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scph5500.bin 26-Aug-2018 20:47 512.0K

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GROKKING NOTES

I liked the way Grokking the coding interview organized problems into learnable patterns. However, the course is expensive and the majority of the time the problems are copy-pasted from leetcode. As the explanations on leetcode are usually just as good, the course really boils down to being a glorified curated list of leetcode problems.

So below I made a list of leetcode problems that are as close to grokking problems as possible.

Pattern: Sliding Window

I have spent quite a bit of time figuring out automounts of NFS shares in OS X...

Somewhere along the line, Apple decided allowing mounts directly into /Volumes should not be possible:

/etc/auto_master (see last line):

#
# Automounter master map
#

+auto_master # Use directory service

	// ranker is a helper type for the rank function.
	type ranker struct {
	f []float64 // Data to be ranked.
	r []int // A list of indexes into f that reflects rank order after sorting.
	}

	// ranker satisfies the sort.Interface without mutating the reference slice, f.
	func (r ranker) Len() int { return len(r.f) }
	func (r ranker) Less(i, j int) bool { return r.f[r.r[i]] < r.f[r.r[j]] }
	func (r ranker) Swap(i, j int) { r.r[i], r.r[j] = r.r[j], r.r[i] }

	import Foundation
	import HealthKit

	struct WorkoutSplit: Hashable {
	let label: String
	let distance: HKQuantity
	let duration: TimeInterval
	}

	extension WorkoutSplit {

	import heapq
	from typing import List


	def djikstra(graph_inner, starting, vertices) -> List:
	pq = []
	dist = [float('inf') for i in range(vertices)]
	dist[starting] = 0
	print(dist)
	heapq.heappush(pq, [0, starting])

	def is_safe(graph, colours, colour, current):
	neighbours = graph[current]
	for neighbour in neighbours:
	if colour == colours[neighbour - 1]:
	return False
	return True

	def graph_traversal(graph, colours, vertices, current):
	if current == vertices + 1:
	return True

	class Node:
	def __init__(self, data: list, level, f_val):
	self.data = data
	self.level = level
	self.f_val = f_val

	def generate_children(self):
	children = []
	values = [[0, 1], [1, 0], [-1, 0], [0, -1]]
	row, col = self.find()

	###################
	# compiled source #
	###################
	*.com
	*.class
	*.dll
	*.exe
	*.pdb
	*.dll.config
	*.cache