mirror of
https://github.com/donnemartin/interactive-coding-challenges.git
synced 2024-03-22 13:11:13 +08:00
209 lines
5.1 KiB
Python
209 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](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 an algorithm to have a robot move from the upper left corner to the bottom right corner of a grid.\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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"* Are there restrictions to how the robot moves?\n",
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" * The robot can only move right and down\n",
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"* Are some cells off limits?\n",
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" * Yes\n",
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"* Is this a rectangular grid? i.e. the grid is not jagged?\n",
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" * Yes\n",
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"* Will there always be a valid way for the robot to get to the bottom right?\n",
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" * No, return None\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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"<pre>\n",
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"o = valid cell\n",
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"x = invalid cell\n",
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"\n",
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" 0 1 2 3\n",
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"0 o o o o\n",
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"1 o x o o\n",
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"2 o o x o\n",
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"3 x o o o\n",
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"4 o o x o\n",
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"5 o o o x\n",
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"6 o x o x\n",
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"7 o x o o\n",
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"</pre>\n",
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"\n",
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"* General case\n",
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"\n",
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"```\n",
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"expected = [(0, 0), (1, 0), (2, 0),\n",
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" (2, 1), (3, 1), (4, 1),\n",
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" (5, 1), (5, 2), (6, 2), \n",
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" (7, 2), (7, 3)]\n",
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"```\n",
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"\n",
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"* No valid path: In above example, row 7 col 2 is also invalid -> None\n",
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"* None input -> None\n",
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"* Empty matrix -> None"
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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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"outputs": [],
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"source": [
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"class Grid(object):\n",
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"\n",
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" def find_path(self, matrix):\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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"outputs": [],
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"source": [
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"# %load test_grid_path.py\n",
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"import unittest\n",
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"\n",
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"\n",
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"class TestGridPath(unittest.TestCase):\n",
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"\n",
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" def test_grid_path(self):\n",
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" grid = Grid()\n",
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" self.assertEqual(grid.find_path(None), None)\n",
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" self.assertEqual(grid.find_path([[]]), None)\n",
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" max_rows = 8\n",
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" max_cols = 4\n",
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" matrix = [[1] * max_cols for _ in range(max_rows)]\n",
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" matrix[1][1] = 0\n",
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" matrix[2][2] = 0\n",
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" matrix[3][0] = 0\n",
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" matrix[4][2] = 0\n",
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" matrix[5][3] = 0\n",
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" matrix[6][1] = 0\n",
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" matrix[6][3] = 0\n",
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" matrix[7][1] = 0\n",
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" result = grid.find_path(matrix)\n",
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" expected = [(0, 0), (1, 0), (2, 0),\n",
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" (2, 1), (3, 1), (4, 1),\n",
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" (5, 1), (5, 2), (6, 2), \n",
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" (7, 2), (7, 3)]\n",
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" self.assertEqual(result, expected)\n",
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" matrix[7][2] = 0\n",
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" result = grid.find_path(matrix)\n",
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" self.assertEqual(result, None)\n",
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" print('Success: test_grid_path')\n",
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"\n",
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"\n",
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"def main():\n",
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" test = TestGridPath()\n",
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" test.test_grid_path()\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": "3.7.2"
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}
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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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