Merge pull request #698 from rivkode/main

[JonghunLee] Week 1

Author: SamTheKorean

contains-duplicate/rivkode.py

@@ -0,0 +1,27 @@
+
+# Time complexity: O(n)
+# The process of traversing a list to generate a set is proportional to the length of the input list.
+# Space complexity: O(n)
+# The size of the set for storing deduplicated elements is proportional to the length of the input list.
+
+class Solution:
+    def containsDuplicate(self, nums: list[int]) -> bool:
+        list_len = len(nums)
+        set_len = len(set(nums))
+
+        return list_len != set_len
+
+if __name__ == "__main__":
+    solution = Solution()
+
+    # test case
+    test_string = [
+        [1,2,3,1],  # True
+        [1,2,3,4], # False
+        [1,1,1,3,3,4,3,2,4,2],  # True
+    ]
+
+    for index, test in enumerate(test_string):
+        print(f"start {index} test")
+        print(f"input : {test}")
+        print(f"Is valid palindrome ? {solution.containsDuplicate(test)}\n")

top-k-frequent-elements/rivkode.py

@@ -0,0 +1,40 @@
+from typing import List
+
+# Time Complexity O(n log n)
+# - traversing for loop takes O(n) to create hash dictionary,
+# - and when sorting by sorted function(TimSort) it takes O(nlogn)
+# Space Complexity O(n log n)
+# - creating hash dictionary takes O(n)
+# - and when sorting takes O(n), hash[x] occupy O(1)
+
+class Solution:
+    def topKFrequent(self, nums: List[int], k: int) -> List[int]:
+        hash = dict()
+
+        # for loop nums to set count for each element in hash(dictionary)
+        for num in nums:
+            if num in hash:
+                hash[num] += 1
+            else:
+                hash[num] = 1
+
+        # sort (TimSort), using lambda function to set a sorting key which is a count
+        return sorted(hash, key=lambda x: hash[x], reverse=True)[:k]
+
+if __name__ == "__main__":
+    solution = Solution()
+
+    # test case
+    nums_list = [
+        [1,1,1,2,2,3], # [1, 2]
+        [1] # [1]
+    ]
+    k_list = [2, 1]
+
+    for i in range(2):
+        nums = nums_list[i]
+        k = k_list[i]
+        result = solution.topKFrequent(nums, k)
+        print(f"start{i}")
+        print(f"input : {nums}, {k}")
+        print(f"result : {result}")

valid-palindrome/rivkode.py

@@ -0,0 +1,48 @@
+import re
+
+
+# Time Complexity O(n)
+# - Both normal preprocessing and two-pointer comparisons have time complexity proportional to the length of the input string.
+# Space Complexity O(n)
+# - The space of the new string joined_string preprocessed from the input string is proportional to the length of the input string.
+
+class Solution:
+    def isPalindrome(self, s: str) -> bool:
+        # Pre-processing using regular expression
+        joined_string = re.sub(r"[^a-zA-Z]", "", s.lower())
+        str_length = len(joined_string)
+
+
+        # for loop n/2, two pointer for verify same or not
+        for i in range(str_length // 2):
+            end = str_length - i - 1
+            if not self.check_palindrome(i, end, joined_string):
+                return False
+
+        return True
+
+    def check_palindrome(self, i, end, joined_string) -> bool:
+        left = joined_string[i]
+        right = joined_string[end]
+
+        if left == right:
+            return True
+        else:
+            return False
+
+if __name__ == "__main__":
+    solution = Solution()
+
+    # test case
+    test_string = [
+        "A man, a plan, a canal: Panama",  # True (회문)
+        "race a car",  # False (회문 아님)
+        " ",  # True (빈 문자열도 회문으로 간주)
+        "abba",  # True (회문)
+        "abcba",  # True (회문)
+    ]
+
+    for index, test in enumerate(test_string):
+        print(f"start {index} test")
+        print(f"input : {test}")
+        print(f"Is valid palindrome ? {solution.isPalindrome(test)}\n")