplemented, NotImplementedError, Exception, AttributeError, ImportError, IndexError, NameError, TypeError, ValueError, StopIteration, RuntimeError, all, any, bytes, classmethod, dict, enumerate, filter, float, frozenset, getattr, hasattr, hash, id, int, isinstance, issubclass, iter, len, list, locals, map, min, max, next, object, property, range, reversed, set, slice, str, sum, super, tuple, type, vars, zip, repr, print = Ellipsis, NotImplemented, NotImplementedError, Exception, AttributeError, ImportError, IndexError, NameError, TypeError, ValueError, StopIteration, RuntimeError, all, any, bytes, classmethod, dict, enumerate, filter, float, frozenset, getattr, hasattr, hash, id, int, isinstance, issubclass, iter, len, list, locals, map, min, max, next, object, property, range, reversed, set, slice, str, sum, super, tuple, type, vars, zip, repr, print
class _coconut_sentinel:
    __slots__ = ()
class _coconut_base_hashable:
    __slots__ = ()
    def __reduce_ex__(self, _):
        return self.__reduce__()
    def __eq__(self, other):
        return self.__class__ is other.__class__ and self.__reduce__() == other.__reduce__()
    def __hash__(self):
        return _coconut.hash(self.__reduce__())
class MatchError(_coconut_base_hashable, Exception):
    """Pattern-matching error. Has attributes .pattern, .value, and .message."""
    __slots__ = ("pattern", "value", "_message")
    max_val_repr_len = 500
    def __init__(self, pattern=None, value=None):
        self.pattern = pattern
        self.value = value
        self._message = None
    @property
    def message(self):
        if self._message is None:
            value_repr = _coconut.repr(self.value)
            self._message = "pattern-matching failed for %s in %s" % (_coconut.repr(self.pattern), value_repr if _coconut.len(value_repr) <= self.max_val_repr_len else value_repr[:self.max_val_repr_len] + "...")
            Exception.__init__(self, self._message)
        return self._message
    def __repr__(self):
        self.message
        return Exception.__repr__(self)
    def __str__(self):
        self.message
        return Exception.__str__(self)
    def __unicode__(self):
        self.message
        return Exception.__unicode__(self)
    def __reduce__(self):
        return (self.__class__, (self.pattern, self.value))
class _coconut_tail_call:
    __slots__ = ("func", "args", "kwargs")
    def __init__(self, _coconut_func, *args, **kwargs):
        self.func = _coconut_func
        self.args = args
        self.kwargs = kwargs
_coconut_tco_func_dict = {}
def _coconut_tco(func):
    @_coconut.functools.wraps(func)
    def tail_call_optimized_func(*args, **kwargs):
        call_func = func
        while True:
            if _coconut.isinstance(call_func, _coconut_base_pattern_func):
                call_func = call_func._coconut_tco_func
            elif _coconut.isinstance(call_func, _coconut.types.MethodType):
                wkref = _coconut_tco_func_dict.get(_coconut.id(call_func.__func__))
                wkref_func = None if wkref is None else wkref()
                if wkref_func is call_func.__func__:
                    if call_func.__self__ is None:
                        call_func = call_func._coconut_tco_func
                    else:
                        call_func = _coconut.functools.partial(call_func._coconut_tco_func, call_func.__self__)
            else:
                wkref = _coconut_tco_func_dict.get(_coconut.id(call_func))
                wkref_func = None if wkref is None else wkref()
                if wkref_func is call_func:
                    call_func = call_func._coconut_tco_func
            result = call_func(*args, **kwargs)  # use coconut --no-tco to clean up your traceback
            if not isinstance(result, _coconut_tail_call):
                return result
            call_func, args, kwargs = result.func, result.args, result.kwargs
    tail_call_optimized_func._coconut_tco_func = func
    tail_call_optimized_func.__module__ = _coconut.getattr(func, "__module__", None)
    tail_call_optimized_func.__name__ = _coconut.getattr(func, "__name__", None)
    tail_call_optimized_func.__qualname__ = _coconut.getattr(func, "__qualname__", None)
    _coconut_tco_func_dict[_coconut.id(tail_call_optimized_func)] = _coconut.weakref.ref(tail_call_optimized_func)
    return tail_call_optimized_func
def _coconut_iter_getitem_special_case(iterable, start, stop, step):
    iterable = _coconut.itertools.islice(iterable, start, None)
    cache = _coconut.collections.deque(_coconut.itertools.islice(iterable, -stop), maxlen=-stop)
    for index, item in _coconut.enumerate(iterable):
        cached_item = cache.popleft()
        if index % step == 0:
            yield cached_item
        cache.append(item)
def _coconut_iter_getitem(iterable, index):
    """Iterator slicing works just like sequence slicing, including support for negative indices and slices, and support for `slice` objects in the same way as can be done with normal slicing.

    Coconut's iterator slicing is very similar to Python's `itertools.islice`, but unlike `itertools.islice`, Coconut's iterator slicing supports negative indices, and will preferentially call an object's `__iter_getitem__` (Coconut-specific magic method, preferred) or `__getitem__` (general Python magic method), if they exist. Coconut's iterator slicing is also optimized to work well with all of Coconut's built-in objects, only computing the elements of each that are actually necessary to extract the desired slice.

    Some code taken from more_itertools under the terms of its MIT license.
    """
    obj_iter_getitem = _coconut.getattr(iterable, "__iter_getitem__", None)
    if obj_iter_getitem is None:
        obj_iter_getitem = _coconut.getattr(iterable, "__getitem__", None)
    if obj_iter_getitem is not None:
        try:
            result = obj_iter_getitem(index)
        except _coconut.NotImplementedError:
            pass
        else:
            if result is not _coconut.NotImplemented:
                return result
    if not _coconut.isinstance(index, _coconut.slice):
        index = _coconut.operator.index(index)
        if index < 0:
            return _coconut.collections.deque(iterable, maxlen=-index)[0]
        result = _coconut.next(_coconut.itertools.islice(iterable, index, index + 1), _coconut_sentinel)
        if result is _coconut_sentinel:
            raise _coconut.IndexError("$[] index out of range")
        return result
    start = _coconut.operator.index(index.start) if index.start is not None else None
    stop = _coconut.operator.index(index.stop) if index.stop is not None else None
    step = _coconut.operator.index(index.step) if index.step is not None else 1
    if step == 0:
        raise _coconut.ValueError("slice step cannot be zero")
    if start is None and stop is None and step == -1:
        obj_reversed = _coconut.getattr(iterable, "__reversed__", None)
        if obj_reversed is not None:
            try:
                result = obj_reversed()
            except _coconut.NotImplementedError:
                pass
            else:
                if result is not _coconut.NotImplemented:
                    return result
    if step >= 0:
        start = 0 if start is None else start
        if start < 0:
            cache = _coconut.collections.deque(_coconut.enumerate(iterable, 1), maxlen=-start)
            len_iter = cache[-1][0] if cache else 0
            i = _coconut.max(len_iter + start, 0)
            if stop is None:
                j = len_iter
            elif stop >= 0:
                j = _coconut.min(stop, len_iter)
            else:
                j = _coconut.max(len_iter + stop, 0)
            n = j - i
            if n <= 0:
                return ()
            if n < -start or step != 1:
                cache = _coconut.itertools.islice(cache, 0, n, step)
            return _coconut_map(_coconut.operator.itemgetter(1), cache)
        elif stop is None or stop >= 0:
            return _coconut.itertools.islice(iterable, start, stop, step)
        else:
            return _coconut_iter_getitem_special_case(iterable, start, stop, step)
    else:
        start = -1 if start is None else start
        if stop is not None and stop < 0:
            n = -stop - 1
            cache = _coconut.collections.deque(_coconut.enumerate(iterable, 1), maxlen=n)
            len_iter = cache[-1][0] if cache else 0
            if start < 0:
                i, j = start, stop
            else:
                i, j = _coconut.min(start - len_iter, -1), None
            return _coconut_map(_coconut.operator.itemgetter(1), _coconut.tuple(cache)[i:j:step])
        else:
            if stop is not None:
                m = stop + 1
                iterable = _coconut.itertools.islice(iterable, m, None)
            if start < 0:
                i = start
                n = None
            elif stop is None:
                i = None
                n = start + 1
            else:
                i = None
                n = start - stop
            if n is not None:
                if n <= 0:
                    return ()
                iterable = _coconut.itertools.islice(iterable, 0, n)
            return _coconut.tuple(iterable)[i::step]
class _coconut_base_compose(_coconut_base_hashable):
    __slots__ = ("func", "funcstars")
    def __init__(self, func, *funcstars):
        self.func = func
        self.funcstars = []
        for f, stars in funcstars:
            if _coconut.isinstance(f, _coconut_base_compose):
                self.funcstars.append((f.func, stars))
                self.funcstars += f.funcstars
            else:
                self.funcstars.append((f, stars))
        self.funcstars = _coconut.tuple(self.funcstars)
    def __call__(self, *args, **kwargs):
        arg = self.func(*args, **kwargs)
        for f, stars in self.funcstars:
            if stars == 0:
                arg = f(arg)
            elif stars == 1:
                arg = f(*arg)
            elif stars == 2:
                arg = f(**arg)
            else:
                raise _coconut.ValueError("invalid arguments to " + _coconut.repr(self))
        return arg
    def __repr__(self):
        return _coconut.repr(self.func) + " " + " ".join(("..*> " if star == 1 else "..**>" if star == 2 else "..> ") + _coconut.repr(f) for f, star in self.funcstars)
    def __reduce__(self):
        return (self.__class__, (self.func,) + self.funcstars)
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        return _coconut.types.MethodType(self, obj)
def _coconut_forward_compose(func, *funcs):
    """Forward composition operator (..>).

    (..>)(f, g) is effectively equivalent to (*args, **kwargs) -> g(f(*args, **kwargs))."""
    return _coconut_base_compose(func, *((f, 0) for f in funcs))
def _coconut_back_compose(*funcs):
    """Backward composition operator (<..).

    (<..)(f, g) is effectively equivalent to (*args, **kwargs) -> f(g(*args, **kwargs))."""
    return _coconut_forward_compose(*_coconut.reversed(funcs))
def _coconut_forward_star_compose(func, *funcs):
    """Forward star composition operator (..*>).

    (..*>)(f, g) is effectively equivalent to (*args, **kwargs) -> g(*f(*args, **kwargs))."""
    return _coconut_base_compose(func, *((f, 1) for f in funcs))
def _coconut_back_star_compose(*funcs):
    """Backward star composition operator (<*..).

    (<*..)(f, g) is effectively equivalent to (*args, **kwargs) -> f(*g(*args, **kwargs))."""
    return _coconut_forward_star_compose(*_coconut.reversed(funcs))
def _coconut_forward_dubstar_compose(func, *funcs):
    """Forward double star composition operator (..**>).

    (..**>)(f, g) is effectively equivalent to (*args, **kwargs) -> g(**f(*args, **kwargs))."""
    return _coconut_base_compose(func, *((f, 2) for f in funcs))
def _coconut_back_dubstar_compose(*funcs):
    """Backward double star composition operator (<**..).

    (<**..)(f, g) is effectively equivalent to (*args, **kwargs) -> f(**g(*args, **kwargs))."""
    return _coconut_forward_dubstar_compose(*_coconut.reversed(funcs))
def _coconut_pipe(x, f):
    """Pipe operator (|>). Equivalent to (x, f) -> f(x)."""
    return f(x)
def _coconut_star_pipe(xs, f):
    """Star pipe operator (*|>). Equivalent to (xs, f) -> f(*xs)."""
    return f(*xs)
def _coconut_dubstar_pipe(kws, f):
    """Double star pipe operator (**|>). Equivalent to (kws, f) -> f(**kws)."""
    return f(**kws)
def _coconut_back_pipe(f, x):
    """Backward pipe operator (<|). Equivalent to (f, x) -> f(x)."""
    return f(x)
def _coconut_back_star_pipe(f, xs):
    """Backward star pipe operator (<*|). Equivalent to (f, xs) -> f(*xs)."""
    return f(*xs)
def _coconut_back_dubstar_pipe(f, kws):
    """Backward double star pipe operator (<**|). Equivalent to (f, kws) -> f(**kws)."""
    return f(**kws)
def _coconut_none_pipe(x, f):
    """Nullable pipe operator (|?>). Equivalent to (x, f) -> f(x) if x is not None else None."""
    return None if x is None else f(x)
def _coconut_none_star_pipe(xs, f):
    """Nullable star pipe operator (|?*>). Equivalent to (xs, f) -> f(*xs) if xs is not None else None."""
    return None if xs is None else f(*xs)
def _coconut_none_dubstar_pipe(kws, f):
    """Nullable double star pipe operator (|?**>). Equivalent to (kws, f) -> f(**kws) if kws is not None else None."""
    return None if kws is None else f(**kws)
def _coconut_assert(cond, msg=None):
    """Assert operator (assert). Asserts condition with optional message."""
    if not cond:
        assert False, msg if msg is not None else "(assert) got falsey value " + _coconut.repr(cond)
def _coconut_raise(exc=None, from_exc=None):
    """Raise operator (raise). Raises exception with optional cause."""
    if exc is None:
        raise
    if from_exc is not None:
        exc.__cause__ = from_exc
    raise exc
def _coconut_bool_and(a, b):
    """Boolean and operator (and). Equivalent to (a, b) -> a and b."""
    return a and b
def _coconut_bool_or(a, b):
    """Boolean or operator (or). Equivalent to (a, b) -> a or b."""
    return a or b
def _coconut_none_coalesce(a, b):
    """None coalescing operator (??). Equivalent to (a, b) -> a if a is not None else b."""
    return b if a is None else a
def _coconut_minus(a, b=_coconut_sentinel):
    """Minus operator (-). Effectively equivalent to (a, b=None) -> a - b if b is not None else -a."""
    if b is _coconut_sentinel:
        return -a
    return a - b
def _coconut_comma_op(*args):
    """Comma operator (,). Equivalent to (*args) -> args."""
    return args
_coconut_matmul = _coconut.operator.matmul
@_coconut.functools.wraps(_coconut.itertools.tee)
def tee(iterable, n=2):
    if n >= 0 and _coconut.isinstance(iterable, (_coconut.tuple, _coconut.frozenset)):
        return (iterable,) * n
    if n > 0 and (_coconut.isinstance(iterable, _coconut.abc.Sequence) or _coconut.getattr(iterable, "__copy__", None) is not None):
        return (iterable,) + _coconut.tuple(_coconut.copy.copy(iterable) for _ in _coconut.range(n - 1))
    return _coconut.itertools.tee(iterable, n)
class reiterable(_coconut_base_hashable):
    """Allow an iterator to be iterated over multiple times with the same results."""
    __slots__ = ("lock", "iter")
    def __new__(cls, iterable):
        if _coconut.isinstance(iterable, _coconut_reiterable):
            return iterable
        self = _coconut.object.__new__(cls)
        self.lock = _coconut.threading.Lock()
        self.iter = iterable
        return self
    def get_new_iter(self):
        with self.lock:
            self.iter, new_iter = _coconut_tee(self.iter)
        return new_iter
    def __iter__(self):
        return _coconut.iter(self.get_new_iter())
    def __getitem__(self, index):
        return _coconut_iter_getitem(self.get_new_iter(), index)
    def __reversed__(self):
        return _coconut_reversed(self.get_new_iter())
    def __len__(self):
        return _coconut.len(self.iter)
    def __repr__(self):
        return "reiterable(%s)" % (_coconut.repr(self.iter),)
    def __reduce__(self):
        return (self.__class__, (self.iter,))
    def __copy__(self):
        return self.__class__(self.get_new_iter())
    def __fmap__(self, func):
        return _coconut_map(func, self)
class scan(_coconut_base_hashable):
    """Reduce func over iterable, yielding intermediate results,
    optionally starting from initial."""
    __slots__ = ("func", "iter", "initial")
    def __init__(self, function, iterable, initial=_coconut_sentinel):
        self.func = function
        self.iter = iterable
        self.initial = initial
    def __iter__(self):
        acc = self.initial
        if acc is not _coconut_sentinel:
            yield acc
        for item in self.iter:
            if acc is _coconut_sentinel:
                acc = item
            else:
                acc = self.func(acc, item)
            yield acc
    def __len__(self):
        return _coconut.len(self.iter)
    def __repr__(self):
        return "scan(%r, %s%s)" % (self.func, _coconut.repr(self.iter), "" if self.initial is _coconut_sentinel else ", " + _coconut.repr(self.initial))
    def __reduce__(self):
        return (self.__class__, (self.func, self.iter, self.initial))
    def __fmap__(self, func):
        return _coconut_map(func, self)
class reversed(_coconut_base_hashable):
    __slots__ = ("iter",)
    if hasattr(_coconut.map, "__doc__"):
        __doc__ = _coconut.reversed.__doc__
    def __new__(cls, iterable):
        if _coconut.isinstance(iterable, _coconut.range):
            return iterable[::-1]
        if not _coconut.hasattr(iterable, "__reversed__") or _coconut.isinstance(iterable, (_coconut.list, _coconut.tuple)):
            return _coconut.object.__new__(cls)
        return _coconut.reversed(iterable)
    def __init__(self, iterable):
        self.iter = iterable
    def __iter__(self):
        return _coconut.iter(_coconut.reversed(self.iter))
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            return _coconut_iter_getitem(self.iter, _coconut.slice(-(index.start + 1) if index.start is not None else None, -(index.stop + 1) if index.stop else None, -(index.step if index.step is not None else 1)))
        return _coconut_iter_getitem(self.iter, -(index + 1))
    def __reversed__(self):
        return self.iter
    def __len__(self):
        return _coconut.len(self.iter)
    def __repr__(self):
        return "reversed(%s)" % (_coconut.repr(self.iter),)
    def __reduce__(self):
        return (self.__class__, (self.iter,))
    def __contains__(self, elem):
        return elem in self.iter
    def count(self, elem):
        """Count the number of times elem appears in the reversed iterable."""
        return self.iter.count(elem)
    def index(self, elem):
        """Find the index of elem in the reversed iterable."""
        return _coconut.len(self.iter) - self.iter.index(elem) - 1
    def __fmap__(self, func):
        return self.__class__(_coconut_map(func, self.iter))
class flatten(_coconut_base_hashable):
    """Flatten an iterable of iterables into a single iterable."""
    __slots__ = ("iter",)
    def __init__(self, iterable):
        self.iter = iterable
    def __iter__(self):
        return _coconut.itertools.chain.from_iterable(self.iter)
    def __reversed__(self):
        return self.__class__(_coconut_reversed(_coconut_map(_coconut_reversed, self.iter)))
    def __repr__(self):
        return "flatten(%s)" % (_coconut.repr(self.iter),)
    def __reduce__(self):
        return (self.__class__, (self.iter,))
    def __contains__(self, elem):
        self.iter, new_iter = _coconut_tee(self.iter)
        return _coconut.any(elem in it for it in new_iter)
    def count(self, elem):
        """Count the number of times elem appears in the flattened iterable."""
        self.iter, new_iter = _coconut_tee(self.iter)
        return _coconut.sum(it.count(elem) for it in new_iter)
    def index(self, elem):
        self.iter, new_iter = _coconut_tee(self.iter)
        ind = 0
        for it in new_iter:
            try:
                return ind + it.index(elem)
            except _coconut.ValueError:
                ind += _coconut.len(it)
        raise ValueError("%r not in %r" % (elem, self))
    def __fmap__(self, func):
        return self.__class__(_coconut_map(_coconut.functools.partial(_coconut_map, func), self.iter))
class map(_coconut_base_hashable, _coconut.map):
    __slots__ = ("func", "iters")
    if hasattr(_coconut.map, "__doc__"):
        __doc__ = _coconut.map.__doc__
    def __new__(cls, function, *iterables):
        new_map = _coconut.map.__new__(cls, function, *iterables)
        new_map.func = function
        new_map.iters = iterables
        return new_map
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            return self.__class__(self.func, *(_coconut_iter_getitem(i, index) for i in self.iters))
        return self.func(*(_coconut_iter_getitem(i, index) for i in self.iters))
    def __reversed__(self):
        return self.__class__(self.func, *(_coconut_reversed(i) for i in self.iters))
    def __len__(self):
        return _coconut.min(_coconut.len(i) for i in self.iters)
    def __repr__(self):
        return "map(%r, %s)" % (self.func, ", ".join((_coconut.repr(i) for i in self.iters)))
    def __reduce__(self):
        return (self.__class__, (self.func,) + self.iters)
    def __iter__(self):
        return _coconut.iter(_coconut.map(self.func, *self.iters))
    def __fmap__(self, func):
        return self.__class__(_coconut_forward_compose(self.func, func), *self.iters)
class _coconut_parallel_concurrent_map_func_wrapper(_coconut_base_hashable):
    __slots__ = ("map_cls", "func", "star")
    def __init__(self, map_cls, func, star):
        self.map_cls = map_cls
        self.func = func
        self.star = star
    def __reduce__(self):
        return (self.__class__, (self.map_cls, self.func, self.star))
    def __call__(self, *args, **kwargs):
        self.map_cls.get_pool_stack().append(None)
        try:
            if self.star:
                assert _coconut.len(args) == 1, "internal parallel/concurrent map error (you should report this at https://github.com/evhub/coconut/issues/new)"
                return self.func(*args[0], **kwargs)
            else:
                return self.func(*args, **kwargs)
        except:
            _coconut.print(self.map_cls.__name__ + " error:")
            _coconut.traceback.print_exc()
            raise
        finally:
            assert self.map_cls.get_pool_stack().pop() is None, "internal parallel/concurrent map error (you should report this at https://github.com/evhub/coconut/issues/new)"
class _coconut_base_parallel_concurrent_map(map):
    __slots__ = ("result", "chunksize")
    @classmethod
    def get_pool_stack(cls):
        return cls.threadlocal_ns.__dict__.setdefault("pool_stack", [None])
    def __new__(cls, function, *iterables, **kwargs):
        self = _coconut_map.__new__(cls, function, *iterables)
        self.result = None
        self.chunksize = kwargs.pop("chunksize", 1)
        if kwargs:
            raise _coconut.TypeError(cls.__name__ + "() got unexpected keyword arguments " + _coconut.repr(kwargs))
        if cls.get_pool_stack()[-1] is not None:
            return self.get_list()
        return self
    @classmethod
    @_coconut.contextlib.contextmanager
    def multiple_sequential_calls(cls, max_workers=None):
        """Context manager that causes nested calls to use the same pool."""
        if cls.get_pool_stack()[-1] is None:
            cls.get_pool_stack()[-1] = cls.make_pool(max_workers)
            try:
                yield
            finally:
                cls.get_pool_stack()[-1].terminate()
                cls.get_pool_stack()[-1] = None
        else:
            yield
    def get_list(self):
        if self.result is None:
            with self.multiple_sequential_calls():
                if _coconut.len(self.iters) == 1:
                    self.result = _coconut.list(self.get_pool_stack()[-1].imap(_coconut_parallel_concurrent_map_func_wrapper(self.__class__, self.func, False), self.iters[0], self.chunksize))
                else:
                    self.result = _coconut.list(self.get_pool_stack()[-1].imap(_coconut_parallel_concurrent_map_func_wrapper(self.__class__, self.func, True), _coconut.zip(*self.iters), self.chunksize))
        return self.result
    def __iter__(self):
        return _coconut.iter(self.get_list())
class parallel_map(_coconut_base_parallel_concurrent_map):
    """Multi-process implementation of map. Requires arguments to be pickleable.

    For multiple sequential calls, use:
        with parallel_map.multiple_sequential_calls():
            ...
    """
    __slots__ = ()
    threadlocal_ns = _coconut.threading.local()
    @staticmethod
    def make_pool(max_workers=None):
        return _coconut.multiprocessing.Pool(max_workers)
    def __repr__(self):
        return "parallel_" + _coconut_map.__repr__(self)
class concurrent_map(_coconut_base_parallel_concurrent_map):
    """Multi-thread implementation of map.

    For multiple sequential calls, use:
        with concurrent_map.multiple_sequential_calls():
            ...
    """
    __slots__ = ()
    threadlocal_ns = _coconut.threading.local()
    @staticmethod
    def make_pool(max_workers=None):
        return _coconut.multiprocessing_dummy.Pool(_coconut.multiprocessing.cpu_count() * 5 if max_workers is None else max_workers)
    def __repr__(self):
        return "concurrent_" + _coconut_map.__repr__(self)
class filter(_coconut_base_hashable, _coconut.filter):
    __slots__ = ("func", "iter")
    if hasattr(_coconut.filter, "__doc__"):
        __doc__ = _coconut.filter.__doc__
    def __new__(cls, function, iterable):
        new_filter = _coconut.filter.__new__(cls, function, iterable)
        new_filter.func = function
        new_filter.iter = iterable
        return new_filter
    def __reversed__(self):
        return self.__class__(self.func, _coconut_reversed(self.iter))
    def __repr__(self):
        return "filter(%r, %s)" % (self.func, _coconut.repr(self.iter))
    def __reduce__(self):
        return (self.__class__, (self.func, self.iter))
    def __iter__(self):
        return _coconut.iter(_coconut.filter(self.func, self.iter))
    def __fmap__(self, func):
        return _coconut_map(func, self)
class zip(_coconut_base_hashable, _coconut.zip):
    __slots__ = ("iters", "strict")
    if hasattr(_coconut.zip, "__doc__"):
        __doc__ = _coconut.zip.__doc__
    def __new__(cls, *iterables, **kwargs):
        new_zip = _coconut.zip.__new__(cls, *iterables)
        new_zip.iters = iterables
        new_zip.strict = kwargs.pop("strict", False)
        if kwargs:
            raise _coconut.TypeError("zip() got unexpected keyword arguments " + _coconut.repr(kwargs))
        return new_zip
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            return self.__class__(*(_coconut_iter_getitem(i, index) for i in self.iters), strict=self.strict)
        return _coconut.tuple(_coconut_iter_getitem(i, index) for i in self.iters)
    def __reversed__(self):
        return self.__class__(*(_coconut_reversed(i) for i in self.iters), strict=self.strict)
    def __len__(self):
        return _coconut.min(_coconut.len(i) for i in self.iters)
    def __repr__(self):
        return "zip(%s%s)" % (", ".join((_coconut.repr(i) for i in self.iters)), ", strict=True" if self.strict else "")
    def __reduce__(self):
        return (self.__class__, self.iters, self.strict)
    def __setstate__(self, strict):
        self.strict = strict
    def __iter__(self):
        for items in _coconut.iter(_coconut.zip_longest(*self.iters, fillvalue=_coconut_sentinel) if self.strict else _coconut.zip(*self.iters)):
            if self.strict and _coconut.any(x is _coconut_sentinel for x in items):
                raise _coconut.ValueError("zip(..., strict=True) arguments have mismatched lengths")
            yield items
    def __fmap__(self, func):
        return _coconut_map(func, self)
class zip_longest(zip):
    __slots__ = ("fillvalue",)
    if hasattr(_coconut.zip_longest, "__doc__"):
        __doc__ = (_coconut.zip_longest).__doc__
    def __new__(cls, *iterables, **kwargs):
        self = _coconut_zip.__new__(cls, *iterables, strict=False)
        self.fillvalue = kwargs.pop("fillvalue", None)
        if kwargs:
            raise _coconut.TypeError("zip_longest() got unexpected keyword arguments " + _coconut.repr(kwargs))
        return self
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            new_ind = _coconut.slice(index.start + self.__len__() if index.start is not None and index.start < 0 else index.start, index.stop + self.__len__() if index.stop is not None and index.stop < 0 else index.stop, index.step)
            return self.__class__(*(_coconut_iter_getitem(i, new_ind) for i in self.iters))
        if index < 0:
            index += self.__len__()
        result = []
        got_non_default = False
        for it in self.iters:
            try:
                result.append(_coconut_iter_getitem(it, index))
            except _coconut.IndexError:
                result.append(self.fillvalue)
            else:
                got_non_default = True
        if not got_non_default:
            raise _coconut.IndexError("zip_longest index out of range")
        return _coconut.tuple(result)
    def __len__(self):
        return _coconut.max(_coconut.len(i) for i in self.iters)
    def __repr__(self):
        return "zip_longest(%s, fillvalue=%s)" % (", ".join((_coconut.repr(i) for i in self.iters)), _coconut.repr(self.fillvalue))
    def __reduce__(self):
        return (self.__class__, self.iters, self.fillvalue)
    def __setstate__(self, fillvalue):
        self.fillvalue = fillvalue
    def __iter__(self):
        return _coconut.iter(_coconut.zip_longest(*self.iters, fillvalue=self.fillvalue))
class enumerate(_coconut_base_hashable, _coconut.enumerate):
    __slots__ = ("iter", "start")
    if hasattr(_coconut.enumerate, "__doc__"):
        __doc__ = _coconut.enumerate.__doc__
    def __new__(cls, iterable, start=0):
        new_enumerate = _coconut.enumerate.__new__(cls, iterable, start)
        new_enumerate.iter = iterable
        new_enumerate.start = start
        return new_enumerate
    def __repr__(self):
        return "enumerate(%s, %r)" % (_coconut.repr(self.iter), self.start)
    def __fmap__(self, func):
        return _coconut_map(func, self)
    def __reduce__(self):
        return (self.__class__, (self.iter, self.start))
    def __iter__(self):
        return _coconut.iter(_coconut.enumerate(self.iter, self.start))
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            return self.__class__(_coconut_iter_getitem(self.iter, index), self.start + (0 if index.start is None else index.start if index.start >= 0 else _coconut.len(self.iter) + index.start))
        return (self.start + index, _coconut_iter_getitem(self.iter, index))
    def __len__(self):
        return _coconut.len(self.iter)
class multi_enumerate(_coconut_base_hashable):
    """Enumerate an iterable of iterables. Works like enumerate, but indexes
    through inner iterables and produces a tuple index representing the index
    in each inner iterable. Supports indexing.

    For numpy arrays, effectively equivalent to:
        it = np.nditer(iterable, flags=["multi_index"])
        for x in it:
            yield it.multi_index, x

    Also supports len for numpy arrays.
    """
    __slots__ = ("iter",)
    def __init__(self, iterable):
        self.iter = iterable
    def __repr__(self):
        return "multi_enumerate(%s)" % (_coconut.repr(self.iter),)
    def __fmap__(self, func):
        return _coconut_map(func, self)
    def __reduce__(self):
        return (self.__class__, (self.iter,))
    @property
    def is_numpy(self):
        return self.iter.__class__.__module__ in _coconut.numpy_modules
    def __iter__(self):
        if self.is_numpy:
            it = _coconut.numpy.nditer(self.iter, flags=["multi_index"])
            for x in it:
                yield it.multi_index, x
        else:
            ind = [-1]
            its = [_coconut.iter(self.iter)]
            while its:
                ind[-1] += 1
                try:
                    x = _coconut.next(its[-1])
                except _coconut.StopIteration:
                    ind.pop()
                    its.pop()
                else:
                    if _coconut.isinstance(x, _coconut.abc.Iterable):
                        ind.append(-1)
                        its.append(_coconut.iter(x))
                    else:
                        yield _coconut.tuple(ind), x
    def __getitem__(self, index):
        if self.is_numpy and not _coconut.isinstance(index, _coconut.slice):
            multi_ind = []
            for i in _coconut.reversed(self.iter.shape):
                multi_ind.append(index % i)
                index //= i
            multi_ind = _coconut.tuple(_coconut.reversed(multi_ind))
            return multi_ind, self.iter[multi_ind]
        return _coconut_iter_getitem(_coconut.iter(self), index)
    def __len__(self):
        if self.is_numpy:
            return self.iter.size
        return _coconut.NotImplemented
class count(_coconut_base_hashable):
    """count(start, step) returns an infinite iterator starting at start and increasing by step.

    If step is set to 0, count will infinitely repeat its first argument.
    """
    __slots__ = ("start", "step")
    def __init__(self, start=0, step=1):
        self.start = start
        self.step = step
    def __iter__(self):
        while True:
            yield self.start
            if self.step:
                self.start += self.step
    def __contains__(self, elem):
        if not self.step:
            return elem == self.start
        if self.step > 0 and elem < self.start or self.step < 0 and elem > self.start:
            return False
        return (elem - self.start) % self.step == 0
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            if (index.start is None or index.start >= 0) and (index.stop is None or index.stop >= 0):
                new_start, new_step = self.start, self.step
                if self.step and index.start is not None:
                    new_start += self.step * index.start
                if self.step and index.step is not None:
                    new_step *= index.step
                if index.stop is None:
                    return self.__class__(new_start, new_step)
                if self.step and _coconut.isinstance(self.start, _coconut.int) and _coconut.isinstance(self.step, _coconut.int):
                    return _coconut.range(new_start, self.start + self.step * index.stop, new_step)
                return _coconut_map(self.__getitem__, _coconut.range(index.start if index.start is not None else 0, index.stop, index.step if index.step is not None else 1))
            raise _coconut.IndexError("count() indices must be positive")
        if index < 0:
            raise _coconut.IndexError("count() indices must be positive")
        return self.start + self.step * index if self.step else self.start
    def count(self, elem):
        """Count the number of times elem appears in the count."""
        if not self.step:
            return _coconut.float("inf") if elem == self.start else 0
        return _coconut.int(elem in self)
    def index(self, elem):
        """Find the index of elem in the count."""
        if elem not in self:
            raise _coconut.ValueError(_coconut.repr(elem) + " not in " + _coconut.repr(self))
        return (elem - self.start) // self.step if self.step else 0
    def __reversed__(self):
        if not self.step:
            return self
        raise _coconut.TypeError(_coconut.repr(self) + " object is not reversible")
    def __repr__(self):
        return "count(%s, %s)" % (_coconut.repr(self.start), _coconut.repr(self.step))
    def __reduce__(self):
        return (self.__class__, (self.start, self.step))
    def __copy__(self):
        return self.__class__(self.start, self.step)
    def __fmap__(self, func):
        return _coconut_map(func, self)
class groupsof(_coconut_base_hashable):
    """groupsof(n, iterable) splits iterable into groups of size n.

    If the length of the iterable is not divisible by n, the last group will be of size < n.
    """
    __slots__ = ("group_size", "iter")
    def __init__(self, n, iterable):
        self.group_size = _coconut.operator.index(n)
        if self.group_size <= 0:
            raise _coconut.ValueError("group size must be > 0; not %r" % (self.group_size,))
        self.iter = iterable
    def __iter__(self):
        iterator = _coconut.iter(self.iter)
        loop = True
        while loop:
            group = []
            for _ in _coconut.range(self.group_size):
                try:
                    group.append(_coconut.next(iterator))
                except _coconut.StopIteration:
                    loop = False
                    break
            if group:
                yield _coconut.tuple(group)
    def __len__(self):
        return _coconut.int(_coconut.math.ceil(_coconut.len(self.iter) / self.group_size))
    def __repr__(self):
        return "groupsof(%s)" % (_coconut.repr(self.iter),)
    def __reduce__(self):
        return (self.__class__, (self.group_size, self.iter))
    def __fmap__(self, func):
        return _coconut_map(func, self)
class recursive_iterator(_coconut_base_hashable):
    """Decorator that optimizes a recursive function that returns an iterator (e.g. a recursive generator)."""
    __slots__ = ("func", "tee_store", "backup_tee_store")
    def __init__(self, func):
        self.func = func
        self.tee_store = {}
        self.backup_tee_store = []
    def __call__(self, *args, **kwargs):
        key = (args, _coconut.frozenset(kwargs.items()))
        use_backup = False
        try:
            _coconut.hash(key)
        except _coconut.Exception:
            try:
                key = _coconut.pickle.dumps(key, -1)
            except _coconut.Exception:
                use_backup = True
        if use_backup:
            for i, (k, v) in _coconut.enumerate(self.backup_tee_store):
                if k == key:
                    to_tee, store_pos = v, i
                    break
            else:
                to_tee = self.func(*args, **kwargs)
                store_pos = None
            to_store, to_return = _coconut_tee(to_tee)
            if store_pos is None:
                self.backup_tee_store.append([key, to_store])
            else:
                self.backup_tee_store[store_pos][1] = to_store
        else:
            it = self.tee_store.get(key)
            if it is None:
                it = self.func(*args, **kwargs)
            self.tee_store[key], to_return = _coconut_tee(it)
        return to_return
    def __repr__(self):
        return "recursive_iterator(%r)" % (self.func,)
    def __reduce__(self):
        return (self.__class__, (self.func,))
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        return _coconut.types.MethodType(self, obj)
class _coconut_FunctionMatchErrorContext:
    __slots__ = ("exc_class", "taken")
    threadlocal_ns = _coconut.threading.local()
    def __init__(self, exc_class):
        self.exc_class = exc_class
        self.taken = False
    @classmethod
    def get_contexts(cls):
        try:
            return cls.threadlocal_ns.contexts
        except _coconut.AttributeError:
            cls.threadlocal_ns.contexts = []
            return cls.threadlocal_ns.contexts
    def __enter__(self):
        self.get_contexts().append(self)
    def __exit__(self, type, value, traceback):
        self.get_contexts().pop()
def _coconut_get_function_match_error():
    try:
        ctx = _coconut_FunctionMatchErrorContext.get_contexts()[-1]
    except _coconut.IndexError:
        return _coconut_MatchError
    if ctx.taken:
        return _coconut_MatchError
    ctx.taken = True
    return ctx.exc_class
class _coconut_base_pattern_func(_coconut_base_hashable):
    __slots__ = ("FunctionMatchError", "patterns", "__doc__", "__name__", "__qualname__")
    _coconut_is_match = True
    def __init__(self, *funcs):
        self.FunctionMatchError = _coconut.type(_coconut_py_str("MatchError"), (_coconut_MatchError,), {})
        self.patterns = []
        self.__doc__ = None
        self.__name__ = None
        self.__qualname__ = None
        for func in funcs:
            self.add_pattern(func)
    def add_pattern(self, func):
        if _coconut.isinstance(func, _coconut_base_pattern_func):
            self.patterns += func.patterns
        else:
            self.patterns.append(func)
        self.__doc__ = _coconut.getattr(func, "__doc__", self.__doc__)
        self.__name__ = _coconut.getattr(func, "__name__", self.__name__)
        self.__qualname__ = _coconut.getattr(func, "__qualname__", self.__qualname__)
    def __call__(self, *args, **kwargs):
        for func in self.patterns[:-1]:
            try:
                with _coconut_FunctionMatchErrorContext(self.FunctionMatchError):
                    return func(*args, **kwargs)
            except self.FunctionMatchError:
                pass
        return self.patterns[-1](*args, **kwargs)
    def _coconut_tco_func(self, *args, **kwargs):
        for func in self.patterns[:-1]:
            try:
                with _coconut_FunctionMatchErrorContext(self.FunctionMatchError):
                    return func(*args, **kwargs)
            except self.FunctionMatchError:
                pass
        return _coconut_tail_call(self.patterns[-1], *args, **kwargs)
    def __repr__(self):
        return "addpattern(%r)(*%r)" % (self.patterns[0], self.patterns[1:])
    def __reduce__(self):
        return (self.__class__, _coconut.tuple(self.patterns))
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        return _coconut.types.MethodType(self, obj)
def _coconut_mark_as_match(base_func):
    base_func._coconut_is_match = True
    return base_func
def addpattern(base_func, new_pattern=None, **kwargs):
    """Decorator to add a new case to a pattern-matching function (where the new case is checked last).

    Pass allow_any_func=True to allow any object as the base_func rather than just pattern-matching functions.
    If new_pattern is passed, addpattern(base_func, new_pattern) is equivalent to addpattern(base_func)(new_pattern).
    """
    allow_any_func = kwargs.pop("allow_any_func", False)
    if not allow_any_func and not _coconut.getattr(base_func, "_coconut_is_match", False):
        _coconut.warnings.warn("Possible misuse of addpattern with non-pattern-matching function " + _coconut.repr(base_func) + " (pass allow_any_func=True to dismiss)", stacklevel=2)
    if kwargs:
        raise _coconut.TypeError("addpattern() got unexpected keyword arguments " + _coconut.repr(kwargs))
    if new_pattern is not None:
        return _coconut_base_pattern_func(base_func, new_pattern)
    return _coconut.functools.partial(_coconut_base_pattern_func, base_func)
_coconut_addpattern = addpattern
def prepattern(base_func, **kwargs):
    """DEPRECATED: use addpattern instead."""
    def pattern_prepender(func):
        return addpattern(func, **kwargs)(base_func)
    return pattern_prepender
class _coconut_partial(_coconut_base_hashable):
    __slots__ = ("func", "_argdict", "_arglen", "_pos_kwargs", "_stargs", "keywords")
    if hasattr(_coconut.functools.partial, "__doc__"):
        __doc__ = _coconut.functools.partial.__doc__
    def __init__(self, _coconut_func, _coconut_argdict, _coconut_arglen, _coconut_pos_kwargs, *args, **kwargs):
        self.func = _coconut_func
        self._argdict = _coconut_argdict
        self._arglen = _coconut_arglen
        self._pos_kwargs = _coconut_pos_kwargs
        self._stargs = args
        self.keywords = kwargs
    def __reduce__(self):
        return (self.__class__, (self.func, self._argdict, self._arglen, self._pos_kwargs) + self._stargs, self.keywords)
    def __setstate__(self, keywords):
        self.keywords = keywords
    @property
    def args(self):
        return _coconut.tuple(self._argdict.get(i) for i in _coconut.range(self._arglen)) + self._stargs
    @property
    def required_nargs(self):
        return self._arglen - _coconut.len(self._argdict) + len(self._pos_kwargs)
    def __call__(self, *args, **kwargs):
        callargs = []
        argind = 0
        for i in _coconut.range(self._arglen):
            if i in self._argdict:
                callargs.append(self._argdict[i])
            elif argind >= _coconut.len(args):
                raise _coconut.TypeError("expected at least " + _coconut.str(self.required_nargs) + " argument(s) to " + _coconut.repr(self))
            else:
                callargs.append(args[argind])
                argind += 1
        for k in self._pos_kwargs:
            if k in kwargs:
                raise _coconut.TypeError(_coconut.repr(k) + " is an invalid keyword argument for " + _coconut.repr(self))
            elif argind >= _coconut.len(args):
                raise _coconut.TypeError("expected at least " + _coconut.str(self.required_nargs) + " argument(s) to " + _coconut.repr(self))
            else:
                kwargs[k] = args[argind]
                argind += 1
        callargs += self._stargs
        callargs += args[argind:]
        callkwargs = self.keywords.copy()
        callkwargs.update(kwargs)
        return self.func(*callargs, **callkwargs)
    def __repr__(self):
        args = []
        for i in _coconut.range(self._arglen):
            if i in self._argdict:
                args.append(_coconut.repr(self._argdict[i]))
            else:
                args.append("?")
        for arg in self._stargs:
            args.append(_coconut.repr(arg))
        for k in self._pos_kwargs:
            args.append(k + "=?")
        for k, v in self.keywords.items():
            args.append(k + "=" + _coconut.repr(v))
        return "%r$(%s)" % (self.func, ", ".join(args))
def consume(iterable, keep_last=0):
    """consume(iterable, keep_last) fully exhausts iterable and returns the last keep_last elements."""
    return _coconut.collections.deque(iterable, maxlen=keep_last)
class starmap(_coconut_base_hashable, _coconut.itertools.starmap):
    __slots__ = ("func", "iter")
    if hasattr(_coconut.itertools.starmap, "__doc__"):
        __doc__ = _coconut.itertools.starmap.__doc__
    def __new__(cls, function, iterable):
        new_map = _coconut.itertools.starmap.__new__(cls, function, iterable)
        new_map.func = function
        new_map.iter = iterable
        return new_map
    def __getitem__(self, index):
        if _coconut.isinstance(index, _coconut.slice):
            return self.__class__(self.func, _coconut_iter_getitem(self.iter, index))
        return self.func(*_coconut_iter_getitem(self.iter, index))
    def __reversed__(self):
        return self.__class__(self.func, *_coconut_reversed(self.iter))
    def __len__(self):
        return _coconut.len(self.iter)
    def __repr__(self):
        return "starmap(%r, %s)" % (self.func, _coconut.repr(self.iter))
    def __reduce__(self):
        return (self.__class__, (self.func, self.iter))
    def __iter__(self):
        return _coconut.iter(_coconut.itertools.starmap(self.func, self.iter))
    def __fmap__(self, func):
        return self.__class__(_coconut_forward_compose(self.func, func), self.iter)
def _coconut_base_makedata(data_type, args):
    if _coconut.hasattr(data_type, "_make") and _coconut.issubclass(data_type, _coconut.tuple):
        return data_type._make(args)
    if _coconut.issubclass(data_type, (_coconut.range, _coconut.abc.Iterator)):
        return args
    if _coconut.issubclass(data_type, _coconut.str):
        return "".join(args)
    return data_type(args)
def makedata(data_type, *args):
    """Construct an object of the given data_type containing the given arguments."""
    return _coconut_base_makedata(data_type, args)
def datamaker(data_type):
    """DEPRECATED: use makedata instead."""
    return _coconut.functools.partial(makedata, data_type)
class _coconut_amap(_coconut_base_hashable):
    __slots__ = ("func", "aiter")
    def __init__(self, func, aiter):
        self.func = func
        self.aiter = aiter
    def __reduce__(self):
        return (self.__class__, (self.func, self.aiter))
    def __aiter__(self):
        return self
    async def __anext__(self):
        return self.func(await self.aiter.__anext__())
def fmap(func, obj, **kwargs):
    """fmap(func, obj) creates a copy of obj with func applied to its contents.
    Supports asynchronous iterables, mappings (maps over .items()), and numpy arrays (uses np.vectorize).

    Override by defining obj.__fmap__(func).
    """
    starmap_over_mappings = kwargs.pop("starmap_over_mappings", False)
    if kwargs:
        raise _coconut.TypeError("fmap() got unexpected keyword arguments " + _coconut.repr(kwargs))
    obj_fmap = _coconut.getattr(obj, "__fmap__", None)
    if obj_fmap is not None:
        try:
            result = obj_fmap(func)
        except _coconut.NotImplementedError:
            pass
        else:
            if result is not _coconut.NotImplemented:
                return result
    if obj.__class__.__module__ in _coconut.jax_numpy_modules:
        import jax.numpy as jnp
        return jnp.vectorize(func)(obj)
    if obj.__class__.__module__ in _coconut.numpy_modules:
        return _coconut.numpy.vectorize(func)(obj)
    obj_aiter = _coconut.getattr(obj, "__aiter__", None)
    if obj_aiter is not None and _coconut_amap is not None:
        try:
            aiter = obj_aiter()
        except _coconut.NotImplementedError:
            pass
        else:
            if aiter is not _coconut.NotImplemented:
                return _coconut_amap(func, aiter)
    if starmap_over_mappings:
        return _coconut_base_makedata(obj.__class__, _coconut_starmap(func, obj.items()) if _coconut.isinstance(obj, _coconut.abc.Mapping) else _coconut_map(func, obj))
    else:
        return _coconut_base_makedata(obj.__class__, _coconut_map(func, obj.items() if _coconut.isinstance(obj, _coconut.abc.Mapping) else obj))
def memoize(maxsize=None, *args, **kwargs):
    """Decorator that memoizes a function, preventing it from being recomputed
    if it is called multiple times with the same arguments."""
    return _coconut.functools.lru_cache(maxsize, *args, **kwargs)
def _coconut_call_set_names(cls): pass
class override(_coconut_base_hashable):
    __slots__ = ("func",)
    def __init__(self, func):
        self.func = func
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self.func
        return _coconut.types.MethodType(self.func, obj)
    def __set_name__(self, obj, name):
        if not _coconut.hasattr(_coconut.super(obj, obj), name):
            raise _coconut.RuntimeError(obj.__name__ + "." + name + " marked with @override but not overriding anything")
    def __reduce__(self):
        return (self.__class__, (self.func,))
def reveal_type(obj):
    """Special function to get MyPy to print the type of the given expression.
    At runtime, reveal_type is the identity function."""
    return obj
def reveal_locals():
    """Special function to get MyPy to print the type of the current locals.
    At runtime, reveal_locals always returns None."""
    pass
def _coconut_handle_cls_kwargs(**kwargs):
    """Some code taken from six under the terms of its MIT license."""
    metaclass = kwargs.pop("metaclass", None)
    if kwargs and metaclass is None:
        raise _coconut.TypeError("unexpected keyword argument(s) in class definition: %r" % (kwargs,))
    def coconut_handle_cls_kwargs_wrapper(cls):
        if metaclass is None:
            return cls
        orig_vars = cls.__dict__.copy()
        slots = orig_vars.get("__slots__")
        if slots is not None:
            if _coconut.isinstance(slots, _coconut.str):
                slots = [slots]
            for slots_var in slots:
                orig_vars.pop(slots_var)
        orig_vars.pop("__dict__", None)
        orig_vars.pop("__weakref__", None)
        if _coconut.hasattr(cls, "__qualname__"):
            orig_vars["__qualname__"] = cls.__qualname__
        return metaclass(cls.__name__, cls.__bases__, orig_vars, **kwargs)
    return coconut_handle_cls_kwargs_wrapper
def _coconut_handle_cls_stargs(*args):
    temp_names = ["_coconut_base_cls_%s" % (i,) for i in _coconut.range(_coconut.len(args))]
    ns = _coconut.dict(_coconut.zip(temp_names, args))
    _coconut_exec("class _coconut_cls_stargs_base(" + ", ".join(temp_names) + "): pass", ns)
    return ns["_coconut_cls_stargs_base"]
def _coconut_dict_merge(*dicts, **kwargs):
    for_func = kwargs.pop("for_func", False)
    assert not kwargs, "error with internal Coconut function _coconut_dict_merge (you should report this at https://github.com/evhub/coconut/issues/new)"
    newdict = {}
    prevlen = 0
    for d in dicts:
        newdict.update(d)
        if for_func:
            if _coconut.len(newdict) != prevlen + _coconut.len(d):
                raise _coconut.TypeError("multiple values for the same keyword argument")
            prevlen = _coconut.len(newdict)
    return newdict
def ident(x, **kwargs):
    """The identity function. Generally equivalent to x -> x. Useful in point-free programming.
    Accepts one keyword-only argument, side_effect, which specifies a function to call on the argument before it is returned."""
    side_effect = kwargs.pop("side_effect", None)
    if kwargs:
        raise _coconut.TypeError("ident() got unexpected keyword arguments " + _coconut.repr(kwargs))
    if side_effect is not None:
        side_effect(x)
    return x
def of(_coconut_f, *args, **kwargs):
    """Function application operator function.

    Equivalent to:
        def of(f, *args, **kwargs) = f(*args, **kwargs).
    """
    return _coconut_f(*args, **kwargs)
class flip(_coconut_base_hashable):
    """Given a function, return a new function with inverse argument order.
    If nargs is passed, only the first nargs arguments are reversed."""
    __slots__ = ("func", "nargs")
    def __init__(self, func, nargs=None):
        self.func = func
        self.nargs = nargs
    def __reduce__(self):
        return (self.__class__, (self.func, self.nargs))
    def __call__(self, *args, **kwargs):
        return self.func(*args[::-1], **kwargs) if self.nargs is None else self.func(*(args[self.nargs-1::-1] + args[self.nargs:]), **kwargs)
    def __repr__(self):
        return "flip(%r%s)" % (self.func, "" if self.nargs is None else ", " + _coconut.repr(self.nargs))
class const(_coconut_base_hashable):
    """Create a function that, whatever its arguments, just returns the given value."""
    __slots__ = ("value",)
    def __init__(self, value):
        self.value = value
    def __reduce__(self):
        return (self.__class__, (self.value,))
    def __call__(self, *args, **kwargs):
        return self.value
    def __repr__(self):
        return "const(%s)" % (_coconut.repr(self.value),)
class _coconut_lifted(_coconut_base_hashable):
    __slots__ = ("func", "func_args", "func_kwargs")
    def __init__(self, _coconut_func, *func_args, **func_kwargs):
        self.func = _coconut_func
        self.func_args = func_args
        self.func_kwargs = func_kwargs
    def __reduce__(self):
        return (self.__class__, (self.func,) + self.func_args, self.func_kwargs)
    def __setstate__(self, func_kwargs):
        self.func_kwargs = func_kwargs
    def __call__(self, *args, **kwargs):
        return self.func(*(g(*args, **kwargs) for g in self.func_args), **_coconut.dict((k, h(*args, **kwargs)) for k, h in self.func_kwargs.items()))
    def __repr__(self):
        return "lift(%r)(%s%s)" % (self.func, ", ".join(_coconut.repr(g) for g in self.func_args), ", ".join(k + "=" + _coconut.repr(h) for k, h in self.func_kwargs.items()))
class lift(_coconut_base_hashable):
    """Lifts a function up so that all of its arguments are functions.

    For a binary function f(x, y) and two unary functions g(z) and h(z), lift works as the S' combinator:
        lift(f)(g, h)(z) == f(g(z), h(z))

    In general, lift is requivalent to:
        def lift(f) = ((*func_args, **func_kwargs) -> (*args, **kwargs) ->
            f(*(g(*args, **kwargs) for g in func_args), **{k: h(*args, **kwargs) for k, h in func_kwargs.items()}))

    lift also supports a shortcut form such that lift(f, *func_args, **func_kwargs) is equivalent to lift(f)(*func_args, **func_kwargs).
    """
    __slots__ = ("func",)
    def __new__(cls, func, *func_args, **func_kwargs):
        self = _coconut.object.__new__(cls)
        self.func = func
        if func_args or func_kwargs:
            self = self(*func_args, **func_kwargs)
        return self
    def __reduce__(self):
        return (self.__class__, (self.func,))
    def __call__(self, *func_args, **func_kwargs):
        return _coconut_lifted(self.func, *func_args, **func_kwargs)
    def __repr__(self):
        return "lift(%r)" % (self.func,)
def all_equal(iterable):
    """For a given iterable, check whether all elements in that iterable are equal to each other.

    Assumes transitivity and 'x != y' being equivalent to 'not (x == y)'.
    """
    first_item = _coconut_sentinel
    for item in iterable:
        if first_item is _coconut_sentinel:
            first_item = item
        elif first_item != item:
            return False
    return True
def collectby(key_func, iterable, value_func=None, reduce_func=None):
    """Collect the items in iterable into a dictionary of lists keyed by key_func(item).

    if value_func is passed, collect value_func(item) into each list instead of item.

    If reduce_func is passed, instead of collecting the items into lists, reduce over
    the items of each key with reduce_func, effectively implementing a MapReduce operation.
    """
    collection = _coconut.collections.defaultdict(_coconut.list) if reduce_func is None else {}
    for item in iterable:
        key = key_func(item)
        if value_func is not None:
            item = value_func(item)
        if reduce_func is None:
            collection[key].append(item)
        else:
            old_item = collection.get(key, _coconut_sentinel)
            if old_item is not _coconut_sentinel:
                item = reduce_func(old_item, item)
            collection[key] = item
    return collection
def _namedtuple_of(**kwargs):
    """Construct an anonymous namedtuple of the given keyword arguments."""
    return _coconut_mk_anon_namedtuple(kwargs.keys(), of_kwargs=kwargs)
def _coconut_mk_anon_namedtuple(fields, types=None, of_kwargs=None):
    if types is None:
        NT = _coconut.collections.namedtuple("_namedtuple_of", fields)
    else:
        NT = _coconut.typing.NamedTuple("_namedtuple_of", [(f, t) for f, t in _coconut.zip(fields, types)])
    _coconut.copyreg.pickle(NT, lambda nt: (_coconut_mk_anon_namedtuple, (nt._fields, types, nt._asdict())))
    if of_kwargs is None:
        return NT
    return NT(**of_kwargs)
def _coconut_ndim(arr):
    if (arr.__class__.__module__ in _coconut.numpy_modules or _coconut.hasattr(arr.__class__, "__matconcat__")) and _coconut.hasattr(arr, "ndim"):
        return arr.ndim
    if not _coconut.isinstance(arr, _coconut.abc.Sequence):
        return 0
    if _coconut.len(arr) == 0:
        return 1
    arr_dim = 1
    inner_arr = arr[0]
    while _coconut.isinstance(inner_arr, _coconut.abc.Sequence):
        arr_dim += 1
        if _coconut.len(inner_arr) < 1:
            break
        inner_arr = inner_arr[0]
    return arr_dim
def _coconut_expand_arr(arr, new_dims):
    if (arr.__class__.__module__ in _coconut.numpy_modules or _coconut.hasattr(arr.__class__, "__matconcat__")) and _coconut.hasattr(arr, "reshape"):
        return arr.reshape((1,) * new_dims + arr.shape)
    for _ in _coconut.range(new_dims):
        arr = [arr]
    return arr
def _coconut_concatenate(arrs, axis):
    matconcat = None
    for a in arrs:
        if a.__class__.__module__ in _coconut.jax_numpy_modules:
            from jax.numpy import concatenate as matconcat
            break
        if a.__class__.__module__ in _coconut.numpy_modules:
            matconcat = _coconut.numpy.concatenate
            break
        if _coconut.hasattr(a.__class__, "__matconcat__"):
            matconcat = a.__class__.__matconcat__
            break
    if matconcat is not None:
        return matconcat(arrs, axis)
    if not axis:
        return _coconut.list(_coconut.itertools.chain.from_iterable(arrs))
    return [_coconut_concatenate(rows, axis - 1) for rows in _coconut.zip(*arrs)]
def _coconut_multi_dim_arr(arrs, dim):
    arr_dims = [_coconut_ndim(a) for a in arrs]
    arrs = [_coconut_expand_arr(a, dim - d) if d < dim else a for a, d in _coconut.zip(arrs, arr_dims)]
    arr_dims.append(dim)
    max_arr_dim = _coconut.max(arr_dims)
    return _coconut_concatenate(arrs, max_arr_dim - dim)
_coconut_self_match_types = (bool, bytearray, bytes, dict, float, frozenset, int, py_int, list, set, str, py_str, tuple)
_coconut_MatchError, _coconut_count, _coconut_enumerate, _coconut_filter, _coconut_map, _coconut_reiterable, _coconut_reversed, _coconut_starmap, _coconut_tee, _coconut_zip, TYPE_CHECKING, reduce, takewhile, dropwhile = MatchError, count, enumerate, filter, map, reiterable, reversed, starmap, tee, zip, False, _coconut.functools.reduce, _coconut.itertools.takewhile, _coconut.itertools.dropwhile