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Merge pull request donnemartin#153 from donnemartin/develop
Add 64 new challenges
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‎README.md

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‎anki_cards/Coding.apkg

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‎arrays_strings/priority_queue/__init__.py

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‎arrays_strings/priority_queue/priority_queue.py

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import sys
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class PriorityQueueNode(object):
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def __init__(self, obj, key):
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self.obj = obj
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self.key = key
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def __repr__(self):
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return str(self.obj) + ': ' + str(self.key)
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class PriorityQueue(object):
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def __init__(self):
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self.array = []
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def __len__(self):
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return len(self.array)
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def insert(self, node):
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self.array.append(node)
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return self.array[-1]
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def extract_min(self):
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if not self.array:
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return None
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minimum = sys.maxsize
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for index, node in enumerate(self.array):
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if node.key < minimum:
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minimum = node.key
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minimum_index = index
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return self.array.pop(minimum_index)
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def decrease_key(self, obj, new_key):
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for node in self.array:
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if node.obj is obj:
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node.key = new_key
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return node
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return None

‎arrays_strings/priority_queue/priority_queue_challenge.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Challenge Notebook"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Problem: Implement a priority queue backed by an array.\n",
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"\n",
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"* [Constraints](#Constraints)\n",
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"* [Test Cases](#Test-Cases)\n",
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"* [Algorithm](#Algorithm)\n",
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"* [Code](#Code)\n",
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"* [Unit Test](#Unit-Test)\n",
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"* [Solution Notebook](#Solution-Notebook)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Constraints\n",
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"\n",
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"* Do we expect the methods to be insert, extract_min, and decrease_key?\n",
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" * Yes\n",
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"* Can we assume there aren't any duplicate keys?\n",
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" * Yes\n",
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"* Do we need to validate inputs?\n",
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" * No\n",
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"* Can we assume this fits memory?\n",
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" * Yes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Test Cases\n",
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"\n",
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"### insert\n",
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"\n",
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"* `insert` general case -> inserted node\n",
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"\n",
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"### extract_min\n",
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"\n",
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"* `extract_min` from an empty list -> None\n",
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"* `extract_min` general case -> min node\n",
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"\n",
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"### decrease_key\n",
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"\n",
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"* `decrease_key` an invalid key -> None\n",
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"* `decrease_key` general case -> updated node"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Algorithm\n",
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"\n",
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"Refer to the [Solution Notebook](https://github.com/donnemartin/interactive-coding-challenges/arrays_strings/priority_queue/priority_queue_solution.ipynb). If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Code"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"class PriorityQueueNode(object):\n",
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"\n",
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" def __init__(self, obj, key):\n",
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" self.obj = obj\n",
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" self.key = key\n",
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"\n",
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" def __repr__(self):\n",
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" return str(self.obj) + ': ' + str(self.key)\n",
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"\n",
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"\n",
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"class PriorityQueue(object):\n",
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"\n",
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" def __init__(self):\n",
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" self.array = []\n",
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"\n",
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" def __len__(self):\n",
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" return len(self.array)\n",
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"\n",
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" def insert(self, node):\n",
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" # TODO: Implement me\n",
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" pass\n",
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"\n",
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" def extract_min(self):\n",
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" # TODO: Implement me\n",
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" pass\n",
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"\n",
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" def decrease_key(self, obj, new_key):\n",
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" # TODO: Implement me\n",
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" pass"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Unit Test"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**The following unit test is expected to fail until you solve the challenge.**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# %load test_priority_queue.py\n",
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"from nose.tools import assert_equal\n",
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"\n",
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"\n",
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"class TestPriorityQueue(object):\n",
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"\n",
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" def test_priority_queue(self):\n",
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" priority_queue = PriorityQueue()\n",
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" assert_equal(priority_queue.extract_min(), None)\n",
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" priority_queue.insert(PriorityQueueNode('a', 20))\n",
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" priority_queue.insert(PriorityQueueNode('b', 5))\n",
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" priority_queue.insert(PriorityQueueNode('c', 15))\n",
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" priority_queue.insert(PriorityQueueNode('d', 22))\n",
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" priority_queue.insert(PriorityQueueNode('e', 40))\n",
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" priority_queue.insert(PriorityQueueNode('f', 3))\n",
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" priority_queue.decrease_key('f', 2)\n",
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" priority_queue.decrease_key('a', 19)\n",
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" mins = []\n",
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" while priority_queue.array:\n",
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" mins.append(priority_queue.extract_min().key)\n",
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" assert_equal(mins, [2, 5, 15, 19, 22, 40])\n",
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" print('Success: test_min_heap')\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestPriorityQueue()\n",
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" test.test_priority_queue()\n",
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"\n",
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"\n",
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"if __name__ == '__main__':\n",
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" main()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Solution Notebook\n",
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"\n",
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"Review the [Solution Notebook](https://github.com/donnemartin/interactive-coding-challenges/arrays_strings/priority_queue/priority_queue_solution.ipynb) for a discussion on algorithms and code solutions."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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