import functools as _functools
import itertools as _itertools
import typing as _t
from ._core.left import Applier as _Applier
from .iterating import expand as _expand
_T1 = _t.TypeVar('_T1')
_T2 = _t.TypeVar('_T2')
[docs]def accumulator(
_function: _t.Callable[[_T2, _T1], _T2], _initial: _T2
) -> _t.Callable[[_t.Iterable[_T1]], _t.Iterable[_T2]]:
"""
Returns function that yields cumulative results of given binary function
starting from given initial object in direction from left to right.
>>> import math
>>> to_pi_approximations = accumulator(round, math.pi)
>>> list(to_pi_approximations(range(5, 0, -1)))
[3.141592653589793, 3.14159, 3.1416, 3.142, 3.14, 3.1]
"""
return _functools.partial(accumulate, _function, _initial)
[docs]def accumulate(_function: _t.Callable[[_T2, _T1], _T2],
_initial: _T2,
_iterable: _t.Iterable[_T1]) -> _t.Iterable[_T2]:
"""
Yields cumulative results of given binary function
starting from given initial object in direction from left to right.
>>> import math
>>> list(accumulate(round, math.pi, range(5, 0, -1)))
[3.141592653589793, 3.14159, 3.1416, 3.142, 3.14, 3.1]
"""
yield from _itertools.accumulate(
attach(_iterable, _initial),
_t.cast(_t.Callable[[_t.Any, _t.Any], _T2], _function)
)
[docs]def attacher(_value: _T1) -> _t.Callable[[_t.Iterable[_T1]], _t.Iterable[_T1]]:
"""
Returns function that prepends given object to iterable.
>>> attach_hundred = attacher(100)
>>> list(attach_hundred(range(10)))
[100, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
"""
return _functools.partial(attach,
_value=_value)
[docs]@_functools.singledispatch
def attach(_target: _t.Iterable[_T1], _value: _T1) -> _t.Iterable[_T1]:
"""
Prepends given value to the target.
"""
yield from _itertools.chain(_expand(_value), _target)
@attach.register(list)
def _(_target: _t.List[_T1], _value: _T1) -> _t.List[_T1]:
"""
Prepends given object to the list.
"""
return [_value] + _target
@attach.register(tuple)
def _(_target: _t.Tuple[_T1, ...], _value: _T1) -> _t.Tuple[_T1, ...]:
"""
Prepends given value to the tuple.
"""
return (_value,) + _target
[docs]def folder(_function: _t.Callable[[_T2, _T1], _T2],
_initial: _T2) -> _t.Callable[[_t.Iterable[_T1]], _T2]:
"""
Returns function that cumulatively applies given binary function
starting from given initial object in direction from left to right.
>>> to_sum_evaluation_order = folder('({} + {})'.format, 0)
>>> to_sum_evaluation_order(range(1, 10))
'(((((((((0 + 1) + 2) + 3) + 4) + 5) + 6) + 7) + 8) + 9)'
"""
return _functools.partial(fold, _function, _initial)
[docs]def fold(_function: _t.Callable[[_T2, _T1], _T2],
_initial: _T2,
_iterable: _t.Iterable[_T1]) -> _T2:
"""
Cumulatively applies given binary function
starting from given initial object in direction from left to right.
>>> fold('({} + {})'.format, 0, range(1, 10))
'(((((((((0 + 1) + 2) + 3) + 4) + 5) + 6) + 7) + 8) + 9)'
"""
return _functools.reduce(_function, _iterable, _initial)
[docs]def applier(_function: _t.Callable[..., _T2],
*args: _T1,
**kwargs: _T1) -> _t.Callable[..., _T2]:
"""
Returns function that behaves like given function
with given arguments partially applied.
Given positional arguments will be added to the left end.
>>> count_from_zero_to = applier(range, 0)
>>> list(count_from_zero_to(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
"""
return _Applier(_function, *args, **kwargs)