feat(algorithms, intervals): interval list intersections

DIRECTORY.md

@@ -95,6 +95,8 @@
   * Intervals
     * Insert Interval
       * [Test Insert Interval](https://github.com/BrianLusina/PythonSnips/blob/master/algorithms/intervals/insert_interval/test_insert_interval.py)
+    * Interval Intersection
+      * [Test Intervals Intersection](https://github.com/BrianLusina/PythonSnips/blob/master/algorithms/intervals/interval_intersection/test_intervals_intersection.py)
     * Meeting Rooms
       * [Test Min Meeting Rooms](https://github.com/BrianLusina/PythonSnips/blob/master/algorithms/intervals/meeting_rooms/test_min_meeting_rooms.py)
     * Merge Intervals

algorithms/intervals/interval_intersection/README.md

@@ -0,0 +1,118 @@
+# Interval List Intersections
+
+Given two lists of closed intervals, interval_list_a and interval_list_b, return the intersection of the two interval 
+lists.
+
+> A closed interval [start, end] (with start <= end) includes all real numbers x such that start <= x <= end.
+
+Each interval in the lists has its own start and end time and is represented as [start, end]. Specifically:
+
+- interval_list_a[i] = [starti, endi]
+- interval_list_b[j] = [startj, endj]
+
+The intersection of two closed intervals i and j is either:
+- An empty set, if they do not overlap, or
+- A closed interval [max(starti, startj), min(endi, endj)] if they do overlap.
+
+Also, each list of intervals is pairwise disjoint(intervals within a list don't overlap) and in sorted order.
+
+## Constraints
+
+- 0 <= `interval_list_a.length`, `interval_list_b.length` <= 1000
+- `interval_list_a.length` + `interval_list_b.length` >= 1
+- 0 <= `starti`  < `endi` <= 10^9
+- `endi`  < `start(i+1)`
+- 0 <= `startj`  < `endj` <= 10^9
+- `endj`  < `start(j+1)`
+
+## Examples
+
+![Example 1](./images/examples/interval_intersection_example_1.png)
+![Example 2](./images/examples/interval_intersection_example_2.png)
+![Example 3](./images/examples/interval_intersection_example_3.png)
+![Example 4](./images/examples/interval_intersection_example_4.png)
+![Example 5](./images/examples/interval_intersection_example_5.png)
+
+## Topics
+
+- Two pointers
+- Intervals
+
+## Solutions
+
+1. [Naive Approach](#naive-approach)
+1. [Using Intervals](#optimized-approach-using-intervals)
+
+### Naive Approach
+
+The naive approach for this problem is to use a nested loop for finding intersecting intervals.
+
+The outer loop will iterate for every interval in interval_list_a and the inner loop will search for any intersecting 
+interval in the interval_list_b.
+
+If such an interval exists, we add it to the intersections list.
+
+Since we are using nested loops, the time complexity for this naive approach will be O(n*m), where n is the length of 
+intervalsA and m is the length of intervalsB.
+
+### Optimized approach using intervals
+
+The essence of this approach is to leverage two key advantages: first, the lists of intervals are sorted, and second, 
+the result requires comparing intervals to check for overlap. The algorithm works by iterating through both sorted lists
+of intervals simultaneously, identifying intersections between intervals from the two lists. At each step, it compares 
+the current intervals from both lists and determines whether there is an intersection by examining the endpoints of the 
+intervals. It adds the intersecting interval to the result list if an intersection exists. To efficiently navigate 
+through the intervals, the algorithm adjusts pointers based on the positions of the intervals’ endpoints, ensuring that 
+it covers all possible intersections. The algorithm accurately computes the interval list intersection by systematically
+traversing the lists, identifying intersections, and adding them to the results list, the algorithm accurately computes 
+the interval list intersection.
+
+The algorithm to solve this problem is as follows:
+
+- We’ll use two indexes, i and j, to iterate through the intervals in both lists, `interval_list_a` and `interval_list_b`, 
+  respectively.
+- To check whether there’s any intersecting point among the given intervals:
+  - Take the starting times of the first pair of intervals from both lists and check which occurs later, storing it in 
+    a variable, say start. 
+  - Also, compare the ending times of the same pair of intervals from both lists and store the minimum end time in 
+    another variable, say, end.
+
+![Solution 1](./images/solutions/interval_intersection_solution_1.png)
+![Solution 2](./images/solutions/interval_intersection_solution_2.png)
+
+- Next, we will check if `interval_list_a[i]` and `interval_list_b[j]` overlap by comparing the start and end times.
+  - If the times overlap, then the intersecting time interval will be added to the resultant list, that is, intersections. 
+  - After the comparison, we need to move forward in one of the two input lists. The decision is taken based on which 
+    of the two intervals being compared ends earlier. If the interval that ends first is in `interval_list_a`, we move 
+    forward in that list, else, we move forward in `interval_list_b`.
+
+The illustrations below show the key steps of the solution.
+
+![Solution 3](./images/solutions/interval_intersection_solution_3.png)
+![Solution 4](./images/solutions/interval_intersection_solution_4.png)
+![Solution 5](./images/solutions/interval_intersection_solution_5.png)
+![Solution 6](./images/solutions/interval_intersection_solution_6.png)
+![Solution 7](./images/solutions/interval_intersection_solution_7.png)
+![Solution 8](./images/solutions/interval_intersection_solution_8.png)
+
+#### Solution summary
+
+Let’s briefly discuss the approach that we have used to solve the above mentioned problem:
+
+- Set two pointers, i and j, at the beginning of both lists, respectively, for their iteration. 
+- While iterating, find the latest starting time and the earliest ending time for each pair of intervals 
+  `interval_list_a[i]` and `interval_list_b[j]`.
+- If the latest starting time is less than or equal to the earliest ending time, store it as an intersection.
+- Increment the pointer (i or j) of the list having the smaller end time of the current interval. 
+- Keep iterating until either list is fully traversed. 
+- Return the list of intersections.
+
+#### Time Complexity
+
+The time complexity is `O(n+m)`, where n and m are the number of meetings in `interval_list_a` and `interval_list_b`, 
+respectively.
+
+#### Space Complexity
+
+The space complexity is `O(1)` as only a fixed amount of memory is consumed by a few temporary variables for computations 
+performed by the algorithm.

algorithms/intervals/interval_intersection/__init__.py

@@ -0,0 +1,60 @@
+from typing import List
+
+
+def intervals_intersection(
+    interval_list_a: List[List[int]], interval_list_b: List[List[int]]
+) -> List[List[int]]:
+    """
+    This function finds the intersections between interval_list_a and interval_list_b and returns the list of
+    intersections.
+
+    Time Complexity is O(n+m): where n is the length of list a and m is the length of list b
+    Space Complexity is O(1) for auxiliary space as no extra space is required other than the pointers used to move along
+    both lists. However, the resultant list returned can have a worst case of O(n+m) in the case we have either list
+    having multiple intervals that are all intersections in the other list.
+
+    Args:
+        interval_list_a(list): list 'a' of intervals.
+        interval_list_b(list): list 'b' of intervals.
+    Returns:
+        list: list of intersected intervals
+    """
+    if not interval_list_a and not interval_list_b:
+        return []
+    # pointers that will move along the interval lists, i moves along the intervals on interval_list_a, while j moves
+    # along the intervals on interval_list_b
+    i, j = 0, 0
+
+    # the final result list
+    intersected_intervals = []
+
+    interval_list_a_len = len(interval_list_a)
+    interval_list_b_len = len(interval_list_b)
+
+    # while loop will break whenever either of the lists ends
+    while i < interval_list_a_len and j < interval_list_b_len:
+        # Let's check if interval_list_a[i] intersects interval_list_b[j]
+        interval_a = interval_list_a[i]
+        interval_b = interval_list_b[j]
+
+        # extract the start and end times of each interval
+        start_a, end_a = interval_a
+        start_b, end_b = interval_b
+
+        # Get the potential startpoint and endpoint of the closed interval intersection
+        closed_interval_start = max(start_a, start_b)
+        closed_interval_end = min(end_a, end_b)
+
+        # if this is an actual intersection
+        if closed_interval_start <= closed_interval_end:
+            # add it to the list
+            closed_interval = [closed_interval_start, closed_interval_end]
+            intersected_intervals.append(closed_interval)
+
+        # Move forward in the list whose interval ends earlier
+        if end_a <= end_b:
+            i += 1
+        else:
+            j += 1
+
+    return intersected_intervals

algorithms/intervals/interval_intersection/test_intervals_intersection.py

@@ -0,0 +1,61 @@
+import unittest
+from typing import List
+from parameterized import parameterized
+from algorithms.intervals.interval_intersection import intervals_intersection
+
+test_cases = [
+    (
+        [[1, 4], [5, 6], [7, 8], [9, 15]],
+        [[2, 4], [5, 7], [9, 15]],
+        [[2, 4], [5, 6], [7, 7], [9, 15]],
+    ),
+    (
+        [[1, 3], [4, 6], [8, 10], [11, 15]],
+        [[2, 3], [10, 15]],
+        [[2, 3], [10, 10], [11, 15]],
+    ),
+    (
+        [[1, 2], [4, 6], [7, 8], [9, 10]],
+        [[3, 6], [7, 8], [9, 10]],
+        [[4, 6], [7, 8], [9, 10]],
+    ),
+    (
+        [[1, 3], [5, 6], [7, 8], [9, 10], [12, 15]],
+        [[2, 4], [7, 10]],
+        [[2, 3], [7, 8], [9, 10]],
+    ),
+    ([[1, 2]], [[1, 2]], [[1, 2]]),
+    ([[3, 9], [20, 31]], [[1, 8], [10, 20], [25, 37]], [[3, 8], [20, 20], [25, 31]]),
+    ([[5, 12], [16, 25], [28, 36]], [[0, 40]], [[5, 12], [16, 25], [28, 36]]),
+    (
+        [[2, 9], [18, 29], [38, 48]],
+        [[4, 14], [20, 26], [34, 44]],
+        [[4, 9], [20, 26], [38, 44]],
+    ),
+    (
+        [[5, 13], [25, 36]],
+        [[13, 25], [40, 50]],
+        [[13, 13], [25, 25]],
+    ),
+    (
+        [[1, 12], [29, 38]],
+        [[16, 27], [40, 48]],
+        [],
+    ),
+]
+
+
+class IntervalsIntersectionTestCases(unittest.TestCase):
+    @parameterized.expand(test_cases)
+    def test_intervals_intersection(
+        self,
+        interval_list_a: List[List[int]],
+        interval_list_b: List[List[int]],
+        expected: List[List[int]],
+    ):
+        actual = intervals_intersection(interval_list_a, interval_list_b)
+        self.assertEqual(expected, actual)
+
+
+if __name__ == "__main__":
+    unittest.main()

datastructures/trees/trie/alphabet_trie/alphabet_trie.py

@@ -6,7 +6,7 @@ def __init__(self):
         self.root = AlphabetTrieNode()
 
     def insert(self, word: str) -> None:
-        if not word or not all('a' <= char.lower() <= 'z' for char in word):
+        if not word or not all("a" <= char.lower() <= "z" for char in word):
             raise ValueError("Word must contain only English letters (a-z)")
         node = self.root
         for char in word: