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Add sentence screen fit challenge
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Donne Martin
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online_judges/sentence_screen_fit/__init__.py
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online_judges/sentence_screen_fit/__init__.py
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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: Find how many times a sentence can fit on a screen.\n",
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"\n",
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"See the [LeetCode](https://leetcode.com/problems/sentence-screen-fitting/) problem page.\n",
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"\n",
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"<pre>\n",
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"Given a rows x cols screen and a sentence represented by a list of non-empty words, find how many times the given sentence can be fitted on the screen.\n",
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"\n",
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"Note:\n",
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"\n",
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"A word cannot be split into two lines.\n",
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"The order of words in the sentence must remain unchanged.\n",
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"Two consecutive words in a line must be separated by a single space.\n",
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"Total words in the sentence won't exceed 100.\n",
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"Length of each word is greater than 0 and won't exceed 10.\n",
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"1 ≤ rows, cols ≤ 20,000.\n",
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"Example 1:\n",
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"\n",
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"Input:\n",
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"rows = 2, cols = 8, sentence = [\"hello\", \"world\"]\n",
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"\n",
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"Output: \n",
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"1\n",
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"\n",
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"Explanation:\n",
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"hello---\n",
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"world---\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"Example 2:\n",
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"\n",
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"Input:\n",
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"rows = 3, cols = 6, sentence = [\"a\", \"bcd\", \"e\"]\n",
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"\n",
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"Output: \n",
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"2\n",
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"\n",
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"Explanation:\n",
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"a-bcd- \n",
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"e-a---\n",
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"bcd-e-\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"Example 3:\n",
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"\n",
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"Input:\n",
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"rows = 4, cols = 5, sentence = [\"I\", \"had\", \"apple\", \"pie\"]\n",
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"\n",
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"Output: \n",
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"1\n",
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"\n",
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"Explanation:\n",
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"I-had\n",
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"apple\n",
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"pie-I\n",
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"had--\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"</pre>\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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"* Can we assume sentence is ASCII?\n",
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" * Yes\n",
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"* Can we assume the inputs are valid?\n",
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" * No\n",
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"* Is the output an integer?\n",
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" * Yes\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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"* None -> TypeError\n",
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"* rows < 0 or cols < 0 -> ValueError\n",
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"* cols = 0 -> 0\n",
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"* sentence = '' -> 0\n",
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"* rows = 2, cols = 8, sentence = [\"hello\", \"world\"] -> 1\n",
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"* rows = 3, cols = 6, sentence = [\"a\", \"bcd\", \"e\"] -> 2\n",
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"* rows = 4, cols = 5, sentence = [\"I\", \"had\", \"apple\", \"pie\"] -> 1"
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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](). 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": false
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},
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"outputs": [],
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"source": [
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"class Solution(object):\n",
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"\n",
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" def count_sentence_fit(self, sentence, rows, cols):\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_count_sentence_fit.py\n",
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"from nose.tools import assert_equal, assert_raises\n",
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"\n",
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"\n",
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"class TestSolution(object):\n",
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"\n",
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" def test_count_sentence_fit(self):\n",
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" solution = Solution()\n",
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" assert_raises(TypeError, solution.count_sentence_fit, \n",
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" None, None, None)\n",
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" assert_raises(ValueError, solution.count_sentence_fit, \n",
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" 'abc', rows=-1, cols=-1)\n",
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" sentence = [\"hello\", \"world\"]\n",
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" expected = 1\n",
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" assert_equal(solution.count_sentence_fit(sentence, rows=2, cols=8),\n",
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" expected)\n",
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" sentence = [\"a\", \"bcd\", \"e\"]\n",
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" expected = 2\n",
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" assert_equal(solution.count_sentence_fit(sentence, rows=3, cols=6),\n",
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" expected)\n",
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" sentence = [\"I\", \"had\", \"apple\", \"pie\"]\n",
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" expected = 1\n",
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" assert_equal(solution.count_sentence_fit(sentence, rows=4, cols=5),\n",
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" expected)\n",
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" print('Success: test_count_sentence_fit')\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestSolution()\n",
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" test.test_count_sentence_fit()\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]() 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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@ -0,0 +1,321 @@
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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": [
|
||||
"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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"# 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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"## Problem: Find how many times a sentence can fit on a screen.\n",
|
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"\n",
|
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"See the [LeetCode](https://leetcode.com/problems/sentence-screen-fitting/) problem page.\n",
|
||||
"\n",
|
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"<pre>\n",
|
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"Given a rows x cols screen and a sentence represented by a list of non-empty words, find how many times the given sentence can be fitted on the screen.\n",
|
||||
"\n",
|
||||
"Note:\n",
|
||||
"\n",
|
||||
"A word cannot be split into two lines.\n",
|
||||
"The order of words in the sentence must remain unchanged.\n",
|
||||
"Two consecutive words in a line must be separated by a single space.\n",
|
||||
"Total words in the sentence won't exceed 100.\n",
|
||||
"Length of each word is greater than 0 and won't exceed 10.\n",
|
||||
"1 ≤ rows, cols ≤ 20,000.\n",
|
||||
"Example 1:\n",
|
||||
"\n",
|
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"Input:\n",
|
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"rows = 2, cols = 8, sentence = [\"hello\", \"world\"]\n",
|
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"\n",
|
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"Output: \n",
|
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"1\n",
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"\n",
|
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"Explanation:\n",
|
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"hello---\n",
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"world---\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"Example 2:\n",
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"\n",
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"Input:\n",
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"rows = 3, cols = 6, sentence = [\"a\", \"bcd\", \"e\"]\n",
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"\n",
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"Output: \n",
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"2\n",
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"\n",
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"Explanation:\n",
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"a-bcd- \n",
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"e-a---\n",
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"bcd-e-\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"Example 3:\n",
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"\n",
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"Input:\n",
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"rows = 4, cols = 5, sentence = [\"I\", \"had\", \"apple\", \"pie\"]\n",
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"\n",
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"Output: \n",
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"1\n",
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"\n",
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"Explanation:\n",
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"I-had\n",
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"apple\n",
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"pie-I\n",
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"had--\n",
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"\n",
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"The character '-' signifies an empty space on the screen.\n",
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"</pre>\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)"
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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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"* Can we assume sentence is ASCII?\n",
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" * Yes\n",
|
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"* Can we assume the inputs are valid?\n",
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" * No\n",
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"* Is the output an integer?\n",
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" * Yes\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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"* None -> TypeError\n",
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"* rows < 0 or cols < 0 -> ValueError\n",
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"* cols = 0 -> 0\n",
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"* sentence = '' -> 0\n",
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"* rows = 2, cols = 8, sentence = [\"hello\", \"world\"] -> 1\n",
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"* rows = 3, cols = 6, sentence = [\"a\", \"bcd\", \"e\"] -> 2\n",
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"* rows = 4, cols = 5, sentence = [\"I\", \"had\", \"apple\", \"pie\"] -> 1"
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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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"It can be relatively straightforward to come up with the brute force solution, check out the method `count_sentence_fit_brute_force` below. \n",
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"\n",
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"The optimized solutions is discussed in more depth [here](https://discuss.leetcode.com/topic/62455/21ms-18-lines-java-solution/25).\n",
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"\n",
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"<pre>\n",
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"rows = 4\n",
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"cols = 6\n",
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"sentence = ['abc', 'de', 'f']\n",
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"\n",
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"\"abc de f abc de f abc de f ...\" // start=0\n",
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" 012345 // start=start+cols+adjustment=0+6+1=7 (1 space removed in screen string)\n",
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" 012345 // start=7+6+0=13\n",
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" 012345 // start=13+6-1=18 (1 space added)\n",
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" 012345 // start=18+6+1=25 (1 space added)\n",
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" 012345\n",
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"</pre>\n",
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"\n",
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"Complexity:\n",
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"* Time: O(1)\n",
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"* Space: O(1)"
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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": 1,
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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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"class Solution(object):\n",
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"\n",
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" def count_sentence_fit_brute_force(self, sentence, rows, cols):\n",
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" if sentence is None:\n",
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" raise TypeError('sentence cannot be None')\n",
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" if rows is None or cols is None:\n",
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" raise TypeError('rows and cols cannot be None')\n",
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" if rows < 0 or cols < 0:\n",
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" raise ValueError('rows and cols cannot be negative')\n",
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" if cols == 0 or not sentence:\n",
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" return 0\n",
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" curr_row = 0\n",
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" curr_col = 0\n",
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" count = 0\n",
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" while curr_row < cols:\n",
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" for word in sentence:\n",
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" # If the current word doesn't fit on the current line,\n",
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" # move to the next line\n",
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" if len(word) > cols - curr_col:\n",
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" curr_col = 0\n",
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" curr_row += 1\n",
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" # If we are beyond the number of rows, return\n",
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" if curr_row >= rows:\n",
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" return count\n",
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" # If the current word fits on the current line,\n",
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" # 'insert' it here\n",
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" if len(word) <= cols - curr_col:\n",
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" curr_col += len(word) + 1\n",
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" # If it still doesn't fit, then the word is too long\n",
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" # and we should just return the current count\n",
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" else:\n",
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" return count\n",
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" count += 1\n",
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" return count\n",
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"\n",
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" def count_sentence_fit(self, sentence, rows, cols):\n",
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" if sentence is None:\n",
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" raise TypeError('sentence cannot be None')\n",
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" if rows is None or cols is None:\n",
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" raise TypeError('rows and cols cannot be None')\n",
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" if rows < 0 or cols < 0:\n",
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" raise ValueError('rows and cols cannot be negative')\n",
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" if cols == 0 or not sentence:\n",
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" return 0\n",
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" string = ' '.join(sentence) + ' '\n",
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" start = 0\n",
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" str_len = len(string)\n",
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" for row in range(rows):\n",
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" start += cols\n",
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" # We don't need extra space for the current row\n",
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" if string[start % str_len] == ' ':\n",
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" start += 1\n",
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" # The current row can't fit, so we'll need to \n",
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" # remove characters from the next word\n",
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" else:\n",
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" while (start > 0 and string[(start - 1) % str_len] != ' '):\n",
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" start -= 1\n",
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" return start // str_len"
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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": [
|
||||
"## Unit Test"
|
||||
]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Overwriting test_count_sentence_fit.py\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"%%writefile test_count_sentence_fit.py\n",
|
||||
"from nose.tools import assert_equal, assert_raises\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"class TestSolution(object):\n",
|
||||
"\n",
|
||||
" def test_count_sentence_fit(self):\n",
|
||||
" solution = Solution()\n",
|
||||
" assert_raises(TypeError, solution.count_sentence_fit, \n",
|
||||
" None, None, None)\n",
|
||||
" assert_raises(ValueError, solution.count_sentence_fit, \n",
|
||||
" 'abc', rows=-1, cols=-1)\n",
|
||||
" sentence = [\"hello\", \"world\"]\n",
|
||||
" expected = 1\n",
|
||||
" assert_equal(solution.count_sentence_fit(sentence, rows=2, cols=8),\n",
|
||||
" expected)\n",
|
||||
" sentence = [\"a\", \"bcd\", \"e\"]\n",
|
||||
" expected = 2\n",
|
||||
" assert_equal(solution.count_sentence_fit(sentence, rows=3, cols=6),\n",
|
||||
" expected)\n",
|
||||
" sentence = [\"I\", \"had\", \"apple\", \"pie\"]\n",
|
||||
" expected = 1\n",
|
||||
" assert_equal(solution.count_sentence_fit(sentence, rows=4, cols=5),\n",
|
||||
" expected)\n",
|
||||
" print('Success: test_count_sentence_fit')\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"def main():\n",
|
||||
" test = TestSolution()\n",
|
||||
" test.test_count_sentence_fit()\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"if __name__ == '__main__':\n",
|
||||
" main()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Success: test_count_sentence_fit\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"%run -i test_count_sentence_fit.py"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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
|
||||
}
|
||||
33
online_judges/sentence_screen_fit/test_count_sentence_fit.py
Normal file
33
online_judges/sentence_screen_fit/test_count_sentence_fit.py
Normal file
|
|
@ -0,0 +1,33 @@
|
|||
from nose.tools import assert_equal, assert_raises
|
||||
|
||||
|
||||
class TestSolution(object):
|
||||
|
||||
def test_count_sentence_fit(self):
|
||||
solution = Solution()
|
||||
assert_raises(TypeError, solution.count_sentence_fit,
|
||||
None, None, None)
|
||||
assert_raises(ValueError, solution.count_sentence_fit,
|
||||
'abc', rows=-1, cols=-1)
|
||||
sentence = ["hello", "world"]
|
||||
expected = 1
|
||||
assert_equal(solution.count_sentence_fit(sentence, rows=2, cols=8),
|
||||
expected)
|
||||
sentence = ["a", "bcd", "e"]
|
||||
expected = 2
|
||||
assert_equal(solution.count_sentence_fit(sentence, rows=3, cols=6),
|
||||
expected)
|
||||
sentence = ["I", "had", "apple", "pie"]
|
||||
expected = 1
|
||||
assert_equal(solution.count_sentence_fit(sentence, rows=4, cols=5),
|
||||
expected)
|
||||
print('Success: test_count_sentence_fit')
|
||||
|
||||
|
||||
def main():
|
||||
test = TestSolution()
|
||||
test.test_count_sentence_fit()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Loading…
Reference in New Issue
Block a user