mirror of
https://github.com/donnemartin/interactive-coding-challenges
synced 2026-01-02 23:48:02 +00:00
200 lines
5.1 KiB
Python
200 lines
5.1 KiB
Python
{
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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](http://donnemartin.com). 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 queue using two stacks.\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 enqueue and dequeue?\n",
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" * Yes\n",
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"* Can we assume we already have a stack class that can be used for this problem?\n",
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" * Yes\n",
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"* Can we push a None value to the Stack?\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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"* Enqueue and dequeue on empty stack\n",
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"* Enqueue and dequeue on non-empty stack\n",
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"* Multiple enqueue in a row\n",
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"* Multiple dequeue in a row\n",
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"* Enqueue after a dequeue\n",
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"* Dequeue after an enqueue"
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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](http://nbviewer.ipython.org/github/donnemartin/interactive-coding-challenges/blob/master/stacks_queues/queue_from_stacks/queue_from_stacks_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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"outputs": [],
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"source": [
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"%run ../stack/stack.py\n",
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"%load ../stack/stack.py"
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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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"outputs": [],
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"source": [
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"class QueueFromStacks(object):\n",
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"\n",
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" def __init__(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 shift_stacks(self, source, destination):\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 enqueue(self, data):\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 dequeue(self):\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\n",
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"\n"
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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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"outputs": [],
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"source": [
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"# %load test_queue_from_stacks.py\n",
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"import unittest\n",
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"\n",
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"\n",
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"class TestQueueFromStacks(unittest.TestCase):\n",
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"\n",
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" def test_queue_from_stacks(self):\n",
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" print('Test: Dequeue on empty stack')\n",
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" queue = QueueFromStacks()\n",
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" self.assertEqual(queue.dequeue(), None)\n",
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"\n",
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" print('Test: Enqueue on empty stack')\n",
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" print('Test: Enqueue on non-empty stack')\n",
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" print('Test: Multiple enqueue in a row')\n",
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" num_items = 3\n",
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" for i in range(0, num_items):\n",
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" queue.enqueue(i)\n",
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"\n",
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" print('Test: Dequeue on non-empty stack')\n",
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" print('Test: Dequeue after an enqueue')\n",
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" self.assertEqual(queue.dequeue(), 0)\n",
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"\n",
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" print('Test: Multiple dequeue in a row')\n",
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" self.assertEqual(queue.dequeue(), 1)\n",
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" self.assertEqual(queue.dequeue(), 2)\n",
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"\n",
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" print('Test: Enqueue after a dequeue')\n",
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" queue.enqueue(5)\n",
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" self.assertEqual(queue.dequeue(), 5)\n",
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"\n",
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" print('Success: test_queue_from_stacks')\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestQueueFromStacks()\n",
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" test.test_queue_from_stacks()\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](http://nbviewer.ipython.org/github/donnemartin/interactive-coding-challenges/blob/master/stacks_queues/queue_from_stacks/queue_from_stacks_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": "3.7.2"
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}
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"nbformat": 4,
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"nbformat_minor": 1
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}
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