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1 | { | |||
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2 | "metadata": { | |||
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3 | "name": "" | |||
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4 | }, | |||
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5 | "nbformat": 3, | |||
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6 | "nbformat_minor": 0, | |||
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7 | "worksheets": [ | |||
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8 | { | |||
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9 | "cells": [ | |||
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10 | { | |||
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11 | "cell_type": "heading", | |||
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12 | "level": 1, | |||
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13 | "metadata": {}, | |||
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14 | "source": [ | |||
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15 | "Basic Output" | |||
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16 | ] | |||
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17 | }, | |||
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18 | { | |||
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19 | "cell_type": "code", | |||
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20 | "collapsed": false, | |||
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21 | "input": [ | |||
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22 | "from IPython.display import display" | |||
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23 | ], | |||
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24 | "language": "python", | |||
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25 | "metadata": {}, | |||
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26 | "outputs": [], | |||
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27 | "prompt_number": 11 | |||
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28 | }, | |||
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29 | { | |||
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30 | "cell_type": "code", | |||
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31 | "collapsed": false, | |||
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32 | "input": [ | |||
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33 | "print 'hi'" | |||
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34 | ], | |||
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35 | "language": "python", | |||
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36 | "metadata": {}, | |||
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37 | "outputs": [ | |||
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38 | { | |||
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39 | "output_type": "stream", | |||
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40 | "stream": "stdout", | |||
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41 | "text": [ | |||
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42 | "hi\n" | |||
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43 | ] | |||
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44 | } | |||
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45 | ], | |||
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46 | "prompt_number": 12 | |||
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47 | }, | |||
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48 | { | |||
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49 | "cell_type": "code", | |||
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50 | "collapsed": false, | |||
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51 | "input": [ | |||
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52 | "display('hi')" | |||
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53 | ], | |||
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54 | "language": "python", | |||
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55 | "metadata": {}, | |||
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56 | "outputs": [ | |||
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57 | { | |||
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58 | "metadata": {}, | |||
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59 | "output_type": "display_data", | |||
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60 | "text": [ | |||
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61 | "'hi'" | |||
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62 | ] | |||
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63 | } | |||
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64 | ], | |||
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65 | "prompt_number": 13 | |||
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66 | }, | |||
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67 | { | |||
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68 | "cell_type": "code", | |||
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69 | "collapsed": false, | |||
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70 | "input": [ | |||
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71 | "1" | |||
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72 | ], | |||
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73 | "language": "python", | |||
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74 | "metadata": {}, | |||
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75 | "outputs": [ | |||
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76 | { | |||
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77 | "metadata": {}, | |||
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78 | "output_type": "pyout", | |||
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79 | "prompt_number": 14, | |||
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80 | "text": [ | |||
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81 | "1" | |||
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82 | ] | |||
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83 | } | |||
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84 | ], | |||
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85 | "prompt_number": 14 | |||
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86 | }, | |||
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87 | { | |||
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88 | "cell_type": "code", | |||
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89 | "collapsed": false, | |||
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90 | "input": [ | |||
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91 | "%matplotlib inline\n", | |||
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92 | "import matplotlib.pyplot as plt\n", | |||
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93 | "plt.plot([1,3,2])" | |||
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94 | ], | |||
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95 | "language": "python", | |||
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96 | "metadata": {}, | |||
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97 | "outputs": [ | |||
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98 | { | |||
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99 | "metadata": {}, | |||
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100 | "output_type": "pyout", | |||
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101 | "prompt_number": 5, | |||
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102 | "text": [ | |||
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103 | "[<matplotlib.lines.Line2D at 0x10a1da150>]" | |||
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104 | ] | |||
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105 | }, | |||
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106 | { | |||
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107 | "metadata": {}, | |||
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108 | "output_type": "display_data", | |||
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109 | "png": 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4nNlRAMDhrooP0fJJaUoK99eMNTla/W05G1VfAooWcB6f5dco41Cl5o1Nlo8X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\nKFoAAAAO8v8BvGxDv1+F5xsAAAAASUVORK5CYII=\n", | |||
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110 | "text": [ | |||
|
|
111 | "<matplotlib.figure.Figure at 0x10a2b5790>" | |||
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112 | ] | |||
|
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113 | } | |||
|
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114 | ], | |||
|
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115 | "prompt_number": 5 | |||
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116 | }, | |||
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117 | { | |||
|
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118 | "cell_type": "code", | |||
|
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119 | "collapsed": false, | |||
|
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120 | "input": [ | |||
|
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121 | "%%javascript\n", | |||
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122 | "console.log(\"I ran!\");" | |||
|
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123 | ], | |||
|
|
124 | "language": "python", | |||
|
|
125 | "metadata": {}, | |||
|
|
126 | "outputs": [ | |||
|
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127 | { | |||
|
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128 | "javascript": [ | |||
|
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129 | "console.log(\"I ran!\");" | |||
|
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130 | ], | |||
|
|
131 | "metadata": {}, | |||
|
|
132 | "output_type": "display_data", | |||
|
|
133 | "text": [ | |||
|
|
134 | "<IPython.core.display.Javascript at 0x10aae8310>" | |||
|
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135 | ] | |||
|
|
136 | } | |||
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137 | ], | |||
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138 | "prompt_number": 20 | |||
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139 | }, | |||
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140 | { | |||
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141 | "cell_type": "code", | |||
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142 | "collapsed": false, | |||
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143 | "input": [ | |||
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144 | "%%html\n", | |||
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145 | "<b>bold</b>" | |||
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146 | ], | |||
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147 | "language": "python", | |||
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148 | "metadata": {}, | |||
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149 | "outputs": [ | |||
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150 | { | |||
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151 | "html": [ | |||
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152 | "<b>bold</b>" | |||
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153 | ], | |||
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154 | "metadata": {}, | |||
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155 | "output_type": "display_data", | |||
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156 | "text": [ | |||
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157 | "<IPython.core.display.HTML at 0x10aae80d0>" | |||
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158 | ] | |||
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159 | } | |||
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160 | ], | |||
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161 | "prompt_number": 21 | |||
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162 | }, | |||
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163 | { | |||
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164 | "cell_type": "code", | |||
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165 | "collapsed": false, | |||
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166 | "input": [ | |||
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167 | "%%latex\n", | |||
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168 | "$$\n", | |||
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169 | "a = 5\n", | |||
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170 | "$$" | |||
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171 | ], | |||
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172 | "language": "python", | |||
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173 | "metadata": {}, | |||
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174 | "outputs": [ | |||
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175 | { | |||
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176 | "latex": [ | |||
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177 | "$$\n", | |||
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178 | "a = 5\n", | |||
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179 | "$$" | |||
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180 | ], | |||
|
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181 | "metadata": {}, | |||
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182 | "output_type": "display_data", | |||
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183 | "text": [ | |||
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184 | "<IPython.core.display.Latex at 0x10aae8310>" | |||
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185 | ] | |||
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186 | } | |||
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187 | ], | |||
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188 | "prompt_number": 22 | |||
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189 | }, | |||
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190 | { | |||
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191 | "cell_type": "heading", | |||
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192 | "level": 1, | |||
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193 | "metadata": {}, | |||
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194 | "source": [ | |||
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195 | "input_request" | |||
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196 | ] | |||
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197 | }, | |||
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198 | { | |||
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199 | "cell_type": "code", | |||
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200 | "collapsed": false, | |||
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201 | "input": [ | |||
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202 | "raw_input(\"prompt > \")" | |||
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203 | ], | |||
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204 | "language": "python", | |||
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205 | "metadata": {}, | |||
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206 | "outputs": [ | |||
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207 | { | |||
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208 | "name": "stdout", | |||
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209 | "output_type": "stream", | |||
|
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210 | "stream": "stdout", | |||
|
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211 | "text": [ | |||
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212 | "prompt > 1\n" | |||
|
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213 | ] | |||
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214 | }, | |||
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215 | { | |||
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216 | "metadata": {}, | |||
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217 | "output_type": "pyout", | |||
|
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218 | "prompt_number": 1, | |||
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219 | "text": [ | |||
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220 | "'1'" | |||
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221 | ] | |||
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222 | } | |||
|
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223 | ], | |||
|
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224 | "prompt_number": 1 | |||
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225 | }, | |||
|
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226 | { | |||
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227 | "cell_type": "heading", | |||
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|
228 | "level": 1, | |||
|
|
229 | "metadata": {}, | |||
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230 | "source": [ | |||
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231 | "set_next_input" | |||
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232 | ] | |||
|
|
233 | }, | |||
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234 | { | |||
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235 | "cell_type": "code", | |||
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236 | "collapsed": false, | |||
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237 | "input": [ | |||
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238 | "%%writefile tst.py\n", | |||
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239 | "def foo():\n", | |||
|
|
240 | " pass\n" | |||
|
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241 | ], | |||
|
|
242 | "language": "python", | |||
|
|
243 | "metadata": {}, | |||
|
|
244 | "outputs": [ | |||
|
|
245 | { | |||
|
|
246 | "output_type": "stream", | |||
|
|
247 | "stream": "stdout", | |||
|
|
248 | "text": [ | |||
|
|
249 | "Overwriting tst.py\n" | |||
|
|
250 | ] | |||
|
|
251 | } | |||
|
|
252 | ], | |||
|
|
253 | "prompt_number": 2 | |||
|
|
254 | }, | |||
|
|
255 | { | |||
|
|
256 | "cell_type": "code", | |||
|
|
257 | "collapsed": false, | |||
|
|
258 | "input": [ | |||
|
|
259 | "%load tst.py" | |||
|
|
260 | ], | |||
|
|
261 | "language": "python", | |||
|
|
262 | "metadata": {}, | |||
|
|
263 | "outputs": [], | |||
|
|
264 | "prompt_number": 3 | |||
|
|
265 | }, | |||
|
|
266 | { | |||
|
|
267 | "cell_type": "heading", | |||
|
|
268 | "level": 1, | |||
|
|
269 | "metadata": {}, | |||
|
|
270 | "source": [ | |||
|
|
271 | "Pager in execute_reply" | |||
|
|
272 | ] | |||
|
|
273 | }, | |||
|
|
274 | { | |||
|
|
275 | "cell_type": "code", | |||
|
|
276 | "collapsed": false, | |||
|
|
277 | "input": [ | |||
|
|
278 | "plt?" | |||
|
|
279 | ], | |||
|
|
280 | "language": "python", | |||
|
|
281 | "metadata": {}, | |||
|
|
282 | "outputs": [], | |||
|
|
283 | "prompt_number": 9 | |||
|
|
284 | }, | |||
|
|
285 | { | |||
|
|
286 | "cell_type": "heading", | |||
|
|
287 | "level": 1, | |||
|
|
288 | "metadata": {}, | |||
|
|
289 | "source": [ | |||
|
|
290 | "object_info" | |||
|
|
291 | ] | |||
|
|
292 | }, | |||
|
|
293 | { | |||
|
|
294 | "cell_type": "code", | |||
|
|
295 | "collapsed": false, | |||
|
|
296 | "input": [ | |||
|
|
297 | "# press tab after parentheses\n", | |||
|
|
298 | "int(" | |||
|
|
299 | ], | |||
|
|
300 | "language": "python", | |||
|
|
301 | "metadata": {}, | |||
|
|
302 | "outputs": [] | |||
|
|
303 | }, | |||
|
|
304 | { | |||
|
|
305 | "cell_type": "heading", | |||
|
|
306 | "level": 1, | |||
|
|
307 | "metadata": {}, | |||
|
|
308 | "source": [ | |||
|
|
309 | "complete" | |||
|
|
310 | ] | |||
|
|
311 | }, | |||
|
|
312 | { | |||
|
|
313 | "cell_type": "code", | |||
|
|
314 | "collapsed": false, | |||
|
|
315 | "input": [ | |||
|
|
316 | "# pres tab after f\n", | |||
|
|
317 | "f" | |||
|
|
318 | ], | |||
|
|
319 | "language": "python", | |||
|
|
320 | "metadata": {}, | |||
|
|
321 | "outputs": [] | |||
|
|
322 | } | |||
|
|
323 | ], | |||
|
|
324 | "metadata": {} | |||
|
|
325 | } | |||
|
|
326 | ] | |||
|
|
327 | } No newline at end of file | |||
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