Stepping Cycle Generator Generator Performance Generators are a great way to optimize memory. An infinite sequence generator is an extreme example of this optimization.
Yield The yield statement suspends a function’s execution and sends a value back to the caller, but retains enough state to enable the function to resume where it left off.
When the function resumes, it continues execution immediately after the last yield run.
This allows its code to produce a series of values over time, rather than computing them at once and sending them back like a list in which we optimized memory usage.
Column does not exist. The column with the most similar name is … When I tried to Patch() a collection to SharePoint, It kept showing
Column does not exist. The column with the most similar name is …
in which the collection is collected by Defaults(someSharePoint). And I never add or delete any column in the collection. So this error seems nonsense to me. Though, when I check the collection, the extra column does appear somehow.
Question Given the head of a linked list, return the list after sorting it in ascending order.
Example 1:
Input: head = [4,2,1,3]
Output: [1,2,3,4]
Example 2:
Input: head = [-1,5,3,4,0]
Output: [-1,0,3,4,5]
Example 3:
Input: head = []
Output: []
Constraints:
The number of nodes in the list is in the range [0, 5 * 104]. -105 <= Node.val <= 105 Follow up: Can you sort the linked list in O(n logn) time and O(1) memory (i.
Task Scheduler - LeetCode
Intuition Task Scheduler Greedy My first instinct was Greedy but fell in local optimum quite easy.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 from collections import defaultdict class Solution: def leastInterval(self, tasks, n: int) -> int: if n == 0: return len(tasks) cd_chrs = defaultdict(int) output = 0 i = 0 while tasks: # when reach the end if i == len(tasks): i = 0 output += 1 # add 'idle' for k in cd_chrs.
