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Added pairwise iteration algorithms (#9645)
* Adds pairwise iteration algorithm * Fixed code typo * updating DIRECTORY.md * updating DIRECTORY.md * updating DIRECTORY.md * Improve documentation for pairwise_iteration_tee Updated documentation to clarify the use of pairwise iteration and added a reference to the itertools.pairwise function. * Correct import and update pairwise test cases Fix import statement for pairwise in pairwise_iteration_tee function and update test cases. * Fix indentation in pairwise_iteration.py docstring * Enhance docstring for pairwise iteration Added docstring explaining the use of itertools.tee for independent iterators. --------- Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: cclauss <cclauss@users.noreply.github.com>
This commit is contained in:
Matheus Farinaro Vesco
co-authored by
Christian Clauss
cclauss
Christian Clauss
cclauss
parent
a10a1ce2cd
commit
7cc80db1f6
@@ -210,6 +210,7 @@
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## [Conversions](conversions)
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* [Astronomical Length Scale Conversion](conversions/astronomical_length_scale_conversion.py)
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* [Base64 To Binary](conversions/base64_to_binary.py)
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* [Binary To Base64](conversions/binary_to_base64.py)
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* [Binary To Decimal](conversions/binary_to_decimal.py)
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* [Binary To Excess3](conversions/binary_to_excess3.py)
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* [Binary To Gray](conversions/binary_to_gray.py)
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@@ -268,6 +269,7 @@
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* [Median Two Array](data_structures/arrays/median_two_array.py)
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* [Monotonic Array](data_structures/arrays/monotonic_array.py)
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* [Pairs With Given Sum](data_structures/arrays/pairs_with_given_sum.py)
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* [Pairwise Iteration](data_structures/arrays/pairwise_iteration.py)
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* [Permutations](data_structures/arrays/permutations.py)
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* [Prefix Sum](data_structures/arrays/prefix_sum.py)
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* [Product Sum](data_structures/arrays/product_sum.py)
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@@ -663,6 +665,7 @@
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* [Minimum Coin Change](greedy_methods/minimum_coin_change.py)
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* [Minimum Waiting Time](greedy_methods/minimum_waiting_time.py)
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* [Optimal Merge Pattern](greedy_methods/optimal_merge_pattern.py)
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* [Sliding Window](greedy_methods/sliding_window.py)
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* [Smallest Range](greedy_methods/smallest_range.py)
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## [Hashes](hashes)
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@@ -0,0 +1,145 @@
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"""
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Author : Matheus F. Vesco
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Date : October 3, 2023
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Implementation of pairwise iteration algorithms, which can be useful in
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many domains.
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Currently, there are two different implementations.
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"""
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from collections.abc import Iterable, Iterator
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from itertools import tee
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def pairwise_iteration_tee(iterable: Iterable) -> Iterator[tuple]:
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"""
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Generate pairs of elements from an iterable just like:
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https://docs.python.org/3/library/itertools.html#itertools.pairwise
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This function uses the `tee` function from the `itertools` module to
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create two independent iterators (`a` and `b`) from the input
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iterable. The `next` function is used to offset the `b` iterator by
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one index, and then the two iterators are zipped together to create
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pairs of elements. This implementation should work with any iterable
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in Python.
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Args:
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iterable (Iterable): The input iterable.
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Yields:
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Iterator[Tuple]: An iterator that yields pairs of objects.
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Examples:
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>>> list(pairwise_iteration_tee([1, 2, 3]))
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[(1, 2), (2, 3)]
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>>> list(pairwise_iteration_tee((4, 3, 5)))
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[(4, 3), (3, 5)]
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>>> list(pairwise_iteration_tee({'x':3, 'y':1, 'z':2, 'foo':4}))
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[('x', 'y'), ('y', 'z'), ('z', 'foo')]
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>>> list(pairwise_iteration_tee('2345'))
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[('2', '3'), ('3', '4'), ('4', '5')]
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>>> list(pairwise_iteration_tee(['ATG','GCT','TGC','TAA']))
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[('ATG', 'GCT'), ('GCT', 'TGC'), ('TGC', 'TAA')]
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>>> list(pairwise_iteration_tee(['a']))
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[]
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>>> from itertools import pairwise
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>>> all(list(pairwise_iteration_tee(test)) == list(pairwise(test))
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... for test in (
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... [1, 2, 3],
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... (4, 3, 5),
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... {'x':3, 'y':1, 'z':2, 'foo':4},
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... '2345',
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... ['ATG','GCT','TGC','TAA'],
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... [],
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... ))
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True
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"""
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# Uses itertools.tee to create two independent iterators (a and b)
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# from the iterable. This means we can use next() on each one
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# without affecting the other, no matter the iterable type
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a, b = tee(iterable)
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# Offsets the second iterator (b) by one step to create a staggered
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# alignment.
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# this means that (a[i],b[i]) represents the same as (a[i],a[i+1])
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next(b, None)
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# Returns a zip generator that pairs items from the two iterators in
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# the format (a[i], a[i+1]).
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return zip(a, b)
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def pairwise_iteration_comprehension(
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iterable: Iterable, step: int = 1
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) -> Iterator[tuple]:
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"""
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Generate pairs of elements from an iterable with a given step size.
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This function uses list comprehensions to get the items that are step
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distance from each other and later the `iter()` conversion to create
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two independent list iterators (`a` and `b`) from the input iterable.
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The `next` function is used to offset the `b` iterator by one index,
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and then the two iterators are zipped together to create pairs of
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elements.
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Args:
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iterable (Iterable): The input iterable.
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step (int, optional): The step size for iterating through the
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input iterable. Defaults to 1.
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Yields:
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Iterator[Tuple]: An iterator that yields pairs of objects.
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Examples:
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>>> list(pairwise_iteration_comprehension([0, 1, 2, 3, 4, 5, 6], step=2))
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[(0, 2), (2, 4), (4, 6)]
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>>> list(pairwise_iteration_comprehension([0, 1, 2, 3, 4, 5, 6], step=3))
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[(0, 3), (3, 6)]
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>>> list(pairwise_iteration_comprehension((0, 1, 2, 3, 4), step=2))
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[(0, 2), (2, 4)]
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>>> python_set = pairwise_iteration_comprehension(
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... {4, 3, 2, 1, 0}, step=2)
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>>> list(python_set) # sets are unordered
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[(0, 2), (2, 4)]
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>>> dictionary = pairwise_iteration_comprehension(
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... {'x1':4, 'y1':5, 'x2':1, 'y2':'a', 'spam':7}, step=2)
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>>> list(dictionary)
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[('x1', 'x2'), ('x2', 'spam')]
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>>> list(pairwise_iteration_comprehension({0, 1, 2, 3, 4, 5, 6}, step=3))
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[(0, 3), (3, 6)]
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>>> list(pairwise_iteration_comprehension(['ATG','GCT','TGC','TAA']))
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[('ATG', 'GCT'), ('GCT', 'TGC'), ('TGC', 'TAA')]
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>>> list(pairwise_iteration_comprehension(['a'], step=1))
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[]
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"""
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# creates a list, using list comprehensions, that only stores items
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# that are n steps apart from each other.
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items = [item for i, item in enumerate(iterable) if i % step == 0]
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# creates two independent list iterators (a and b) from the list
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# we created earlier, using the iter() function. This means we can
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# use next() on each one without affecting the other, no matter the
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# iterable type
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a, b = (iter(items), iter(items))
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# Offsets the second iterator (b) by one step to create a staggered
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# alignment.
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# this means that (a[i],b[i]) represents the same as (a[i],a[i+1])
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next(b, None)
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# Returns a zip generator that pairs items from the two iterators in
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# the format (a[i], a[i+1]).
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return zip(a, b)
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