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https://github.com/donnemartin/interactive-coding-challenges
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Add anagrams challenge
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Donne Martin
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sorting_searching/anagrams/anagrams_solution.ipynb
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sorting_searching/anagrams/anagrams_solution.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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"# 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: Sort an array of strings so all anagrams are next to each other.\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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"* Are there any other sorting requirements other than the grouping of anagrams?\n",
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" * No\n",
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"* Can we assume the inputs are valid?\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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"* None -> Exception\n",
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"* [] -> []\n",
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"* General case\n",
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" * Input: ['ram', 'act', 'arm', 'bat', 'cat', 'tab']\n",
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" * Result: ['arm', 'ram', 'act', 'cat', 'bat', 'tab']"
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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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"<pre>\n",
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"Input: ['ram', 'act', 'arm', 'bat', 'cat', 'tab']\n",
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"\n",
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"Sort the chars for each item:\n",
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"\n",
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"'ram' -> 'amr'\n",
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"'act' -> 'act'\n",
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"'arm' -> 'amr'\n",
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"'abt' -> 'bat'\n",
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"'cat' -> 'act'\n",
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"'abt' -> 'tab'\n",
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"\n",
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"Use a map of sorted chars to each item to group anagrams:\n",
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"\n",
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"{\n",
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" 'amr': ['ram', 'arm'], \n",
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" 'act': ['act', 'cat'], \n",
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" 'abt': ['bat', 'tab']\n",
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"}\n",
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"\n",
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"Result: ['arm', 'ram', 'act', 'cat', 'bat', 'tab']\n",
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"</pre>\n",
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"\n",
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"Complexity:\n",
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"* Time: O(k * n), due to the modified bucket sort\n",
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"* Space: O(n)"
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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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"from collections import OrderedDict\n",
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"\n",
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"\n",
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"class Anagram(object):\n",
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"\n",
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" def group_anagrams(self, items):\n",
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" if items is None:\n",
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" raise TypeError('items cannot be None')\n",
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" if not items:\n",
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" return items\n",
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" anagram_map = OrderedDict()\n",
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" for item in items:\n",
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" # Use a tuple, which is hashable and\n",
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" # serves as the key in anagram_map\n",
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" sorted_chars = tuple(sorted(item))\n",
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" if sorted_chars in anagram_map:\n",
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" anagram_map[sorted_chars].append(item)\n",
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" else:\n",
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" anagram_map[sorted_chars] = [item]\n",
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" result = []\n",
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" for value in anagram_map.values():\n",
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" result.extend(value)\n",
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" return result"
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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": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Overwriting test_anagrams.py\n"
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]
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}
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],
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"source": [
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"%%writefile test_anagrams.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 TestAnagrams(object):\n",
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"\n",
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" def test_group_anagrams(self):\n",
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" anagram = Anagram()\n",
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" assert_raises(TypeError, anagram.group_anagrams, None)\n",
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" data = ['ram', 'act', 'arm', 'bat', 'cat', 'tab']\n",
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" expected = ['ram', 'arm', 'act', 'cat', 'bat', 'tab']\n",
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" assert_equal(anagram.group_anagrams(data), expected)\n",
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"\n",
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" print('Success: test_group_anagrams')\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestAnagrams()\n",
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" test.test_group_anagrams()\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": "code",
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Success: test_group_anagrams\n"
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]
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}
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],
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"source": [
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"%run -i test_anagrams.py"
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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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