Submodules

filtration module

lz.filtration.grabber(predicate: Callable[[Domain], bool] = None) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from the beginning of iterable while given predicate is satisfied.

If predicate is not specified than true-like objects are selected.

>>> grab_while_true_like = grabber()
>>> list(grab_while_true_like(range(10)))
[]
>>> from operator import gt
>>> from functools import partial
>>> grab_while_less_than_five = grabber(partial(gt, 5))
>>> list(grab_while_less_than_five(range(10)))
[0, 1, 2, 3, 4]
lz.filtration.kicker(predicate: Callable[[Domain], bool] = None) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that skips elements from the beginning of iterable while given predicate is satisfied.

If predicate is not specified than true-like objects are skipped.

>>> kick_while_true_like = kicker()
>>> list(kick_while_true_like(range(10)))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> from operator import gt
>>> from functools import partial
>>> kick_while_less_than_five = kicker(partial(gt, 5))
>>> list(kick_while_less_than_five(range(10)))
[5, 6, 7, 8, 9]
lz.filtration.scavenger(predicate: Callable[[Domain], bool] = None) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from iterable which dissatisfy given predicate.

If predicate is not specified than false-like objects are selected.

>>> to_false_like = scavenger()
>>> list(to_false_like(range(10)))
[0]
>>> def is_even(number: int) -> bool:
...     return number % 2 == 0
>>> to_odd = scavenger(is_even)
>>> list(to_odd(range(10)))
[1, 3, 5, 7, 9]
lz.filtration.separator(predicate: Callable[[Domain], bool] = None) → Callable[[Iterable[Domain]], Tuple[Iterable[Domain], Iterable[Domain]]][source]

Returns function that returns pair of iterables first of which consists of elements that dissatisfy given predicate and second one consists of elements that satisfy given predicate.

>>> split_by_truth = separator()
>>> tuple(map(list, split_by_truth(range(10))))
([0], [1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> def is_even(number: int) -> bool:
...     return number % 2 == 0
>>> split_by_evenness = separator(is_even)
>>> tuple(map(list, split_by_evenness(range(10))))
([1, 3, 5, 7, 9], [0, 2, 4, 6, 8])
lz.filtration.sifter(predicate: Callable[[Domain], bool] = None) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from iterable which satisfy given predicate.

If predicate is not specified than true-like objects are selected.

>>> to_true_like = sifter()
>>> list(to_true_like(range(10)))
[1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> def is_even(number: int) -> bool:
...     return number % 2 == 0
>>> to_even = sifter(is_even)
>>> list(to_even(range(10)))
[0, 2, 4, 6, 8]

functional module

lz.functional.apply(function: Callable[[...], Range], args: Iterable[Domain], kwargs: Dict[str, Any] = mappingproxy({})) → Range[source]

Calls given function with given positional and keyword arguments.

lz.functional.cleave(*functions: Callable[[...], Range]) → Callable[[...], Iterable[Range]][source]

Returns function that separately applies given functions to the same arguments.

>>> to_min_and_max = cleave(min, max)
>>> list(to_min_and_max(range(10)))
[0, 9]
>>> list(to_min_and_max(range(0), default=None))
[None, None]
lz.functional.combine(*maps: Callable[[Domain], Range]) → Callable[[Iterable[Domain]], Iterable[Range]][source]

Returns function that applies each map to corresponding argument.

>>> encoder_decoder = combine(str.encode, bytes.decode)
>>> list(encoder_decoder(['hello', b'world']))
[b'hello', 'world']
lz.functional.compose(last_function: Callable[[Any], Range], *front_functions: Callable[[...], Any]) → Callable[[...], Range][source]

Returns functions composition.

>>> sum_of_first_n_natural_numbers = compose(sum, range)
>>> sum_of_first_n_natural_numbers(10)
45
lz.functional.curry(function: Callable[[...], Range], *, signature: Optional[paradigm.models.Base] = None) → lz.functional.Curry[source]

Returns curried version of given function.

>>> curried_pow = curry(pow)
>>> two_to_power = curried_pow(2)
>>> two_to_power(10)
1024
lz.functional.flatmap(function: Callable[[Domain], Iterable[Range]], *iterables: Iterable[Domain]) → Iterable[Range][source]

Applies given function to the arguments aggregated from given iterables and concatenates results into plain iterable.

>>> list(flatmap(range, range(5)))
[0, 0, 1, 0, 1, 2, 0, 1, 2, 3]
lz.functional.flip(function: Callable[[...], Range]) → Callable[[...], Range][source]

Returns function with positional arguments flipped.

>>> flipped_power = flip(pow)
>>> flipped_power(2, 4)
16
lz.functional.identity(argument: Domain) → Domain[source]

Returns object itself.

>>> identity(0)
0
lz.functional.pack(function: Callable[[...], Range]) → Callable[[Iterable[Domain]], Range][source]

Returns function that works with single iterable parameter by unpacking elements to given function.

>>> packed_int = pack(int)
>>> packed_int(['10'])
10
>>> packed_int(['10'], {'base': 2})
2
lz.functional.to_constant(object_: Domain) → Callable[[...], Domain][source]

Returns function that always returns given object.

>>> always_zero = to_constant(0)
>>> always_zero()
0
>>> always_zero(1)
0
>>> always_zero(how_about=2)
0

iterating module

lz.iterating.capacity(iterable: Iterable[Any]) → int[source]

Returns number of elements in iterable.

>>> capacity(range(0))
0
>>> capacity(range(10))
10
lz.iterating.chop(iterable: Iterable[Domain], *, size: int) → Iterable[Sequence[Domain]][source]

Splits iterable into chunks of given size.

lz.iterating.chopper(size: int) → Callable[[Iterable[Domain]], Iterable[Sequence[Domain]]][source]

Returns function that splits iterable into chunks of given size.

>>> in_three = chopper(3)
>>> list(map(tuple, in_three(range(10))))
[(0, 1, 2), (3, 4, 5), (6, 7, 8), (9,)]
lz.iterating.cut(iterable: Iterable[Domain], *, slice_: slice) → Iterable[Domain][source]

Selects elements from iterable based on given slice.

Slice fields supposed to be unset or non-negative since it is hard to evaluate negative indices/step for arbitrary iterable which may be potentially infinite or change previous elements if iterating made backwards.

lz.iterating.cutter(slice_: slice) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from iterable based on given slice.

>>> to_first_triplet = cutter(slice(3))
>>> list(to_first_triplet(range(10)))
[0, 1, 2]
>>> to_second_triplet = cutter(slice(3, 6))
>>> list(to_second_triplet(range(10)))
[3, 4, 5]
>>> cut_out_every_third = cutter(slice(0, None, 3))
>>> list(cut_out_every_third(range(10)))
[0, 3, 6, 9]
lz.iterating.expand(object_: Domain) → Iterable[Domain][source]

Wraps object into iterable.

>>> list(expand(0))
[0]
lz.iterating.first(iterable: Iterable[Domain]) → Domain[source]

Returns first element of iterable.

>>> first(range(10))
0
lz.iterating.flatmapper(map_: Callable[[Domain], Iterable[Range]]) → Callable[[Iterable[Domain]], Iterable[Range]][source]

Returns function that applies map to the each element of iterable and flattens results.

>>> relay = flatmapper(range)
>>> list(relay(range(5)))
[0, 0, 1, 0, 1, 2, 0, 1, 2, 3]
lz.iterating.flatten(iterable: Iterable[Iterable[Domain]]) → Iterable[Domain][source]

Returns plain iterable from iterable of iterables.

>>> list(flatten([range(5), range(10, 20)]))
[0, 1, 2, 3, 4, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]
lz.iterating.group_by(iterable: Iterable[Domain], *, key: Callable[[Domain], Hashable], mapping_cls: Type[MutableMapping]) → Iterable[Tuple[Hashable, Iterable[Domain]]][source]

Groups iterable elements based on given key.

lz.iterating.grouper(key: Callable[[Domain], Hashable], *, mapping_cls: Type[MutableMapping] = <class 'collections.OrderedDict'>) → Callable[[Iterable[Domain]], Iterable[Tuple[Hashable, Iterable[Domain]]]][source]

Returns function that groups iterable elements based on given key.

>>> group_by_absolute_value = grouper(abs)
>>> list(group_by_absolute_value(range(-5, 5)))
[(5, [-5]), (4, [-4, 4]), (3, [-3, 3]), (2, [-2, 2]), (1, [-1, 1]), (0, [0])]
>>> def modulo_two(number: int) -> int:
...     return number % 2
>>> group_by_evenness = grouper(modulo_two)
>>> list(group_by_evenness(range(10)))
[(0, [0, 2, 4, 6, 8]), (1, [1, 3, 5, 7, 9])]
lz.iterating.header(size: int) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from the beginning of iterable. Resulted iterable will have size not greater than given one.

>>> to_first_pair = header(2)
>>> list(to_first_pair(range(10)))
[0, 1]
lz.iterating.in_four(iterable: Iterable[Domain], *, size: int = 4) → Iterable[Sequence[Domain]]

Splits iterable into chunks of size 4.

lz.iterating.in_three(iterable: Iterable[Domain], *, size: int = 3) → Iterable[Sequence[Domain]]

Splits iterable into chunks of size 3.

lz.iterating.in_two(iterable: Iterable[Domain], *, size: int = 2) → Iterable[Sequence[Domain]]

Splits iterable into chunks of size 2.

lz.iterating.interleave(iterable: Iterable[Iterable[Domain]]) → Iterable[Domain][source]

Interleaves elements from given iterable of iterables.

>>> list(interleave([range(5), range(10, 20)]))
[0, 10, 1, 11, 2, 12, 3, 13, 4, 14, 15, 16, 17, 18, 19]
lz.iterating.last(iterable: Iterable[Domain]) → Domain[source]

Returns last element of iterable.

>>> last(range(10))
9
lz.iterating.mapper(map_: Callable[[Domain], Range]) → Callable[[Iterable[Domain]], Iterable[Range]][source]

Returns function that applies given map to the each element of iterable.

>>> to_str = mapper(str)
>>> list(to_str(range(10)))
['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
lz.iterating.pairwise(iterable: Iterable[Domain], *, size: int = 2) → Iterable[Tuple[Domain, ...]]

Slides over iterable with window of size 2.

lz.iterating.quadruplewise(iterable: Iterable[Domain], *, size: int = 4) → Iterable[Tuple[Domain, ...]]

Slides over iterable with window of size 4.

lz.iterating.slide(iterable: Iterable[Domain], *, size: int) → Iterable[Tuple[Domain, ...]][source]

Slides over iterable with window of given size.

lz.iterating.slider(size: int) → Callable[[Iterable[Domain]], Iterable[Tuple[Domain, ...]]][source]

Returns function that slides over iterable with window of given size.

>>> pairwise = slider(2)
>>> list(pairwise(range(10)))
[(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)]
lz.iterating.trail(iterable: Iterable[Domain], *, size: int) → Iterable[Domain][source]

Selects elements from the end of iterable. Resulted iterable will have size not greater than given one.

lz.iterating.trailer(size: int) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that selects elements from the end of iterable. Resulted iterable will have size not greater than given one.

>>> to_last_pair = trailer(2)
>>> list(to_last_pair(range(10)))
[8, 9]
lz.iterating.triplewise(iterable: Iterable[Domain], *, size: int = 3) → Iterable[Tuple[Domain, ...]]

Slides over iterable with window of size 3.

left module

lz.left.accumulator(function: Callable[[Range, Domain], Range], initial: Range) → Callable[[Iterable[Domain]], Iterable[Range]][source]

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]
lz.left.applier(function: Callable[[...], Range], *args: Domain, **kwargs: Domain) → Callable[[...], Range][source]

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]
lz.left.attach(iterable: Iterable[Domain], object_: Domain) → Iterable[Domain][source]

Prepends given object to the iterable.

lz.left.attacher(object_: Domain) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

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]
lz.left.folder(function: Callable[[Range, Domain], Range], initial: Range) → Callable[[Iterable[Domain]], Range][source]

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)'

logical module

lz.logical.conjoin(*predicates: Callable[[Domain], bool]) → Callable[[Domain], bool][source]

Returns conjunction of given predicates.

>>> is_valid_constant_identifier = conjoin(str.isupper, str.isidentifier)
>>> is_valid_constant_identifier('SECOND_SECTION')
True
>>> is_valid_constant_identifier('2ND_SECTION')
False
lz.logical.disjoin(*predicates: Callable[[Domain], bool]) → Callable[[Domain], bool][source]

Returns disjunction of given predicates.

>>> alphabetic_or_numeric = disjoin(str.isalpha, str.isnumeric)
>>> alphabetic_or_numeric('Hello')
True
>>> alphabetic_or_numeric('42')
True
>>> alphabetic_or_numeric('Hello42')
False
lz.logical.exclusive_disjoin(*predicates: Callable[[Domain], bool]) → Callable[[Domain], bool][source]

Returns exclusive disjunction of given predicates.

>>> from keyword import iskeyword
>>> valid_object_name = exclusive_disjoin(str.isidentifier, iskeyword)
>>> valid_object_name('valid_object_name')
True
>>> valid_object_name('_')
True
>>> valid_object_name('1')
False
>>> valid_object_name('lambda')
False
lz.logical.negate(predicate: Callable[[Domain], bool]) → Callable[[Domain], bool][source]

Returns negated version of given predicate.

>>> from lz.logical import negate
>>> false_like = negate(bool)
>>> false_like([])
True
>>> false_like([0])
False

replication module

lz.replication.duplicate(object_: Domain, *, count: int = 2) → Iterable[Domain]

Duplicates given object.

lz.replication.replicate(object_: Domain, *, count: int) → Iterable[Domain][source]

Returns given number of object replicas.

lz.replication.replicator(count: int) → Callable[[Domain], Iterable[Domain]][source]

Returns function that replicates passed object.

>>> triplicate = replicator(3)
>>> list(map(tuple, triplicate(range(5))))
[(0, 1, 2, 3, 4), (0, 1, 2, 3, 4), (0, 1, 2, 3, 4)]

reversal module

lz.reversal.reverse(object_: Domain, **_: Any) → Range[source]

Returns reversed object.

>>> list(reverse(range(10)))
[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
>>> import io
>>> list(reverse(io.BytesIO(b'Hello\nWorld!')))
[b'World!', b'Hello\n']

right module

lz.right.accumulator(function: Callable[[Domain, Range], Range], initial: Range) → Callable[[Iterable[Domain]], Iterable[Iterable[Range]]][source]

Returns function that yields cumulative results of given binary function starting from given initial object in direction from right to left.

>>> def to_next_fraction(partial_denominator: int,
...                      reciprocal: float) -> float:
...     return partial_denominator + 1 / reciprocal
>>> to_simple_continued_fractions = accumulator(to_next_fraction, 1)
>>> from itertools import repeat
>>> [round(fraction, 4)
...  for fraction in to_simple_continued_fractions(list(repeat(1, 10)))]
[1, 2.0, 1.5, 1.6667, 1.6, 1.625, 1.6154, 1.619, 1.6176, 1.6182, 1.618]
lz.right.applier(function: Callable[[...], Range], *args: Domain, **kwargs: Domain) → Callable[[...], Range][source]

Returns function that behaves like given function with given arguments partially applied. Given positional arguments will be added to the right end.

>>> square = applier(pow, 2)
>>> square(10)
100
lz.right.attach(iterable: Iterable[Domain], object_: Domain) → Iterable[Domain][source]

Appends given object to the iterable.

lz.right.attacher(object_: Domain) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that appends given object to iterable.

>>> attach_hundred = attacher(100)
>>> list(attach_hundred(range(10)))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 100]
lz.right.folder(function: Callable[[Domain, Range], Range], initial: Range) → Callable[[Iterable[Domain]], Range][source]

Returns function that cumulatively applies given binary function starting from given initial object in direction from right to left.

>>> to_sum_evaluation_order = folder('({} + {})'.format, 0)
>>> to_sum_evaluation_order(range(1, 10))
'(1 + (2 + (3 + (4 + (5 + (6 + (7 + (8 + (9 + 0)))))))))'

sorting module

lz.sorting.register_implementation(algorithm: str, implementation: Optional[Callable[[...], Iterable[Domain]]] = None, *, stable: bool = False, overwrite: bool = False) → Union[Callable[[Callable[[...], Iterable[Domain]]], Callable[[...], Iterable[Domain]]], Callable[[...], Iterable[Domain]]][source]

Registers implementation of sorting algorithm.

>>> from typing import Any
>>> @register_implementation('CUSTOMSORTING')
... def custom_sorting(iterable: Iterable[Domain],
...                    *,
...                    key: Optional[Map[Domain, Any]] = None
...                    ) -> Iterable[Domain]:
...     ...
lz.sorting.sorter(*, algorithm: str = 'TIMSORT', key: Callable[[Domain], lz.hints.Sortable] = None) → Callable[[Iterable[Domain]], Iterable[Domain]][source]

Returns function that generates sorted iterable by given key with specified algorithm.

>>> sort = sorter()
>>> sort('Hello World!')
[' ', '!', 'H', 'W', 'd', 'e', 'l', 'l', 'l', 'o', 'o', 'r']

transposition module

lz.transposition.transpose(object_: Domain) → Range[source]

Transposes given object.

>>> list(map(tuple, transpose(zip(range(10), range(10, 20)))))
[(0, 1, 2, 3, 4, 5, 6, 7, 8, 9), (10, 11, 12, 13, 14, 15, 16, 17, 18, 19)]

typology module

lz.typology.instance_of(*types: type) → Callable[[Domain], bool][source]

Creates predicate that checks if object is instance of given types.

>>> is_any_string = instance_of(str, bytes, bytearray)
>>> is_any_string(b'')
True
>>> is_any_string('')
True
>>> is_any_string(1)
False
lz.typology.subclass_of(*types: type) → Callable[[Domain], bool][source]

Creates predicate that checks if type is subclass of given types.

>>> is_metaclass = subclass_of(type)
>>> is_metaclass(type)
True
>>> is_metaclass(object)
False