{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "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)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Challenge Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Given a list of stock prices on each consecutive day, determine the max profits with k transactions.\n", "\n", "* [Constraints](#Constraints)\n", "* [Test Cases](#Test-Cases)\n", "* [Algorithm](#Algorithm)\n", "* [Code](#Code)\n", "* [Unit Test](#Unit-Test)\n", "* [Solution Notebook](#Solution-Notebook)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constraints\n", "\n", "* Is k the number of sell transactions?\n", " * Yes\n", "* Can we assume the prices input is an array of ints?\n", " * Yes\n", "* Can we assume the inputs are valid?\n", " * No\n", "* If the prices are all decreasing and there is no opportunity to make a profit, do we just return 0?\n", " * Yes\n", "* Should the output be the max profit and days to buy and sell?\n", " * Yes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "
\n", "* Prices: None or k: None -> None\n", "* Prices: [] or k <= 0 -> []\n", "* Prices: [0, -1, -2, -3, -4, -5]\n", " * (max profit, list of transactions)\n", " * (0, [])\n", "* Prices: [2, 5, 7, 1, 4, 3, 1, 3] k: 3\n", " * (max profit, list of transactions)\n", " * (10, [Type.SELL day: 7 price: 3, \n", " Type.BUY day: 6 price: 1, \n", " Type.SELL day: 4 price: 4, \n", " Type.BUY day: 3 price: 1, \n", " Type.SELL day: 2 price: 7, \n", " Type.BUY day: 0 price: 2])\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Refer to the [Solution Notebook](). If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from enum import Enum # Python 2 users: Run pip install enum34\n", "\n", "\n", "class Type(Enum):\n", " SELL = 0\n", " BUY = 1\n", "\n", "\n", "class Transaction(object):\n", "\n", " def __init__(self, type, day, price):\n", " self.type = type\n", " self.day = day\n", " self.price = price\n", "\n", " def __eq__(self, other):\n", " return self.type == other.type and \\\n", " self.day == other.day and \\\n", " self.price == other.price\n", "\n", " def __repr__(self):\n", " return str(self.type) + ' day: ' + \\\n", " str(self.day) + ' price: ' + \\\n", " str(self.price)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "class StockTrader(object):\n", "\n", " def find_max_profit(self, prices, k):\n", " # TODO: Implement me\n", " pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**The following unit test is expected to fail until you solve the challenge.**" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# %load test_max_profit.py\n", "from nose.tools import assert_equal\n", "from nose.tools import assert_raises\n", "from nose.tools import assert_true\n", "\n", "\n", "class TestMaxProfit(object):\n", "\n", " def test_max_profit(self):\n", " stock_trader = StockTrader()\n", " assert_raises(TypeError, stock_trader.find_max_profit, None, None)\n", " assert_equal(stock_trader.find_max_profit(prices=[], k=0), [])\n", " prices = [5, 4, 3, 2, 1]\n", " k = 3\n", " assert_equal(stock_trader.find_max_profit(prices, k), (0, []))\n", " prices = [2, 5, 7, 1, 4, 3, 1, 3]\n", " profit, transactions = stock_trader.find_max_profit(prices, k)\n", " assert_equal(profit, 10)\n", " assert_true(Transaction(Type.SELL,\n", " day=7,\n", " price=3) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=6,\n", " price=1) in transactions)\n", " assert_true(Transaction(Type.SELL,\n", " day=4,\n", " price=4) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=3,\n", " price=1) in transactions)\n", " assert_true(Transaction(Type.SELL,\n", " day=2,\n", " price=7) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=0,\n", " price=2) in transactions)\n", " print('Success: test_max_profit')\n", "\n", "\n", "def main():\n", " test = TestMaxProfit()\n", " test.test_max_profit()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solution Notebook\n", "\n", "Review the [Solution Notebook]() for a discussion on algorithms and code solutions." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.0" } }, "nbformat": 4, "nbformat_minor": 0 }