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Author SHA1 Message Date
manas-1110
682f6e5aaf
Merge ea87c243c3 into fcf82a1eda 2024-10-05 23:35:47 +05:30
Vineet Kumar
fcf82a1eda
Implemented Exponential Search with binary search for improved perfor… (#11666)
* Implemented Exponential Search with binary search for improved performance on large sorted arrays.

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* Added type hints and doctests for binary_search and exponential_search functions. Improved code documentation and ensured testability.

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* Update and rename Exponential_Search.py to exponential_search.py

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2024-10-05 10:34:48 -07:00
Andrey Ivanov
ad6395d340
Update ruff usage example in CONTRIBUTING.md (#11772)
* Update ruff usage example

* Update CONTRIBUTING.md

Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>

---------

Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
2024-10-05 10:24:58 -07:00
Jeel Rupapara
50aca04c67
feat: increase test coverage of longest_common_subsequence to 75% (#11777) 2024-10-05 10:21:43 -07:00
1227haran
5a8655d306
Added new algorithm to generate numbers in lexicographical order (#11674)
* Added algorithm to generate numbers in lexicographical order

* Removed the test cases

* Updated camelcase to snakecase

* Added doctest

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* Added descriptive name for n

* Reduced the number of letters

* Updated the return type

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* Updated import statement

* Updated return type to Iterator[int]

* removed parentheses

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2024-10-05 10:19:58 -07:00
4 changed files with 170 additions and 1 deletions

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@ -96,7 +96,7 @@ We want your work to be readable by others; therefore, we encourage you to note
```bash
python3 -m pip install ruff # only required the first time
ruff .
ruff check
```
- Original code submission require docstrings or comments to describe your work.

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@ -0,0 +1,38 @@
from collections.abc import Iterator
def lexical_order(max_number: int) -> Iterator[int]:
"""
Generate numbers in lexical order from 1 to max_number.
>>> " ".join(map(str, lexical_order(13)))
'1 10 11 12 13 2 3 4 5 6 7 8 9'
>>> list(lexical_order(1))
[1]
>>> " ".join(map(str, lexical_order(20)))
'1 10 11 12 13 14 15 16 17 18 19 2 20 3 4 5 6 7 8 9'
>>> " ".join(map(str, lexical_order(25)))
'1 10 11 12 13 14 15 16 17 18 19 2 20 21 22 23 24 25 3 4 5 6 7 8 9'
>>> list(lexical_order(12))
[1, 10, 11, 12, 2, 3, 4, 5, 6, 7, 8, 9]
"""
stack = [1]
while stack:
num = stack.pop()
if num > max_number:
continue
yield num
if (num % 10) != 9:
stack.append(num + 1)
stack.append(num * 10)
if __name__ == "__main__":
from doctest import testmod
testmod()
print(f"Numbers from 1 to 25 in lexical order: {list(lexical_order(26))}")

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@ -28,6 +28,24 @@ def longest_common_subsequence(x: str, y: str):
(2, 'ph')
>>> longest_common_subsequence("computer", "food")
(1, 'o')
>>> longest_common_subsequence("", "abc") # One string is empty
(0, '')
>>> longest_common_subsequence("abc", "") # Other string is empty
(0, '')
>>> longest_common_subsequence("", "") # Both strings are empty
(0, '')
>>> longest_common_subsequence("abc", "def") # No common subsequence
(0, '')
>>> longest_common_subsequence("abc", "abc") # Identical strings
(3, 'abc')
>>> longest_common_subsequence("a", "a") # Single character match
(1, 'a')
>>> longest_common_subsequence("a", "b") # Single character no match
(0, '')
>>> longest_common_subsequence("abcdef", "ace") # Interleaved subsequence
(3, 'ace')
>>> longest_common_subsequence("ABCD", "ACBD") # No repeated characters
(3, 'ABD')
"""
# find the length of strings

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@ -0,0 +1,113 @@
#!/usr/bin/env python3
"""
Pure Python implementation of exponential search algorithm
For more information, see the Wikipedia page:
https://en.wikipedia.org/wiki/Exponential_search
For doctests run the following command:
python3 -m doctest -v exponential_search.py
For manual testing run:
python3 exponential_search.py
"""
from __future__ import annotations
def binary_search_by_recursion(
sorted_collection: list[int], item: int, left: int = 0, right: int = -1
) -> int:
"""Pure implementation of binary search algorithm in Python using recursion
Be careful: the collection must be ascending sorted otherwise, the result will be
unpredictable.
:param sorted_collection: some ascending sorted collection with comparable items
:param item: item value to search
:param left: starting index for the search
:param right: ending index for the search
:return: index of the found item or -1 if the item is not found
Examples:
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 0, 0, 4)
0
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 15, 0, 4)
4
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 5, 0, 4)
1
>>> binary_search_by_recursion([0, 5, 7, 10, 15], 6, 0, 4)
-1
"""
if right < 0:
right = len(sorted_collection) - 1
if list(sorted_collection) != sorted(sorted_collection):
raise ValueError("sorted_collection must be sorted in ascending order")
if right < left:
return -1
midpoint = left + (right - left) // 2
if sorted_collection[midpoint] == item:
return midpoint
elif sorted_collection[midpoint] > item:
return binary_search_by_recursion(sorted_collection, item, left, midpoint - 1)
else:
return binary_search_by_recursion(sorted_collection, item, midpoint + 1, right)
def exponential_search(sorted_collection: list[int], item: int) -> int:
"""
Pure implementation of an exponential search algorithm in Python.
For more information, refer to:
https://en.wikipedia.org/wiki/Exponential_search
Be careful: the collection must be ascending sorted, otherwise the result will be
unpredictable.
:param sorted_collection: some ascending sorted collection with comparable items
:param item: item value to search
:return: index of the found item or -1 if the item is not found
The time complexity of this algorithm is O(log i) where i is the index of the item.
Examples:
>>> exponential_search([0, 5, 7, 10, 15], 0)
0
>>> exponential_search([0, 5, 7, 10, 15], 15)
4
>>> exponential_search([0, 5, 7, 10, 15], 5)
1
>>> exponential_search([0, 5, 7, 10, 15], 6)
-1
"""
if list(sorted_collection) != sorted(sorted_collection):
raise ValueError("sorted_collection must be sorted in ascending order")
if sorted_collection[0] == item:
return 0
bound = 1
while bound < len(sorted_collection) and sorted_collection[bound] < item:
bound *= 2
left = bound // 2
right = min(bound, len(sorted_collection) - 1)
return binary_search_by_recursion(sorted_collection, item, left, right)
if __name__ == "__main__":
import doctest
doctest.testmod()
# Manual testing
user_input = input("Enter numbers separated by commas: ").strip()
collection = sorted(int(item) for item in user_input.split(","))
target = int(input("Enter a number to search for: "))
result = exponential_search(sorted_collection=collection, item=target)
if result == -1:
print(f"{target} was not found in {collection}.")
else:
print(f"{target} was found at index {result} in {collection}.")