| #include <iostream> | |
| #include <optional> | |
| #include <cassert> | |
| /* | |
| * Fast exponentiation using iterative binary exponentiation. | |
| * This efficiently computes (base ^ exponent) % modulo (if provided) in O(log exponent) time. | |
| * When modulo is provided, intermediate values stay small and avoid overflow. | |
| * Without modulo, results can quickly exceed the storage limits of the int type. | |
| INT_MAX is typically 2,147,483,647 for 32-bit int. |
This document introduces a modular and extensible fee estimation system for Bitcoin Core. The design is centered around a fee rate forecasting manager that integrates multiple fee rate forecasting strategies and performs mempool health checks to determine the most appropriate strategy for providing fee rate forecast. This approach facilitates the additions of new strategies while ensuring smooth integration with existing systems.
The system is organized into two primary components:
| #User function Template for python3 | |
| import math | |
| class Solution: | |
| def solveQueries(self, nums, Queries, k): | |
| originalLocation = Solution.saveQueryLocation(Queries) | |
| Queries = Solution.sortQ(Queries,len(nums),nums) | |
| function findMovingMovingMedian(arr){ | |
| //check edge cases | |
| let median = '' | |
| if(arr.length==0){ | |
| return median | |
| } | |
| if(arr.length ==1){ | |
| return arr[0] | |
| } |
| function generateId(startIn?: number){ | |
| startIn? null: startIn = 1 | |
| if(startIn>1000000){ | |
| return false; | |
| } | |
| let randomId:number = 100000+Math.floor(Math.random() * 9000000); | |
| if(startIn>0){ |
| class Node { | |
| constructor(element) { | |
| this.element = element; | |
| this.next = null; | |
| } | |
| } | |
| class LinkedList { | |
| constructor() { | |
| this.head = null, | |
| this.size = 0 |