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1 | 1 | ================= |
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2 | 2 | IPython reference |
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3 | 3 | ================= |
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4 | 4 | |
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5 | 5 | .. _command_line_options: |
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6 | 6 | |
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7 | 7 | Command-line usage |
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8 | 8 | ================== |
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9 | 9 | |
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10 | 10 | You start IPython with the command:: |
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11 | 11 | |
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12 | 12 | $ ipython [options] files |
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13 | 13 | |
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14 | 14 | .. note:: |
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15 | 15 | |
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16 | 16 | For IPython on Python 3, use ``ipython3`` in place of ``ipython``. |
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17 | 17 | |
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18 | 18 | If invoked with no options, it executes all the files listed in sequence |
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19 | 19 | and drops you into the interpreter while still acknowledging any options |
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20 | 20 | you may have set in your ipython_config.py. This behavior is different from |
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21 | 21 | standard Python, which when called as python -i will only execute one |
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22 | 22 | file and ignore your configuration setup. |
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23 | 23 | |
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24 | 24 | Please note that some of the configuration options are not available at |
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25 | 25 | the command line, simply because they are not practical here. Look into |
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26 | 26 | your configuration files for details on those. There are separate configuration |
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27 | 27 | files for each profile, and the files look like "ipython_config.py" or |
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28 | 28 | "ipython_config_<frontendname>.py". Profile directories look like |
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29 | 29 | "profile_profilename" and are typically installed in the IPYTHONDIR directory, |
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30 | 30 | which defaults to :file:`$HOME/.ipython`. For Windows users, :envvar:`HOME` |
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31 | 31 | resolves to :file:`C:\\Documents and Settings\\YourUserName` in most |
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32 | 32 | instances. |
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33 | 33 | |
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34 | 34 | |
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35 | 35 | Eventloop integration |
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36 | 36 | --------------------- |
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37 | 37 | |
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38 | 38 | Previously IPython had command line options for controlling GUI event loop |
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39 | 39 | integration (-gthread, -qthread, -q4thread, -wthread, -pylab). As of IPython |
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40 | 40 | version 0.11, these have been removed. Please see the new ``%gui`` |
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41 | 41 | magic command or :ref:`this section <gui_support>` for details on the new |
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42 | 42 | interface, or specify the gui at the commandline:: |
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43 | 43 | |
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44 | 44 | $ ipython --gui=qt |
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45 | 45 | |
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46 | 46 | |
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47 | 47 | Command-line Options |
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48 | 48 | -------------------- |
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49 | 49 | |
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50 | 50 | To see the options IPython accepts, use ``ipython --help`` (and you probably |
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51 | 51 | should run the output through a pager such as ``ipython --help | less`` for |
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52 | 52 | more convenient reading). This shows all the options that have a single-word |
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53 | 53 | alias to control them, but IPython lets you configure all of its objects from |
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54 | 54 | the command-line by passing the full class name and a corresponding value; type |
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55 | 55 | ``ipython --help-all`` to see this full list. For example:: |
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56 | 56 | |
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57 | 57 | ipython --matplotlib qt |
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58 | 58 | |
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59 | 59 | is equivalent to:: |
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60 | 60 | |
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61 | 61 | ipython --TerminalIPythonApp.matplotlib='qt' |
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62 | 62 | |
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63 | 63 | Note that in the second form, you *must* use the equal sign, as the expression |
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64 | 64 | is evaluated as an actual Python assignment. While in the above example the |
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65 | 65 | short form is more convenient, only the most common options have a short form, |
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66 | 66 | while any configurable variable in IPython can be set at the command-line by |
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67 | 67 | using the long form. This long form is the same syntax used in the |
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68 | 68 | configuration files, if you want to set these options permanently. |
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69 | 69 | |
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70 | 70 | |
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71 | 71 | Interactive use |
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72 | 72 | =============== |
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73 | 73 | |
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74 | 74 | IPython is meant to work as a drop-in replacement for the standard interactive |
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75 | 75 | interpreter. As such, any code which is valid python should execute normally |
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76 | 76 | under IPython (cases where this is not true should be reported as bugs). It |
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77 | 77 | does, however, offer many features which are not available at a standard python |
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78 | 78 | prompt. What follows is a list of these. |
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79 | 79 | |
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80 | 80 | |
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81 | 81 | Caution for Windows users |
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82 | 82 | ------------------------- |
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83 | 83 | |
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84 | 84 | Windows, unfortunately, uses the '\\' character as a path separator. This is a |
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85 | 85 | terrible choice, because '\\' also represents the escape character in most |
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86 | 86 | modern programming languages, including Python. For this reason, using '/' |
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87 | 87 | character is recommended if you have problems with ``\``. However, in Windows |
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88 | 88 | commands '/' flags options, so you can not use it for the root directory. This |
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89 | 89 | means that paths beginning at the root must be typed in a contrived manner |
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90 | 90 | like: ``%copy \opt/foo/bar.txt \tmp`` |
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91 | 91 | |
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92 | 92 | .. _magic: |
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93 | 93 | |
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94 | 94 | Magic command system |
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95 | 95 | -------------------- |
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96 | 96 | |
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97 | 97 | IPython will treat any line whose first character is a % as a special |
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98 | 98 | call to a 'magic' function. These allow you to control the behavior of |
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99 | 99 | IPython itself, plus a lot of system-type features. They are all |
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100 | 100 | prefixed with a % character, but parameters are given without |
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101 | 101 | parentheses or quotes. |
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102 | 102 | |
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103 | 103 | Lines that begin with ``%%`` signal a *cell magic*: they take as arguments not |
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104 | 104 | only the rest of the current line, but all lines below them as well, in the |
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105 | 105 | current execution block. Cell magics can in fact make arbitrary modifications |
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106 | 106 | to the input they receive, which need not even be valid Python code at all. |
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107 | 107 | They receive the whole block as a single string. |
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108 | 108 | |
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109 | 109 | As a line magic example, the ``%cd`` magic works just like the OS command of |
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110 | 110 | the same name:: |
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111 | 111 | |
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112 | 112 | In [8]: %cd |
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113 | 113 | /home/fperez |
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114 | 114 | |
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115 | 115 | The following uses the builtin ``timeit`` in cell mode:: |
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116 | 116 | |
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117 | 117 | In [10]: %%timeit x = range(10000) |
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118 | 118 | ...: min(x) |
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119 | 119 | ...: max(x) |
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120 | 120 | ...: |
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121 | 121 | 1000 loops, best of 3: 438 us per loop |
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122 | 122 | |
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123 | 123 | In this case, ``x = range(10000)`` is called as the line argument, and the |
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124 | 124 | block with ``min(x)`` and ``max(x)`` is called as the cell body. The |
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125 | 125 | ``timeit`` magic receives both. |
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126 | 126 | |
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127 | 127 | If you have 'automagic' enabled (as it by default), you don't need to type in |
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128 | 128 | the single ``%`` explicitly for line magics; IPython will scan its internal |
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129 | 129 | list of magic functions and call one if it exists. With automagic on you can |
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130 | 130 | then just type ``cd mydir`` to go to directory 'mydir':: |
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131 | 131 | |
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132 | 132 | In [9]: cd mydir |
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133 | 133 | /home/fperez/mydir |
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134 | 134 | |
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135 | 135 | Note that cell magics *always* require an explicit ``%%`` prefix, automagic |
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136 | 136 | calling only works for line magics. |
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137 | 137 | |
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138 | 138 | The automagic system has the lowest possible precedence in name searches, so |
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139 | 139 | defining an identifier with the same name as an existing magic function will |
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140 | 140 | shadow it for automagic use. You can still access the shadowed magic function |
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141 | 141 | by explicitly using the ``%`` character at the beginning of the line. |
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142 | 142 | |
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143 | 143 | An example (with automagic on) should clarify all this: |
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144 | 144 | |
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145 | 145 | .. sourcecode:: ipython |
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146 | 146 | |
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147 | 147 | In [1]: cd ipython # %cd is called by automagic |
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148 | 148 | /home/fperez/ipython |
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149 | 149 | |
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150 | 150 | In [2]: cd=1 # now cd is just a variable |
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151 | 151 | |
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152 | 152 | In [3]: cd .. # and doesn't work as a function anymore |
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153 | 153 | File "<ipython-input-3-9fedb3aff56c>", line 1 |
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154 | 154 | cd .. |
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155 | 155 | ^ |
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156 | 156 | SyntaxError: invalid syntax |
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157 | 157 | |
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158 | 158 | |
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159 | 159 | In [4]: %cd .. # but %cd always works |
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160 | 160 | /home/fperez |
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161 | 161 | |
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162 | 162 | In [5]: del cd # if you remove the cd variable, automagic works again |
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163 | 163 | |
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164 | 164 | In [6]: cd ipython |
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165 | 165 | |
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166 | 166 | /home/fperez/ipython |
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167 | 167 | |
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168 | 168 | Defining your own magics |
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169 | 169 | ++++++++++++++++++++++++ |
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170 | 170 | |
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171 | 171 | There are two main ways to define your own magic functions: from standalone |
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172 | 172 | functions and by inheriting from a base class provided by IPython: |
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173 | 173 | :class:`IPython.core.magic.Magics`. Below we show code you can place in a file |
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174 | 174 | that you load from your configuration, such as any file in the ``startup`` |
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175 | 175 | subdirectory of your default IPython profile. |
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176 | 176 | |
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177 | 177 | First, let us see the simplest case. The following shows how to create a line |
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178 | 178 | magic, a cell one and one that works in both modes, using just plain functions: |
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179 | 179 | |
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180 | 180 | .. sourcecode:: python |
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181 | 181 | |
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182 | 182 | from IPython.core.magic import (register_line_magic, register_cell_magic, |
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183 | 183 | register_line_cell_magic) |
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184 | ||
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184 | ||
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185 | 185 | @register_line_magic |
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186 | 186 | def lmagic(line): |
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187 | 187 | "my line magic" |
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188 |
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188 | return line | |
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189 | 189 | |
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190 | 190 | @register_cell_magic |
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191 | 191 | def cmagic(line, cell): |
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192 | 192 | "my cell magic" |
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193 | 193 | return line, cell |
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194 | 194 | |
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195 | 195 | @register_line_cell_magic |
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196 | 196 | def lcmagic(line, cell=None): |
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197 | 197 | "Magic that works both as %lcmagic and as %%lcmagic" |
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198 |
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199 |
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200 |
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201 | else: | |
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202 |
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198 | if cell is None: | |
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199 | print("Called as line magic") | |
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200 | return line | |
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201 | else: | |
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202 | print("Called as cell magic") | |
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203 | 203 | return line, cell |
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204 | 204 | |
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205 | 205 | # We delete these to avoid name conflicts for automagic to work |
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206 | 206 | del lmagic, lcmagic |
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207 | 207 | |
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208 | 208 | |
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209 | 209 | You can also create magics of all three kinds by inheriting from the |
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210 | 210 | :class:`IPython.core.magic.Magics` class. This lets you create magics that can |
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211 | 211 | potentially hold state in between calls, and that have full access to the main |
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212 | 212 | IPython object: |
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213 | 213 | |
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214 | 214 | .. sourcecode:: python |
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215 | ||
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215 | ||
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216 | 216 | # This code can be put in any Python module, it does not require IPython |
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217 | 217 | # itself to be running already. It only creates the magics subclass but |
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218 | 218 | # doesn't instantiate it yet. |
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219 | from __future__ import print_function | |
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219 | 220 | from IPython.core.magic import (Magics, magics_class, line_magic, |
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220 | 221 | cell_magic, line_cell_magic) |
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221 | 222 | |
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222 | 223 | # The class MUST call this class decorator at creation time |
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223 | 224 | @magics_class |
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224 | 225 | class MyMagics(Magics): |
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225 | 226 | |
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226 | 227 | @line_magic |
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227 | 228 | def lmagic(self, line): |
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228 | 229 | "my line magic" |
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229 |
print |
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230 |
print |
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230 | print("Full access to the main IPython object:", self.shell) | |
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231 | print("Variables in the user namespace:", list(self.shell.user_ns.keys())) | |
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231 | 232 | return line |
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232 | 233 | |
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233 | 234 | @cell_magic |
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234 | 235 | def cmagic(self, line, cell): |
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235 | 236 | "my cell magic" |
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236 | 237 | return line, cell |
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237 | 238 | |
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238 | 239 | @line_cell_magic |
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239 | 240 | def lcmagic(self, line, cell=None): |
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240 | 241 | "Magic that works both as %lcmagic and as %%lcmagic" |
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241 | 242 | if cell is None: |
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242 |
print |
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243 | print("Called as line magic") | |
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243 | 244 | return line |
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244 | 245 | else: |
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245 |
print |
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246 | print("Called as cell magic") | |
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246 | 247 | return line, cell |
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247 | 248 | |
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248 | 249 | |
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249 | 250 | # In order to actually use these magics, you must register them with a |
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250 | 251 | # running IPython. This code must be placed in a file that is loaded once |
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251 | 252 | # IPython is up and running: |
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252 | 253 | ip = get_ipython() |
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253 | 254 | # You can register the class itself without instantiating it. IPython will |
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254 | 255 | # call the default constructor on it. |
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255 | 256 | ip.register_magics(MyMagics) |
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256 | 257 | |
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257 | 258 | If you want to create a class with a different constructor that holds |
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258 | 259 | additional state, then you should always call the parent constructor and |
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259 | 260 | instantiate the class yourself before registration: |
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260 | 261 | |
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261 | 262 | .. sourcecode:: python |
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262 | ||
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263 | ||
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263 | 264 | @magics_class |
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264 | 265 | class StatefulMagics(Magics): |
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265 | 266 | "Magics that hold additional state" |
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266 | ||
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267 | ||
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267 | 268 | def __init__(self, shell, data): |
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268 | 269 | # You must call the parent constructor |
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269 | 270 | super(StatefulMagics, self).__init__(shell) |
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270 | 271 | self.data = data |
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271 | 272 | |
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272 | 273 | # etc... |
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273 | 274 | |
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274 | 275 | # This class must then be registered with a manually created instance, |
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275 | 276 | # since its constructor has different arguments from the default: |
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276 | 277 | ip = get_ipython() |
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277 | 278 | magics = StatefulMagics(ip, some_data) |
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278 | 279 | ip.register_magics(magics) |
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279 | 280 | |
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280 | 281 | |
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281 | 282 | In earlier versions, IPython had an API for the creation of line magics (cell |
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282 | 283 | magics did not exist at the time) that required you to create functions with a |
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283 | 284 | method-looking signature and to manually pass both the function and the name. |
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284 | 285 | While this API is no longer recommended, it remains indefinitely supported for |
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285 | 286 | backwards compatibility purposes. With the old API, you'd create a magic as |
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286 | 287 | follows: |
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287 | 288 | |
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288 | 289 | .. sourcecode:: python |
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289 | 290 | |
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290 | 291 | def func(self, line): |
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291 |
print |
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292 |
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292 | print("Line magic called with line:", line) | |
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293 | print("IPython object:", self.shell) | |
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293 | 294 | |
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294 | 295 | ip = get_ipython() |
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295 | 296 | # Declare this function as the magic %mycommand |
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296 | 297 | ip.define_magic('mycommand', func) |
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297 | 298 | |
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298 | 299 | Type ``%magic`` for more information, including a list of all available magic |
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299 | 300 | functions at any time and their docstrings. You can also type |
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300 | 301 | ``%magic_function_name?`` (see :ref:`below <dynamic_object_info>` for |
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301 | 302 | information on the '?' system) to get information about any particular magic |
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302 | 303 | function you are interested in. |
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303 | 304 | |
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304 | 305 | The API documentation for the :mod:`IPython.core.magic` module contains the full |
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305 | 306 | docstrings of all currently available magic commands. |
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306 | 307 | |
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307 | 308 | |
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308 | 309 | Access to the standard Python help |
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309 | 310 | ---------------------------------- |
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310 | 311 | |
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311 | 312 | Simply type ``help()`` to access Python's standard help system. You can |
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312 | 313 | also type ``help(object)`` for information about a given object, or |
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313 | 314 | ``help('keyword')`` for information on a keyword. You may need to configure your |
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314 | 315 | PYTHONDOCS environment variable for this feature to work correctly. |
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315 | 316 | |
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316 | 317 | .. _dynamic_object_info: |
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317 | 318 | |
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318 | 319 | Dynamic object information |
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319 | 320 | -------------------------- |
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320 | 321 | |
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321 | 322 | Typing ``?word`` or ``word?`` prints detailed information about an object. If |
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322 | 323 | certain strings in the object are too long (e.g. function signatures) they get |
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323 | 324 | snipped in the center for brevity. This system gives access variable types and |
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324 | 325 | values, docstrings, function prototypes and other useful information. |
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325 | 326 | |
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326 | 327 | If the information will not fit in the terminal, it is displayed in a pager |
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327 | 328 | (``less`` if available, otherwise a basic internal pager). |
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328 | 329 | |
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329 | 330 | Typing ``??word`` or ``word??`` gives access to the full information, including |
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330 | 331 | the source code where possible. Long strings are not snipped. |
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331 | 332 | |
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332 | 333 | The following magic functions are particularly useful for gathering |
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333 | 334 | information about your working environment. You can get more details by |
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334 | 335 | typing ``%magic`` or querying them individually (``%function_name?``); |
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335 | 336 | this is just a summary: |
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336 | 337 | |
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337 | 338 | * **%pdoc <object>**: Print (or run through a pager if too long) the |
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338 | 339 | docstring for an object. If the given object is a class, it will |
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339 | 340 | print both the class and the constructor docstrings. |
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340 | 341 | * **%pdef <object>**: Print the call signature for any callable |
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341 | 342 | object. If the object is a class, print the constructor information. |
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342 | 343 | * **%psource <object>**: Print (or run through a pager if too long) |
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343 | 344 | the source code for an object. |
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344 | 345 | * **%pfile <object>**: Show the entire source file where an object was |
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345 | 346 | defined via a pager, opening it at the line where the object |
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346 | 347 | definition begins. |
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347 | 348 | * **%who/%whos**: These functions give information about identifiers |
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348 | 349 | you have defined interactively (not things you loaded or defined |
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349 | 350 | in your configuration files). %who just prints a list of |
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350 | 351 | identifiers and %whos prints a table with some basic details about |
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351 | 352 | each identifier. |
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352 | 353 | |
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353 | 354 | Note that the dynamic object information functions (?/??, ``%pdoc``, |
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354 | 355 | ``%pfile``, ``%pdef``, ``%psource``) work on object attributes, as well as |
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355 | 356 | directly on variables. For example, after doing ``import os``, you can use |
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356 | 357 | ``os.path.abspath??``. |
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357 | 358 | |
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358 | 359 | .. _readline: |
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359 | 360 | |
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360 | 361 | Readline-based features |
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361 | 362 | ----------------------- |
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362 | 363 | |
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363 | 364 | These features require the GNU readline library, so they won't work if your |
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364 | 365 | Python installation lacks readline support. We will first describe the default |
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365 | 366 | behavior IPython uses, and then how to change it to suit your preferences. |
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366 | 367 | |
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367 | 368 | |
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368 | 369 | Command line completion |
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369 | 370 | +++++++++++++++++++++++ |
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370 | 371 | |
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371 | 372 | At any time, hitting TAB will complete any available python commands or |
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372 | 373 | variable names, and show you a list of the possible completions if |
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373 | 374 | there's no unambiguous one. It will also complete filenames in the |
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374 | 375 | current directory if no python names match what you've typed so far. |
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375 | 376 | |
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376 | 377 | |
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377 | 378 | Search command history |
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378 | 379 | ++++++++++++++++++++++ |
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379 | 380 | |
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380 | 381 | IPython provides two ways for searching through previous input and thus |
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381 | 382 | reduce the need for repetitive typing: |
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382 | 383 | |
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383 | 384 | 1. Start typing, and then use Ctrl-p (previous,up) and Ctrl-n |
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384 | 385 | (next,down) to search through only the history items that match |
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385 | 386 | what you've typed so far. If you use Ctrl-p/Ctrl-n at a blank |
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386 | 387 | prompt, they just behave like normal arrow keys. |
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387 | 388 | 2. Hit Ctrl-r: opens a search prompt. Begin typing and the system |
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388 | 389 | searches your history for lines that contain what you've typed so |
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389 | 390 | far, completing as much as it can. |
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390 | 391 | |
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391 | 392 | |
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392 | 393 | Persistent command history across sessions |
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393 | 394 | ++++++++++++++++++++++++++++++++++++++++++ |
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394 | 395 | |
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395 | 396 | IPython will save your input history when it leaves and reload it next |
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396 | 397 | time you restart it. By default, the history file is named |
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397 | 398 | $IPYTHONDIR/profile_<name>/history.sqlite. This allows you to keep |
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398 | 399 | separate histories related to various tasks: commands related to |
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399 | 400 | numerical work will not be clobbered by a system shell history, for |
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400 | 401 | example. |
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401 | 402 | |
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402 | 403 | |
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403 | 404 | Autoindent |
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404 | 405 | ++++++++++ |
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405 | 406 | |
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406 | 407 | IPython can recognize lines ending in ':' and indent the next line, |
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407 | 408 | while also un-indenting automatically after 'raise' or 'return'. |
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408 | 409 | |
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409 | 410 | This feature uses the readline library, so it will honor your |
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410 | 411 | :file:`~/.inputrc` configuration (or whatever file your INPUTRC variable points |
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411 | 412 | to). Adding the following lines to your :file:`.inputrc` file can make |
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412 | 413 | indenting/unindenting more convenient (M-i indents, M-u unindents):: |
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413 | 414 | |
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414 | 415 | # if you don't already have a ~/.inputrc file, you need this include: |
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415 | 416 | $include /etc/inputrc |
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416 | 417 | |
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417 | 418 | $if Python |
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418 | 419 | "\M-i": " " |
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419 | 420 | "\M-u": "\d\d\d\d" |
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420 | 421 | $endif |
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421 | 422 | |
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422 | 423 | Note that there are 4 spaces between the quote marks after "M-i" above. |
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423 | 424 | |
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424 | 425 | .. warning:: |
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425 | 426 | |
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426 | 427 | Setting the above indents will cause problems with unicode text entry in |
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427 | 428 | the terminal. |
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428 | 429 | |
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429 | 430 | .. warning:: |
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430 | 431 | |
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431 | 432 | Autoindent is ON by default, but it can cause problems with the pasting of |
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432 | 433 | multi-line indented code (the pasted code gets re-indented on each line). A |
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433 | 434 | magic function %autoindent allows you to toggle it on/off at runtime. You |
|
434 | 435 | can also disable it permanently on in your :file:`ipython_config.py` file |
|
435 | 436 | (set TerminalInteractiveShell.autoindent=False). |
|
436 | 437 | |
|
437 | 438 | If you want to paste multiple lines in the terminal, it is recommended that |
|
438 | 439 | you use ``%paste``. |
|
439 | 440 | |
|
440 | 441 | |
|
441 | 442 | Customizing readline behavior |
|
442 | 443 | +++++++++++++++++++++++++++++ |
|
443 | 444 | |
|
444 | 445 | All these features are based on the GNU readline library, which has an |
|
445 | 446 | extremely customizable interface. Normally, readline is configured via a |
|
446 | 447 | file which defines the behavior of the library; the details of the |
|
447 | 448 | syntax for this can be found in the readline documentation available |
|
448 | 449 | with your system or on the Internet. IPython doesn't read this file (if |
|
449 | 450 | it exists) directly, but it does support passing to readline valid |
|
450 | 451 | options via a simple interface. In brief, you can customize readline by |
|
451 | 452 | setting the following options in your configuration file (note |
|
452 | 453 | that these options can not be specified at the command line): |
|
453 | 454 | |
|
454 | 455 | * **readline_parse_and_bind**: this holds a list of strings to be executed |
|
455 | 456 | via a readline.parse_and_bind() command. The syntax for valid commands |
|
456 | 457 | of this kind can be found by reading the documentation for the GNU |
|
457 | 458 | readline library, as these commands are of the kind which readline |
|
458 | 459 | accepts in its configuration file. |
|
459 | 460 | * **readline_remove_delims**: a string of characters to be removed |
|
460 | 461 | from the default word-delimiters list used by readline, so that |
|
461 | 462 | completions may be performed on strings which contain them. Do not |
|
462 | 463 | change the default value unless you know what you're doing. |
|
463 | 464 | |
|
464 | 465 | You will find the default values in your configuration file. |
|
465 | 466 | |
|
466 | 467 | |
|
467 | 468 | Session logging and restoring |
|
468 | 469 | ----------------------------- |
|
469 | 470 | |
|
470 | 471 | You can log all input from a session either by starting IPython with the |
|
471 | 472 | command line switch ``--logfile=foo.py`` (see :ref:`here <command_line_options>`) |
|
472 | 473 | or by activating the logging at any moment with the magic function %logstart. |
|
473 | 474 | |
|
474 | 475 | Log files can later be reloaded by running them as scripts and IPython |
|
475 | 476 | will attempt to 'replay' the log by executing all the lines in it, thus |
|
476 | 477 | restoring the state of a previous session. This feature is not quite |
|
477 | 478 | perfect, but can still be useful in many cases. |
|
478 | 479 | |
|
479 | 480 | The log files can also be used as a way to have a permanent record of |
|
480 | 481 | any code you wrote while experimenting. Log files are regular text files |
|
481 | 482 | which you can later open in your favorite text editor to extract code or |
|
482 | 483 | to 'clean them up' before using them to replay a session. |
|
483 | 484 | |
|
484 | 485 | The `%logstart` function for activating logging in mid-session is used as |
|
485 | 486 | follows:: |
|
486 | 487 | |
|
487 | 488 | %logstart [log_name [log_mode]] |
|
488 | 489 | |
|
489 | 490 | If no name is given, it defaults to a file named 'ipython_log.py' in your |
|
490 | 491 | current working directory, in 'rotate' mode (see below). |
|
491 | 492 | |
|
492 | 493 | '%logstart name' saves to file 'name' in 'backup' mode. It saves your |
|
493 | 494 | history up to that point and then continues logging. |
|
494 | 495 | |
|
495 | 496 | %logstart takes a second optional parameter: logging mode. This can be |
|
496 | 497 | one of (note that the modes are given unquoted): |
|
497 | 498 | |
|
498 | 499 | * [over:] overwrite existing log_name. |
|
499 | 500 | * [backup:] rename (if exists) to log_name~ and start log_name. |
|
500 | 501 | * [append:] well, that says it. |
|
501 | 502 | * [rotate:] create rotating logs log_name.1~, log_name.2~, etc. |
|
502 | 503 | |
|
503 | 504 | The %logoff and %logon functions allow you to temporarily stop and |
|
504 | 505 | resume logging to a file which had previously been started with |
|
505 | 506 | %logstart. They will fail (with an explanation) if you try to use them |
|
506 | 507 | before logging has been started. |
|
507 | 508 | |
|
508 | 509 | .. _system_shell_access: |
|
509 | 510 | |
|
510 | 511 | System shell access |
|
511 | 512 | ------------------- |
|
512 | 513 | |
|
513 | 514 | Any input line beginning with a ! character is passed verbatim (minus |
|
514 | 515 | the !, of course) to the underlying operating system. For example, |
|
515 | 516 | typing ``!ls`` will run 'ls' in the current directory. |
|
516 | 517 | |
|
517 | 518 | Manual capture of command output |
|
518 | 519 | -------------------------------- |
|
519 | 520 | |
|
520 | 521 | You can assign the result of a system command to a Python variable with the |
|
521 | 522 | syntax ``myfiles = !ls``. This gets machine readable output from stdout |
|
522 | 523 | (e.g. without colours), and splits on newlines. To explicitly get this sort of |
|
523 | 524 | output without assigning to a variable, use two exclamation marks (``!!ls``) or |
|
524 | 525 | the ``%sx`` magic command. |
|
525 | 526 | |
|
526 | 527 | The captured list has some convenience features. ``myfiles.n`` or ``myfiles.s`` |
|
527 | 528 | returns a string delimited by newlines or spaces, respectively. ``myfiles.p`` |
|
528 | 529 | produces `path objects <http://pypi.python.org/pypi/path.py>`_ from the list items. |
|
529 | 530 | See :ref:`string_lists` for details. |
|
530 | 531 | |
|
531 | 532 | IPython also allows you to expand the value of python variables when |
|
532 | 533 | making system calls. Wrap variables or expressions in {braces}:: |
|
533 | 534 | |
|
534 | 535 | In [1]: pyvar = 'Hello world' |
|
535 | 536 | In [2]: !echo "A python variable: {pyvar}" |
|
536 | 537 | A python variable: Hello world |
|
537 | 538 | In [3]: import math |
|
538 | 539 | In [4]: x = 8 |
|
539 | 540 | In [5]: !echo {math.factorial(x)} |
|
540 | 541 | 40320 |
|
541 | 542 | |
|
542 | 543 | For simple cases, you can alternatively prepend $ to a variable name:: |
|
543 | 544 | |
|
544 | 545 | In [6]: !echo $sys.argv |
|
545 | 546 | [/home/fperez/usr/bin/ipython] |
|
546 | 547 | In [7]: !echo "A system variable: $$HOME" # Use $$ for literal $ |
|
547 | 548 | A system variable: /home/fperez |
|
548 | 549 | |
|
549 | 550 | System command aliases |
|
550 | 551 | ---------------------- |
|
551 | 552 | |
|
552 | 553 | The %alias magic function allows you to define magic functions which are in fact |
|
553 | 554 | system shell commands. These aliases can have parameters. |
|
554 | 555 | |
|
555 | 556 | ``%alias alias_name cmd`` defines 'alias_name' as an alias for 'cmd' |
|
556 | 557 | |
|
557 | 558 | Then, typing ``alias_name params`` will execute the system command 'cmd |
|
558 | 559 | params' (from your underlying operating system). |
|
559 | 560 | |
|
560 | 561 | You can also define aliases with parameters using %s specifiers (one per |
|
561 | 562 | parameter). The following example defines the parts function as an |
|
562 | 563 | alias to the command 'echo first %s second %s' where each %s will be |
|
563 | 564 | replaced by a positional parameter to the call to %parts:: |
|
564 | 565 | |
|
565 | 566 | In [1]: %alias parts echo first %s second %s |
|
566 | 567 | In [2]: parts A B |
|
567 | 568 | first A second B |
|
568 | 569 | In [3]: parts A |
|
569 | 570 | ERROR: Alias <parts> requires 2 arguments, 1 given. |
|
570 | 571 | |
|
571 | 572 | If called with no parameters, %alias prints the table of currently |
|
572 | 573 | defined aliases. |
|
573 | 574 | |
|
574 | 575 | The %rehashx magic allows you to load your entire $PATH as |
|
575 | 576 | ipython aliases. See its docstring for further details. |
|
576 | 577 | |
|
577 | 578 | |
|
578 | 579 | .. _dreload: |
|
579 | 580 | |
|
580 | 581 | Recursive reload |
|
581 | 582 | ---------------- |
|
582 | 583 | |
|
583 | 584 | The :mod:`IPython.lib.deepreload` module allows you to recursively reload a |
|
584 | 585 | module: changes made to any of its dependencies will be reloaded without |
|
585 | 586 | having to exit. To start using it, do:: |
|
586 | 587 | |
|
587 | 588 | from IPython.lib.deepreload import reload as dreload |
|
588 | 589 | |
|
589 | 590 | |
|
590 | 591 | Verbose and colored exception traceback printouts |
|
591 | 592 | ------------------------------------------------- |
|
592 | 593 | |
|
593 | 594 | IPython provides the option to see very detailed exception tracebacks, |
|
594 | 595 | which can be especially useful when debugging large programs. You can |
|
595 | 596 | run any Python file with the %run function to benefit from these |
|
596 | 597 | detailed tracebacks. Furthermore, both normal and verbose tracebacks can |
|
597 | 598 | be colored (if your terminal supports it) which makes them much easier |
|
598 | 599 | to parse visually. |
|
599 | 600 | |
|
600 | 601 | See the magic xmode and colors functions for details (just type %magic). |
|
601 | 602 | |
|
602 | 603 | These features are basically a terminal version of Ka-Ping Yee's cgitb |
|
603 | 604 | module, now part of the standard Python library. |
|
604 | 605 | |
|
605 | 606 | |
|
606 | 607 | .. _input_caching: |
|
607 | 608 | |
|
608 | 609 | Input caching system |
|
609 | 610 | -------------------- |
|
610 | 611 | |
|
611 | 612 | IPython offers numbered prompts (In/Out) with input and output caching |
|
612 | 613 | (also referred to as 'input history'). All input is saved and can be |
|
613 | 614 | retrieved as variables (besides the usual arrow key recall), in |
|
614 | 615 | addition to the %rep magic command that brings a history entry |
|
615 | 616 | up for editing on the next command line. |
|
616 | 617 | |
|
617 | 618 | The following GLOBAL variables always exist (so don't overwrite them!): |
|
618 | 619 | |
|
619 | 620 | * _i, _ii, _iii: store previous, next previous and next-next previous inputs. |
|
620 | 621 | * In, _ih : a list of all inputs; _ih[n] is the input from line n. If you |
|
621 | 622 | overwrite In with a variable of your own, you can remake the assignment to the |
|
622 | 623 | internal list with a simple ``In=_ih``. |
|
623 | 624 | |
|
624 | 625 | Additionally, global variables named _i<n> are dynamically created (<n> |
|
625 | 626 | being the prompt counter), so ``_i<n> == _ih[<n>] == In[<n>]``. |
|
626 | 627 | |
|
627 | 628 | For example, what you typed at prompt 14 is available as _i14, _ih[14] |
|
628 | 629 | and In[14]. |
|
629 | 630 | |
|
630 | 631 | This allows you to easily cut and paste multi line interactive prompts |
|
631 | 632 | by printing them out: they print like a clean string, without prompt |
|
632 | 633 | characters. You can also manipulate them like regular variables (they |
|
633 | 634 | are strings), modify or exec them (typing ``exec _i9`` will re-execute the |
|
634 | 635 | contents of input prompt 9. |
|
635 | 636 | |
|
636 | 637 | You can also re-execute multiple lines of input easily by using the |
|
637 | 638 | magic %rerun or %macro functions. The macro system also allows you to re-execute |
|
638 | 639 | previous lines which include magic function calls (which require special |
|
639 | 640 | processing). Type %macro? for more details on the macro system. |
|
640 | 641 | |
|
641 | 642 | A history function %hist allows you to see any part of your input |
|
642 | 643 | history by printing a range of the _i variables. |
|
643 | 644 | |
|
644 | 645 | You can also search ('grep') through your history by typing |
|
645 | 646 | ``%hist -g somestring``. This is handy for searching for URLs, IP addresses, |
|
646 | 647 | etc. You can bring history entries listed by '%hist -g' up for editing |
|
647 | 648 | with the %recall command, or run them immediately with %rerun. |
|
648 | 649 | |
|
649 | 650 | .. _output_caching: |
|
650 | 651 | |
|
651 | 652 | Output caching system |
|
652 | 653 | --------------------- |
|
653 | 654 | |
|
654 | 655 | For output that is returned from actions, a system similar to the input |
|
655 | 656 | cache exists but using _ instead of _i. Only actions that produce a |
|
656 | 657 | result (NOT assignments, for example) are cached. If you are familiar |
|
657 | 658 | with Mathematica, IPython's _ variables behave exactly like |
|
658 | 659 | Mathematica's % variables. |
|
659 | 660 | |
|
660 | 661 | The following GLOBAL variables always exist (so don't overwrite them!): |
|
661 | 662 | |
|
662 | 663 | * [_] (a single underscore) : stores previous output, like Python's |
|
663 | 664 | default interpreter. |
|
664 | 665 | * [__] (two underscores): next previous. |
|
665 | 666 | * [___] (three underscores): next-next previous. |
|
666 | 667 | |
|
667 | 668 | Additionally, global variables named _<n> are dynamically created (<n> |
|
668 | 669 | being the prompt counter), such that the result of output <n> is always |
|
669 | 670 | available as _<n> (don't use the angle brackets, just the number, e.g. |
|
670 | 671 | _21). |
|
671 | 672 | |
|
672 | 673 | These variables are also stored in a global dictionary (not a |
|
673 | 674 | list, since it only has entries for lines which returned a result) |
|
674 | 675 | available under the names _oh and Out (similar to _ih and In). So the |
|
675 | 676 | output from line 12 can be obtained as _12, Out[12] or _oh[12]. If you |
|
676 | 677 | accidentally overwrite the Out variable you can recover it by typing |
|
677 | 678 | 'Out=_oh' at the prompt. |
|
678 | 679 | |
|
679 | 680 | This system obviously can potentially put heavy memory demands on your |
|
680 | 681 | system, since it prevents Python's garbage collector from removing any |
|
681 | 682 | previously computed results. You can control how many results are kept |
|
682 | 683 | in memory with the option (at the command line or in your configuration |
|
683 | 684 | file) cache_size. If you set it to 0, the whole system is completely |
|
684 | 685 | disabled and the prompts revert to the classic '>>>' of normal Python. |
|
685 | 686 | |
|
686 | 687 | |
|
687 | 688 | Directory history |
|
688 | 689 | ----------------- |
|
689 | 690 | |
|
690 | 691 | Your history of visited directories is kept in the global list _dh, and |
|
691 | 692 | the magic %cd command can be used to go to any entry in that list. The |
|
692 | 693 | %dhist command allows you to view this history. Do ``cd -<TAB>`` to |
|
693 | 694 | conveniently view the directory history. |
|
694 | 695 | |
|
695 | 696 | |
|
696 | 697 | Automatic parentheses and quotes |
|
697 | 698 | -------------------------------- |
|
698 | 699 | |
|
699 | 700 | These features were adapted from Nathan Gray's LazyPython. They are |
|
700 | 701 | meant to allow less typing for common situations. |
|
701 | 702 | |
|
702 | 703 | |
|
703 | 704 | Automatic parentheses |
|
704 | 705 | +++++++++++++++++++++ |
|
705 | 706 | |
|
706 | 707 | Callable objects (i.e. functions, methods, etc) can be invoked like this |
|
707 | 708 | (notice the commas between the arguments):: |
|
708 | 709 | |
|
709 | 710 | In [1]: callable_ob arg1, arg2, arg3 |
|
710 | 711 | ------> callable_ob(arg1, arg2, arg3) |
|
711 | 712 | |
|
712 | 713 | You can force automatic parentheses by using '/' as the first character |
|
713 | 714 | of a line. For example:: |
|
714 | 715 | |
|
715 | 716 | In [2]: /globals # becomes 'globals()' |
|
716 | 717 | |
|
717 | 718 | Note that the '/' MUST be the first character on the line! This won't work:: |
|
718 | 719 | |
|
719 | 720 | In [3]: print /globals # syntax error |
|
720 | 721 | |
|
721 | 722 | In most cases the automatic algorithm should work, so you should rarely |
|
722 | 723 | need to explicitly invoke /. One notable exception is if you are trying |
|
723 | 724 | to call a function with a list of tuples as arguments (the parenthesis |
|
724 | 725 | will confuse IPython):: |
|
725 | 726 | |
|
726 | 727 | In [4]: zip (1,2,3),(4,5,6) # won't work |
|
727 | 728 | |
|
728 | 729 | but this will work:: |
|
729 | 730 | |
|
730 | 731 | In [5]: /zip (1,2,3),(4,5,6) |
|
731 | 732 | ------> zip ((1,2,3),(4,5,6)) |
|
732 | 733 | Out[5]: [(1, 4), (2, 5), (3, 6)] |
|
733 | 734 | |
|
734 | 735 | IPython tells you that it has altered your command line by displaying |
|
735 | 736 | the new command line preceded by ->. e.g.:: |
|
736 | 737 | |
|
737 | 738 | In [6]: callable list |
|
738 | 739 | ------> callable(list) |
|
739 | 740 | |
|
740 | 741 | |
|
741 | 742 | Automatic quoting |
|
742 | 743 | +++++++++++++++++ |
|
743 | 744 | |
|
744 | 745 | You can force automatic quoting of a function's arguments by using ',' |
|
745 | 746 | or ';' as the first character of a line. For example:: |
|
746 | 747 | |
|
747 | 748 | In [1]: ,my_function /home/me # becomes my_function("/home/me") |
|
748 | 749 | |
|
749 | 750 | If you use ';' the whole argument is quoted as a single string, while ',' splits |
|
750 | 751 | on whitespace:: |
|
751 | 752 | |
|
752 | 753 | In [2]: ,my_function a b c # becomes my_function("a","b","c") |
|
753 | 754 | |
|
754 | 755 | In [3]: ;my_function a b c # becomes my_function("a b c") |
|
755 | 756 | |
|
756 | 757 | Note that the ',' or ';' MUST be the first character on the line! This |
|
757 | 758 | won't work:: |
|
758 | 759 | |
|
759 | 760 | In [4]: x = ,my_function /home/me # syntax error |
|
760 | 761 | |
|
761 | 762 | IPython as your default Python environment |
|
762 | 763 | ========================================== |
|
763 | 764 | |
|
764 | 765 | Python honors the environment variable :envvar:`PYTHONSTARTUP` and will |
|
765 | 766 | execute at startup the file referenced by this variable. If you put the |
|
766 | 767 | following code at the end of that file, then IPython will be your working |
|
767 | 768 | environment anytime you start Python:: |
|
768 | 769 | |
|
769 | 770 | import os, IPython |
|
770 | 771 | os.environ['PYTHONSTARTUP'] = '' # Prevent running this again |
|
771 | 772 | IPython.start_ipython() |
|
772 | 773 | raise SystemExit |
|
773 | 774 | |
|
774 | 775 | The ``raise SystemExit`` is needed to exit Python when |
|
775 | 776 | it finishes, otherwise you'll be back at the normal Python '>>>' |
|
776 | 777 | prompt. |
|
777 | 778 | |
|
778 | 779 | This is probably useful to developers who manage multiple Python |
|
779 | 780 | versions and don't want to have correspondingly multiple IPython |
|
780 | 781 | versions. Note that in this mode, there is no way to pass IPython any |
|
781 | 782 | command-line options, as those are trapped first by Python itself. |
|
782 | 783 | |
|
783 | 784 | .. _Embedding: |
|
784 | 785 | |
|
785 | 786 | Embedding IPython |
|
786 | 787 | ================= |
|
787 | 788 | |
|
788 | 789 | You can start a regular IPython session with |
|
789 | 790 | |
|
790 | 791 | .. sourcecode:: python |
|
791 | 792 | |
|
792 | 793 | import IPython |
|
793 | 794 | IPython.start_ipython() |
|
794 | 795 | |
|
795 | 796 | at any point in your program. This will load IPython configuration, |
|
796 | 797 | startup files, and everything, just as if it were a normal IPython session. |
|
797 | 798 | In addition to this, |
|
798 | 799 | it is possible to embed an IPython instance inside your own Python programs. |
|
799 | 800 | This allows you to evaluate dynamically the state of your code, |
|
800 | 801 | operate with your variables, analyze them, etc. Note however that |
|
801 | 802 | any changes you make to values while in the shell do not propagate back |
|
802 | 803 | to the running code, so it is safe to modify your values because you |
|
803 | 804 | won't break your code in bizarre ways by doing so. |
|
804 | 805 | |
|
805 | 806 | .. note:: |
|
806 | 807 | |
|
807 | 808 | At present, embedding IPython cannot be done from inside IPython. |
|
808 | 809 | Run the code samples below outside IPython. |
|
809 | 810 | |
|
810 | 811 | This feature allows you to easily have a fully functional python |
|
811 | 812 | environment for doing object introspection anywhere in your code with a |
|
812 | 813 | simple function call. In some cases a simple print statement is enough, |
|
813 | 814 | but if you need to do more detailed analysis of a code fragment this |
|
814 | 815 | feature can be very valuable. |
|
815 | 816 | |
|
816 | 817 | It can also be useful in scientific computing situations where it is |
|
817 | 818 | common to need to do some automatic, computationally intensive part and |
|
818 | 819 | then stop to look at data, plots, etc. |
|
819 | 820 | Opening an IPython instance will give you full access to your data and |
|
820 | 821 | functions, and you can resume program execution once you are done with |
|
821 | 822 | the interactive part (perhaps to stop again later, as many times as |
|
822 | 823 | needed). |
|
823 | 824 | |
|
824 | 825 | The following code snippet is the bare minimum you need to include in |
|
825 | 826 | your Python programs for this to work (detailed examples follow later):: |
|
826 | 827 | |
|
827 | 828 | from IPython import embed |
|
828 | 829 | |
|
829 | 830 | embed() # this call anywhere in your program will start IPython |
|
830 | 831 | |
|
831 | 832 | .. note:: |
|
832 | 833 | |
|
833 | 834 | As of 0.13, you can embed an IPython *kernel*, for use with qtconsole, |
|
834 | 835 | etc. via ``IPython.embed_kernel()`` instead of ``IPython.embed()``. |
|
835 | 836 | It should function just the same as regular embed, but you connect |
|
836 | 837 | an external frontend rather than IPython starting up in the local |
|
837 | 838 | terminal. |
|
838 | 839 | |
|
839 | 840 | You can run embedded instances even in code which is itself being run at |
|
840 | 841 | the IPython interactive prompt with '%run <filename>'. Since it's easy |
|
841 | 842 | to get lost as to where you are (in your top-level IPython or in your |
|
842 | 843 | embedded one), it's a good idea in such cases to set the in/out prompts |
|
843 | 844 | to something different for the embedded instances. The code examples |
|
844 | 845 | below illustrate this. |
|
845 | 846 | |
|
846 | 847 | You can also have multiple IPython instances in your program and open |
|
847 | 848 | them separately, for example with different options for data |
|
848 | 849 | presentation. If you close and open the same instance multiple times, |
|
849 | 850 | its prompt counters simply continue from each execution to the next. |
|
850 | 851 | |
|
851 | 852 | Please look at the docstrings in the :mod:`~IPython.frontend.terminal.embed` |
|
852 | 853 | module for more details on the use of this system. |
|
853 | 854 | |
|
854 | 855 | The following sample file illustrating how to use the embedding |
|
855 | 856 | functionality is provided in the examples directory as example-embed.py. |
|
856 | 857 | It should be fairly self-explanatory: |
|
857 | 858 | |
|
858 | 859 | .. literalinclude:: ../../../examples/core/example-embed.py |
|
859 | 860 | :language: python |
|
860 | 861 | |
|
861 | 862 | Once you understand how the system functions, you can use the following |
|
862 | 863 | code fragments in your programs which are ready for cut and paste: |
|
863 | 864 | |
|
864 | 865 | .. literalinclude:: ../../../examples/core/example-embed-short.py |
|
865 | 866 | :language: python |
|
866 | 867 | |
|
867 | 868 | Using the Python debugger (pdb) |
|
868 | 869 | =============================== |
|
869 | 870 | |
|
870 | 871 | Running entire programs via pdb |
|
871 | 872 | ------------------------------- |
|
872 | 873 | |
|
873 | 874 | pdb, the Python debugger, is a powerful interactive debugger which |
|
874 | 875 | allows you to step through code, set breakpoints, watch variables, |
|
875 | 876 | etc. IPython makes it very easy to start any script under the control |
|
876 | 877 | of pdb, regardless of whether you have wrapped it into a 'main()' |
|
877 | 878 | function or not. For this, simply type '%run -d myscript' at an |
|
878 | 879 | IPython prompt. See the %run command's documentation (via '%run?' or |
|
879 | 880 | in Sec. magic_ for more details, including how to control where pdb |
|
880 | 881 | will stop execution first. |
|
881 | 882 | |
|
882 | 883 | For more information on the use of the pdb debugger, read the included |
|
883 | 884 | pdb.doc file (part of the standard Python distribution). On a stock |
|
884 | 885 | Linux system it is located at /usr/lib/python2.3/pdb.doc, but the |
|
885 | 886 | easiest way to read it is by using the help() function of the pdb module |
|
886 | 887 | as follows (in an IPython prompt):: |
|
887 | 888 | |
|
888 | 889 | In [1]: import pdb |
|
889 | 890 | In [2]: pdb.help() |
|
890 | 891 | |
|
891 | 892 | This will load the pdb.doc document in a file viewer for you automatically. |
|
892 | 893 | |
|
893 | 894 | |
|
894 | 895 | Automatic invocation of pdb on exceptions |
|
895 | 896 | ----------------------------------------- |
|
896 | 897 | |
|
897 | 898 | IPython, if started with the ``--pdb`` option (or if the option is set in |
|
898 | 899 | your config file) can call the Python pdb debugger every time your code |
|
899 | 900 | triggers an uncaught exception. This feature |
|
900 | 901 | can also be toggled at any time with the %pdb magic command. This can be |
|
901 | 902 | extremely useful in order to find the origin of subtle bugs, because pdb |
|
902 | 903 | opens up at the point in your code which triggered the exception, and |
|
903 | 904 | while your program is at this point 'dead', all the data is still |
|
904 | 905 | available and you can walk up and down the stack frame and understand |
|
905 | 906 | the origin of the problem. |
|
906 | 907 | |
|
907 | 908 | Furthermore, you can use these debugging facilities both with the |
|
908 | 909 | embedded IPython mode and without IPython at all. For an embedded shell |
|
909 | 910 | (see sec. Embedding_), simply call the constructor with |
|
910 | 911 | ``--pdb`` in the argument string and pdb will automatically be called if an |
|
911 | 912 | uncaught exception is triggered by your code. |
|
912 | 913 | |
|
913 | 914 | For stand-alone use of the feature in your programs which do not use |
|
914 | 915 | IPython at all, put the following lines toward the top of your 'main' |
|
915 | 916 | routine:: |
|
916 | 917 | |
|
917 | 918 | import sys |
|
918 | 919 | from IPython.core import ultratb |
|
919 | 920 | sys.excepthook = ultratb.FormattedTB(mode='Verbose', |
|
920 | 921 | color_scheme='Linux', call_pdb=1) |
|
921 | 922 | |
|
922 | 923 | The mode keyword can be either 'Verbose' or 'Plain', giving either very |
|
923 | 924 | detailed or normal tracebacks respectively. The color_scheme keyword can |
|
924 | 925 | be one of 'NoColor', 'Linux' (default) or 'LightBG'. These are the same |
|
925 | 926 | options which can be set in IPython with ``--colors`` and ``--xmode``. |
|
926 | 927 | |
|
927 | 928 | This will give any of your programs detailed, colored tracebacks with |
|
928 | 929 | automatic invocation of pdb. |
|
929 | 930 | |
|
930 | 931 | |
|
931 | 932 | Extensions for syntax processing |
|
932 | 933 | ================================ |
|
933 | 934 | |
|
934 | 935 | This isn't for the faint of heart, because the potential for breaking |
|
935 | 936 | things is quite high. But it can be a very powerful and useful feature. |
|
936 | 937 | In a nutshell, you can redefine the way IPython processes the user input |
|
937 | 938 | line to accept new, special extensions to the syntax without needing to |
|
938 | 939 | change any of IPython's own code. |
|
939 | 940 | |
|
940 | 941 | In the IPython/extensions directory you will find some examples |
|
941 | 942 | supplied, which we will briefly describe now. These can be used 'as is' |
|
942 | 943 | (and both provide very useful functionality), or you can use them as a |
|
943 | 944 | starting point for writing your own extensions. |
|
944 | 945 | |
|
945 | 946 | .. _pasting_with_prompts: |
|
946 | 947 | |
|
947 | 948 | Pasting of code starting with Python or IPython prompts |
|
948 | 949 | ------------------------------------------------------- |
|
949 | 950 | |
|
950 | 951 | IPython is smart enough to filter out input prompts, be they plain Python ones |
|
951 | 952 | (``>>>`` and ``...``) or IPython ones (``In [N]:`` and ``...:``). You can |
|
952 | 953 | therefore copy and paste from existing interactive sessions without worry. |
|
953 | 954 | |
|
954 | 955 | The following is a 'screenshot' of how things work, copying an example from the |
|
955 | 956 | standard Python tutorial:: |
|
956 | 957 | |
|
957 | 958 | In [1]: >>> # Fibonacci series: |
|
958 | 959 | |
|
959 | 960 | In [2]: ... # the sum of two elements defines the next |
|
960 | 961 | |
|
961 | 962 | In [3]: ... a, b = 0, 1 |
|
962 | 963 | |
|
963 | 964 | In [4]: >>> while b < 10: |
|
964 |
...: ... print |
|
|
965 | ...: ... print(b) | |
|
965 | 966 | ...: ... a, b = b, a+b |
|
966 | 967 | ...: |
|
967 | 968 | 1 |
|
968 | 969 | 1 |
|
969 | 970 | 2 |
|
970 | 971 | 3 |
|
971 | 972 | 5 |
|
972 | 973 | 8 |
|
973 | 974 | |
|
974 | 975 | And pasting from IPython sessions works equally well:: |
|
975 | 976 | |
|
976 | 977 | In [1]: In [5]: def f(x): |
|
977 | 978 | ...: ...: "A simple function" |
|
978 | 979 | ...: ...: return x**2 |
|
979 | 980 | ...: ...: |
|
980 | 981 | |
|
981 | 982 | In [2]: f(3) |
|
982 | 983 | Out[2]: 9 |
|
983 | 984 | |
|
984 | 985 | .. _gui_support: |
|
985 | 986 | |
|
986 | 987 | GUI event loop support |
|
987 | 988 | ====================== |
|
988 | 989 | |
|
989 | 990 | .. versionadded:: 0.11 |
|
990 | 991 | The ``%gui`` magic and :mod:`IPython.lib.inputhook`. |
|
991 | 992 | |
|
992 | 993 | IPython has excellent support for working interactively with Graphical User |
|
993 | 994 | Interface (GUI) toolkits, such as wxPython, PyQt4/PySide, PyGTK and Tk. This is |
|
994 | 995 | implemented using Python's builtin ``PyOSInputHook`` hook. This implementation |
|
995 | 996 | is extremely robust compared to our previous thread-based version. The |
|
996 | 997 | advantages of this are: |
|
997 | 998 | |
|
998 | 999 | * GUIs can be enabled and disabled dynamically at runtime. |
|
999 | 1000 | * The active GUI can be switched dynamically at runtime. |
|
1000 | 1001 | * In some cases, multiple GUIs can run simultaneously with no problems. |
|
1001 | 1002 | * There is a developer API in :mod:`IPython.lib.inputhook` for customizing |
|
1002 | 1003 | all of these things. |
|
1003 | 1004 | |
|
1004 | 1005 | For users, enabling GUI event loop integration is simple. You simple use the |
|
1005 | 1006 | ``%gui`` magic as follows:: |
|
1006 | 1007 | |
|
1007 | 1008 | %gui [GUINAME] |
|
1008 | 1009 | |
|
1009 | 1010 | With no arguments, ``%gui`` removes all GUI support. Valid ``GUINAME`` |
|
1010 | 1011 | arguments are ``wx``, ``qt``, ``gtk`` and ``tk``. |
|
1011 | 1012 | |
|
1012 | 1013 | Thus, to use wxPython interactively and create a running :class:`wx.App` |
|
1013 | 1014 | object, do:: |
|
1014 | 1015 | |
|
1015 | 1016 | %gui wx |
|
1016 | 1017 | |
|
1017 | 1018 | For information on IPython's matplotlib_ integration (and the ``matplotlib`` |
|
1018 | 1019 | mode) see :ref:`this section <matplotlib_support>`. |
|
1019 | 1020 | |
|
1020 | 1021 | For developers that want to use IPython's GUI event loop integration in the |
|
1021 | 1022 | form of a library, these capabilities are exposed in library form in the |
|
1022 | 1023 | :mod:`IPython.lib.inputhook` and :mod:`IPython.lib.guisupport` modules. |
|
1023 | 1024 | Interested developers should see the module docstrings for more information, |
|
1024 | 1025 | but there are a few points that should be mentioned here. |
|
1025 | 1026 | |
|
1026 | 1027 | First, the ``PyOSInputHook`` approach only works in command line settings |
|
1027 | 1028 | where readline is activated. The integration with various eventloops |
|
1028 | 1029 | is handled somewhat differently (and more simply) when using the standalone |
|
1029 | 1030 | kernel, as in the qtconsole and notebook. |
|
1030 | 1031 | |
|
1031 | 1032 | Second, when using the ``PyOSInputHook`` approach, a GUI application should |
|
1032 | 1033 | *not* start its event loop. Instead all of this is handled by the |
|
1033 | 1034 | ``PyOSInputHook``. This means that applications that are meant to be used both |
|
1034 | 1035 | in IPython and as standalone apps need to have special code to detects how the |
|
1035 | 1036 | application is being run. We highly recommend using IPython's support for this. |
|
1036 | 1037 | Since the details vary slightly between toolkits, we point you to the various |
|
1037 | 1038 | examples in our source directory :file:`examples/lib` that demonstrate |
|
1038 | 1039 | these capabilities. |
|
1039 | 1040 | |
|
1040 | 1041 | Third, unlike previous versions of IPython, we no longer "hijack" (replace |
|
1041 | 1042 | them with no-ops) the event loops. This is done to allow applications that |
|
1042 | 1043 | actually need to run the real event loops to do so. This is often needed to |
|
1043 | 1044 | process pending events at critical points. |
|
1044 | 1045 | |
|
1045 | 1046 | Finally, we also have a number of examples in our source directory |
|
1046 | 1047 | :file:`examples/lib` that demonstrate these capabilities. |
|
1047 | 1048 | |
|
1048 | 1049 | PyQt and PySide |
|
1049 | 1050 | --------------- |
|
1050 | 1051 | |
|
1051 | 1052 | .. attempt at explanation of the complete mess that is Qt support |
|
1052 | 1053 | |
|
1053 | 1054 | When you use ``--gui=qt`` or ``--matplotlib=qt``, IPython can work with either |
|
1054 | 1055 | PyQt4 or PySide. There are three options for configuration here, because |
|
1055 | 1056 | PyQt4 has two APIs for QString and QVariant - v1, which is the default on |
|
1056 | 1057 | Python 2, and the more natural v2, which is the only API supported by PySide. |
|
1057 | 1058 | v2 is also the default for PyQt4 on Python 3. IPython's code for the QtConsole |
|
1058 | 1059 | uses v2, but you can still use any interface in your code, since the |
|
1059 | 1060 | Qt frontend is in a different process. |
|
1060 | 1061 | |
|
1061 | 1062 | The default will be to import PyQt4 without configuration of the APIs, thus |
|
1062 | 1063 | matching what most applications would expect. It will fall back of PySide if |
|
1063 | 1064 | PyQt4 is unavailable. |
|
1064 | 1065 | |
|
1065 | 1066 | If specified, IPython will respect the environment variable ``QT_API`` used |
|
1066 | 1067 | by ETS. ETS 4.0 also works with both PyQt4 and PySide, but it requires |
|
1067 | 1068 | PyQt4 to use its v2 API. So if ``QT_API=pyside`` PySide will be used, |
|
1068 | 1069 | and if ``QT_API=pyqt`` then PyQt4 will be used *with the v2 API* for |
|
1069 | 1070 | QString and QVariant, so ETS codes like MayaVi will also work with IPython. |
|
1070 | 1071 | |
|
1071 | 1072 | If you launch IPython in matplotlib mode with ``ipython --matplotlib=qt``, |
|
1072 | 1073 | then IPython will ask matplotlib which Qt library to use (only if QT_API is |
|
1073 | 1074 | *not set*), via the 'backend.qt4' rcParam. If matplotlib is version 1.0.1 or |
|
1074 | 1075 | older, then IPython will always use PyQt4 without setting the v2 APIs, since |
|
1075 | 1076 | neither v2 PyQt nor PySide work. |
|
1076 | 1077 | |
|
1077 | 1078 | .. warning:: |
|
1078 | 1079 | |
|
1079 | 1080 | Note that this means for ETS 4 to work with PyQt4, ``QT_API`` *must* be set |
|
1080 | 1081 | to work with IPython's qt integration, because otherwise PyQt4 will be |
|
1081 | 1082 | loaded in an incompatible mode. |
|
1082 | 1083 | |
|
1083 | 1084 | It also means that you must *not* have ``QT_API`` set if you want to |
|
1084 | 1085 | use ``--gui=qt`` with code that requires PyQt4 API v1. |
|
1085 | 1086 | |
|
1086 | 1087 | |
|
1087 | 1088 | .. _matplotlib_support: |
|
1088 | 1089 | |
|
1089 | 1090 | Plotting with matplotlib |
|
1090 | 1091 | ======================== |
|
1091 | 1092 | |
|
1092 | 1093 | matplotlib_ provides high quality 2D and 3D plotting for Python. matplotlib_ |
|
1093 | 1094 | can produce plots on screen using a variety of GUI toolkits, including Tk, |
|
1094 | 1095 | PyGTK, PyQt4 and wxPython. It also provides a number of commands useful for |
|
1095 | 1096 | scientific computing, all with a syntax compatible with that of the popular |
|
1096 | 1097 | Matlab program. |
|
1097 | 1098 | |
|
1098 | 1099 | To start IPython with matplotlib support, use the ``--matplotlib`` switch. If |
|
1099 | 1100 | IPython is already running, you can run the ``%matplotlib`` magic. If no |
|
1100 | 1101 | arguments are given, IPython will automatically detect your choice of |
|
1101 | 1102 | matplotlib backend. You can also request a specific backend with |
|
1102 | 1103 | ``%matplotlib backend``, where ``backend`` must be one of: 'tk', 'qt', 'wx', |
|
1103 | 1104 | 'gtk', 'osx'. In the web notebook and Qt console, 'inline' is also a valid |
|
1104 | 1105 | backend value, which produces static figures inlined inside the application |
|
1105 | 1106 | window instead of matplotlib's interactive figures that live in separate |
|
1106 | 1107 | windows. |
|
1107 | 1108 | |
|
1108 | 1109 | .. _interactive_demos: |
|
1109 | 1110 | |
|
1110 | 1111 | Interactive demos with IPython |
|
1111 | 1112 | ============================== |
|
1112 | 1113 | |
|
1113 | 1114 | IPython ships with a basic system for running scripts interactively in |
|
1114 | 1115 | sections, useful when presenting code to audiences. A few tags embedded |
|
1115 | 1116 | in comments (so that the script remains valid Python code) divide a file |
|
1116 | 1117 | into separate blocks, and the demo can be run one block at a time, with |
|
1117 | 1118 | IPython printing (with syntax highlighting) the block before executing |
|
1118 | 1119 | it, and returning to the interactive prompt after each block. The |
|
1119 | 1120 | interactive namespace is updated after each block is run with the |
|
1120 | 1121 | contents of the demo's namespace. |
|
1121 | 1122 | |
|
1122 | 1123 | This allows you to show a piece of code, run it and then execute |
|
1123 | 1124 | interactively commands based on the variables just created. Once you |
|
1124 | 1125 | want to continue, you simply execute the next block of the demo. The |
|
1125 | 1126 | following listing shows the markup necessary for dividing a script into |
|
1126 | 1127 | sections for execution as a demo: |
|
1127 | 1128 | |
|
1128 | 1129 | .. literalinclude:: ../../../examples/lib/example-demo.py |
|
1129 | 1130 | :language: python |
|
1130 | 1131 | |
|
1131 | 1132 | In order to run a file as a demo, you must first make a Demo object out |
|
1132 | 1133 | of it. If the file is named myscript.py, the following code will make a |
|
1133 | 1134 | demo:: |
|
1134 | 1135 | |
|
1135 | 1136 | from IPython.lib.demo import Demo |
|
1136 | 1137 | |
|
1137 | 1138 | mydemo = Demo('myscript.py') |
|
1138 | 1139 | |
|
1139 | 1140 | This creates the mydemo object, whose blocks you run one at a time by |
|
1140 | 1141 | simply calling the object with no arguments. If you have autocall active |
|
1141 | 1142 | in IPython (the default), all you need to do is type:: |
|
1142 | 1143 | |
|
1143 | 1144 | mydemo |
|
1144 | 1145 | |
|
1145 | 1146 | and IPython will call it, executing each block. Demo objects can be |
|
1146 | 1147 | restarted, you can move forward or back skipping blocks, re-execute the |
|
1147 | 1148 | last block, etc. Simply use the Tab key on a demo object to see its |
|
1148 | 1149 | methods, and call '?' on them to see their docstrings for more usage |
|
1149 | 1150 | details. In addition, the demo module itself contains a comprehensive |
|
1150 | 1151 | docstring, which you can access via:: |
|
1151 | 1152 | |
|
1152 | 1153 | from IPython.lib import demo |
|
1153 | 1154 | |
|
1154 | 1155 | demo? |
|
1155 | 1156 | |
|
1156 | 1157 | Limitations: It is important to note that these demos are limited to |
|
1157 | 1158 | fairly simple uses. In particular, you cannot break up sections within |
|
1158 | 1159 | indented code (loops, if statements, function definitions, etc.) |
|
1159 | 1160 | Supporting something like this would basically require tracking the |
|
1160 | 1161 | internal execution state of the Python interpreter, so only top-level |
|
1161 | 1162 | divisions are allowed. If you want to be able to open an IPython |
|
1162 | 1163 | instance at an arbitrary point in a program, you can use IPython's |
|
1163 | 1164 | embedding facilities, see :func:`IPython.embed` for details. |
|
1164 | 1165 | |
|
1165 | 1166 | .. include:: ../links.txt |
@@ -1,102 +1,102 b'' | |||
|
1 | 1 | .. _tips: |
|
2 | 2 | |
|
3 | 3 | ===================== |
|
4 | 4 | IPython Tips & Tricks |
|
5 | 5 | ===================== |
|
6 | 6 | |
|
7 | 7 | The `IPython cookbook |
|
8 | 8 | <https://github.com/ipython/ipython/wiki?path=Cookbook>`_ details more things |
|
9 | 9 | you can do with IPython. |
|
10 | 10 | |
|
11 | 11 | .. This is not in the current version: |
|
12 | 12 | |
|
13 | 13 | |
|
14 | 14 | Embed IPython in your programs |
|
15 | 15 | ------------------------------ |
|
16 | 16 | |
|
17 | 17 | A few lines of code are enough to load a complete IPython inside your own |
|
18 | 18 | programs, giving you the ability to work with your data interactively after |
|
19 | 19 | automatic processing has been completed. See :ref:`the embedding section <embedding>`. |
|
20 | 20 | |
|
21 | 21 | Run doctests |
|
22 | 22 | ------------ |
|
23 | 23 | |
|
24 | 24 | Run your doctests from within IPython for development and debugging. The |
|
25 | 25 | special %doctest_mode command toggles a mode where the prompt, output and |
|
26 | 26 | exceptions display matches as closely as possible that of the default Python |
|
27 | 27 | interpreter. In addition, this mode allows you to directly paste in code that |
|
28 | 28 | contains leading '>>>' prompts, even if they have extra leading whitespace |
|
29 | 29 | (as is common in doctest files). This combined with the ``%history -t`` call |
|
30 | 30 | to see your translated history allows for an easy doctest workflow, where you |
|
31 | 31 | can go from doctest to interactive execution to pasting into valid Python code |
|
32 | 32 | as needed. |
|
33 | 33 | |
|
34 | 34 | Use IPython to present interactive demos |
|
35 | 35 | ---------------------------------------- |
|
36 | 36 | |
|
37 | 37 | Use the :class:`IPython.lib.demo.Demo` class to load any Python script as an interactive |
|
38 | 38 | demo. With a minimal amount of simple markup, you can control the execution of |
|
39 | 39 | the script, stopping as needed. See :ref:`here <interactive_demos>` for more. |
|
40 | 40 | |
|
41 | 41 | Suppress output |
|
42 | 42 | --------------- |
|
43 | 43 | |
|
44 | 44 | Put a ';' at the end of a line to suppress the printing of output. This is |
|
45 | 45 | useful when doing calculations which generate long output you are not |
|
46 | 46 | interested in seeing. It also keeps the object out of the output cache, so if |
|
47 | 47 | you're working with large temporary objects, they'll be released from memory sooner. |
|
48 | 48 | |
|
49 | 49 | Lightweight 'version control' |
|
50 | 50 | ----------------------------- |
|
51 | 51 | |
|
52 | 52 | When you call ``%edit`` with no arguments, IPython opens an empty editor |
|
53 | 53 | with a temporary file, and it returns the contents of your editing |
|
54 | 54 | session as a string variable. Thanks to IPython's output caching |
|
55 | 55 | mechanism, this is automatically stored:: |
|
56 | 56 | |
|
57 | 57 | In [1]: %edit |
|
58 | 58 | |
|
59 | 59 | IPython will make a temporary file named: /tmp/ipython_edit_yR-HCN.py |
|
60 | 60 | |
|
61 | 61 | Editing... done. Executing edited code... |
|
62 | 62 | |
|
63 | 63 | hello - this is a temporary file |
|
64 | 64 | |
|
65 |
Out[1]: "print |
|
|
65 | Out[1]: "print('hello - this is a temporary file')\n" | |
|
66 | 66 | |
|
67 | 67 | Now, if you call ``%edit -p``, IPython tries to open an editor with the |
|
68 | 68 | same data as the last time you used %edit. So if you haven't used %edit |
|
69 | 69 | in the meantime, this same contents will reopen; however, it will be |
|
70 | 70 | done in a new file. This means that if you make changes and you later |
|
71 | 71 | want to find an old version, you can always retrieve it by using its |
|
72 | 72 | output number, via '%edit _NN', where NN is the number of the output |
|
73 | 73 | prompt. |
|
74 | 74 | |
|
75 | 75 | Continuing with the example above, this should illustrate this idea:: |
|
76 | 76 | |
|
77 | 77 | In [2]: edit -p |
|
78 | 78 | |
|
79 | 79 | IPython will make a temporary file named: /tmp/ipython_edit_nA09Qk.py |
|
80 | 80 | |
|
81 | 81 | Editing... done. Executing edited code... |
|
82 | 82 | |
|
83 | 83 | hello - now I made some changes |
|
84 | 84 | |
|
85 |
Out[2]: "print |
|
|
85 | Out[2]: "print('hello - now I made some changes')\n" | |
|
86 | 86 | |
|
87 | 87 | In [3]: edit _1 |
|
88 | 88 | |
|
89 | 89 | IPython will make a temporary file named: /tmp/ipython_edit_gy6-zD.py |
|
90 | 90 | |
|
91 | 91 | Editing... done. Executing edited code... |
|
92 | 92 | |
|
93 | 93 | hello - this is a temporary file |
|
94 | 94 | |
|
95 | 95 | IPython version control at work :) |
|
96 | 96 | |
|
97 |
Out[3]: "print |
|
|
97 | Out[3]: "print('hello - this is a temporary file')\nprint('IPython version control at work :)')\n" | |
|
98 | 98 | |
|
99 | 99 | |
|
100 | 100 | This section was written after a contribution by Alexander Belchenko on |
|
101 | 101 | the IPython user list. |
|
102 | 102 |
@@ -1,101 +1,99 b'' | |||
|
1 | 1 | """A simple example of how to use IPython.config.application.Application. |
|
2 | 2 | |
|
3 | 3 | This should serve as a simple example that shows how the IPython config |
|
4 | 4 | system works. The main classes are: |
|
5 | 5 | |
|
6 | 6 | * IPython.config.configurable.Configurable |
|
7 | 7 | * IPython.config.configurable.SingletonConfigurable |
|
8 | 8 | * IPython.config.loader.Config |
|
9 | 9 | * IPython.config.application.Application |
|
10 | 10 | |
|
11 | 11 | To see the command line option help, run this program from the command line:: |
|
12 | 12 | |
|
13 | 13 | $ python appconfig.py -h |
|
14 | 14 | |
|
15 | 15 | To make one of your classes configurable (from the command line and config |
|
16 | 16 | files) inherit from Configurable and declare class attributes as traits (see |
|
17 | 17 | classes Foo and Bar below). To make the traits configurable, you will need |
|
18 | 18 | to set the following options: |
|
19 | 19 | |
|
20 | 20 | * ``config``: set to ``True`` to make the attribute configurable. |
|
21 | 21 | * ``shortname``: by default, configurable attributes are set using the syntax |
|
22 | 22 | "Classname.attributename". At the command line, this is a bit verbose, so |
|
23 | 23 | we allow "shortnames" to be declared. Setting a shortname is optional, but |
|
24 | 24 | when you do this, you can set the option at the command line using the |
|
25 | 25 | syntax: "shortname=value". |
|
26 | 26 | * ``help``: set the help string to display a help message when the ``-h`` |
|
27 | 27 | option is given at the command line. The help string should be valid ReST. |
|
28 | 28 | |
|
29 | 29 | When the config attribute of an Application is updated, it will fire all of |
|
30 | 30 | the trait's events for all of the config=True attributes. |
|
31 | 31 | """ |
|
32 | 32 | |
|
33 | import sys | |
|
34 | ||
|
35 | 33 | from IPython.config.configurable import Configurable |
|
36 | 34 | from IPython.config.application import Application |
|
37 | 35 | from IPython.utils.traitlets import ( |
|
38 | 36 | Bool, Unicode, Int, Float, List, Dict |
|
39 | 37 | ) |
|
40 | 38 | |
|
41 | 39 | |
|
42 | 40 | class Foo(Configurable): |
|
43 | 41 | """A class that has configurable, typed attributes. |
|
44 | 42 | |
|
45 | 43 | """ |
|
46 | 44 | |
|
47 | 45 | i = Int(0, config=True, help="The integer i.") |
|
48 | 46 | j = Int(1, config=True, help="The integer j.") |
|
49 | 47 | name = Unicode(u'Brian', config=True, help="First name.") |
|
50 | 48 | |
|
51 | 49 | |
|
52 | 50 | class Bar(Configurable): |
|
53 | 51 | |
|
54 | 52 | enabled = Bool(True, config=True, help="Enable bar.") |
|
55 | 53 | |
|
56 | 54 | |
|
57 | 55 | class MyApp(Application): |
|
58 | 56 | |
|
59 | 57 | name = Unicode(u'myapp') |
|
60 | 58 | running = Bool(False, config=True, |
|
61 | 59 | help="Is the app running?") |
|
62 | 60 | classes = List([Bar, Foo]) |
|
63 | 61 | config_file = Unicode(u'', config=True, |
|
64 | 62 | help="Load this config file") |
|
65 | 63 | |
|
66 | 64 | aliases = Dict(dict(i='Foo.i',j='Foo.j',name='Foo.name', running='MyApp.running', |
|
67 | 65 | enabled='Bar.enabled', log_level='MyApp.log_level')) |
|
68 | 66 | |
|
69 | 67 | flags = Dict(dict(enable=({'Bar': {'enabled' : True}}, "Enable Bar"), |
|
70 | 68 | disable=({'Bar': {'enabled' : False}}, "Disable Bar"), |
|
71 | 69 | debug=({'MyApp':{'log_level':10}}, "Set loglevel to DEBUG") |
|
72 | 70 | )) |
|
73 | 71 | |
|
74 | 72 | def init_foo(self): |
|
75 | 73 | # Pass config to other classes for them to inherit the config. |
|
76 | 74 | self.foo = Foo(config=self.config) |
|
77 | 75 | |
|
78 | 76 | def init_bar(self): |
|
79 | 77 | # Pass config to other classes for them to inherit the config. |
|
80 | 78 | self.bar = Bar(config=self.config) |
|
81 | 79 | |
|
82 | 80 | def initialize(self, argv=None): |
|
83 | 81 | self.parse_command_line(argv) |
|
84 | 82 | if self.config_file: |
|
85 | 83 | self.load_config_file(self.config_file) |
|
86 | 84 | self.init_foo() |
|
87 | 85 | self.init_bar() |
|
88 | 86 | |
|
89 | 87 | def start(self): |
|
90 |
print |
|
|
91 |
print |
|
|
88 | print("app.config:") | |
|
89 | print(self.config) | |
|
92 | 90 | |
|
93 | 91 | |
|
94 | 92 | def main(): |
|
95 | 93 | app = MyApp() |
|
96 | 94 | app.initialize() |
|
97 | 95 | app.start() |
|
98 | 96 | |
|
99 | 97 | |
|
100 | 98 | if __name__ == "__main__": |
|
101 | 99 | main() |
@@ -1,38 +1,37 b'' | |||
|
1 | 1 | #!/usr/bin/env python |
|
2 | 2 | """Extract a session from the IPython input history. |
|
3 | 3 | |
|
4 | 4 | Usage: |
|
5 | 5 | ipython-get-history.py sessionnumber [outputfile] |
|
6 | 6 | |
|
7 | 7 | If outputfile is not given, the relevant history is written to stdout. If |
|
8 | 8 | outputfile has a .py extension, the translated history (without IPython's |
|
9 | 9 | special syntax) will be extracted. |
|
10 | 10 | |
|
11 | 11 | Example: |
|
12 | 12 | ./ipython-get-history.py 57 record.ipy |
|
13 | 13 | |
|
14 | 14 | |
|
15 | 15 | This script is a simple demonstration of HistoryAccessor. It should be possible |
|
16 | 16 | to build much more flexible and powerful tools to browse and pull from the |
|
17 | 17 | history database. |
|
18 | 18 | """ |
|
19 | 19 | import sys |
|
20 | import codecs | |
|
21 | 20 | |
|
22 | 21 | from IPython.core.history import HistoryAccessor |
|
23 | 22 | |
|
24 | 23 | session_number = int(sys.argv[1]) |
|
25 | 24 | if len(sys.argv) > 2: |
|
26 | 25 | dest = open(sys.argv[2], "w") |
|
27 | 26 | raw = not sys.argv[2].endswith('.py') |
|
28 | 27 | else: |
|
29 | 28 | dest = sys.stdout |
|
30 | 29 | raw = True |
|
31 | 30 | dest.write("# coding: utf-8\n") |
|
32 | 31 | |
|
33 | 32 | # Profiles other than 'default' can be specified here with a profile= argument: |
|
34 | 33 | hist = HistoryAccessor() |
|
35 | 34 | |
|
36 | 35 | for session, lineno, cell in hist.get_range(session=session_number, raw=raw): |
|
37 | # To use this in Python 3, remove the .encode() here: | |
|
38 |
dest.write(cell |
|
|
36 | cell = cell.encode('utf-8') # This line is only needed on Python 2. | |
|
37 | dest.write(cell + '\n') |
@@ -1,45 +1,46 b'' | |||
|
1 | from __future__ import print_function | |
|
1 | 2 | import os |
|
2 | 3 | |
|
3 | 4 | from IPython.qt.console.rich_ipython_widget import RichIPythonWidget |
|
4 | 5 | from IPython.qt.inprocess import QtInProcessKernelManager |
|
5 | 6 | from IPython.lib import guisupport |
|
6 | 7 | |
|
7 | 8 | |
|
8 | 9 | def print_process_id(): |
|
9 |
print |
|
|
10 | print('Process ID is:', os.getpid()) | |
|
10 | 11 | |
|
11 | 12 | |
|
12 | 13 | def main(): |
|
13 | 14 | # Print the ID of the main process |
|
14 | 15 | print_process_id() |
|
15 | 16 | |
|
16 | 17 | app = guisupport.get_app_qt4() |
|
17 | 18 | |
|
18 | 19 | # Create an in-process kernel |
|
19 | 20 | # >>> print_process_id() |
|
20 | 21 | # will print the same process ID as the main process |
|
21 | 22 | kernel_manager = QtInProcessKernelManager() |
|
22 | 23 | kernel_manager.start_kernel() |
|
23 | 24 | kernel = kernel_manager.kernel |
|
24 | 25 | kernel.gui = 'qt4' |
|
25 | 26 | kernel.shell.push({'foo': 43, 'print_process_id': print_process_id}) |
|
26 | 27 | |
|
27 | 28 | kernel_client = kernel_manager.client() |
|
28 | 29 | kernel_client.start_channels() |
|
29 | 30 | |
|
30 | 31 | def stop(): |
|
31 | 32 | kernel_client.stop_channels() |
|
32 | 33 | kernel_manager.shutdown_kernel() |
|
33 | 34 | app.exit() |
|
34 | 35 | |
|
35 | 36 | control = RichIPythonWidget() |
|
36 | 37 | control.kernel_manager = kernel_manager |
|
37 | 38 | control.kernel_client = kernel_client |
|
38 | 39 | control.exit_requested.connect(stop) |
|
39 | 40 | control.show() |
|
40 | 41 | |
|
41 | 42 | guisupport.start_event_loop_qt4(app) |
|
42 | 43 | |
|
43 | 44 | |
|
44 | 45 | if __name__ == '__main__': |
|
45 | 46 | main() |
@@ -1,30 +1,31 b'' | |||
|
1 | from __future__ import print_function | |
|
1 | 2 | import os |
|
2 | 3 | |
|
3 | 4 | from IPython.kernel.inprocess import InProcessKernelManager |
|
4 | 5 | from IPython.terminal.console.interactiveshell import ZMQTerminalInteractiveShell |
|
5 | 6 | |
|
6 | 7 | |
|
7 | 8 | def print_process_id(): |
|
8 |
print |
|
|
9 | print('Process ID is:', os.getpid()) | |
|
9 | 10 | |
|
10 | 11 | |
|
11 | 12 | def main(): |
|
12 | 13 | print_process_id() |
|
13 | 14 | |
|
14 | 15 | # Create an in-process kernel |
|
15 | 16 | # >>> print_process_id() |
|
16 | 17 | # will print the same process ID as the main process |
|
17 | 18 | kernel_manager = InProcessKernelManager() |
|
18 | 19 | kernel_manager.start_kernel() |
|
19 | 20 | kernel = kernel_manager.kernel |
|
20 | 21 | kernel.gui = 'qt4' |
|
21 | 22 | kernel.shell.push({'foo': 43, 'print_process_id': print_process_id}) |
|
22 | 23 | client = kernel_manager.client() |
|
23 | 24 | client.start_channels() |
|
24 | 25 | |
|
25 | 26 | shell = ZMQTerminalInteractiveShell(manager=kernel_manager, client=client) |
|
26 | 27 | shell.mainloop() |
|
27 | 28 | |
|
28 | 29 | |
|
29 | 30 | if __name__ == '__main__': |
|
30 | 31 | main() |
@@ -1,381 +1,360 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 |
"name": " |
|
|
3 | "name": "" | |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "markdown", |
|
12 | 12 | "metadata": {}, |
|
13 | 13 | "source": [ |
|
14 | 14 | "# Simple interactive bacgkround jobs with IPython\n", |
|
15 | 15 | "\n", |
|
16 | 16 | "We start by loading the `backgroundjobs` library and defining a few trivial functions to illustrate things with." |
|
17 | 17 | ] |
|
18 | 18 | }, |
|
19 | 19 | { |
|
20 | 20 | "cell_type": "code", |
|
21 | 21 | "collapsed": false, |
|
22 | 22 | "input": [ |
|
23 | "from __future__ import print_function\n", | |
|
23 | 24 | "from IPython.lib import backgroundjobs as bg\n", |
|
24 | 25 | "\n", |
|
25 | 26 | "import sys\n", |
|
26 | 27 | "import time\n", |
|
27 | 28 | "\n", |
|
28 | 29 | "def sleepfunc(interval=2, *a, **kw):\n", |
|
29 | 30 | " args = dict(interval=interval,\n", |
|
30 | 31 | " args=a,\n", |
|
31 | 32 | " kwargs=kw)\n", |
|
32 | 33 | " time.sleep(interval)\n", |
|
33 | 34 | " return args\n", |
|
34 | 35 | "\n", |
|
35 | 36 | "def diefunc(interval=2, *a, **kw):\n", |
|
36 | 37 | " time.sleep(interval)\n", |
|
37 | 38 | " raise Exception(\"Dead job with interval %s\" % interval)\n", |
|
38 | 39 | "\n", |
|
39 | 40 | "def printfunc(interval=1, reps=5):\n", |
|
40 | 41 | " for n in range(reps):\n", |
|
41 | 42 | " time.sleep(interval)\n", |
|
42 |
" print |
|
|
43 | " print('In the background...', n)\n", | |
|
43 | 44 | " sys.stdout.flush()\n", |
|
44 |
" print |
|
|
45 | " print('All done!')\n", | |
|
45 | 46 | " sys.stdout.flush()" |
|
46 | 47 | ], |
|
47 | 48 | "language": "python", |
|
48 | 49 | "metadata": {}, |
|
49 | 50 | "outputs": [], |
|
50 |
"prompt_number": |
|
|
51 | "prompt_number": 1 | |
|
51 | 52 | }, |
|
52 | 53 | { |
|
53 | 54 | "cell_type": "markdown", |
|
54 | 55 | "metadata": {}, |
|
55 | 56 | "source": [ |
|
56 | 57 | "Now, we can create a job manager (called simply `jobs`) and use it to submit new jobs.\n", |
|
57 | 58 | "<br>\n", |
|
58 | 59 | "Run the cell below and wait a few seconds for the whole thing to finish, until you see the \"All done!\" printout." |
|
59 | 60 | ] |
|
60 | 61 | }, |
|
61 | 62 | { |
|
62 | 63 | "cell_type": "code", |
|
63 | 64 | "collapsed": false, |
|
64 | 65 | "input": [ |
|
65 | 66 | "jobs = bg.BackgroundJobManager()\n", |
|
66 | 67 | "\n", |
|
67 | 68 | "# Start a few jobs, the first one will have ID # 0\n", |
|
68 | 69 | "jobs.new(sleepfunc, 4)\n", |
|
69 | 70 | "jobs.new(sleepfunc, kw={'reps':2})\n", |
|
70 | 71 | "jobs.new('printfunc(1,3)')\n", |
|
71 | 72 | "\n", |
|
72 | 73 | "# This makes a couple of jobs which will die. Let's keep a reference to\n", |
|
73 | 74 | "# them for easier traceback reporting later\n", |
|
74 | 75 | "diejob1 = jobs.new(diefunc, 1)\n", |
|
75 | 76 | "diejob2 = jobs.new(diefunc, 2)" |
|
76 | 77 | ], |
|
77 | 78 | "language": "python", |
|
78 | 79 | "metadata": {}, |
|
79 | 80 | "outputs": [ |
|
80 | 81 | { |
|
81 | 82 | "output_type": "stream", |
|
82 | 83 | "stream": "stdout", |
|
83 | 84 | "text": [ |
|
84 | 85 | "Starting job # 0 in a separate thread.\n", |
|
85 | 86 | "Starting job # 2 in a separate thread.\n", |
|
86 | 87 | "Starting job # 3 in a separate thread.\n", |
|
87 | 88 | "Starting job # 4 in a separate thread.\n", |
|
88 | 89 | "Starting job # 5 in a separate thread.\n" |
|
89 | 90 | ] |
|
90 | }, | |
|
91 | { | |
|
92 | "output_type": "stream", | |
|
93 | "stream": "stdout", | |
|
94 | "text": [ | |
|
95 | "In the background... 0\n" | |
|
96 | ] | |
|
97 | }, | |
|
98 | { | |
|
99 | "output_type": "stream", | |
|
100 | "stream": "stdout", | |
|
101 | "text": [ | |
|
102 | "In the background... 1\n" | |
|
103 | ] | |
|
104 | }, | |
|
105 | { | |
|
106 | "output_type": "stream", | |
|
107 | "stream": "stdout", | |
|
108 | "text": [ | |
|
109 | "In the background... 2\n" | |
|
110 | ] | |
|
111 | }, | |
|
112 | { | |
|
113 | "output_type": "stream", | |
|
114 | "stream": "stdout", | |
|
115 | "text": [ | |
|
116 | "All done!\n" | |
|
117 | ] | |
|
118 | 91 | } |
|
119 | 92 | ], |
|
120 |
"prompt_number": |
|
|
93 | "prompt_number": 2 | |
|
121 | 94 | }, |
|
122 | 95 | { |
|
123 | 96 | "cell_type": "markdown", |
|
124 | 97 | "metadata": {}, |
|
125 | 98 | "source": [ |
|
126 | 99 | "You can check the status of your jobs at any time:" |
|
127 | 100 | ] |
|
128 | 101 | }, |
|
129 | 102 | { |
|
130 | 103 | "cell_type": "code", |
|
131 | 104 | "collapsed": false, |
|
132 | 105 | "input": [ |
|
133 | 106 | "jobs.status()" |
|
134 | 107 | ], |
|
135 | 108 | "language": "python", |
|
136 | 109 | "metadata": {}, |
|
137 | 110 | "outputs": [ |
|
138 | 111 | { |
|
139 | 112 | "output_type": "stream", |
|
140 | 113 | "stream": "stdout", |
|
141 | 114 | "text": [ |
|
142 | "Completed jobs:\n", | |
|
143 | "0 : <function sleepfunc at 0x30e1578>\n", | |
|
144 | "2 : <function sleepfunc at 0x30e1578>\n", | |
|
115 | "In the background... 0\n", | |
|
116 | "Running jobs:" | |
|
117 | ] | |
|
118 | }, | |
|
119 | { | |
|
120 | "output_type": "stream", | |
|
121 | "stream": "stdout", | |
|
122 | "text": [ | |
|
123 | "\n", | |
|
124 | "0 : <function sleepfunc at 0x7f2a1c9963b0>\n", | |
|
125 | "2 : <function sleepfunc at 0x7f2a1c9963b0>\n", | |
|
145 | 126 | "3 : printfunc(1,3)\n", |
|
127 | "5 : <function diefunc at 0x7f2a1c996440>\n", | |
|
146 | 128 | "\n", |
|
147 | 129 | "Dead jobs:\n", |
|
148 |
"4 : |
|
|
149 | "5 : <function diefunc at 0x304d488>\n", | |
|
130 | "4 : <function diefunc at 0x7f2a1c996440>\n", | |
|
150 | 131 | "\n" |
|
151 | 132 | ] |
|
152 | 133 | } |
|
153 | 134 | ], |
|
154 |
"prompt_number": 3 |
|
|
135 | "prompt_number": 3 | |
|
155 | 136 | }, |
|
156 | 137 | { |
|
157 | 138 | "cell_type": "markdown", |
|
158 | 139 | "metadata": {}, |
|
159 | 140 | "source": [ |
|
160 | 141 | "For any completed job, you can get its result easily:" |
|
161 | 142 | ] |
|
162 | 143 | }, |
|
163 | 144 | { |
|
164 | 145 | "cell_type": "code", |
|
165 | 146 | "collapsed": false, |
|
166 | 147 | "input": [ |
|
167 | 148 | "jobs[0].result\n", |
|
168 | 149 | "j0 = jobs[0]\n", |
|
169 | 150 | "j0.join?" |
|
170 | 151 | ], |
|
171 | 152 | "language": "python", |
|
172 | 153 | "metadata": {}, |
|
173 |
"outputs": [ |
|
|
174 | "prompt_number": 43 | |
|
154 | "outputs": [ | |
|
155 | { | |
|
156 | "output_type": "stream", | |
|
157 | "stream": "stdout", | |
|
158 | "text": [ | |
|
159 | "In the background... 1\n", | |
|
160 | "In the background... 2\n", | |
|
161 | "All done!\n" | |
|
162 | ] | |
|
163 | } | |
|
164 | ], | |
|
165 | "prompt_number": 4 | |
|
175 | 166 | }, |
|
176 | 167 | { |
|
177 | 168 | "cell_type": "markdown", |
|
178 | 169 | "metadata": {}, |
|
179 | 170 | "source": [ |
|
180 | 171 | "You can get the traceback of any dead job. Run the line\n", |
|
181 | 172 | "below again interactively until it prints a traceback (check the status\n", |
|
182 | 173 | "of the job):\n" |
|
183 | 174 | ] |
|
184 | 175 | }, |
|
185 | 176 | { |
|
186 | 177 | "cell_type": "code", |
|
187 | 178 | "collapsed": false, |
|
188 | 179 | "input": [ |
|
189 | 180 | "print \"Status of diejob1:\", diejob1.status\n", |
|
190 | 181 | "diejob1.traceback() # jobs.traceback(4) would also work here, with the job number" |
|
191 | 182 | ], |
|
192 | 183 | "language": "python", |
|
193 | 184 | "metadata": {}, |
|
194 | 185 | "outputs": [ |
|
195 | 186 | { |
|
196 | "output_type": "stream", | |
|
197 | "stream": "stdout", | |
|
198 | "text": [ | |
|
199 | "Status of diejob1: Dead (Exception), call jobs.traceback() for details\n", | |
|
200 | "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n", | |
|
201 | "<span class=\"ansired\">Exception</span> Traceback (most recent call last)\n", | |
|
202 | "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n", | |
|
203 | "<span class=\"ansigreen\"> 462</span> <span class=\"ansiyellow\"></span>\n", | |
|
204 | "<span class=\"ansigreen\"> 463</span> <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
205 | "<span class=\"ansigreen\">--> 464</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
206 | "\n", | |
|
207 | "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/<ipython-input-15-54795a097787></span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n", | |
|
208 | "<span class=\"ansigreen\"> 14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
209 | "<span class=\"ansigreen\"> 15</span> time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
210 | "<span class=\"ansigreen\">---> 16</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"Dead job with interval %s"</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
211 | "<span class=\"ansigreen\"> 17</span> <span class=\"ansiyellow\"></span>\n", | |
|
212 | "<span class=\"ansigreen\"> 18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
213 | "\n", | |
|
214 | "<span class=\"ansired\">Exception</span>: Dead job with interval 1\n" | |
|
187 | "ename": "SyntaxError", | |
|
188 | "evalue": "invalid syntax (<ipython-input-5-a90bd59af669>, line 1)", | |
|
189 | "output_type": "pyerr", | |
|
190 | "traceback": [ | |
|
191 | "\u001b[1;36m File \u001b[1;32m\"<ipython-input-5-a90bd59af669>\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m print \"Status of diejob1:\", diejob1.status\u001b[0m\n\u001b[1;37m ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n" | |
|
215 | 192 | ] |
|
216 | 193 | } |
|
217 | 194 | ], |
|
218 |
"prompt_number": |
|
|
195 | "prompt_number": 5 | |
|
219 | 196 | }, |
|
220 | 197 | { |
|
221 | 198 | "cell_type": "markdown", |
|
222 | 199 | "metadata": {}, |
|
223 | 200 | "source": [ |
|
224 | 201 | "This will print all tracebacks for all dead jobs:" |
|
225 | 202 | ] |
|
226 | 203 | }, |
|
227 | 204 | { |
|
228 | 205 | "cell_type": "code", |
|
229 | 206 | "collapsed": false, |
|
230 | 207 | "input": [ |
|
231 | 208 | "jobs.traceback()" |
|
232 | 209 | ], |
|
233 | 210 | "language": "python", |
|
234 | 211 | "metadata": {}, |
|
235 | 212 | "outputs": [ |
|
236 | 213 | { |
|
237 | 214 | "output_type": "stream", |
|
238 | 215 | "stream": "stdout", |
|
239 | 216 | "text": [ |
|
240 |
"Traceback for: |
|
|
241 |
" |
|
|
242 |
" |
|
|
243 | "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n", | |
|
244 | "<span class=\"ansigreen\"> 462</span> <span class=\"ansiyellow\"></span>\n", | |
|
245 | "<span class=\"ansigreen\"> 463</span> <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
246 | "<span class=\"ansigreen\">--> 464</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
217 | "Traceback for: <BackgroundJob #4: <function diefunc at 0x7f2a1c996440>>\n", | |
|
218 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n", | |
|
219 | "\u001b[1;31mException\u001b[0m Traceback (most recent call last)\n", | |
|
220 | "\u001b[1;32m/home/takluyver/.local/lib/python3.3/site-packages/IPython/lib/backgroundjobs.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n", | |
|
221 | "\u001b[0;32m 489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
222 | "\u001b[0;32m 490\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
223 | "\u001b[1;32m--> 491\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
224 | "\u001b[0m\n", | |
|
225 | "\u001b[1;32m<ipython-input-1-7391f8ae281b>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n", | |
|
226 | "\u001b[0;32m 14\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiefunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
227 | "\u001b[0;32m 15\u001b[0m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
228 | "\u001b[1;32m---> 16\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Dead job with interval %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
229 | "\u001b[0m\u001b[0;32m 17\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
230 | "\u001b[0;32m 18\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mprintfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
247 | 231 | "\n", |
|
248 | "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/<ipython-input-15-54795a097787></span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n", | |
|
249 | "<span class=\"ansigreen\"> 14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
250 | "<span class=\"ansigreen\"> 15</span> time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
251 | "<span class=\"ansigreen\">---> 16</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"Dead job with interval %s"</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
252 | "<span class=\"ansigreen\"> 17</span> <span class=\"ansiyellow\"></span>\n", | |
|
253 | "<span class=\"ansigreen\"> 18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
232 | "\u001b[1;31mException\u001b[0m: Dead job with interval 1\n", | |
|
254 | 233 | "\n", |
|
255 | "<span class=\"ansired\">Exception</span>: Dead job with interval 1\n", | |
|
234 | "Traceback for: <BackgroundJob #5: <function diefunc at 0x7f2a1c996440>>\n", | |
|
235 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n", | |
|
236 | "\u001b[1;31mException\u001b[0m Traceback (most recent call last)\n", | |
|
237 | "\u001b[1;32m/home/takluyver/.local/lib/python3.3/site-packages/IPython/lib/backgroundjobs.py\u001b[0m in \u001b[0;36mcall\u001b[1;34m(self)\u001b[0m\n", | |
|
238 | "\u001b[0;32m 489\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
239 | "\u001b[0;32m 490\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
240 | "\u001b[1;32m--> 491\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
241 | "\u001b[0m\n", | |
|
242 | "\u001b[1;32m<ipython-input-1-7391f8ae281b>\u001b[0m in \u001b[0;36mdiefunc\u001b[1;34m(interval, *a, **kw)\u001b[0m\n", | |
|
243 | "\u001b[0;32m 14\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiefunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
244 | "\u001b[0;32m 15\u001b[0m \u001b[0mtime\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
245 | "\u001b[1;32m---> 16\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Dead job with interval %s\"\u001b[0m \u001b[1;33m%\u001b[0m \u001b[0minterval\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
246 | "\u001b[0m\u001b[0;32m 17\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
247 | "\u001b[0;32m 18\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mprintfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreps\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", | |
|
256 | 248 | "\n", |
|
257 | "Traceback for: <BackgroundJob #5: <function diefunc at 0x30df758>>\n", | |
|
258 | "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n", | |
|
259 | "<span class=\"ansired\">Exception</span> Traceback (most recent call last)\n", | |
|
260 | "<span class=\"ansigreen\">/home/fperez/usr/lib/python2.6/site-packages/IPython/lib/backgroundjobs.py</span> in <span class=\"ansicyan\">call</span><span class=\"ansiblue\">(self)</span>\n", | |
|
261 | "<span class=\"ansigreen\"> 462</span> <span class=\"ansiyellow\"></span>\n", | |
|
262 | "<span class=\"ansigreen\"> 463</span> <span class=\"ansigreen\">def</span> call<span class=\"ansiyellow\">(</span>self<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
263 | "<span class=\"ansigreen\">--> 464</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">return</span> self<span class=\"ansiyellow\">.</span>func<span class=\"ansiyellow\">(</span><span class=\"ansiyellow\">*</span>self<span class=\"ansiyellow\">.</span>args<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>self<span class=\"ansiyellow\">.</span>kwargs<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
264 | "\n", | |
|
265 | "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/lib/<ipython-input-15-54795a097787></span> in <span class=\"ansicyan\">diefunc</span><span class=\"ansiblue\">(interval, *a, **kw)</span>\n", | |
|
266 | "<span class=\"ansigreen\"> 14</span> <span class=\"ansigreen\">def</span> diefunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">2</span><span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">*</span>a<span class=\"ansiyellow\">,</span> <span class=\"ansiyellow\">**</span>kw<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
267 | "<span class=\"ansigreen\"> 15</span> time<span class=\"ansiyellow\">.</span>sleep<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
268 | "<span class=\"ansigreen\">---> 16</span><span class=\"ansiyellow\"> </span><span class=\"ansigreen\">raise</span> Exception<span class=\"ansiyellow\">(</span><span class=\"ansiblue\">"Dead job with interval %s"</span> <span class=\"ansiyellow\">%</span> interval<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n", | |
|
269 | "<span class=\"ansigreen\"> 17</span> <span class=\"ansiyellow\"></span>\n", | |
|
270 | "<span class=\"ansigreen\"> 18</span> <span class=\"ansigreen\">def</span> printfunc<span class=\"ansiyellow\">(</span>interval<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">,</span> reps<span class=\"ansiyellow\">=</span><span class=\"ansicyan\">5</span><span class=\"ansiyellow\">)</span><span class=\"ansiyellow\">:</span><span class=\"ansiyellow\"></span>\n", | |
|
271 | "\n", | |
|
272 | "<span class=\"ansired\">Exception</span>: Dead job with interval 2\n", | |
|
249 | "\u001b[1;31mException\u001b[0m: Dead job with interval 2\n", | |
|
273 | 250 | "\n" |
|
274 | 251 | ] |
|
275 | 252 | } |
|
276 | 253 | ], |
|
277 |
"prompt_number": |
|
|
254 | "prompt_number": 6 | |
|
278 | 255 | }, |
|
279 | 256 | { |
|
280 | 257 | "cell_type": "markdown", |
|
281 | 258 | "metadata": {}, |
|
282 | 259 | "source": [ |
|
283 | 260 | "The job manager can be flushed of all completed jobs at any time:" |
|
284 | 261 | ] |
|
285 | 262 | }, |
|
286 | 263 | { |
|
287 | 264 | "cell_type": "code", |
|
288 | 265 | "collapsed": false, |
|
289 | 266 | "input": [ |
|
290 | 267 | "jobs.flush()" |
|
291 | 268 | ], |
|
292 | 269 | "language": "python", |
|
293 | 270 | "metadata": {}, |
|
294 | 271 | "outputs": [ |
|
295 | 272 | { |
|
296 | 273 | "output_type": "stream", |
|
297 | 274 | "stream": "stdout", |
|
298 | 275 | "text": [ |
|
299 | "No jobs to flush.\n" | |
|
276 | "Flushing 3 Completed jobs.\n", | |
|
277 | "Flushing 2 Dead jobs.\n" | |
|
300 | 278 | ] |
|
301 | 279 | } |
|
302 | 280 | ], |
|
303 |
"prompt_number": |
|
|
281 | "prompt_number": 7 | |
|
304 | 282 | }, |
|
305 | 283 | { |
|
306 | 284 | "cell_type": "markdown", |
|
307 | 285 | "metadata": {}, |
|
308 | 286 | "source": [ |
|
309 | 287 | "After that, the status is simply empty:" |
|
310 | 288 | ] |
|
311 | 289 | }, |
|
312 | 290 | { |
|
313 | 291 | "cell_type": "code", |
|
314 | 292 | "collapsed": true, |
|
315 | 293 | "input": [ |
|
316 | 294 | "jobs.status()" |
|
317 | 295 | ], |
|
318 | 296 | "language": "python", |
|
319 | 297 | "metadata": {}, |
|
320 | 298 | "outputs": [], |
|
321 |
"prompt_number": |
|
|
299 | "prompt_number": 8 | |
|
322 | 300 | }, |
|
323 | 301 | { |
|
324 | 302 | "cell_type": "markdown", |
|
325 | 303 | "metadata": {}, |
|
326 | 304 | "source": [ |
|
327 | 305 | "It's easy to wait on a job:" |
|
328 | 306 | ] |
|
329 | 307 | }, |
|
330 | 308 | { |
|
331 | 309 | "cell_type": "code", |
|
332 | 310 | "collapsed": false, |
|
333 | 311 | "input": [ |
|
334 | 312 | "j = jobs.new(sleepfunc, 2)\n", |
|
335 |
"print |
|
|
313 | "print(\"Will wait for j now...\")\n", | |
|
336 | 314 | "sys.stdout.flush()\n", |
|
337 | 315 | "j.join()\n", |
|
338 |
"print |
|
|
316 | "print(\"Result from j:\")\n", | |
|
339 | 317 | "j.result" |
|
340 | 318 | ], |
|
341 | 319 | "language": "python", |
|
342 | 320 | "metadata": {}, |
|
343 | 321 | "outputs": [ |
|
344 | 322 | { |
|
345 | 323 | "output_type": "stream", |
|
346 | 324 | "stream": "stdout", |
|
347 | 325 | "text": [ |
|
348 |
"Starting job # |
|
|
326 | "Starting job # 0 in a separate thread.\n", | |
|
349 | 327 | "Will wait for j now...\n" |
|
350 | 328 | ] |
|
351 | 329 | }, |
|
352 | 330 | { |
|
353 | 331 | "output_type": "stream", |
|
354 | 332 | "stream": "stdout", |
|
355 | 333 | "text": [ |
|
356 | 334 | "Result from j:\n" |
|
357 | 335 | ] |
|
358 | 336 | }, |
|
359 | 337 | { |
|
338 | "metadata": {}, | |
|
360 | 339 | "output_type": "pyout", |
|
361 |
"prompt_number": |
|
|
340 | "prompt_number": 9, | |
|
362 | 341 | "text": [ |
|
363 | "{'args': (), 'interval': 2, 'kwargs': {}}" | |
|
342 | "{'kwargs': {}, 'args': (), 'interval': 2}" | |
|
364 | 343 | ] |
|
365 | 344 | } |
|
366 | 345 | ], |
|
367 |
"prompt_number": |
|
|
346 | "prompt_number": 9 | |
|
368 | 347 | }, |
|
369 | 348 | { |
|
370 | 349 | "cell_type": "code", |
|
371 | 350 | "collapsed": true, |
|
372 | 351 | "input": [], |
|
373 | 352 | "language": "python", |
|
374 | 353 | "metadata": {}, |
|
375 | 354 | "outputs": [] |
|
376 | 355 | } |
|
377 | 356 | ], |
|
378 | 357 | "metadata": {} |
|
379 | 358 | } |
|
380 | 359 | ] |
|
381 | 360 | } No newline at end of file |
@@ -1,41 +1,40 b'' | |||
|
1 | 1 | #!/usr/bin/env python |
|
2 | 2 | """Simple Qt4 example to manually test event loop integration. |
|
3 | 3 | |
|
4 | 4 | This is meant to run tests manually in ipython as: |
|
5 | 5 | |
|
6 | 6 | In [5]: %gui qt |
|
7 | 7 | |
|
8 | 8 | In [6]: %run gui-qt.py |
|
9 | 9 | |
|
10 | 10 | Ref: Modified from http://zetcode.com/tutorials/pyqt4/firstprograms/ |
|
11 | 11 | """ |
|
12 | 12 | |
|
13 | import sys | |
|
14 | 13 | from PyQt4 import QtGui, QtCore |
|
15 | 14 | |
|
16 | 15 | class SimpleWindow(QtGui.QWidget): |
|
17 | 16 | def __init__(self, parent=None): |
|
18 | 17 | QtGui.QWidget.__init__(self, parent) |
|
19 | 18 | |
|
20 | 19 | self.setGeometry(300, 300, 200, 80) |
|
21 | 20 | self.setWindowTitle('Hello World') |
|
22 | 21 | |
|
23 | 22 | quit = QtGui.QPushButton('Close', self) |
|
24 | 23 | quit.setGeometry(10, 10, 60, 35) |
|
25 | 24 | |
|
26 | 25 | self.connect(quit, QtCore.SIGNAL('clicked()'), |
|
27 | 26 | self, QtCore.SLOT('close()')) |
|
28 | 27 | |
|
29 | 28 | if __name__ == '__main__': |
|
30 | 29 | app = QtCore.QCoreApplication.instance() |
|
31 | 30 | if app is None: |
|
32 | 31 | app = QtGui.QApplication([]) |
|
33 | 32 | |
|
34 | 33 | sw = SimpleWindow() |
|
35 | 34 | sw.show() |
|
36 | 35 | |
|
37 | 36 | try: |
|
38 | 37 | from IPython.lib.guisupport import start_event_loop_qt4 |
|
39 | 38 | start_event_loop_qt4(app) |
|
40 | 39 | except ImportError: |
|
41 | 40 | app.exec_() |
@@ -1,32 +1,35 b'' | |||
|
1 | 1 | #!/usr/bin/env python |
|
2 | 2 | """Simple Tk example to manually test event loop integration. |
|
3 | 3 | |
|
4 | 4 | This is meant to run tests manually in ipython as: |
|
5 | 5 | |
|
6 | 6 | In [5]: %gui tk |
|
7 | 7 | |
|
8 | 8 | In [6]: %run gui-tk.py |
|
9 | 9 | """ |
|
10 | 10 | |
|
11 | from Tkinter import * | |
|
11 | try: | |
|
12 | from tkinter import * # Python 3 | |
|
13 | except ImportError: | |
|
14 | from Tkinter import * # Python 2 | |
|
12 | 15 | |
|
13 | 16 | class MyApp: |
|
14 | 17 | |
|
15 | 18 | def __init__(self, root): |
|
16 | 19 | frame = Frame(root) |
|
17 | 20 | frame.pack() |
|
18 | 21 | |
|
19 | 22 | self.button = Button(frame, text="Hello", command=self.hello_world) |
|
20 | 23 | self.button.pack(side=LEFT) |
|
21 | 24 | |
|
22 | 25 | def hello_world(self): |
|
23 | 26 | print("Hello World!") |
|
24 | 27 | |
|
25 | 28 | root = Tk() |
|
26 | 29 | |
|
27 | 30 | app = MyApp(root) |
|
28 | 31 | |
|
29 | 32 | try: |
|
30 | 33 | from IPython.lib.inputhook import enable_tk; enable_tk(root) |
|
31 | 34 | except ImportError: |
|
32 | 35 | root.mainloop() |
@@ -1,59 +1,58 b'' | |||
|
1 | 1 | #----------------------------------------------------------------------------- |
|
2 | 2 | # Imports |
|
3 | 3 | #----------------------------------------------------------------------------- |
|
4 | 4 | |
|
5 | import subprocess | |
|
6 | 5 | import sys |
|
7 | 6 | |
|
8 | 7 | from IPython.lib.kernel import connect_qtconsole |
|
9 | 8 | from IPython.kernel.zmq.kernelapp import IPKernelApp |
|
10 | 9 | |
|
11 | 10 | #----------------------------------------------------------------------------- |
|
12 | 11 | # Functions and classes |
|
13 | 12 | #----------------------------------------------------------------------------- |
|
14 | 13 | def pylab_kernel(gui): |
|
15 | 14 | """Launch and return an IPython kernel with pylab support for the desired gui |
|
16 | 15 | """ |
|
17 | 16 | kernel = IPKernelApp.instance() |
|
18 | 17 | kernel.initialize(['python', '--pylab=%s' % gui, |
|
19 | 18 | #'--log-level=10' |
|
20 | 19 | ]) |
|
21 | 20 | return kernel |
|
22 | 21 | |
|
23 | 22 | |
|
24 | 23 | class InternalIPKernel(object): |
|
25 | 24 | |
|
26 | 25 | def init_ipkernel(self, backend): |
|
27 | 26 | # Start IPython kernel with GUI event loop and pylab support |
|
28 | 27 | self.ipkernel = pylab_kernel(backend) |
|
29 | 28 | # To create and track active qt consoles |
|
30 | 29 | self.consoles = [] |
|
31 | 30 | |
|
32 | 31 | # This application will also act on the shell user namespace |
|
33 | 32 | self.namespace = self.ipkernel.shell.user_ns |
|
34 | 33 | # Keys present at startup so we don't print the entire pylab/numpy |
|
35 | 34 | # namespace when the user clicks the 'namespace' button |
|
36 | 35 | self._init_keys = set(self.namespace.keys()) |
|
37 | 36 | |
|
38 | 37 | # Example: a variable that will be seen by the user in the shell, and |
|
39 | 38 | # that the GUI modifies (the 'Counter++' button increments it): |
|
40 | 39 | self.namespace['app_counter'] = 0 |
|
41 | 40 | #self.namespace['ipkernel'] = self.ipkernel # dbg |
|
42 | 41 | |
|
43 | 42 | def print_namespace(self, evt=None): |
|
44 | 43 | print("\n***Variables in User namespace***") |
|
45 |
for k, v in self.namespace. |
|
|
44 | for k, v in self.namespace.items(): | |
|
46 | 45 | if k not in self._init_keys and not k.startswith('_'): |
|
47 | 46 | print('%s -> %r' % (k, v)) |
|
48 | 47 | sys.stdout.flush() |
|
49 | 48 | |
|
50 | 49 | def new_qt_console(self, evt=None): |
|
51 | 50 | """start a new qtconsole connected to our kernel""" |
|
52 | 51 | return connect_qtconsole(self.ipkernel.connection_file, profile=self.ipkernel.profile) |
|
53 | 52 | |
|
54 | 53 | def count(self, evt=None): |
|
55 | 54 | self.namespace['app_counter'] += 1 |
|
56 | 55 | |
|
57 | 56 | def cleanup_consoles(self, evt=None): |
|
58 | 57 | for c in self.consoles: |
|
59 | 58 | c.kill() |
@@ -1,322 +1,321 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "name": "" |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "heading", |
|
12 | 12 | "level": 1, |
|
13 | 13 | "metadata": {}, |
|
14 | 14 | "source": [ |
|
15 | 15 | "The Frontend/Kernel Model" |
|
16 | 16 | ] |
|
17 | 17 | }, |
|
18 | 18 | { |
|
19 | 19 | "cell_type": "markdown", |
|
20 | 20 | "metadata": {}, |
|
21 | 21 | "source": [ |
|
22 | 22 | "The traditional IPython (`ipython`) consists of a single process that combines a terminal based UI with the process that runs the users code.\n", |
|
23 | 23 | "\n", |
|
24 | 24 | "While this traditional application still exists, the modern IPython consists of two processes:\n", |
|
25 | 25 | "\n", |
|
26 | 26 | "* Kernel: this is the process that runs the users code.\n", |
|
27 | 27 | "* Frontend: this is the process that provides the user interface where the user types code and sees results.\n", |
|
28 | 28 | "\n", |
|
29 | 29 | "IPython currently has 3 frontends:\n", |
|
30 | 30 | "\n", |
|
31 | 31 | "* Terminal Console (`ipython console`)\n", |
|
32 | 32 | "* Qt Console (`ipython qtconsole`)\n", |
|
33 | 33 | "* Notebook (`ipython notebook`)\n", |
|
34 | 34 | "\n", |
|
35 | 35 | "The Kernel and Frontend communicate over a ZeroMQ/JSON based messaging protocol, which allows multiple Frontends (even of different types) to communicate with a single Kernel. This opens the door for all sorts of interesting things, such as connecting a Console or Qt Console to a Notebook's Kernel. For example, you may want to connect a Qt console to your Notebook's Kernel and use it as a help\n", |
|
36 | 36 | "browser, calling `??` on objects in the Qt console (whose pager is more flexible than the\n", |
|
37 | 37 | "one in the notebook). \n", |
|
38 | 38 | "\n", |
|
39 | 39 | "This Notebook describes how you would connect another Frontend to a Kernel that is associated with a Notebook." |
|
40 | 40 | ] |
|
41 | 41 | }, |
|
42 | 42 | { |
|
43 | 43 | "cell_type": "heading", |
|
44 | 44 | "level": 2, |
|
45 | 45 | "metadata": {}, |
|
46 | 46 | "source": [ |
|
47 | 47 | "Manual connection" |
|
48 | 48 | ] |
|
49 | 49 | }, |
|
50 | 50 | { |
|
51 | 51 | "cell_type": "markdown", |
|
52 | 52 | "metadata": {}, |
|
53 | 53 | "source": [ |
|
54 | 54 | "To connect another Frontend to a Kernel manually, you first need to find out the connection information for the Kernel using the `%connect_info` magic:" |
|
55 | 55 | ] |
|
56 | 56 | }, |
|
57 | 57 | { |
|
58 | 58 | "cell_type": "code", |
|
59 | 59 | "collapsed": false, |
|
60 | 60 | "input": [ |
|
61 | 61 | "%connect_info" |
|
62 | 62 | ], |
|
63 | 63 | "language": "python", |
|
64 | 64 | "metadata": {}, |
|
65 | 65 | "outputs": [ |
|
66 | 66 | { |
|
67 | 67 | "output_type": "stream", |
|
68 | 68 | "stream": "stdout", |
|
69 | 69 | "text": [ |
|
70 | 70 | "{\n", |
|
71 | 71 | " \"stdin_port\": 52858, \n", |
|
72 | 72 | " \"ip\": \"127.0.0.1\", \n", |
|
73 | 73 | " \"hb_port\": 52859, \n", |
|
74 | 74 | " \"key\": \"7efd45ca-d8a2-41b0-9cea-d9116d0fb883\", \n", |
|
75 | 75 | " \"shell_port\": 52856, \n", |
|
76 | 76 | " \"iopub_port\": 52857\n", |
|
77 | 77 | "}\n", |
|
78 | 78 | "\n", |
|
79 | 79 | "Paste the above JSON into a file, and connect with:\n", |
|
80 | 80 | " $> ipython <app> --existing <file>\n", |
|
81 | 81 | "or, if you are local, you can connect with just:\n", |
|
82 | 82 | " $> ipython <app> --existing kernel-b3bac7c1-8b2c-4536-8082-8d1df24f99ac.json \n", |
|
83 | 83 | "or even just:\n", |
|
84 | 84 | " $> ipython <app> --existing \n", |
|
85 | 85 | "if this is the most recent IPython session you have started.\n" |
|
86 | 86 | ] |
|
87 | 87 | } |
|
88 | 88 | ], |
|
89 | 89 | "prompt_number": 6 |
|
90 | 90 | }, |
|
91 | 91 | { |
|
92 | 92 | "cell_type": "markdown", |
|
93 | 93 | "metadata": {}, |
|
94 | 94 | "source": [ |
|
95 | 95 | "You can see that this magic displays everything you need to connect to this Notebook's Kernel." |
|
96 | 96 | ] |
|
97 | 97 | }, |
|
98 | 98 | { |
|
99 | 99 | "cell_type": "heading", |
|
100 | 100 | "level": 2, |
|
101 | 101 | "metadata": {}, |
|
102 | 102 | "source": [ |
|
103 | 103 | "Automatic connection using a new Qt Console" |
|
104 | 104 | ] |
|
105 | 105 | }, |
|
106 | 106 | { |
|
107 | 107 | "cell_type": "markdown", |
|
108 | 108 | "metadata": {}, |
|
109 | 109 | "source": [ |
|
110 | 110 | "You can also start a new Qt Console connected to your current Kernel by using the `%qtconsole` magic. This will detect the necessary connection\n", |
|
111 | 111 | "information and start the Qt Console for you automatically." |
|
112 | 112 | ] |
|
113 | 113 | }, |
|
114 | 114 | { |
|
115 | 115 | "cell_type": "code", |
|
116 | 116 | "collapsed": false, |
|
117 | 117 | "input": [ |
|
118 | 118 | "a = 10" |
|
119 | 119 | ], |
|
120 | 120 | "language": "python", |
|
121 | 121 | "metadata": {}, |
|
122 | 122 | "outputs": [], |
|
123 | 123 | "prompt_number": 1 |
|
124 | 124 | }, |
|
125 | 125 | { |
|
126 | 126 | "cell_type": "code", |
|
127 | 127 | "collapsed": false, |
|
128 | 128 | "input": [ |
|
129 | 129 | "%qtconsole" |
|
130 | 130 | ], |
|
131 | 131 | "language": "python", |
|
132 | 132 | "metadata": {}, |
|
133 | 133 | "outputs": [], |
|
134 | 134 | "prompt_number": 2 |
|
135 | 135 | }, |
|
136 | 136 | { |
|
137 | 137 | "cell_type": "heading", |
|
138 | 138 | "level": 2, |
|
139 | 139 | "metadata": {}, |
|
140 | 140 | "source": [ |
|
141 | 141 | "The kernel's `raw_input` and `%debug`" |
|
142 | 142 | ] |
|
143 | 143 | }, |
|
144 | 144 | { |
|
145 | 145 | "cell_type": "markdown", |
|
146 | 146 | "metadata": {}, |
|
147 | 147 | "source": [ |
|
148 | 148 | "The Notebook has added support for `raw_input` and `%debug`, as of 1.0." |
|
149 | 149 | ] |
|
150 | 150 | }, |
|
151 | 151 | { |
|
152 | 152 | "cell_type": "code", |
|
153 | 153 | "collapsed": false, |
|
154 | 154 | "input": [ |
|
155 | 155 | "# Python 3 compat\n", |
|
156 |
" |
|
|
157 | " raw_input\n", | |
|
158 | "except NameError:\n", | |
|
156 | "import sys\n", | |
|
157 | "if sys.version_info[0] >= 3:\n", | |
|
159 | 158 | " raw_input = input" |
|
160 | 159 | ], |
|
161 | 160 | "language": "python", |
|
162 | 161 | "metadata": {}, |
|
163 | 162 | "outputs": [], |
|
164 | 163 | "prompt_number": 1 |
|
165 | 164 | }, |
|
166 | 165 | { |
|
167 | 166 | "cell_type": "code", |
|
168 | 167 | "collapsed": false, |
|
169 | 168 | "input": [ |
|
170 | 169 | "name = raw_input(\"What is your name? \")\n", |
|
171 | 170 | "name" |
|
172 | 171 | ], |
|
173 | 172 | "language": "python", |
|
174 | 173 | "metadata": {}, |
|
175 | 174 | "outputs": [ |
|
176 | 175 | { |
|
177 | 176 | "name": "stdout", |
|
178 | 177 | "output_type": "stream", |
|
179 | 178 | "stream": "stdout", |
|
180 | 179 | "text": [ |
|
181 | 180 | "What is your name? Sir Robin\n" |
|
182 | 181 | ] |
|
183 | 182 | }, |
|
184 | 183 | { |
|
185 | 184 | "metadata": {}, |
|
186 | 185 | "output_type": "pyout", |
|
187 | 186 | "prompt_number": 2, |
|
188 | 187 | "text": [ |
|
189 | 188 | "'Sir Robin'" |
|
190 | 189 | ] |
|
191 | 190 | } |
|
192 | 191 | ], |
|
193 | 192 | "prompt_number": 2 |
|
194 | 193 | }, |
|
195 | 194 | { |
|
196 | 195 | "cell_type": "markdown", |
|
197 | 196 | "metadata": {}, |
|
198 | 197 | "source": [ |
|
199 | 198 | "**Python 2-only**: the eval input works as well (`input` is just `eval(raw_input(prompt))`)" |
|
200 | 199 | ] |
|
201 | 200 | }, |
|
202 | 201 | { |
|
203 | 202 | "cell_type": "code", |
|
204 | 203 | "collapsed": false, |
|
205 | 204 | "input": [ |
|
206 | 205 | "fingers = input(\"How many fingers? \")\n", |
|
207 | 206 | "fingers, type(fingers)" |
|
208 | 207 | ], |
|
209 | 208 | "language": "python", |
|
210 | 209 | "metadata": {}, |
|
211 | 210 | "outputs": [ |
|
212 | 211 | { |
|
213 | 212 | "name": "stdout", |
|
214 | 213 | "output_type": "stream", |
|
215 | 214 | "stream": "stdout", |
|
216 | 215 | "text": [ |
|
217 | 216 | "How many fingers? 4\n" |
|
218 | 217 | ] |
|
219 | 218 | }, |
|
220 | 219 | { |
|
221 | 220 | "metadata": {}, |
|
222 | 221 | "output_type": "pyout", |
|
223 | 222 | "prompt_number": 3, |
|
224 | 223 | "text": [ |
|
225 | 224 | "(4, int)" |
|
226 | 225 | ] |
|
227 | 226 | } |
|
228 | 227 | ], |
|
229 | 228 | "prompt_number": 3 |
|
230 | 229 | }, |
|
231 | 230 | { |
|
232 | 231 | "cell_type": "code", |
|
233 | 232 | "collapsed": false, |
|
234 | 233 | "input": [ |
|
235 | 234 | "def div(x, y):\n", |
|
236 | 235 | " return x/y\n", |
|
237 | 236 | "\n", |
|
238 | 237 | "div(1,0)" |
|
239 | 238 | ], |
|
240 | 239 | "language": "python", |
|
241 | 240 | "metadata": {}, |
|
242 | 241 | "outputs": [ |
|
243 | 242 | { |
|
244 | 243 | "ename": "ZeroDivisionError", |
|
245 | 244 | "evalue": "integer division or modulo by zero", |
|
246 | 245 | "output_type": "pyerr", |
|
247 | 246 | "traceback": [ |
|
248 | 247 | "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", |
|
249 | 248 | "\u001b[1;32m<ipython-input-4-a5097cc0c0c5>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", |
|
250 | 249 | "\u001b[1;32m<ipython-input-4-a5097cc0c0c5>\u001b[0m in \u001b[0;36mdiv\u001b[1;34m(x, y)\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", |
|
251 | 250 | "\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero" |
|
252 | 251 | ] |
|
253 | 252 | } |
|
254 | 253 | ], |
|
255 | 254 | "prompt_number": 4 |
|
256 | 255 | }, |
|
257 | 256 | { |
|
258 | 257 | "cell_type": "code", |
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259 | 258 | "collapsed": false, |
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260 | 259 | "input": [ |
|
261 | 260 | "%debug" |
|
262 | 261 | ], |
|
263 | 262 | "language": "python", |
|
264 | 263 | "metadata": {}, |
|
265 | 264 | "outputs": [ |
|
266 | 265 | { |
|
267 | 266 | "output_type": "stream", |
|
268 | 267 | "stream": "stdout", |
|
269 | 268 | "text": [ |
|
270 | 269 | "> \u001b[1;32m<ipython-input-4-a5097cc0c0c5>\u001b[0m(2)\u001b[0;36mdiv\u001b[1;34m()\u001b[0m\n", |
|
271 | 270 | "\u001b[1;32m 1 \u001b[1;33m\u001b[1;32mdef\u001b[0m \u001b[0mdiv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", |
|
272 | 271 | "\u001b[0m\u001b[1;32m----> 2 \u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", |
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273 | 272 | "\u001b[0m\u001b[1;32m 3 \u001b[1;33m\u001b[1;33m\u001b[0m\u001b[0m\n", |
|
274 | 273 | "\u001b[0m\n" |
|
275 | 274 | ] |
|
276 | 275 | }, |
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277 | 276 | { |
|
278 | 277 | "name": "stdout", |
|
279 | 278 | "output_type": "stream", |
|
280 | 279 | "stream": "stdout", |
|
281 | 280 | "text": [ |
|
282 | 281 | "ipdb> x\n" |
|
283 | 282 | ] |
|
284 | 283 | }, |
|
285 | 284 | { |
|
286 | 285 | "output_type": "stream", |
|
287 | 286 | "stream": "stdout", |
|
288 | 287 | "text": [ |
|
289 | 288 | "1\n" |
|
290 | 289 | ] |
|
291 | 290 | }, |
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292 | 291 | { |
|
293 | 292 | "name": "stdout", |
|
294 | 293 | "output_type": "stream", |
|
295 | 294 | "stream": "stdout", |
|
296 | 295 | "text": [ |
|
297 | 296 | "ipdb> y\n" |
|
298 | 297 | ] |
|
299 | 298 | }, |
|
300 | 299 | { |
|
301 | 300 | "output_type": "stream", |
|
302 | 301 | "stream": "stdout", |
|
303 | 302 | "text": [ |
|
304 | 303 | "0\n" |
|
305 | 304 | ] |
|
306 | 305 | }, |
|
307 | 306 | { |
|
308 | 307 | "name": "stdout", |
|
309 | 308 | "output_type": "stream", |
|
310 | 309 | "stream": "stdout", |
|
311 | 310 | "text": [ |
|
312 | 311 | "ipdb> exit\n" |
|
313 | 312 | ] |
|
314 | 313 | } |
|
315 | 314 | ], |
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316 | 315 | "prompt_number": 5 |
|
317 | 316 | } |
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318 | 317 | ], |
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319 | 318 | "metadata": {} |
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320 | 319 | } |
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321 | 320 | ] |
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322 | 321 | } No newline at end of file |
@@ -1,790 +1,790 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "gist_id": "6011986", |
|
4 | 4 | "name": "" |
|
5 | 5 | }, |
|
6 | 6 | "nbformat": 3, |
|
7 | 7 | "nbformat_minor": 0, |
|
8 | 8 | "worksheets": [ |
|
9 | 9 | { |
|
10 | 10 | "cells": [ |
|
11 | 11 | { |
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12 | 12 | "cell_type": "heading", |
|
13 | 13 | "level": 1, |
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14 | 14 | "metadata": {}, |
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15 | 15 | "source": [ |
|
16 | 16 | "Importing IPython Notebooks as Modules" |
|
17 | 17 | ] |
|
18 | 18 | }, |
|
19 | 19 | { |
|
20 | 20 | "cell_type": "markdown", |
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21 | 21 | "metadata": {}, |
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22 | 22 | "source": [ |
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23 | 23 | "It is a common problem that people want to import code from IPython Notebooks.\n", |
|
24 | 24 | "This is made difficult by the fact that Notebooks are not plain Python files,\n", |
|
25 | 25 | "and thus cannot be imported by the regular Python machinery.\n", |
|
26 | 26 | "\n", |
|
27 | 27 | "Fortunately, Python provides some fairly sophisticated [hooks](http://www.python.org/dev/peps/pep-0302/) into the import machinery,\n", |
|
28 | 28 | "so we can actually make IPython notebooks importable without much difficulty,\n", |
|
29 | 29 | "and only using public APIs." |
|
30 | 30 | ] |
|
31 | 31 | }, |
|
32 | 32 | { |
|
33 | 33 | "cell_type": "code", |
|
34 | 34 | "collapsed": false, |
|
35 | 35 | "input": [ |
|
36 | 36 | "import io, os, sys, types" |
|
37 | 37 | ], |
|
38 | 38 | "language": "python", |
|
39 | 39 | "metadata": {}, |
|
40 | 40 | "outputs": [], |
|
41 | 41 | "prompt_number": 1 |
|
42 | 42 | }, |
|
43 | 43 | { |
|
44 | 44 | "cell_type": "code", |
|
45 | 45 | "collapsed": false, |
|
46 | 46 | "input": [ |
|
47 | 47 | "from IPython.nbformat import current\n", |
|
48 | 48 | "from IPython.core.interactiveshell import InteractiveShell" |
|
49 | 49 | ], |
|
50 | 50 | "language": "python", |
|
51 | 51 | "metadata": {}, |
|
52 | 52 | "outputs": [], |
|
53 | 53 | "prompt_number": 2 |
|
54 | 54 | }, |
|
55 | 55 | { |
|
56 | 56 | "cell_type": "markdown", |
|
57 | 57 | "metadata": {}, |
|
58 | 58 | "source": [ |
|
59 | 59 | "Import hooks typically take the form of two objects:\n", |
|
60 | 60 | "\n", |
|
61 | 61 | "1. a Module **Loader**, which takes a module name (e.g. `'IPython.display'`), and returns a Module\n", |
|
62 | 62 | "2. a Module **Finder**, which figures out whether a module might exist, and tells Python what **Loader** to use" |
|
63 | 63 | ] |
|
64 | 64 | }, |
|
65 | 65 | { |
|
66 | 66 | "cell_type": "code", |
|
67 | 67 | "collapsed": false, |
|
68 | 68 | "input": [ |
|
69 | 69 | "def find_notebook(fullname, path=None):\n", |
|
70 | 70 | " \"\"\"find a notebook, given its fully qualified name and an optional path\n", |
|
71 | 71 | " \n", |
|
72 | 72 | " This turns \"foo.bar\" into \"foo/bar.ipynb\"\n", |
|
73 | 73 | " and tries turning \"Foo_Bar\" into \"Foo Bar\" if Foo_Bar\n", |
|
74 | 74 | " does not exist.\n", |
|
75 | 75 | " \"\"\"\n", |
|
76 | 76 | " name = fullname.rsplit('.', 1)[-1]\n", |
|
77 | 77 | " if not path:\n", |
|
78 | 78 | " path = ['']\n", |
|
79 | 79 | " for d in path:\n", |
|
80 | 80 | " nb_path = os.path.join(d, name + \".ipynb\")\n", |
|
81 | 81 | " if os.path.isfile(nb_path):\n", |
|
82 | 82 | " return nb_path\n", |
|
83 | 83 | " # let import Notebook_Name find \"Notebook Name.ipynb\"\n", |
|
84 | 84 | " nb_path = nb_path.replace(\"_\", \" \")\n", |
|
85 | 85 | " if os.path.isfile(nb_path):\n", |
|
86 | 86 | " return nb_path\n", |
|
87 | 87 | " " |
|
88 | 88 | ], |
|
89 | 89 | "language": "python", |
|
90 | 90 | "metadata": {}, |
|
91 | 91 | "outputs": [], |
|
92 | 92 | "prompt_number": 3 |
|
93 | 93 | }, |
|
94 | 94 | { |
|
95 | 95 | "cell_type": "heading", |
|
96 | 96 | "level": 2, |
|
97 | 97 | "metadata": {}, |
|
98 | 98 | "source": [ |
|
99 | 99 | "Notebook Loader" |
|
100 | 100 | ] |
|
101 | 101 | }, |
|
102 | 102 | { |
|
103 | 103 | "cell_type": "markdown", |
|
104 | 104 | "metadata": {}, |
|
105 | 105 | "source": [ |
|
106 | 106 | "Here we have our Notebook Loader.\n", |
|
107 | 107 | "It's actually quite simple - once we figure out the filename of the module,\n", |
|
108 | 108 | "all it does is:\n", |
|
109 | 109 | "\n", |
|
110 | 110 | "1. load the notebook document into memory\n", |
|
111 | 111 | "2. create an empty Module\n", |
|
112 | 112 | "3. execute every cell in the Module namespace\n", |
|
113 | 113 | "\n", |
|
114 | 114 | "Since IPython cells can have extended syntax,\n", |
|
115 | 115 | "the IPython transform is applied to turn each of these cells into their pure-Python counterparts before executing them.\n", |
|
116 | 116 | "If all of your notebook cells are pure-Python,\n", |
|
117 | 117 | "this step is unnecessary." |
|
118 | 118 | ] |
|
119 | 119 | }, |
|
120 | 120 | { |
|
121 | 121 | "cell_type": "code", |
|
122 | 122 | "collapsed": false, |
|
123 | 123 | "input": [ |
|
124 | 124 | "class NotebookLoader(object):\n", |
|
125 | 125 | " \"\"\"Module Loader for IPython Notebooks\"\"\"\n", |
|
126 | 126 | " def __init__(self, path=None):\n", |
|
127 | 127 | " self.shell = InteractiveShell.instance()\n", |
|
128 | 128 | " self.path = path\n", |
|
129 | 129 | " \n", |
|
130 | 130 | " def load_module(self, fullname):\n", |
|
131 | 131 | " \"\"\"import a notebook as a module\"\"\"\n", |
|
132 | 132 | " path = find_notebook(fullname, self.path)\n", |
|
133 | 133 | " \n", |
|
134 | 134 | " print (\"importing IPython notebook from %s\" % path)\n", |
|
135 | 135 | " \n", |
|
136 | 136 | " # load the notebook object\n", |
|
137 | 137 | " with io.open(path, 'r', encoding='utf-8') as f:\n", |
|
138 | 138 | " nb = current.read(f, 'json')\n", |
|
139 | 139 | " \n", |
|
140 | 140 | " \n", |
|
141 | 141 | " # create the module and add it to sys.modules\n", |
|
142 | 142 | " # if name in sys.modules:\n", |
|
143 | 143 | " # return sys.modules[name]\n", |
|
144 | 144 | " mod = types.ModuleType(fullname)\n", |
|
145 | 145 | " mod.__file__ = path\n", |
|
146 | 146 | " mod.__loader__ = self\n", |
|
147 | 147 | " sys.modules[fullname] = mod\n", |
|
148 | 148 | " \n", |
|
149 | 149 | " # extra work to ensure that magics that would affect the user_ns\n", |
|
150 | 150 | " # actually affect the notebook module's ns\n", |
|
151 | 151 | " save_user_ns = self.shell.user_ns\n", |
|
152 | 152 | " self.shell.user_ns = mod.__dict__\n", |
|
153 | 153 | " \n", |
|
154 | 154 | " try:\n", |
|
155 | 155 | " for cell in nb.worksheets[0].cells:\n", |
|
156 | 156 | " if cell.cell_type == 'code' and cell.language == 'python':\n", |
|
157 | 157 | " # transform the input to executable Python\n", |
|
158 | 158 | " code = self.shell.input_transformer_manager.transform_cell(cell.input)\n", |
|
159 | 159 | " # run the code in themodule\n", |
|
160 |
" exec |
|
|
160 | " exec(code, mod.__dict__)\n", | |
|
161 | 161 | " finally:\n", |
|
162 | 162 | " self.shell.user_ns = save_user_ns\n", |
|
163 | 163 | " return mod\n" |
|
164 | 164 | ], |
|
165 | 165 | "language": "python", |
|
166 | 166 | "metadata": {}, |
|
167 | 167 | "outputs": [], |
|
168 | 168 | "prompt_number": 4 |
|
169 | 169 | }, |
|
170 | 170 | { |
|
171 | 171 | "cell_type": "heading", |
|
172 | 172 | "level": 2, |
|
173 | 173 | "metadata": {}, |
|
174 | 174 | "source": [ |
|
175 | 175 | "The Module Finder" |
|
176 | 176 | ] |
|
177 | 177 | }, |
|
178 | 178 | { |
|
179 | 179 | "cell_type": "markdown", |
|
180 | 180 | "metadata": {}, |
|
181 | 181 | "source": [ |
|
182 | 182 | "The finder is a simple object that tells you whether a name can be imported,\n", |
|
183 | 183 | "and returns the appropriate loader.\n", |
|
184 | 184 | "All this one does is check, when you do:\n", |
|
185 | 185 | "\n", |
|
186 | 186 | "```python\n", |
|
187 | 187 | "import mynotebook\n", |
|
188 | 188 | "```\n", |
|
189 | 189 | "\n", |
|
190 | 190 | "it checks whether `mynotebook.ipynb` exists.\n", |
|
191 | 191 | "If a notebook is found, then it returns a NotebookLoader.\n", |
|
192 | 192 | "\n", |
|
193 | 193 | "Any extra logic is just for resolving paths within packages." |
|
194 | 194 | ] |
|
195 | 195 | }, |
|
196 | 196 | { |
|
197 | 197 | "cell_type": "code", |
|
198 | 198 | "collapsed": false, |
|
199 | 199 | "input": [ |
|
200 | 200 | "class NotebookFinder(object):\n", |
|
201 | 201 | " \"\"\"Module finder that locates IPython Notebooks\"\"\"\n", |
|
202 | 202 | " def __init__(self):\n", |
|
203 | 203 | " self.loaders = {}\n", |
|
204 | 204 | " \n", |
|
205 | 205 | " def find_module(self, fullname, path=None):\n", |
|
206 | 206 | " nb_path = find_notebook(fullname, path)\n", |
|
207 | 207 | " if not nb_path:\n", |
|
208 | 208 | " return\n", |
|
209 | 209 | " \n", |
|
210 | 210 | " key = path\n", |
|
211 | 211 | " if path:\n", |
|
212 | 212 | " # lists aren't hashable\n", |
|
213 | 213 | " key = os.path.sep.join(path)\n", |
|
214 | 214 | " \n", |
|
215 | 215 | " if key not in self.loaders:\n", |
|
216 | 216 | " self.loaders[key] = NotebookLoader(path)\n", |
|
217 | 217 | " return self.loaders[key]\n" |
|
218 | 218 | ], |
|
219 | 219 | "language": "python", |
|
220 | 220 | "metadata": {}, |
|
221 | 221 | "outputs": [], |
|
222 | 222 | "prompt_number": 5 |
|
223 | 223 | }, |
|
224 | 224 | { |
|
225 | 225 | "cell_type": "heading", |
|
226 | 226 | "level": 2, |
|
227 | 227 | "metadata": {}, |
|
228 | 228 | "source": [ |
|
229 | 229 | "Register the hook" |
|
230 | 230 | ] |
|
231 | 231 | }, |
|
232 | 232 | { |
|
233 | 233 | "cell_type": "markdown", |
|
234 | 234 | "metadata": {}, |
|
235 | 235 | "source": [ |
|
236 | 236 | "Now we register the `NotebookFinder` with `sys.meta_path`" |
|
237 | 237 | ] |
|
238 | 238 | }, |
|
239 | 239 | { |
|
240 | 240 | "cell_type": "code", |
|
241 | 241 | "collapsed": false, |
|
242 | 242 | "input": [ |
|
243 | 243 | "sys.meta_path.append(NotebookFinder())" |
|
244 | 244 | ], |
|
245 | 245 | "language": "python", |
|
246 | 246 | "metadata": {}, |
|
247 | 247 | "outputs": [], |
|
248 | 248 | "prompt_number": 6 |
|
249 | 249 | }, |
|
250 | 250 | { |
|
251 | 251 | "cell_type": "markdown", |
|
252 | 252 | "metadata": {}, |
|
253 | 253 | "source": [ |
|
254 | 254 | "After this point, my notebooks should be importable.\n", |
|
255 | 255 | "\n", |
|
256 | 256 | "Let's look at what we have in the CWD:" |
|
257 | 257 | ] |
|
258 | 258 | }, |
|
259 | 259 | { |
|
260 | 260 | "cell_type": "code", |
|
261 | 261 | "collapsed": false, |
|
262 | 262 | "input": [ |
|
263 | 263 | "ls nbimp" |
|
264 | 264 | ], |
|
265 | 265 | "language": "python", |
|
266 | 266 | "metadata": {}, |
|
267 | 267 | "outputs": [ |
|
268 | 268 | { |
|
269 | 269 | "output_type": "stream", |
|
270 | 270 | "stream": "stdout", |
|
271 | 271 | "text": [ |
|
272 | 272 | "__init__.py __init__.pyc bs.ipynb mynotebook.ipynb \u001b[34mnbs\u001b[m\u001b[m/\r\n" |
|
273 | 273 | ] |
|
274 | 274 | } |
|
275 | 275 | ], |
|
276 | 276 | "prompt_number": 7 |
|
277 | 277 | }, |
|
278 | 278 | { |
|
279 | 279 | "cell_type": "markdown", |
|
280 | 280 | "metadata": {}, |
|
281 | 281 | "source": [ |
|
282 | 282 | "So I should be able to `import nbimp.mynotebook`.\n" |
|
283 | 283 | ] |
|
284 | 284 | }, |
|
285 | 285 | { |
|
286 | 286 | "cell_type": "heading", |
|
287 | 287 | "level": 3, |
|
288 | 288 | "metadata": {}, |
|
289 | 289 | "source": [ |
|
290 | 290 | "Aside: displaying notebooks" |
|
291 | 291 | ] |
|
292 | 292 | }, |
|
293 | 293 | { |
|
294 | 294 | "cell_type": "markdown", |
|
295 | 295 | "metadata": {}, |
|
296 | 296 | "source": [ |
|
297 | 297 | "Here is some simple code to display the contents of a notebook\n", |
|
298 | 298 | "with syntax highlighting, etc." |
|
299 | 299 | ] |
|
300 | 300 | }, |
|
301 | 301 | { |
|
302 | 302 | "cell_type": "code", |
|
303 | 303 | "collapsed": false, |
|
304 | 304 | "input": [ |
|
305 | 305 | "from pygments import highlight\n", |
|
306 | 306 | "from pygments.lexers import PythonLexer\n", |
|
307 | 307 | "from pygments.formatters import HtmlFormatter\n", |
|
308 | 308 | "\n", |
|
309 | 309 | "from IPython.display import display, HTML\n", |
|
310 | 310 | "\n", |
|
311 | 311 | "formatter = HtmlFormatter()\n", |
|
312 | 312 | "lexer = PythonLexer()\n", |
|
313 | 313 | "\n", |
|
314 | 314 | "# publish the CSS for pygments highlighting\n", |
|
315 | 315 | "display(HTML(\"\"\"\n", |
|
316 | 316 | "<style type='text/css'>\n", |
|
317 | 317 | "%s\n", |
|
318 | 318 | "</style>\n", |
|
319 | 319 | "\"\"\" % formatter.get_style_defs()\n", |
|
320 | 320 | "))" |
|
321 | 321 | ], |
|
322 | 322 | "language": "python", |
|
323 | 323 | "metadata": {}, |
|
324 | 324 | "outputs": [ |
|
325 | 325 | { |
|
326 | 326 | "html": [ |
|
327 | 327 | "\n", |
|
328 | 328 | "<style type='text/css'>\n", |
|
329 | 329 | ".hll { background-color: #ffffcc }\n", |
|
330 | 330 | ".c { color: #408080; font-style: italic } /* Comment */\n", |
|
331 | 331 | ".err { border: 1px solid #FF0000 } /* Error */\n", |
|
332 | 332 | ".k { color: #008000; font-weight: bold } /* Keyword */\n", |
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344 | 344 | ".gp { color: #000080; font-weight: bold } /* Generic.Prompt */\n", |
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346 | 346 | ".gu { color: #800080; font-weight: bold } /* Generic.Subheading */\n", |
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347 | 347 | ".gt { color: #0044DD } /* Generic.Traceback */\n", |
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348 | 348 | ".kc { color: #008000; font-weight: bold } /* Keyword.Constant */\n", |
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349 | 349 | ".kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\n", |
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350 | 350 | ".kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\n", |
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351 | 351 | ".kp { color: #008000 } /* Keyword.Pseudo */\n", |
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352 | 352 | ".kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\n", |
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365 | 365 | ".nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\n", |
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366 | 366 | ".nt { color: #008000; font-weight: bold } /* Name.Tag */\n", |
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367 | 367 | ".nv { color: #19177C } /* Name.Variable */\n", |
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368 | 368 | ".ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\n", |
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375 | 375 | ".sc { color: #BA2121 } /* Literal.String.Char */\n", |
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376 | 376 | ".sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\n", |
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377 | 377 | ".s2 { color: #BA2121 } /* Literal.String.Double */\n", |
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378 | 378 | ".se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\n", |
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379 | 379 | ".sh { color: #BA2121 } /* Literal.String.Heredoc */\n", |
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380 | 380 | ".si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\n", |
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381 | 381 | ".sx { color: #008000 } /* Literal.String.Other */\n", |
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382 | 382 | ".sr { color: #BB6688 } /* Literal.String.Regex */\n", |
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383 | 383 | ".s1 { color: #BA2121 } /* Literal.String.Single */\n", |
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384 | 384 | ".ss { color: #19177C } /* Literal.String.Symbol */\n", |
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385 | 385 | ".bp { color: #008000 } /* Name.Builtin.Pseudo */\n", |
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386 | 386 | ".vc { color: #19177C } /* Name.Variable.Class */\n", |
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387 | 387 | ".vg { color: #19177C } /* Name.Variable.Global */\n", |
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388 | 388 | ".vi { color: #19177C } /* Name.Variable.Instance */\n", |
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389 | 389 | ".il { color: #666666 } /* Literal.Number.Integer.Long */\n", |
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390 | 390 | "</style>\n" |
|
391 | 391 | ], |
|
392 | 392 | "metadata": {}, |
|
393 | 393 | "output_type": "display_data", |
|
394 | 394 | "text": [ |
|
395 | 395 | "<IPython.core.display.HTML at 0x10a006890>" |
|
396 | 396 | ] |
|
397 | 397 | } |
|
398 | 398 | ], |
|
399 | 399 | "prompt_number": 8 |
|
400 | 400 | }, |
|
401 | 401 | { |
|
402 | 402 | "cell_type": "code", |
|
403 | 403 | "collapsed": false, |
|
404 | 404 | "input": [ |
|
405 | 405 | "def show_notebook(fname):\n", |
|
406 | 406 | " \"\"\"display a short summary of the cells of a notebook\"\"\"\n", |
|
407 | 407 | " with io.open(fname, 'r', encoding='utf-8') as f:\n", |
|
408 | 408 | " nb = current.read(f, 'json')\n", |
|
409 | 409 | " html = []\n", |
|
410 | 410 | " for cell in nb.worksheets[0].cells:\n", |
|
411 | 411 | " html.append(\"<h4>%s cell</h4>\" % cell.cell_type)\n", |
|
412 | 412 | " if cell.cell_type == 'code':\n", |
|
413 | 413 | " html.append(highlight(cell.input, lexer, formatter))\n", |
|
414 | 414 | " else:\n", |
|
415 | 415 | " html.append(\"<pre>%s</pre>\" % cell.source)\n", |
|
416 | 416 | " display(HTML('\\n'.join(html)))\n", |
|
417 | 417 | "\n", |
|
418 | 418 | "show_notebook(os.path.join(\"nbimp\", \"mynotebook.ipynb\"))" |
|
419 | 419 | ], |
|
420 | 420 | "language": "python", |
|
421 | 421 | "metadata": {}, |
|
422 | 422 | "outputs": [ |
|
423 | 423 | { |
|
424 | 424 | "html": [ |
|
425 | 425 | "<h4>heading cell</h4>\n", |
|
426 | 426 | "<pre>My Notebook</pre>\n", |
|
427 | 427 | "<h4>code cell</h4>\n", |
|
428 | 428 | "<div class=\"highlight\"><pre><span class=\"k\">def</span> <span class=\"nf\">foo</span><span class=\"p\">():</span>\n", |
|
429 | 429 | " <span class=\"k\">return</span> <span class=\"s\">"foo"</span>\n", |
|
430 | 430 | "</pre></div>\n", |
|
431 | 431 | "\n", |
|
432 | 432 | "<h4>code cell</h4>\n", |
|
433 | 433 | "<div class=\"highlight\"><pre><span class=\"k\">def</span> <span class=\"nf\">has_ip_syntax</span><span class=\"p\">():</span>\n", |
|
434 | 434 | " <span class=\"n\">listing</span> <span class=\"o\">=</span> <span class=\"err\">!</span><span class=\"n\">ls</span>\n", |
|
435 | 435 | " <span class=\"k\">return</span> <span class=\"n\">listing</span>\n", |
|
436 | 436 | "</pre></div>\n", |
|
437 | 437 | "\n", |
|
438 | 438 | "<h4>code cell</h4>\n", |
|
439 | 439 | "<div class=\"highlight\"><pre><span class=\"k\">def</span> <span class=\"nf\">whatsmyname</span><span class=\"p\">():</span>\n", |
|
440 | 440 | " <span class=\"k\">return</span> <span class=\"n\">__name__</span>\n", |
|
441 | 441 | "</pre></div>\n" |
|
442 | 442 | ], |
|
443 | 443 | "metadata": {}, |
|
444 | 444 | "output_type": "display_data", |
|
445 | 445 | "text": [ |
|
446 | 446 | "<IPython.core.display.HTML at 0x10ad7af10>" |
|
447 | 447 | ] |
|
448 | 448 | } |
|
449 | 449 | ], |
|
450 | 450 | "prompt_number": 9 |
|
451 | 451 | }, |
|
452 | 452 | { |
|
453 | 453 | "cell_type": "markdown", |
|
454 | 454 | "metadata": {}, |
|
455 | 455 | "source": [ |
|
456 | 456 | "So my notebook has a heading cell and some code cells,\n", |
|
457 | 457 | "one of which contains some IPython syntax.\n", |
|
458 | 458 | "\n", |
|
459 | 459 | "Let's see what happens when we import it" |
|
460 | 460 | ] |
|
461 | 461 | }, |
|
462 | 462 | { |
|
463 | 463 | "cell_type": "code", |
|
464 | 464 | "collapsed": false, |
|
465 | 465 | "input": [ |
|
466 | 466 | "from nbimp import mynotebook" |
|
467 | 467 | ], |
|
468 | 468 | "language": "python", |
|
469 | 469 | "metadata": {}, |
|
470 | 470 | "outputs": [ |
|
471 | 471 | { |
|
472 | 472 | "output_type": "stream", |
|
473 | 473 | "stream": "stdout", |
|
474 | 474 | "text": [ |
|
475 | 475 | "importing IPython notebook from nbimp/mynotebook.ipynb\n" |
|
476 | 476 | ] |
|
477 | 477 | } |
|
478 | 478 | ], |
|
479 | 479 | "prompt_number": 10 |
|
480 | 480 | }, |
|
481 | 481 | { |
|
482 | 482 | "cell_type": "markdown", |
|
483 | 483 | "metadata": {}, |
|
484 | 484 | "source": [ |
|
485 | 485 | "Hooray, it imported! Does it work?" |
|
486 | 486 | ] |
|
487 | 487 | }, |
|
488 | 488 | { |
|
489 | 489 | "cell_type": "code", |
|
490 | 490 | "collapsed": false, |
|
491 | 491 | "input": [ |
|
492 | 492 | "mynotebook.foo()" |
|
493 | 493 | ], |
|
494 | 494 | "language": "python", |
|
495 | 495 | "metadata": {}, |
|
496 | 496 | "outputs": [ |
|
497 | 497 | { |
|
498 | 498 | "metadata": {}, |
|
499 | 499 | "output_type": "pyout", |
|
500 | 500 | "prompt_number": 11, |
|
501 | 501 | "text": [ |
|
502 | 502 | "'foo'" |
|
503 | 503 | ] |
|
504 | 504 | } |
|
505 | 505 | ], |
|
506 | 506 | "prompt_number": 11 |
|
507 | 507 | }, |
|
508 | 508 | { |
|
509 | 509 | "cell_type": "markdown", |
|
510 | 510 | "metadata": {}, |
|
511 | 511 | "source": [ |
|
512 | 512 | "Hooray again!\n", |
|
513 | 513 | "\n", |
|
514 | 514 | "Even the function that contains IPython syntax works:" |
|
515 | 515 | ] |
|
516 | 516 | }, |
|
517 | 517 | { |
|
518 | 518 | "cell_type": "code", |
|
519 | 519 | "collapsed": false, |
|
520 | 520 | "input": [ |
|
521 | 521 | "mynotebook.has_ip_syntax()" |
|
522 | 522 | ], |
|
523 | 523 | "language": "python", |
|
524 | 524 | "metadata": {}, |
|
525 | 525 | "outputs": [ |
|
526 | 526 | { |
|
527 | 527 | "metadata": {}, |
|
528 | 528 | "output_type": "pyout", |
|
529 | 529 | "prompt_number": 12, |
|
530 | 530 | "text": [ |
|
531 | 531 | "['Animations Using clear_output.ipynb',\n", |
|
532 | 532 | " 'Cell Magics.ipynb',\n", |
|
533 | 533 | " 'Custom Display Logic.ipynb',\n", |
|
534 | 534 | " 'Cython Magics.ipynb',\n", |
|
535 | 535 | " 'Data Publication API.ipynb',\n", |
|
536 | 536 | " 'Frontend-Kernel Model.ipynb',\n", |
|
537 | 537 | " 'Importing Notebooks.ipynb',\n", |
|
538 | 538 | " 'Octave Magic.ipynb',\n", |
|
539 | 539 | " 'Part 1 - Running Code.ipynb',\n", |
|
540 | 540 | " 'Part 2 - Basic Output.ipynb',\n", |
|
541 | 541 | " 'Part 3 - Plotting with Matplotlib.ipynb',\n", |
|
542 | 542 | " 'Part 4 - Markdown Cells.ipynb',\n", |
|
543 | 543 | " 'Part 5 - Rich Display System.ipynb',\n", |
|
544 | 544 | " 'Progress Bars.ipynb',\n", |
|
545 | 545 | " 'R Magics.ipynb',\n", |
|
546 | 546 | " 'README.md',\n", |
|
547 | 547 | " 'Script Magics.ipynb',\n", |
|
548 | 548 | " 'SymPy Examples.ipynb',\n", |
|
549 | 549 | " 'Trapezoid Rule.ipynb',\n", |
|
550 | 550 | " 'Typesetting Math Using MathJax.ipynb',\n", |
|
551 | 551 | " 'animation.m4v',\n", |
|
552 | 552 | " 'foo.pyx',\n", |
|
553 | 553 | " 'lnum.py',\n", |
|
554 | 554 | " 'logo',\n", |
|
555 | 555 | " 'nbimp',\n", |
|
556 | 556 | " 'python-logo.svg',\n", |
|
557 | 557 | " 'test.html']" |
|
558 | 558 | ] |
|
559 | 559 | } |
|
560 | 560 | ], |
|
561 | 561 | "prompt_number": 12 |
|
562 | 562 | }, |
|
563 | 563 | { |
|
564 | 564 | "cell_type": "heading", |
|
565 | 565 | "level": 2, |
|
566 | 566 | "metadata": {}, |
|
567 | 567 | "source": [ |
|
568 | 568 | "Notebooks in packages" |
|
569 | 569 | ] |
|
570 | 570 | }, |
|
571 | 571 | { |
|
572 | 572 | "cell_type": "markdown", |
|
573 | 573 | "metadata": {}, |
|
574 | 574 | "source": [ |
|
575 | 575 | "We also have a notebook inside the `nb` package,\n", |
|
576 | 576 | "so let's make sure that works as well." |
|
577 | 577 | ] |
|
578 | 578 | }, |
|
579 | 579 | { |
|
580 | 580 | "cell_type": "code", |
|
581 | 581 | "collapsed": false, |
|
582 | 582 | "input": [ |
|
583 | 583 | "ls nbimp/nbs" |
|
584 | 584 | ], |
|
585 | 585 | "language": "python", |
|
586 | 586 | "metadata": {}, |
|
587 | 587 | "outputs": [ |
|
588 | 588 | { |
|
589 | 589 | "output_type": "stream", |
|
590 | 590 | "stream": "stdout", |
|
591 | 591 | "text": [ |
|
592 | 592 | "__init__.py __init__.pyc other.ipynb\r\n" |
|
593 | 593 | ] |
|
594 | 594 | } |
|
595 | 595 | ], |
|
596 | 596 | "prompt_number": 13 |
|
597 | 597 | }, |
|
598 | 598 | { |
|
599 | 599 | "cell_type": "markdown", |
|
600 | 600 | "metadata": {}, |
|
601 | 601 | "source": [ |
|
602 | 602 | "Note that the `__init__.py` is necessary for `nb` to be considered a package,\n", |
|
603 | 603 | "just like usual." |
|
604 | 604 | ] |
|
605 | 605 | }, |
|
606 | 606 | { |
|
607 | 607 | "cell_type": "code", |
|
608 | 608 | "collapsed": false, |
|
609 | 609 | "input": [ |
|
610 | 610 | "show_notebook(os.path.join(\"nbimp\", \"nbs\", \"other.ipynb\"))" |
|
611 | 611 | ], |
|
612 | 612 | "language": "python", |
|
613 | 613 | "metadata": {}, |
|
614 | 614 | "outputs": [ |
|
615 | 615 | { |
|
616 | 616 | "html": [ |
|
617 | 617 | "<h4>markdown cell</h4>\n", |
|
618 | 618 | "<pre>This notebook just defines `bar`</pre>\n", |
|
619 | 619 | "<h4>code cell</h4>\n", |
|
620 | 620 | "<div class=\"highlight\"><pre><span class=\"k\">def</span> <span class=\"nf\">bar</span><span class=\"p\">(</span><span class=\"n\">x</span><span class=\"p\">):</span>\n", |
|
621 | 621 | " <span class=\"k\">return</span> <span class=\"s\">"bar"</span> <span class=\"o\">*</span> <span class=\"n\">x</span>\n", |
|
622 | 622 | "</pre></div>\n" |
|
623 | 623 | ], |
|
624 | 624 | "metadata": {}, |
|
625 | 625 | "output_type": "display_data", |
|
626 | 626 | "text": [ |
|
627 | 627 | "<IPython.core.display.HTML at 0x10ad56090>" |
|
628 | 628 | ] |
|
629 | 629 | } |
|
630 | 630 | ], |
|
631 | 631 | "prompt_number": 14 |
|
632 | 632 | }, |
|
633 | 633 | { |
|
634 | 634 | "cell_type": "code", |
|
635 | 635 | "collapsed": false, |
|
636 | 636 | "input": [ |
|
637 | 637 | "from nbimp.nbs import other\n", |
|
638 | 638 | "other.bar(5)" |
|
639 | 639 | ], |
|
640 | 640 | "language": "python", |
|
641 | 641 | "metadata": {}, |
|
642 | 642 | "outputs": [ |
|
643 | 643 | { |
|
644 | 644 | "output_type": "stream", |
|
645 | 645 | "stream": "stdout", |
|
646 | 646 | "text": [ |
|
647 | 647 | "importing IPython notebook from nbimp/nbs/other.ipynb\n" |
|
648 | 648 | ] |
|
649 | 649 | }, |
|
650 | 650 | { |
|
651 | 651 | "metadata": {}, |
|
652 | 652 | "output_type": "pyout", |
|
653 | 653 | "prompt_number": 15, |
|
654 | 654 | "text": [ |
|
655 | 655 | "'barbarbarbarbar'" |
|
656 | 656 | ] |
|
657 | 657 | } |
|
658 | 658 | ], |
|
659 | 659 | "prompt_number": 15 |
|
660 | 660 | }, |
|
661 | 661 | { |
|
662 | 662 | "cell_type": "markdown", |
|
663 | 663 | "metadata": {}, |
|
664 | 664 | "source": [ |
|
665 | 665 | "So now we have importable notebooks, from both the local directory and inside packages.\n", |
|
666 | 666 | "\n", |
|
667 | 667 | "I can even put a notebook inside IPython, to further demonstrate that this is working properly:" |
|
668 | 668 | ] |
|
669 | 669 | }, |
|
670 | 670 | { |
|
671 | 671 | "cell_type": "code", |
|
672 | 672 | "collapsed": false, |
|
673 | 673 | "input": [ |
|
674 | 674 | "import shutil\n", |
|
675 | 675 | "from IPython.utils.path import get_ipython_package_dir\n", |
|
676 | 676 | "\n", |
|
677 | 677 | "utils = os.path.join(get_ipython_package_dir(), 'utils')\n", |
|
678 | 678 | "shutil.copy(os.path.join(\"nbimp\", \"mynotebook.ipynb\"),\n", |
|
679 | 679 | " os.path.join(utils, \"inside_ipython.ipynb\")\n", |
|
680 | 680 | ")" |
|
681 | 681 | ], |
|
682 | 682 | "language": "python", |
|
683 | 683 | "metadata": {}, |
|
684 | 684 | "outputs": [], |
|
685 | 685 | "prompt_number": 16 |
|
686 | 686 | }, |
|
687 | 687 | { |
|
688 | 688 | "cell_type": "markdown", |
|
689 | 689 | "metadata": {}, |
|
690 | 690 | "source": [ |
|
691 | 691 | "and import the notebook from `IPython.utils`" |
|
692 | 692 | ] |
|
693 | 693 | }, |
|
694 | 694 | { |
|
695 | 695 | "cell_type": "code", |
|
696 | 696 | "collapsed": false, |
|
697 | 697 | "input": [ |
|
698 | 698 | "from IPython.utils import inside_ipython\n", |
|
699 | 699 | "inside_ipython.whatsmyname()" |
|
700 | 700 | ], |
|
701 | 701 | "language": "python", |
|
702 | 702 | "metadata": {}, |
|
703 | 703 | "outputs": [ |
|
704 | 704 | { |
|
705 | 705 | "output_type": "stream", |
|
706 | 706 | "stream": "stdout", |
|
707 | 707 | "text": [ |
|
708 | 708 | "importing IPython notebook from /Users/minrk/dev/ip/mine/IPython/utils/inside_ipython.ipynb\n" |
|
709 | 709 | ] |
|
710 | 710 | }, |
|
711 | 711 | { |
|
712 | 712 | "metadata": {}, |
|
713 | 713 | "output_type": "pyout", |
|
714 | 714 | "prompt_number": 17, |
|
715 | 715 | "text": [ |
|
716 | 716 | "'IPython.utils.inside_ipython'" |
|
717 | 717 | ] |
|
718 | 718 | } |
|
719 | 719 | ], |
|
720 | 720 | "prompt_number": 17 |
|
721 | 721 | }, |
|
722 | 722 | { |
|
723 | 723 | "cell_type": "heading", |
|
724 | 724 | "level": 2, |
|
725 | 725 | "metadata": {}, |
|
726 | 726 | "source": [ |
|
727 | 727 | "Even Cython magics" |
|
728 | 728 | ] |
|
729 | 729 | }, |
|
730 | 730 | { |
|
731 | 731 | "cell_type": "markdown", |
|
732 | 732 | "metadata": {}, |
|
733 | 733 | "source": [ |
|
734 | 734 | "With a bit of extra magic for handling the IPython interactive namespace during load,\n", |
|
735 | 735 | "even magics like `%%cython` can be used:" |
|
736 | 736 | ] |
|
737 | 737 | }, |
|
738 | 738 | { |
|
739 | 739 | "cell_type": "code", |
|
740 | 740 | "collapsed": false, |
|
741 | 741 | "input": [ |
|
742 | 742 | "import Cython_Magics" |
|
743 | 743 | ], |
|
744 | 744 | "language": "python", |
|
745 | 745 | "metadata": {}, |
|
746 | 746 | "outputs": [ |
|
747 | 747 | { |
|
748 | 748 | "output_type": "stream", |
|
749 | 749 | "stream": "stdout", |
|
750 | 750 | "text": [ |
|
751 | 751 | "importing IPython notebook from Cython Magics.ipynb\n", |
|
752 | 752 | "1000000 loops, best of 3: 439 ns per loop" |
|
753 | 753 | ] |
|
754 | 754 | }, |
|
755 | 755 | { |
|
756 | 756 | "output_type": "stream", |
|
757 | 757 | "stream": "stdout", |
|
758 | 758 | "text": [ |
|
759 | 759 | "\n", |
|
760 | 760 | "sin(1)= 0.841470984808\n" |
|
761 | 761 | ] |
|
762 | 762 | } |
|
763 | 763 | ], |
|
764 | 764 | "prompt_number": 18 |
|
765 | 765 | }, |
|
766 | 766 | { |
|
767 | 767 | "cell_type": "code", |
|
768 | 768 | "collapsed": false, |
|
769 | 769 | "input": [ |
|
770 | 770 | "Cython_Magics.black_scholes(100.0, 100.0, 1.0, 0.3, 0.03, 0.0, -1)" |
|
771 | 771 | ], |
|
772 | 772 | "language": "python", |
|
773 | 773 | "metadata": {}, |
|
774 | 774 | "outputs": [ |
|
775 | 775 | { |
|
776 | 776 | "metadata": {}, |
|
777 | 777 | "output_type": "pyout", |
|
778 | 778 | "prompt_number": 19, |
|
779 | 779 | "text": [ |
|
780 | 780 | "10.327861752731728" |
|
781 | 781 | ] |
|
782 | 782 | } |
|
783 | 783 | ], |
|
784 | 784 | "prompt_number": 19 |
|
785 | 785 | } |
|
786 | 786 | ], |
|
787 | 787 | "metadata": {} |
|
788 | 788 | } |
|
789 | 789 | ] |
|
790 | 790 | } No newline at end of file |
@@ -1,1331 +1,1313 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "name": "" |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "heading", |
|
12 | 12 | "level": 1, |
|
13 | 13 | "metadata": {}, |
|
14 | 14 | "source": [ |
|
15 | 15 | "IPython's Rich Display System" |
|
16 | 16 | ] |
|
17 | 17 | }, |
|
18 | 18 | { |
|
19 | 19 | "cell_type": "markdown", |
|
20 | 20 | "metadata": {}, |
|
21 | 21 | "source": [ |
|
22 | 22 | "In Python, objects can declare their textual representation using the `__repr__` method. IPython expands on this idea and allows objects to declare other, richer representations including:\n", |
|
23 | 23 | "\n", |
|
24 | 24 | "* HTML\n", |
|
25 | 25 | "* JSON\n", |
|
26 | 26 | "* PNG\n", |
|
27 | 27 | "* JPEG\n", |
|
28 | 28 | "* SVG\n", |
|
29 | 29 | "* LaTeX\n", |
|
30 | 30 | "\n", |
|
31 | 31 | "A single object can declare some or all of these representations; all are handled by IPython's *display system*. This Notebook shows how you can use this display system to incorporate a broad range of content into your Notebooks." |
|
32 | 32 | ] |
|
33 | 33 | }, |
|
34 | 34 | { |
|
35 | 35 | "cell_type": "heading", |
|
36 | 36 | "level": 2, |
|
37 | 37 | "metadata": {}, |
|
38 | 38 | "source": [ |
|
39 | 39 | "Basic display imports" |
|
40 | 40 | ] |
|
41 | 41 | }, |
|
42 | 42 | { |
|
43 | 43 | "cell_type": "markdown", |
|
44 | 44 | "metadata": {}, |
|
45 | 45 | "source": [ |
|
46 | 46 | "The `display` function is a general purpose tool for displaying different representations of objects. Think of it as `print` for these rich representations." |
|
47 | 47 | ] |
|
48 | 48 | }, |
|
49 | 49 | { |
|
50 | 50 | "cell_type": "code", |
|
51 | 51 | "collapsed": false, |
|
52 | 52 | "input": [ |
|
53 | 53 | "from IPython.display import display" |
|
54 | 54 | ], |
|
55 | 55 | "language": "python", |
|
56 | 56 | "metadata": {}, |
|
57 | 57 | "outputs": [], |
|
58 | 58 | "prompt_number": 8 |
|
59 | 59 | }, |
|
60 | 60 | { |
|
61 | 61 | "cell_type": "markdown", |
|
62 | 62 | "metadata": {}, |
|
63 | 63 | "source": [ |
|
64 | 64 | "A few points:\n", |
|
65 | 65 | "\n", |
|
66 | 66 | "* Calling `display` on an object will send **all** possible representations to the Notebook.\n", |
|
67 | 67 | "* These representations are stored in the Notebook document.\n", |
|
68 | 68 | "* In general the Notebook will use the richest available representation.\n", |
|
69 | 69 | "\n", |
|
70 | 70 | "If you want to display a particular representation, there are specific functions for that:" |
|
71 | 71 | ] |
|
72 | 72 | }, |
|
73 | 73 | { |
|
74 | 74 | "cell_type": "code", |
|
75 | 75 | "collapsed": false, |
|
76 | 76 | "input": [ |
|
77 | 77 | "from IPython.display import display_pretty, display_html, display_jpeg, display_png, display_json, display_latex, display_svg" |
|
78 | 78 | ], |
|
79 | 79 | "language": "python", |
|
80 | 80 | "metadata": {}, |
|
81 | 81 | "outputs": [], |
|
82 | 82 | "prompt_number": 11 |
|
83 | 83 | }, |
|
84 | 84 | { |
|
85 | 85 | "cell_type": "heading", |
|
86 | 86 | "level": 2, |
|
87 | 87 | "metadata": {}, |
|
88 | 88 | "source": [ |
|
89 | 89 | "Images" |
|
90 | 90 | ] |
|
91 | 91 | }, |
|
92 | 92 | { |
|
93 | 93 | "cell_type": "markdown", |
|
94 | 94 | "metadata": {}, |
|
95 | 95 | "source": [ |
|
96 | 96 | "To work with images (JPEG, PNG) use the `Image` class." |
|
97 | 97 | ] |
|
98 | 98 | }, |
|
99 | 99 | { |
|
100 | 100 | "cell_type": "code", |
|
101 | 101 | "collapsed": false, |
|
102 | 102 | "input": [ |
|
103 | 103 | "from IPython.display import Image" |
|
104 | 104 | ], |
|
105 | 105 | "language": "python", |
|
106 | 106 | "metadata": {}, |
|
107 | 107 | "outputs": [], |
|
108 | 108 | "prompt_number": 2 |
|
109 | 109 | }, |
|
110 | 110 | { |
|
111 | 111 | "cell_type": "code", |
|
112 | 112 | "collapsed": false, |
|
113 | 113 | "input": [ |
|
114 | 114 | "i = Image(filename='logo/logo.png')" |
|
115 | 115 | ], |
|
116 | 116 | "language": "python", |
|
117 | 117 | "metadata": {}, |
|
118 | 118 | "outputs": [], |
|
119 | 119 | "prompt_number": 5 |
|
120 | 120 | }, |
|
121 | 121 | { |
|
122 | 122 | "cell_type": "markdown", |
|
123 | 123 | "metadata": {}, |
|
124 | 124 | "source": [ |
|
125 | 125 | "Returning an `Image` object from an expression will automatically display it:" |
|
126 | 126 | ] |
|
127 | 127 | }, |
|
128 | 128 | { |
|
129 | 129 | "cell_type": "code", |
|
130 | 130 | "collapsed": false, |
|
131 | 131 | "input": [ |
|
132 | 132 | "i" |
|
133 | 133 | ], |
|
134 | 134 | "language": "python", |
|
135 | 135 | "metadata": {}, |
|
136 | 136 | "outputs": [ |
|
137 | 137 | { |
|
138 | 138 | "output_type": "pyout", |
|
139 | 139 | "png": 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|
|
140 | 140 | "prompt_number": 6, |
|
141 | 141 | "text": [ |
|
142 | 142 | "<IPython.core.display.Image at 0x107ea26d0>" |
|
143 | 143 | ] |
|
144 | 144 | } |
|
145 | 145 | ], |
|
146 | 146 | "prompt_number": 6 |
|
147 | 147 | }, |
|
148 | 148 | { |
|
149 | 149 | "cell_type": "markdown", |
|
150 | 150 | "metadata": {}, |
|
151 | 151 | "source": [ |
|
152 | 152 | "Or you can pass it to `display`:" |
|
153 | 153 | ] |
|
154 | 154 | }, |
|
155 | 155 | { |
|
156 | 156 | "cell_type": "code", |
|
157 | 157 | "collapsed": false, |
|
158 | 158 | "input": [ |
|
159 | 159 | "display(i)" |
|
160 | 160 | ], |
|
161 | 161 | "language": "python", |
|
162 | 162 | "metadata": {}, |
|
163 | 163 | "outputs": [ |
|
164 | 164 | { |
|
165 | 165 | "output_type": "display_data", |
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166 | 166 | "png": 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|
|
167 | 167 | "text": [ |
|
168 | 168 | "<IPython.core.display.Image at 0x107ea26d0>" |
|
169 | 169 | ] |
|
170 | 170 | } |
|
171 | 171 | ], |
|
172 | 172 | "prompt_number": 9 |
|
173 | 173 | }, |
|
174 | 174 | { |
|
175 | 175 | "cell_type": "markdown", |
|
176 | 176 | "metadata": {}, |
|
177 | 177 | "source": [ |
|
178 | 178 | "An image can also be displayed from raw data or a url" |
|
179 | 179 | ] |
|
180 | 180 | }, |
|
181 | 181 | { |
|
182 | 182 | "cell_type": "code", |
|
183 | 183 | "collapsed": false, |
|
184 | 184 | "input": [ |
|
185 | 185 | "Image(url='http://python.org/images/python-logo.gif')" |
|
186 | 186 | ], |
|
187 | 187 | "language": "python", |
|
188 | 188 | "metadata": {}, |
|
189 | 189 | "outputs": [ |
|
190 | 190 | { |
|
191 | 191 | "html": [ |
|
192 | 192 | "<img src=\"http://python.org/images/python-logo.gif\" />" |
|
193 | 193 | ], |
|
194 | 194 | "output_type": "pyout", |
|
195 | 195 | "prompt_number": 2, |
|
196 | 196 | "text": [ |
|
197 | 197 | "<IPython.core.display.Image at 0x1060e7410>" |
|
198 | 198 | ] |
|
199 | 199 | } |
|
200 | 200 | ], |
|
201 | 201 | "prompt_number": 2 |
|
202 | 202 | }, |
|
203 | 203 | { |
|
204 | 204 | "cell_type": "markdown", |
|
205 | 205 | "metadata": {}, |
|
206 | 206 | "source": [ |
|
207 | 207 | "SVG images are also supported out of the box (since modern browsers do a good job of rendering them):" |
|
208 | 208 | ] |
|
209 | 209 | }, |
|
210 | 210 | { |
|
211 | 211 | "cell_type": "code", |
|
212 | 212 | "collapsed": false, |
|
213 | 213 | "input": [ |
|
214 | 214 | "from IPython.display import SVG\n", |
|
215 | 215 | "SVG(filename='python-logo.svg')" |
|
216 | 216 | ], |
|
217 | 217 | "language": "python", |
|
218 | 218 | "metadata": {}, |
|
219 | 219 | "outputs": [ |
|
220 | 220 | { |
|
221 | 221 | "output_type": "pyout", |
|
222 | 222 | "prompt_number": 3, |
|
223 | 223 | "svg": [ |
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224 | 224 | "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", |
|
225 | 225 | " <metadata id=\"metadata2193\">\n", |
|
226 | 226 | " <rdf:RDF>\n", |
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227 | 227 | " <cc:Work rdf:about=\"\">\n", |
|
228 | 228 | " <dc:format>image/svg+xml</dc:format>\n", |
|
229 | 229 | " <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n", |
|
230 | 230 | " </cc:Work>\n", |
|
231 | 231 | " </rdf:RDF>\n", |
|
232 | 232 | " </metadata>\n", |
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233 | 233 | " <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n", |
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234 | 234 | " <defs id=\"defs4\">\n", |
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235 | 235 | " <linearGradient id=\"linearGradient2795\">\n", |
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236 | 236 | " <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n", |
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237 | 237 | " <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n", |
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238 | 238 | " </linearGradient>\n", |
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239 | 239 | " <linearGradient id=\"linearGradient2787\">\n", |
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240 | 240 | " <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n", |
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241 | 241 | " <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n", |
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242 | 242 | " </linearGradient>\n", |
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243 | 243 | " <linearGradient id=\"linearGradient3676\">\n", |
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244 | 244 | " <stop id=\"stop3678\" offset=\"0\" style=\"stop-color:#b2b2b2;stop-opacity:0.5\"/>\n", |
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245 | 245 | " <stop id=\"stop3680\" offset=\"1\" style=\"stop-color:#b3b3b3;stop-opacity:0\"/>\n", |
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246 | 246 | " </linearGradient>\n", |
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247 | 247 | " <linearGradient id=\"linearGradient3236\">\n", |
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248 | 248 | " <stop id=\"stop3244\" offset=\"0\" style=\"stop-color:#f4f4f4;stop-opacity:1\"/>\n", |
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249 | 249 | " <stop id=\"stop3240\" offset=\"1\" style=\"stop-color:#ffffff;stop-opacity:1\"/>\n", |
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250 | 250 | " </linearGradient>\n", |
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251 | 251 | " <linearGradient id=\"linearGradient4671\">\n", |
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252 | 252 | " <stop id=\"stop4673\" offset=\"0\" style=\"stop-color:#ffd43b;stop-opacity:1\"/>\n", |
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253 | 253 | " <stop id=\"stop4675\" offset=\"1\" style=\"stop-color:#ffe873;stop-opacity:1\"/>\n", |
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254 | 254 | " </linearGradient>\n", |
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255 | 255 | " <linearGradient id=\"linearGradient4689\">\n", |
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256 | 256 | " <stop id=\"stop4691\" offset=\"0\" style=\"stop-color:#5a9fd4;stop-opacity:1\"/>\n", |
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257 | 257 | " <stop id=\"stop4693\" offset=\"1\" style=\"stop-color:#306998;stop-opacity:1\"/>\n", |
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258 | 258 | " </linearGradient>\n", |
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259 | 259 | " <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2987\" x1=\"224.23996\" x2=\"-65.308502\" xlink:href=\"#linearGradient4671\" y1=\"144.75717\" y2=\"144.75717\"/>\n", |
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282 | 282 | " <path d=\"M 110.46717 132.28575 A 48.948284 8.6066771 0 1 1 12.570599,132.28575 A 48.948284 8.6066771 0 1 1 110.46717 132.28575 z\" id=\"path1894\" style=\"opacity:0.44382019;fill:url(#radialGradient1480);fill-opacity:1;fill-rule:nonzero;stroke:none;stroke-width:20;stroke-miterlimit:4;stroke-dasharray:none;stroke-opacity:1\" transform=\"matrix(0.73406,0,0,0.809524,16.24958,27.00935)\"/>\n", |
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283 | 283 | " </g>\n", |
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284 | 284 | "</svg>" |
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285 | 285 | ], |
|
286 | 286 | "text": [ |
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287 | 287 | "<IPython.core.display.SVG at 0x10fb998d0>" |
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288 | 288 | ] |
|
289 | 289 | } |
|
290 | 290 | ], |
|
291 | 291 | "prompt_number": 3 |
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292 | 292 | }, |
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293 | 293 | { |
|
294 | 294 | "cell_type": "heading", |
|
295 | 295 | "level": 2, |
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296 | 296 | "metadata": {}, |
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297 | 297 | "source": [ |
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298 | 298 | "Links to local files" |
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299 | 299 | ] |
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300 | 300 | }, |
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301 | 301 | { |
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302 | 302 | "cell_type": "markdown", |
|
303 | 303 | "metadata": {}, |
|
304 | 304 | "source": [ |
|
305 | 305 | "If we want to create a link to one of them, we can call use the `FileLink` object." |
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306 | 306 | ] |
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307 | 307 | }, |
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308 | 308 | { |
|
309 | 309 | "cell_type": "code", |
|
310 | 310 | "collapsed": false, |
|
311 | 311 | "input": [ |
|
312 | 312 | "from IPython.display import FileLink, FileLinks\n", |
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313 | 313 | "FileLink('Part 1 - Running Code.ipynb')" |
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314 | 314 | ], |
|
315 | 315 | "language": "python", |
|
316 | 316 | "metadata": {}, |
|
317 | 317 | "outputs": [ |
|
318 | 318 | { |
|
319 | 319 | "html": [ |
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320 | 320 | "<a href='files/Part 1 - Running Code.ipynb' target='_blank'>Part 1 - Running Code.ipynb</a><br>" |
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321 | 321 | ], |
|
322 | 322 | "output_type": "pyout", |
|
323 | 323 | "prompt_number": 2, |
|
324 | 324 | "text": [ |
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325 | 325 | "/home/bgranger/Documents/ipython/examples/notebooks/Part 1 - Running Code.ipynb" |
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326 | 326 | ] |
|
327 | 327 | } |
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328 | 328 | ], |
|
329 | 329 | "prompt_number": 2 |
|
330 | 330 | }, |
|
331 | 331 | { |
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332 | 332 | "cell_type": "markdown", |
|
333 | 333 | "metadata": {}, |
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334 | 334 | "source": [ |
|
335 | 335 | "Alternatively, if we want to link to all of the files in a directory, we can use the `FileLinks` object, passing `'.'` to indicate that we want links generated for the current working directory. Note that if there were other directories under the current directory, `FileLinks` would work in a recursive manner creating links to files in all sub-directories as well." |
|
336 | 336 | ] |
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337 | 337 | }, |
|
338 | 338 | { |
|
339 | 339 | "cell_type": "code", |
|
340 | 340 | "collapsed": false, |
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341 | 341 | "input": [ |
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342 | 342 | "FileLinks('.')" |
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343 | 343 | ], |
|
344 | 344 | "language": "python", |
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345 | 345 | "metadata": {}, |
|
346 | 346 | "outputs": [ |
|
347 | 347 | { |
|
348 | 348 | "html": [ |
|
349 | 349 | "./<br>\n", |
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350 | 350 | " <a href='files/./Animations Using clear_output.ipynb' target='_blank'>Animations Using clear_output.ipynb</a><br>\n", |
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351 | 351 | " <a href='files/./Custom Display Logic.ipynb' target='_blank'>Custom Display Logic.ipynb</a><br>\n", |
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352 | 352 | " <a href='files/./SymPy Examples.ipynb' target='_blank'>SymPy Examples.ipynb</a><br>\n", |
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353 | 353 | " <a href='files/./Part 2 - Basic Output.ipynb' target='_blank'>Part 2 - Basic Output.ipynb</a><br>\n", |
|
354 | 354 | " <a href='files/./Frontend-Kernel Model.ipynb' target='_blank'>Frontend-Kernel Model.ipynb</a><br>\n", |
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355 | 355 | " <a href='files/./Part 5 - Rich Display System.ipynb' target='_blank'>Part 5 - Rich Display System.ipynb</a><br>\n", |
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356 | 356 | " <a href='files/./animation.m4v' target='_blank'>animation.m4v</a><br>\n", |
|
357 | 357 | " <a href='files/./Trapezoid Rule.ipynb' target='_blank'>Trapezoid Rule.ipynb</a><br>\n", |
|
358 | 358 | " <a href='files/./Part 4 - Markdown Cells.ipynb' target='_blank'>Part 4 - Markdown Cells.ipynb</a><br>\n", |
|
359 | 359 | " <a href='files/./R Magics.ipynb' target='_blank'>R Magics.ipynb</a><br>\n", |
|
360 | 360 | " <a href='files/./Part 1 - Running Code.ipynb' target='_blank'>Part 1 - Running Code.ipynb</a><br>\n", |
|
361 | 361 | " <a href='files/./Typesetting Math Using MathJax.ipynb' target='_blank'>Typesetting Math Using MathJax.ipynb</a><br>\n", |
|
362 | 362 | " <a href='files/./Part 3 - Pylab and Matplotlib.ipynb' target='_blank'>Part 3 - Pylab and Matplotlib.ipynb</a><br>\n", |
|
363 | 363 | " <a href='files/./Script Magics.ipynb' target='_blank'>Script Magics.ipynb</a><br>\n", |
|
364 | 364 | " <a href='files/./Octave Magic.ipynb' target='_blank'>Octave Magic.ipynb</a><br>\n", |
|
365 | 365 | " <a href='files/./Cell Magics.ipynb' target='_blank'>Cell Magics.ipynb</a><br>\n", |
|
366 | 366 | " <a href='files/./python-logo.svg' target='_blank'>python-logo.svg</a><br>\n", |
|
367 | 367 | " <a href='files/./Data Publication API.ipynb' target='_blank'>Data Publication API.ipynb</a><br>\n", |
|
368 | 368 | " <a href='files/./Progress Bars.ipynb' target='_blank'>Progress Bars.ipynb</a><br>\n", |
|
369 | 369 | " <a href='files/./Cython Magics.ipynb' target='_blank'>Cython Magics.ipynb</a><br>" |
|
370 | 370 | ], |
|
371 | 371 | "output_type": "pyout", |
|
372 | 372 | "prompt_number": 3, |
|
373 | 373 | "text": [ |
|
374 | 374 | "./\n", |
|
375 | 375 | " Animations Using clear_output.ipynb\n", |
|
376 | 376 | " Custom Display Logic.ipynb\n", |
|
377 | 377 | " SymPy Examples.ipynb\n", |
|
378 | 378 | " Part 2 - Basic Output.ipynb\n", |
|
379 | 379 | " Frontend-Kernel Model.ipynb\n", |
|
380 | 380 | " Part 5 - Rich Display System.ipynb\n", |
|
381 | 381 | " animation.m4v\n", |
|
382 | 382 | " Trapezoid Rule.ipynb\n", |
|
383 | 383 | " Part 4 - Markdown Cells.ipynb\n", |
|
384 | 384 | " R Magics.ipynb\n", |
|
385 | 385 | " Part 1 - Running Code.ipynb\n", |
|
386 | 386 | " Typesetting Math Using MathJax.ipynb\n", |
|
387 | 387 | " Part 3 - Pylab and Matplotlib.ipynb\n", |
|
388 | 388 | " Script Magics.ipynb\n", |
|
389 | 389 | " Octave Magic.ipynb\n", |
|
390 | 390 | " Cell Magics.ipynb\n", |
|
391 | 391 | " python-logo.svg\n", |
|
392 | 392 | " Data Publication API.ipynb\n", |
|
393 | 393 | " Progress Bars.ipynb\n", |
|
394 | 394 | " Cython Magics.ipynb" |
|
395 | 395 | ] |
|
396 | 396 | } |
|
397 | 397 | ], |
|
398 | 398 | "prompt_number": 3 |
|
399 | 399 | }, |
|
400 | 400 | { |
|
401 | 401 | "cell_type": "heading", |
|
402 | 402 | "level": 3, |
|
403 | 403 | "metadata": {}, |
|
404 | 404 | "source": [ |
|
405 | 405 | "Embedded vs Non-embedded Images" |
|
406 | 406 | ] |
|
407 | 407 | }, |
|
408 | 408 | { |
|
409 | 409 | "cell_type": "markdown", |
|
410 | 410 | "metadata": {}, |
|
411 | 411 | "source": [ |
|
412 | 412 | "By default, image data is embedded in the Notebook document so that the images can be viewed offline. However it is also possible to tell the `Image` class to only store a *link* to the image. Let's see how this works using a webcam at Berkeley." |
|
413 | 413 | ] |
|
414 | 414 | }, |
|
415 | 415 | { |
|
416 | 416 | "cell_type": "code", |
|
417 | 417 | "collapsed": false, |
|
418 | 418 | "input": [ |
|
419 | 419 | "from IPython.display import Image\n", |
|
420 | 420 | "\n", |
|
421 | 421 | "# by default Image data are embedded\n", |
|
422 | 422 | "Embed = Image( 'http://scienceview.berkeley.edu/view/images/newview.jpg')\n", |
|
423 | 423 | "\n", |
|
424 | 424 | "# if kwarg `url` is given, the embedding is assumed to be false\n", |
|
425 | 425 | "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n", |
|
426 | 426 | "\n", |
|
427 | 427 | "# In each case, embed can be specified explicitly with the `embed` kwarg\n", |
|
428 | 428 | "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)" |
|
429 | 429 | ], |
|
430 | 430 | "language": "python", |
|
431 | 431 | "metadata": {}, |
|
432 | 432 | "outputs": [], |
|
433 | 433 | "prompt_number": 4 |
|
434 | 434 | }, |
|
435 | 435 | { |
|
436 | 436 | "cell_type": "markdown", |
|
437 | 437 | "metadata": {}, |
|
438 | 438 | "source": [ |
|
439 | 439 | "Here is the embedded version. Note that this image was pulled from the webcam when this code cell was originally run and stored in the Notebook. Unless we rerun this cell, this is not todays image." |
|
440 | 440 | ] |
|
441 | 441 | }, |
|
442 | 442 | { |
|
443 | 443 | "cell_type": "code", |
|
444 | 444 | "collapsed": false, |
|
445 | 445 | "input": [ |
|
446 | 446 | "Embed" |
|
447 | 447 | ], |
|
448 | 448 | "language": "python", |
|
449 | 449 | "metadata": {}, |
|
450 | 450 | "outputs": [ |
|
451 | 451 | { |
|
452 | 452 | "jpeg": 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+lASoKhSUc4oCA1M0AM+tDNAHPGaG6oAbsVCc1RQpNAmhAZoE0KLm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JsEjY4wSD5ZrN0s+s9D9PaXqHQ/Ul3rd9ds/i313vAgg+nw8Rs7qAQSuMHO0epxzknJKK/3Nc1D\n3Lr4+T6R0x13quvaVpsJ6XW61fT8JqPgXlvFlTN/DmCOx3LhH3NgZLNtOQceC+NmvW/VEWn6fpuq\n2iWbM6Xby3MSRrMFP0Bl+k8p3zngDNcU8j9RFy/T/wCjvilB4JWvcv8Ak8501bdL9Oa6s+p9RdLT\nXM9igtbRNQVEaRyozISjKAULYweTjjHI9r1w8dhFq2nRroNn8xahYUuriMFyT9fiKqg42gYIbntj\nmvbNRlvyeSLk1w8d0fka76s1LSOp75tE1BbQwzyKi2cjohBPIHZsc8Z5r6d8M9M1Dpq6n13W+nr2\n21G+jc2Es0DMHkwSW+rJHbkn15xzW4Yo4/d8nnlyl7UbfjJ8Wn0bpV9E0WSZbjXb1w08iPHIlrGi\n7gFIGCzuwz3wpHnXh+sPj4+s9A2WgW9ui3jWaW086qqnCnaR27sqjJ/9xro4ctFWRw/lI63QnxQ0\n9+gk0FtKvp9Vs7aSSORYfGAUONjHnju/PGAoHpSRfHDSms5bHqLpcQeBcRQu9vK/iOobLsYydpO0\nY9MnjFR4k22ajmcYqhND+M83VHVb6VpfSdpYWUrM8KW6sXh2xsA58txOOQB3Irj6tqGnX/V9zD1f\nd6jp0EUKpbFRxuUe4zhjk5x+ted4+OWl5Vnb8nPHe6swat1lrdrYw6FpNxLNBfxQ/OQCH8UgwQrH\nkscjk8c+QzitHUVxd2+k290RtvpVELBGLMByCAB65xz6mvXxUU+Pk87yOT34NOp6h1PovTkNpcaZ\nYILeMeB4agupJG4Nsbhuc4IPnXh9KMFxdQXNzq9xZLEkzTrC4jljAXP07iM53YxnOM8VUl2yTS0l\no9vB8Kr270bWJtV6kn0/T9JT52KHUG8NowQTuZRu78jjkn0r3sHx/wCodB0DTenX0bTruKTTozHJ\nbsu2WIrtDFycgnHIxnPueMSm5KjWOCVSf/nR8Ut5dU1rqqTWoFSO4gZzKfEDRJCwKbACcngkdyce\nXFPN8KOsdVt/3loOnx3dtuZBKtwgDbe/DEdsH9K6rVGGuTb82ed0PQtWu5J54Li3iFm22VZX/EQe\nwA4IzXoum7e80/UZtZ1XpXVZdNkRlEtkhgXaP5lkZGXsM+talVHJRa2ed1rVtMuL17zRFuIrWMqf\n/UOryI2ewIxkcelU6Brk9tNPBKgnhnffIduTGScbx781FH20w5btHptQ0Sxvi0EOoM1wqgw+IhXx\nPXnke3fjiieqtW0GKO3vFiaUSfVbiLDCLAwcg47kgDHl9qlclSOlcdnV/fUGj6Hcano1pcWGqTMj\nfLvGribOTnBB4GTwMH+tczTPiNqGk9PzWWoESXzOxRpoQXXLZJyfLkjB/LtWFHkn8muXFoOlfEGH\nqC/g0/V9HyFjZTdWrES5GTnb+EjyPGffyru650BoV/pMl90RrL6jqayb3tnmG7aTydpA4GRW1Fx7\nZnk5dnA6y/eXSmkQx6rYWccrRIFMcagGTHfcBkH1FfLW1/qCeaOY6jIy25/hr4mRHnsFHpx6Vzq3\n30anVKlWj03TvUPTe4p1bZao0qvuMlvMhVhzn6WHPl/NWyx6j0See+sNI0yORbhtlu966gxgnsSc\nJ69+2e5rX5X0cqrZ4jV760vrsxJcm3ESFcAExl8+oziuO7FY/DtmT6hyV5LfnWG77NJM8ct0SQsk\nauCGGDyBkentVYuHlZpSy5YkHAwOPLFdKIW/wmiUb8nPY0oVM7t4B7nJyDUQCspGHBJz5dq22c5E\noZ1IU8EL6VJIp9DsnlWxtz4TKjLwO/FbIxOzBwje+Tiu8a4pnLyWi5JYZUlh2Oc16PpLp3XtV1+x\nhtLNwZLmNTJLlI0yw5du4HPJqTaitmoJuSSP0z098OfEnEvUVvp2pIoVIooZdsaqvfcn8/ccmp1l\n0vpmmW8dxJoOnxW0RLBPDLiTaQRhWztAAAwfTt5V4IZm5VZ6pwpWz0vQWs6dqenKq6Wb6cxgssjI\nNmDgkbvXI4wBwfznX9xY2a2MsGnJYT3EjWsEUpjEUzuRgsVOQQAcH3o1CMqLcmk0cOH9z6femDqW\nxlbU0gjjn8FUKBVJaMAMSPwtzg85rCeoel7K7jtb1rDFw4FuJreNSVAOcnYQTyv+dzjz2bjNxpJn\niviLe6Iscmr6ZqUFrc2SRxS28QVS24HC42DBzz+vavGab1jeSyR61LaWkgW4JlC2/wBCA7QDwB5Z\nwM9xmukMacbZl5pp1eji/Eq7k1W506/GGM1vklF2jLOTgDJx9smvOi2KIwDfxSeQGGACa9N1FI8k\nv2AYbpmEezdGG4IIxivU2un6fHYLILgEMhkJT6WDZPHHnwKzKUUhSZwr2K8hud7ztI0ox9THPsO/\nNaCtyU2r9Kj8ZY8fbmp+RUmSmel6G0a7vNat9Sm0e8vNPiWYOEgdozL4TeGNwBAO8pya9RqGk618\n4o1vUpbMv9UcFuN21OMEkMCCeTzXlzuLdtWfQ9HzmvxwlVnIh63NhruotqlzfNbCFoEEMqLJleEb\nLKwz3JwBnJ5Ga+onrCa+6XXRn1DUEguPCZppIVklk28jksvf6c//AI+XNebLgqNRWmenHL/FKUZz\n3/B8x656hMFpZWNh1DdXEQmed0aLwwh4GeHbcccZ4/rVx1K0t0ttEbWpZne3abc6FQME5GCTwVUc\neorpgxrDiUUjyfh4ylFSuq/ucfRvinrHTq6nb6VfTRC7VYyVkIUqD+Igd2wTzWLqP4idT9SafDou\npaxdXEJn8VUkkLgsRjP9f612WFqds4/mk48T610hcaIvTel2mpaRq1xJC5eUyLHPGZBkKVBdMBcM\nBkHv3r6DY/GKJ7+2s7vU9UmClc2s8CMWyvAI8Q4wSD+XnUuMNLyd3Lk7kdu8+LXS9/a+F+8r2xnk\nQFZl04uyKexAIYeXmDXndG1roiCa5u4uvdTvLucby11p0srAgHB+pMcAduBxVatCLV0mfIeuOvNK\nu9ftNWu+or7UjaXjkmaMJIYtoG0IG2xjk4AHmc47VVZa3HrfUcs8VpIIYbhZTEknhFVCOqjI4Hfn\n17ZrotK0jnKbb4vo4WqapqK9RWs+p6lHGBatEz7hjYN2AQp7n2PfmvtvQ0+lv0pbdQadramaGeOV\n7S0slmeEuzKRsGX5RVAbB/FjGeaxL2oQ/ZnG62+Jtz0/cjS9NstRkguZ5pbm0u7JrdjFKAjbFIBI\nIBGG4xkeZryV313oV1od90tpvTYs4riPElxbTlJ53UNt8QtkEYY8Y45ryyg0rgq+b/0Ojz297OF0\n7f2fR0ctzrnS8966xlrVbktDErkdyCPrBHcZGR7GvQaJ8ftXi6HPSeoaTpVzFZyNLaysZFuYm3eI\nmGU4Cq2Dt7HAGMV6eKls4qfHR53T+uOqOnL+frHS9YW4klOy/lkG9JC53bSDwTlSfy9DXN6n+OfU\n+tW11pK/IpY3aKGjitEVY/qZ/o4+glpCxIwSQOauLGpOktGfyNKmfR/gVrXTEOgW8PUeiw6o31l1\nntbZ1JZiR9TRF2AXb/P6jyxXO+NOj9TdT9TJrr9VxDRNyRRRXVz4RgLYBGMbAOO4P4R24qzgnO5d\nLo3GVQqHbOXHb6RoHScl10/Fp1xrNvKpGpyunhkBi5GWJXd+DBHJAHPPPK074prbaTCmqmAXNpIz\nwR28exVDBslSMBPxN277jWuLaMqSh4M3xD0u26rjsZej0e8uYYo2uRDEyrGHRSE9Mhg+SAM4zk54\n6ll8PejxpMEWqaReG8SJfHcGRQXwNxHOK0p0kkTipybfR86N7qEGvX9j0ha3YLIbcxwgyuY+z9hn\nBJP5Vh6lL2E1pataXVrcJFmdJv8AUWbG0YBA2he+TnPPNdYw3bOTfaXSH6f1nW9FuV1fp/VZ7DUF\nBTxYX2nYc5yR+XH/ABXp9K6pGt6g3/Xmq6nqzyBI/pYeKSpXYVZgRnjB4yfXk1mWnfk1BtKvB2Pi\nRr2kJqlvqXS9o1gYECyJcZE4nB3HOBwQGXtXnNJ6p1vWdU8dx480DrN+LOSGGODyfIcVxWNtObZX\n+1Lyehf4m3D3k9rqpjt5VVTHM6u7RPvJ3FSfqwrcDgZrgdOatH/1B+/b820kgnaWYXiqwlQ/6RgD\ndjnsPKusaxq0WTeR8Ojh/Ev4gydX9UareaK01rpl40axQSybiVRQMn88nHbmuT07dzQXUJuJpJYR\nHtwGyO5OPYfb1rFa+xOW6R7Z9d6Ytory403TL+zllTCML3cC+Dyw2c8nOBgcDjzr1mhdSz6T0rp6\nAi5lSNtwjkX6i8h2r3z/ADj/AAZrMnzVSOuJq78I8r0L1snw+6j1T/qDSre8SeJibObbIPF3qVJZ\nc9lLcZ57V0tX+Leoa1r+mDRPB0nT4LA6d8tGMQfUCGbbhsA/T64AFdk7lRw5KCb8/wD4eK1fQ7PR\nLrwNR1mwu45fqM1lIZFB5wvIXnj7c96ostKSaMvbTqgADb2yAG8l963z5aRy4u6Z7+21fVNY1u0n\n1LV55WgiMYaW5knJ88MD2BOe1cnqTVtAvkaa3SGW5Scx5RGXAyfX/OaKlGkdNrsrsdbjsLNYvlY5\nZlm8RJZFV2CbAu0ZBx2rTqMNprSRSW+jpNOE2sykKQOO4PHryPU1yjkXI3FKii2hh6NuBq7RzZ2M\nghfG05HqDkVwNe6xbV72F7e2j0yKAfUtqzDJOMtknJ9hXRV+xlx4a+Tnar17qF2nganHb36RI4tx\nMgAi3cZ45JwOMnivIiRGl3xxZLDIOcAGsX5Qbb7FW4lU/wART7necA/rQOougclyNgwNpwD+dRxT\nIedk1O5lLISdvOQfKgLq4iXwUPYZJPf8q1xRbOVGjvukd2VRhmY8+foe/wBqQkl2mCAoWO3y7+3l\nWl8EoeJojJ9ceVUEn0/pWyC3e9lZba2WQqu/Cg4VR3OPKo9A22FhYMJXvVxtjLKoB+rscA+/b296\n0250qS7TCSW8OVBQHcRgAZz5nz7DvXK2za41s+oQ6xpEemW7iyktXSRYozLIT4kezLSN6HJX2O6q\n9XljglDxIPrORgeXrTHt0Znx3xPon7POj6DrXWdxc9SWCTW1lYvcL4qZRX8RFDY9gx/vX6hKaCdP\nmh0vUbqOPCpIYZGIUbsAYbjzP9axmlJZKR1xwTgjztrp3TlhdSalZ6jf20tnEFdiuBjAycEHk4yf\nzxgcUupdbdMXMCRXXxCmg3koBFhHzj1UA+YwfWvPxd3R1cr1Z6zQoNMtrR4W6huJ4ool8WeaZyWD\nklWLOcfysOPXmvz98dOtNP1DXNJHT9+Lq2tEDrIVCN4hO0gnAxgRr+pPnXTHblTRzzOkjBr/AMRJ\nlsYJbIq8syj6uQFPqB9/WvM9S6zZ9Vy6NZF2jnEnhzhGAZSdig5YgeR7nHqa9MVxOM5ctGTV+ntN\n0m/msrO5kv3uRLEkcrqXEivkNlMqQBgHDckNwBXnDrtnpzPGbxFWAgShPI+QwPPNSck9GWnWjVN1\nbpU6ok+oiR44wiK4xt9j6HnFC/NnKFkt5YghUsCsgG/8z58GuUMj5WVq42Mb2yJitre6ilmK4ZY3\nU4J7DH5/3raVmgmSJnAEagcnOT+X61pyTOe+ii5n8GUPI7M44Bz2z5n+lVrJLslDMCGYDHOMfb/j\nitJWhbR6rp/rAdPbBdSEbVTwiODHk8kc5HcVuuutDcXN+qTgSyOzRSu5fPHqM5JxnPvXnlicpW+j\n62D1sceNNL3VV/7nl1sby+DyO+8TjLkjJPrjP+favQjrLXdKttK06SUiOxVkhHIIjbP0kqeRhmH2\nY812lHno+bGTgzzGtahJdsXuZGliZ2bd4YAXcSSBjtzWLVdal1HUY7tgsYhh2gIAv0jOO3HmK0o0\nTm6aOPe3Tq3jAt/E45zit1lfylEeLw9ygEFuwI5zXSUfbZhOj0Ftq3VnUV2LKC6YbRveTeViT34+\n33rtXXT0ukwHVv8AqmCaW2KO0TRsrE45w3POe2cV5prHBV5PVHDPJjeW+iq1+I1+Li3Et/K0UGNy\nNIVGM7sHHfue/wDsK9Za/Ei0Mdx40oQJbskWCSSWBxnJOTknP2HJrjFSiqmYx5G9s+UXZso2mnkd\n7hm7qW4ByDnjvXR0vq/UIlubZbUyeMq4aPht7cAv/qGM+nNeyNtWZTpnGaSWWCLxQFAcx4kGNp+n\nzr3fw10Xpu56gFz1Prt3p2i2yb7i5ihlLSsFIEabAcZIPJz6AZIqN6o1jg5PR9MvOq/h5a9b+FoE\nun6jZx6WzPcX1nNI8MgkC4znLN35KkAOMAnBGr4h2vwY0/T5OoXhSa81JWNvHpCzw26yNGhLyCba\neJN4AX6drfhBxjnKNLo7uKdp9nx3TusdIt7bUIJtIjaa5DeGzyuVGVcZ2k44baAeSMn0ryc8M9qt\nxqU108cFyMKkRILA+fPl9q1H/LdNHCTT0S11K41i0t+nVvpXiWQeBG2ZCXPkg8sknjzJrdHoOo2+\nJjo2ooY49rF7d/LO7y9ePyo3KLaSObkz6R8LvjhffD+0GialbQXGmJlms54MYLYyRwR5e3c1r67+\nJvRfxC1m00i00m0sPFtFaViNsC3P1HICDOQjAZ5ya5QhJTcmzvDJGS4tHy75PT/3heaQLy1u4bUP\n4U48RGfjjbuHHccEDt5Vw76FI4txuULhxlFyOK9Cn7qOMo0zuafr+paS62lpeTReDxgngEZH/P61\n6C3+IPV81ysMIWW3Zfqc7cg/3rEV7qkbxzrR4e0Ov9N6wutmBoXWQsJZI0fLHPYMCM1s1LUNT+In\nUEmp6zezTTrAF8TaoOFHA4wO2e1elyS2jMYuXt+TzsTypbSOv4QdvHGKyLLdM7OmSPI5qultmbaV\nH174LHRtafV06ksV1CWGGN4RJGHPAKnDHHYADGcU3xGk0vQtftr3piw/du+35FsCsgkBO7JycHkD\nGeMGvLkuTqJ1jH28zxcl2b64NzqFn807nMniKd7cebcH+tcnWtRt/Ba3iiVfBVmT6Pqydo2fkATm\nkNas53btnkyJvmCXikRlO0nHAzW23uQYwwBVgSBz39a6XWyPZum1GXarMfoT6ee+ftUXWLuBURxI\nFI4zkfY1wcOezVUUzajFLL/Eyxc7i+3kn1rHLdFWcRkk87W7E+ldoxoskqMyyyzEjD57cnJP9a9Z\n0RZ6v1JrltoGkWr3dzJuMcaYDSBVLHuRnABOPPHFdKMdbZ7SDRuoLz5mC3lVFLGJ8ziFi/fBDkOO\n54xn1rzfTcGnWt5LaavdbHkkKnCeJt2+2QO+ecmrFxcaNZE7s0dQRafp1mt1pOptP4pbIeLw3Q5+\n5H6GufoWuXtpcRXGI5XRvwyLvHbuRg5rm4JKyXWj6Zpeo9P9S6DHowEdtfRxiIT3FhbvLI2G4D4B\nI98ZGBXy7VdCvbbWn0+UxYiYrJcIrGEHGTubbk/pRNSZqm1Z5a7WO3vZFkUtscqxjBA49M1k3xON\nviAEHy8h/ao20iVsTcka4LLnGMse/vWC+uFEbJBIryP+JscUTtijmDHHKh/PjzqpwQgP845Jzzj0\nrqQw+OrlI2l2he/HAOeaUyEyyQjLbufpPBI8+3aolRbBG2wFc/iHIxWm3uTaNvRjnz29vt/ejIWw\nzPJJje3IwOe1a7a4a3limQqChBXIyOKxQR3rvq6K9vTf32nqSQPpicoOMgf1wf19a7Gj9e6RLfXF\nxrGjN8t4JSCOGYjZIcAMS2d2BnI4zXLjJL2slJvZ7roPWun9V6muLC86nvLbRLxzEm1GjljiLnaZ\nViVgey58hx3r9e9Bp/8AS4RQ6D01FrviJBeRahI80gmSRPFQ4G1Tje38ucg+lcZSa9p3gnBcu0Y9\nc+Imu/FXqa56b6l6nj0PTJFa1udLiklgwCT3JVgWPPDHPIIXFdG3/ZO6StVi1HQdZ1OSXkFNUi8S\nPaBkFQiDJ4GDn1GCTXVUujLV1MuuJE6F1aXQ7q2utVazkjBnikijjkVVDKpSSFwdpJH9uMVz+pNH\nvfifp9zP1GNM6U6NRClxfTRWsLR7SCCHEaF2OCMAD0rCfF2atZFxo/PPXHRHwx6e/eOq6N8Rb27s\nLRdwnlshm4lbJVEVT9IIBILbfsK+D9VdY6VLctDoPzJiTvJK4DOfXC9ufLJ7V25vIqOMocXTZ59u\nob+6t2Wa+lZWYMFaQ4/SsE+rXpdIJJmKfiyTyOB/sB+lIwXQK4rtvqHzD8n6RXTk17Uhaonj+JFE\nOIwMbfImkoqwVWnUc0DfMMZA0RyNpxgnjuOa97oHVk+pWRjuosNG4SJUGS+e/BPf/wAVlrhstWe9\n6O6I6v8AiJdT2/Suk3VybR9lztXAi9nHcfpmvY//AEQ6n6fmOofEA3Gl6PEPGnMER8SRARkBmXC+\nQzg4yOKxk9RHHpJs7YfRvO7clFfYdd6i/Zt00O2o9J9RsY8ASLcuA6jGW+rAz6Djt715rSOqPhRc\ndQpFoen6hqMV/ujjS4IVrELyS20BZMgfkeeSasM02txMPBGEtzs+hdOL8KtcVon1S6WW2QsUjaMb\nCv8ArYkjz54715Lq3V+gNMubi2bUdRCxndE6qr5Q5wc7cHJ4yMVVJyYeOK8nz3qDWdMs4/mZ7iWO\nCUgQBipkcYzuwDhR28q85cdb6IsckaM/0LhcgEt61rm26o4tGmPUdOuNLbU5rzMKjMion1IeOP1N\ncAdbxWriKKBnVTwc8EZ7GtLI5WqMpbPoPRnxOg6W1Np4oUn8SJVe3L7c+hyPTJ/X2ro6r1vedT31\nyOLa1vNhMY+vBUYUZ4J71mUOScjty9nA50txZ6bbkLOs025mO5fM+39K6nRHRmtdYampsrb/ANNk\nE7gQi4GSSewHH/imOLpy+TFeEfXLP4QdLaTfROiS3kkWWlkmYNG5zn8JGNo7c/nW0N8P7bS/+obj\nTdDgtJTthuRbRqr87edmDwQBXoaVUzpBK6Rm0rSbPTL2a+vbLQJYr5Asdu3hGNPPxB4xbB5xhfvz\n2rua0vRukY0rpttMuLJY0IuNtv4gLD61QGRWUbjndk5weB2PyPze902l/DPpQxJRWt/yfLOpOi4/\n3qdet+oVu55mDG1YYZ8j8IZHIAHbGQeDjypOsIdSGhPFdMsQYRpbQOXYxKGwQN5JwT9WcnnOK9uP\nNGdJHknhlFts8WOnZlDajdsGjjiLHaQe2DyD3yM8e1cSe5n1S4S1hVXeRtkaA4A9AB2Ar0UpO/g8\n0k06O1pXwu67uJBdabaRGSA+IDHcopDA8YJIwa950bqPxG6ZtJrHVIhIBKz/APqG8RkOfqwyt2Jy\nfOpOUWrR0hF3Ujg9cdeyazcldRtomTwDBvRNy7ckseeQ3uD5V84mlb5i4u9OgdI1bMYBJIX71MPv\nXJ9GJuMuvAA+qySJMFkBlHDEHk1+hYP2crK36Si1rXddvP3m8CyzQrCoSJj/AC4P1MAc5ORkc8Vu\nXGO0ZinKVHya6jsmkLRQqIw5AZeNy54yMn9KttrhYZd8Upx/pxgf+K8cpNsVxZ7S06Ri6t6XlvYO\nobGDYcTJMrZjAwSc4x2P+3vXF6E6EvJNdkNpLYzi0Cv4N3IbZpIzgqwyrcMpB+xr1wpo29tM0de9\nMP0U1vq50HTVsbv+D8vHctOqyYJJZuDyOf1ry0vQRe10zU59asrW31RWMUsgKxDDMu0Hu3K8+nnW\nZyV0xxvo+gdG/Dm80SzfWtN1GX942DxtMLJhzvwfCYE7WAHJ/wByMVd8Suq7PqHT9Niis3372lk8\nWNkMbgbSuc4P5e1eec7VI6cXGOz5vf6jbwwNOxjBTuccj8vOvn2p6hNcTeKlw27cSWP/ABTDF3s5\nAs715Akdy34vpDYxir4jdNfN4SncoIz2/SuvBLXgiuzrNKEtT8ykUjqAxHO7NLJfokXjojbOwUkD\nHt/eoo0d29fZke4W6TdMAjofoJ4wPt/zWJ4JjmWKF5QSQGUErWuSSOL9w1tK1rMZDE0UjKyYYHOC\nCCR+Rq6wh1/5uG60GCdJEO6JkcI+727HtzmqpctWRp1R6ifXOt105LjqSzml+XLpbXExDSIW5ILA\n5x58+p9TXnd98B80wABBb6WB48/PIrDVeStOqYY9Tu/l/BnDvAw43jOD7H15/rTJbanADKtrcAPg\nqVhJyv6VqD4poy4ts6EfVJss7C4uBhcDIYY759POqb/rfWNQg+UnuJFCgbC0m9QB5DviuS9sjopc\nVR5u5leSR1km3iQcEtnJ+/51lkWFVTfNgMQSoXBFdk72Y7ONczu0rKGwu7g+1LGV2k72U/r3rolo\ngr7lcbX3R9+TzVckcqykORgtjNUHHQu0hTaBzgehq5yYVKQygFsqQO+M+tOwU+MQx2DHoKcd95PJ\n5xVBphGcbeOfWtUSmRdvi8+nr7GubIPPE8kShGGQR354p4S6SxrdBVQZDFDgt6fn/Ss2aXZ39FgW\nbUPkgWSKeRVRXYFm5H8wH9QPyr6jJp3V2gtDPpfUF5A4H0qkpIJxgDv+X2rxZsyxzSZ68OGU48oM\n87q0fXejagdZfUL5ZGkMjyRSHc3b6t3qeefv5V9t6R626x6g6bGvv1N1FaBUkQgXCGE4VwHJ4Ycg\ndgOccHmu2OcZrkjn/mY7i9Hm/iJ8dusukp7Wz6d+Ieq3dzC7G4ZrnchXCkfgwO/598+VfGOq/iz1\n11xZmDXupL26hWbxvCmuHYeJz9XJ74bFaUU90cpTntM8ZL1BqqWktjJezrbysJPB3EKzDsceZGa5\ntnI0k7Ox5UE8Gu8YpLRzLZbkLtWJsknH2p5YCsYZWDSpyRnuPMU6BVG0by/SzMBye3FaDHHtaMzF\nSedx5Ao3RTCoaCUqRuVTn13Yrs6dqt2ky3CzSRtGdyEHBB9QfKpNckE6PqvTH7QHXnRFsP8AovWn\n0i8YBri6thtkuGGwjxf5X5QHJGcjOcls4etvjb8S/iTcnVOtuqrrVp0G2Lx5AViBxkInCqDgE4Hc\nc15vxK7Z0eV1R4/Ueob3VyDqd88hjTYMsTx6H29awNqz2x8SxIhIO4GM859jniuqj48HO/ILXqK6\nty7K7qZEaN2DH8J4NPLr101ttjmkWEfQSSSe+e/3quAs5Vzqs1wQZpizN3LHNY/mmdsAYyf5R5V0\njGkQ6D3UktofCZ1SPJAU8Z96wvJcwhZGYg57VIpeQdCzneJ/mmlJZhkgcED1r1PTfUem2Nz8vqEd\n7N4rr4ZhnC7BzuOCpyeR5jsfyw7TtFPsa6Z0Zf2elalZzSTSSxeJJBcSqHQbSSWAwScg49cj1xX1\nfpHr3piz0i30PT9Jn0s7wjGQjdOx5VmbsO5wOOKuFt1fR1/HXRV1l1nDFol/baLcbr908JVEgRl3\nfzDuCRz5ivPdCy3fS/SsUGt3tpEl3M/yok+pYyQSd2OMZUnv3NdZZEqkRY23R7v5wGIalHrcdxGA\nHUY2eK7FT9JUdsgdz/54951VPbSpZmbP0Ylw7kQENn6jvDNnP8oPAIPFfJfpsLer/t/2PpLLk8pf\n3/7nA6nvYeoZk2ar4Bt2CQMkDhn2k/Ud7HjnuefYVwNWiS81C3sHvluRaRruI+lcA5fuTljnHp/W\nvTgxY4tcdtHHJOdNdJnL6nniu2Qvb2tsqRgbVLL3+nkjOTjv5cnAFWfD3T7C01q5vby2hRI7cpE1\nw6YV9yk4DcA4B/w1qeSUXL+x5MHGWZc+j3uqX82nW3j6Vq9hBvKbTG8T4J7kqjZ478+nasvU+vWd\n1pd++kyJLcTKUtgCdzlmIAwWJ7ZJ4HFc3k1Ff7nu447nf+h8k0630yG6e0166YXEoEaw7SqgMPNu\nT2P9a9DaW3TKWzafAphMilNySDgeZyRntkfn7V0nNxpRWj50car7OxpfSFp001t1KmswyxQOJYbe\na5EhlKtnGxcFRxzzXf62+NnUHUenDR5NO0+1ikV0do5H3HICjHPoW4ORz7U/Op6SPTwjijcnvwfK\np4o1ZUK7177QfP7elUGXTkmkEl0I3zztc/ix+YFXb6PJ9s9T0pc2FgDBNq0kSXE4kmjCB1CKckEd\nnBO3jHlgg19Ks+tugLWeA3XSVx43hpC1w12VEqpGiqDjGRtjTAI4yfU1pZ/FHWEVJbZ8X+LHxDte\ns9dCaRBLa6TYgRwQmQyAPgbnzxnPl7Adua4mndaXVjcRWcoTULOJPDi8YP8Awc5wVG7ggtnHbNbi\nuW2Ry3SPe9GPqXUhu9TtL9enbVYzLLLHcsGucLz3bOB9RLHPJrjdbdZ6NK8emW+qTao9mDE12TlJ\nfUqSAx59ay9+1I3J+22eF1S6W/iga0uCVyxZWbgenH61zks7WOcSzXWSRu2heTRSa0ls4HRiltmI\nT5aNmAypGDtI8896vM4ktDDbqBPJ3lLYz5f8ViKae2dYaYs+o3VrAsUtsAjY3suO4HJ4rmS6iRzG\nVAI8uPzrUlekSbbdMNpdmV/GYb8MAGP4R71ql1JpH2I25VJZsMR39vSsPFYi+Jkj1ZmbZHCFYkgk\nr29x6V6norqa+0/V4bZoIXtpmCt4jhWUtgA7u/61pY1BpyY5OtH0fqLqfT9OtHsX08TNNBLKrPKB\ntC8MM9jjJOO9fDJNWguLidxCfl8HEZcsEb19+c/rWob2byOkke66Zh6U1PQIrPWNbu49SkZ5UCQh\nlU4GEUZyzE4OeO+ADjlviPY3cOgdM29nHermKUzSyTALK5fCkAgEcc457/c1pxRmLdfZ4C6hhhjA\nku1kkb/uKvG31GT3NZfCjaMKuRISed3BFT+DFBhmW2OwMJG8ty5ANYrxWaTY5wW5z5VqPditGB1M\nL5ifcCecVRhnO1mG2uq3shA+7ajADbxxRlZhetCoGA2M+lCHJaV5cYOCcsTnuaRIpZGLFsHOePM1\negRoJRklO3GRnIp1XCjeQBn86A1QqIlDE5yM0znYSVPAHesMGiC43YSTJBOB5Yq1F3Sfx2+jdjPk\nBWHpg970DrcEGt2NjJFG8YlOyR41LoD5Z8u+TivuFxNaC1+YkRWEZGAF4I/2r4vrYNZLPs+jfKBm\nubrSxGskkCosnGH5xV3TuqJ0rPLfQQxz2si/TbyH+GTg4OB964YskodM65MKltnyDrXpe2v9Yu7y\nH+EbyV5hHnhAxzj+vpXg9Q6Yu9PQujvMNu76eQeP/mvs4MqcUmfJyYHDo4ctlcTbRcBgueMd84zi\ns1xIbcrEhC9h2r1LejzgiLKpkIBz6CszXEjSb88itJWyIut7mRAyqM+I2WA74+9aEmSRtiKCx7D0\nFRookltgqUkALEAjdyKY7oisbriQd8Hil2B0vFXBEZJbPc0Bes7sXyAD3B7UoFcl4NuUb6u3HpSP\nPlAMHIBqqILorjYMqfwgHv3NWRsJFLK2ARyv+9ZeiGWS0cSCSKQSZ7qByK0Latv3TLswOcDijkDT\nAYCjw7f4ajsPPmrWBnTaioBztz3FY2nsDBRCm1kBLHgt2NKCoQjAVgpAIPAz61E92DXpWrXtvvjt\nZ/D3soY9gwHlX0DS+oGszazZguo0O4xv+Bh5g1iSaejcXR9Kt7vTLjT0vl6V00GaRV2pebfpKhgT\n9XfB7d6ya/rMKNY25s3FokbFrZLsumdxAGckYxzxjzrTt1b/ALHok4qNo6Ova/b2Gj/u+C3u4AYo\ntgN4WGGXPA9sCvLXvUut3yM9o773yJGRSR/+o55J/Ss8FJbM5Mj6RTbapdQOPGu2+kkZfKlvfHvW\nrTtatJNSjF1eyIkj5aaXPhr6k7FLY58gTWE/xv2IwpOqP0t0j0t8Nrext9YsviD0fezXMqS3D3ex\nHES52wokpDIckliQCeOO1dLq260vR+pNG1Cy666LvF1S9W3kWKUTOm4EtLJIFyoHb7n2rrzUtnb/\nAA01Hk46PV3HTsWqavHcafq/SN1axKUkiN4m1mIGGGY8tht3IZQc48sn8uftA9RXVh123T8OnaRZ\nnRsLv01gyys6KXJde/mMeXI9aik5OrM5MUscbcWj5NqWpT3WpRahbyusq7VDbsspUYU/kAAPtXru\ng+jOptennvtKaxljQeHKJ5O5Jz/MuPI+9dVFOKTPMn7j2MfTmvx3sWh2Fto93cXbN4vgNsYKp+oZ\nOB5Ht/pNeL6i0yGy1uSK4d4Zx/3oWkSRV4xxtPGPTvXGUXF8kemc4yhxraMlx8tp8YceGGY8Oo5N\nPo3w71HX7O41VNUtIIgxMXi53SkHnt+EZ8z6UwTu3I8z3o9fol98FtLa00vW3cTxWyC9u4Z5HRps\nkFUAVs4GDzgcHkefhOstZ0WXWL7/AKcup5dOCNDB8yACATncAO3bzyeTWpJN2kbrjGrPDXFxwu2M\n/Tx+HBNVb4jKgZMmU8AV0SMo0JfywRFDePHEcgoGPI+w/Osy3trLtSCzCljg7mzkevsay027WjV/\nJdBAYTmZiwJ7A4Bqu4aK4nUsdqcgADsBRNt2T6E8Z4AGi3N7kY7Vs0tm8OUzS4U+Q5A4q15LHsyX\nl2zLtedcnt9PGK5ElzMztGvCNycmkUZZbDJMUGWwgJ3e/vXobB7Aae0hlnN038NI9v8ADMZHJDeT\nD0PBz3qt0yo508V29zNcEIUVcM4AAKg4rp6fq0E1mImsY/FtxtjYIuDk8lsjk47EEYqS2ir7JrvU\n93qrpGzFTFF4aIvAC4AK/njn3rhQXC2jKy7Rzzkcg5qQ0Rttmi21RrN1uEUCWN96OrHIOc8Y9P8A\neul1F1dr/V7W8uq3pkjtl8OKMLtAB5JAHmT596r+WVOujleHG6ndKq7OQMYzWVQ6OQ5ABHke33pF\n+B0IJUjUqrHf7+dJNdB8Ftr7DyDWq8k8GaVg6FgoHPGP9qpCESLkjae/sK0mZGuYX+qWJlOMbscm\ni1q/zXD/AI2XHPrVbRWcmGJpGLugHl6dq3Kqxqzxx5B4wPXHrUZCsbNhO8k98Z5rLJ+Pb5HnGOwo\ngaYlRF24U4Hn3zVyRxPyVHHkRk/ao2BPAVGBXdjJ48qv+ZjUgSAHvx6/rWGrBvtJjFPHdW6ANxxg\nGvv3Ser3F1poa5uYZnIUnb9IGR2weRxj8818310U4pvs+j6F7aBrFi96wR5tqxtuG054/Kujb3Nv\na2aWc6b0UEBmHFeCtI+jeqZ5TVtWtXu5JGRRsx9TEdq85da9pruyR2ylT9IGOCM17cMJHlyOPRI7\nDQ9RhDTxK2QT7q2eR/bmvO6/8MVuWN5p14jBc5V+GJxwOBj869GP1DxyqR5cnp+S5RPO3vTt9pVq\nvzEJ2RgMD7k/p51w5LC2WdXjyQTnYeSa9kJ3tHilFxdMWe2QK0m54z6Y4qq0LQnxAgJOME10u0ZH\nmeQPvKAFucgVXPcb05ckqaJAph8Sc7PEwq+taAgjBLOORWvoAVYwihCoJ7k1XKmXGZhuJoBXm2gR\npkj7963W8SLDlG+vseM59azLopqhi8FzOrbS67QM8fnT/NeICkm3Hsa5tcnZDK8qxFsJnPOM9qZJ\n2DBh5+VarQRr8G6eMMYGZPMjmhLbusYk5Q/5/wAVi0UxwzESlEzjOc+1e16auY7qD5e4VFVBkLs+\np/sT2FJ62Vdn03QCr6WtkohiUXDOxniDjaV24XPtxmqdS0a7uwz20lodj7EVGK8EnJ9PSvO/U44Q\ntvo6SfJUjm3t6OLe9ceMkSxPlckhcAfpTxXCWkXy6y7TIPpIH6n9aOdrRzi/ds5t7cRS3EbFizld\nwC8g4H/mm0fU9Ss5ZXgd4/GXw35CgxnkjH6fpWkqjs1e7PRH4lXHTNte2ltbQtJeWqWfMavscHAl\nAP4W2ZG4e33rvav1noV/0/ot2bo3F0Q/zMDRqxWXawD7+OM7Tt9zWYN9GuXaB0715pcfTbWGp6Ha\nTTpI7fMupDBW2/SdpAPbgkZHOOM14PXr394a1PLbjKSSNtwOACeOAMD+1XHKbyOMukSc+UEjjZlR\n23AgIcZJ7+p96+gfDT4i698PdWW80+5ij8WOQTRzQCRSGIbBBB80U58sd69E/wBdHKDXJX0a9D+M\nnWWha4ur2s8MzjxcpLCrI3iFi+fX8bc9/wBBXP1XqB+oNVvNVvIYvHvJTcSCNQqqcnAGOwGe1cZq\nVdm3K/Bwb+4hv5w1xdYt4TghTk5P5Vc+sXsekPpVnqNxbaU58RlEnDMQAcc+YA5NcG5Korr/AKsi\ne7POrLZWxeK3PjZ5Dt3/AKVRIkqIz5B3HgdjivTG/wCryZOVd3xRWTazMMnAFWJJP4UF1GoG+Ik5\n7jDY/LNd60aTMU84uJ1SQncDjcOTz/eulE3y+3w7dW5yxI4yKzJaoq7L7qUSSeMhCsTuKgYGayi6\ntlBMx+pTkgnOTWUmlRX2SV1dPF8Y7ccAc5zRsjGGaNsxh+Ru9qrftJsyXTQiVtoDbTySf7VjuZVx\nhI1XH83bikb8gltFKwUu+EPcscDFdDFusR/iSudvG1R9I9MUcqYRQ17tk3LDG2eCu4k/p501xqrt\nH9MKxyucFV8/es8W+xZkDXMj7jMEzzwB5VSY5GUzkk7eT9XauiIBbmTww6McBjj/AJq0X1yRnOV8\nzijiEwxy+CB/MXBzUeZAAo48+aUUoupF2hg3b8qoMjGPGAPq5PrWkRhlYOApOFxjIFZ/HZDhhx2z\nREDHMyNg8hvL2q+WcidWUAc/pirQObMk0E5gfaDH32MGAJ8sgkVcZSYQqAgdvc1OwZhOex59Mnmk\nluDL2Ta3H1Y7+1WgRXk3YY58+fWtCXBVtx5znio0CPNLJledo7A/1pljwiqd7N/nap0Dt6DbLPMs\nMkbnxOFHkT/nvX0KyivdPhJgmONwypIHHrXj9QlLTPZ6W47OlpPUN/JM5R32k7c4z5+ldS71VBjx\nJHKHG4bT34r58oVLR9HlyVnl+o0a4g8KEF3kO8kD6VUf715e3EonRVBVMgBiDg17Mb9h5Zq5nrrD\nRguHnnZEyCTx511bS0KyrMPEMRxgHkYwOa8s58ts9MIcVQ2sWunXQdJtuzYACMDmuCnRmhX86TIA\nrRHJGOWJxj2866Y80scdHDJgWSdGPXPhTdXRW50mJ44lGcNx+ef6V4TWel9R0i5jtJY8k9mx3969\nmD1Mcip9nizeneJ/RnvtNn+XRY7R/GXBOOc8c5/OuQyNE7pcJhgcYIxg+leqLTRwaoyl2ViIcj14\n4qo3DM5BJ58jXRIhf46AhcE5HJNIpZ5M5AHlz2oCHfHLgEEnvkVrgupYvpZfpHlmo9gulvd6ZPfG\nO9VpcZXOBn1Pmayo0QeKF5w5GPpHPPNaLZIgAsqkEc5JqNg3fPhVAXaMcZx5VoEnjRgFi6nABI7Z\nrk40UqvLRI8TRxr3GSB2rRpL4uVZmYODkYOORz+lO1sUe+s9ZMUQhjYcfyse+ece/eutBqj3CK5D\nK6/UTHgFcf52r5WbEr5Es8p1B1J4l8B3RAFLeaZ78+fnWeHWUe8CXLGSJA2BnOR3rvig4RQ82PBq\njyTv4MY8N1IXb388cVNR1WSLf4h5UBeMcH/M10duO+yXoxXdyt54Ld2LZYjGT+vlXRjvYlttquAE\ncHA42gADH9P7VLaVks9DoV/d3ls1ppJAN1Hsk5wTnuCf886W/sNY0j/1N9AsSn6Y8MDk/wD6T6V0\ng49Ptnepzx34X/JzzLHdp4lwygwgFlX+bPtVc12fGjdiysw7kcen+9d4bOHRVFeq84PiAAEk5Uk4\n98VumvbtohFAwjDAggPjIPamSktizmTzeGWhQorMfq+rP+Gsl5qciwKJufDARSGPPvUjDls0WWcD\nj6FVQzfU5zjA9zW3wbDIEkkmcZ78Z+9YnOV1EiM94tkAJYMZBwSQT/vWK5uIYoDDAw3S4y3mpBOf\nyrcHJqmai0jm2qA3Znbb9OWOOwrY9ycFQx7iu3bNIKMWjYgtxjGBn0rnTsrTusiFSCMmpQYsN7cb\n2hjX+EgHKkZPpTyatdW52vGAhwBg5zWeCYsW5k+ZBkQ+G5GSDxXL3zCVUZiBmtxXghqiu2J2kbhz\nmr4btEYDuDycHtjtUcSiSsgbI7HONtDLRuZeMICDzV8ApaMlDLnae/fg0bSUujeP+EcDHY08EEkZ\nFz4TlQR28qNvNJHnuy47d/1qiy1t0QzknJyfzrPLI5fcDnzqRA8gBKs2MKO1VPKjZC8nFUFfisi7\nW4FUGQu2WHA9atELsxtggZXjt5VcpikmEkhJAJY1CnZurma2incyxBpSp8KSNTkAZHlwSBjjHl61\n5528QO6BUAbJHkc+lcMK1ZqZWyxlR/DC84qqe2kLb1XGO4zXZOjBVGcnjzrWtsXjMgUtjAJz2qt0\nCsH/AO2dp9TXSisyirMSjgnJJ4ArMmairOpp0ge6gMa7Y4uQQeCfWvVz69FaQbWLmRyY02jJB8sA\n14skW5Kj1Y5cYNmXRdaFtatLPO0lwZSdqj6iM9yfKuy/UltOsk8TuSjCJBjgnGTx27VyniuVnWGZ\nKCTL9JvHc/LylQeNjsNviZ5JGe9ejTSbedUTwoZAfqyEHA9e3NcMj4vR6cXujsvl0FHtjM06hQwy\nqKxLfkM1Vcy2VhF8pC5TKcZHOeMZBFcU3PR0fs2zzl1bXTOzRQeLbvyccEf4a16Pp2oWwW+a2fw0\nwUyeMZr0OUVGjlFNy5Hel6kjDeCCVZdo4PnWTVYLDUbNJ30vxpO27uVOK4RTxtNHSSjlTiziaFot\ntcak0N1atAmDtb861a58L9Fu0C2sSCQ87jHkEbvb8+a9C9RLHP6PPL0qnE8BqfwZ1m3jNxbjxAxO\n1VOTj8v715S/+H+u2szRvZsGUZJI/pX0cXqoZPJ4J4Jw7Rxzoupl2jNuw2k7jj8PuaMek3caksFD\nfevQ5xOPQ0unr4RIfMoOQ2arW2dmUuTgd8nzopWSx3SJSVX17U0MEZcbnIXvS9A6ShVXbA2FI+oA\n+dZ5Ew2N2AeSawUtigeYEoAcD1rSvzNu5glUBgT3Pl7VG10DWjyhSGhLAjkkUIZYN4BRsrnBHnmu\nbXwDRJcTRgKGZTvBEi88Z4ziu9Hrnhovhy4baCzY7n/5rhOKk9mfJ5zWdpn8U5O7JPI4JP8AapZ3\nAlXYIgjkBBn+uT9q2v1Bo03U445SpIVsbcgYG3y/tWea58e42/VknDKRxwayouyF0NwDFsyVG7lf\nPPANIl02xoFyfr5yM96lDo9HoGovZbXXgJzx/n3r0Wu9Qw6g1tHcFgVRyORjBxjk+fH9a5uLTUkb\njkcYuHhnE0x1a2uZVkDJuwEC/Uw+/liqmu4oHaOK3+sDLEtnn9K9OPaozV9jC3kcq7StGz8lAvYf\nkadpSyGKABk7ZVs8+9ZlLk6Jd6KJY5LeJXu0Cx9ghILffNZxcxupFsi8fiLeVdF7la6NCPdyxL4Q\nOVHLE8bjTLJF8uBPErSSHKkHsDTjXRDDcm7J8NCsaZ4w3P3xUh06SRlMjMFOckjkj2FaclBWEXnS\noIbdpbeTL+YPpWCR5kym4Aj+9MWT8i2bRotbkxbJJJEAXk5pNVvE1ErL4ipgFR7/AH/WtN29GvBg\njuYIIxbA7TyWx5tTpJEyb5OWQk7SO/2q/ZEV3ErFgVXLMBwOce1Z/DTJMvLDtzVWiCGRYmKA8Yxk\neVWwsnP08Y8/WjsFxkhyAMAgceXNKcq/hyJuVgM5PFAUzOGkVgQFBxgHtSu7eIQ+FAPlVoDIIXZt\n54/vSMhiJIcbT+VSwSUyBNyHepOcj1qyGQJHuI+sjt6Ve0Cm4mbOEwM9zValgN4UAeXvTogkso/D\n3JNUu5/DWgNFuHIIxjFbY4SkV4SchNig+mef7CjKjNJevcuJWBC4AC98D0/rSzOUjGwADBJB9f8A\nMVhRrRHt2UxyqxBRSD557c1tRIp4jukTdzz60YQ1gYYG8POXz+v61oQIysFxhzgcc1zd3Y8lHyDB\ngZG+pm744I8q69rZqwGIQUPqDg1mcjvjirOxpejwR5mUhYY+WGAT38v1roX8OmwrE93GT40eYwwO\nD6nNeZycpHoqMY0eLuJY4WdZDtcNxgnaRn9a9d0bb3WpyN8tdpFBbLudOM4/PyzW8rUYWzhhTlkS\nPcRrpjENM3jzqf4coHAOAM+3byrpW9iuTidQue68A/Y/818xya7PrRil0G61VLC2Gd0pOcEYII9s\nd68Jfa/LcXfjiMkZwD7V39NC/czz+pk9JG7SNfkkd7eeAlVwQSMA4NeghuIb24RS7xjbykbcdqma\nHF6OmCfKKMGpaGhumnguWPHKnIFdOLU5bHSzbyBc+bdyKw3+RJG0uDbOTa67MsxeWEkKPob0rtTa\nykMouIziMRcZYnJ70nDeixlaPPatr928okgvghABKhsYrP8A9UQnbbX5jkVnGZMjdjB969EMGlXZ\n5J56nT6N9nofTWqWxt7WdUkfO3I5z6H7DFeP6r6Au9NjL28IcFR4YUZz+f3zXTFmanxmc8uGMo84\nHGtvhvrkth8/cRGMMNyq3H9/avPzafc2pkR0x4ZOcrg5Hf8AtXsjljNtI8c8bglZnS3ZZlucF88Y\nK9j51pSyWeQ5UYVSQwXAz5CtOVbOZolsLrwg4aNCVyFHB58jSSaV4UKM1xvLH6kUfqc/pWPyLwDT\nZ+BbDKAdyxDHtzWqe4SXEoVWYDGTznntXOVuVkCsw3srsxYDdhRweP8AP0rMfrkVgI1KNlsdx/mK\nLRouTeqPHgFXACtn8J9qqaSREIAVWHHPA9fKs+TPky3hfcElUhx3b29OKqbesQjWfADbt2e/+f7V\n0XQYkdwzSPuVMkZxjHn2Bou7HDpGSRwQDVqmCJeEgrLwB2bz9gavs7jEgZju4IwBUcaK0diwuRH/\nAN4khVx6HHr+taL67Uq1y2GaNyuMA5B7cV53d0ZaJpl/JGhdT4S7QfzI860C+08zRuEaRpAxGX4D\nDsMVW5R/UPovF00k7wRhm7g47DP9qFpPeWMex4gN/wDMACB7/wBqsKlcWEZtVvJbiH6UYGP6hu7G\ns+nuZUaeUBFJAUKvfHfH6ivTFcYUijXzMCLhYnAHYYPHvVUF7LMpb8Tj6Rgc/bFVJUCqAzQTtcXC\nlih3Ip827c/3/KtYvnKmeQM8jkrypGAOw+1csqvaKWCbcpUsFwMZ57VxL648KYzABixyBj/amBVa\nL0ZjcSM5KrgEYI8sU7IsVs04OShC8HgZ8/716FophjZ5ieRn3row4xtUnsBnzFWXREVySHdkAfQc\ncd8UklxC0qqg8vzqJFRSkYY7xn7Z5qCR8lQPbmtdix9xkGGI+mrk2MCWYkKOQBWWQR3XHCkb+QKp\nkkDMFRWHPBPf7VUB3+kx4YZ43H0NU3kgDGNDkYFXtgKMwiXB49R5UZPpwQ34uBzU8gjorYw2AO/v\nVUjy71A7AcY7YqoFLuAc98e9KpLZOPPvVAwQnGGAFdSWeL5URQgkTbWkJHP0jA/3qMqN8uh27aOt\n5bKuFQ7XGQX+rByO3b/Oa89MyxqVZSeeMVyxzcrssmr0UxbDIEP0/UM+1dW0sySd4zG44P29K1N0\njI62weRgjZXPYDtitUaJBmVApC48vyrnJ2ArcRbsMAHPOCMD2+5rXDcSoojVcZwCcZxz6VzaNRk0\n7Ogs6xW7z+KQgBAVn/EMn/Pyrm6pq93PFFtuCUgXhSck/Y/Y4rEY27Zpza6PPTmd5x4sLxrjIBFe\nn6SvZLYzJ9TPOu0LnjvXXKrhRvC6kmfSNGvmhtxCPlzJn0JwfLNdG4vLmWNbeWEAHhnBwSPQdua+\nRKPus+vFrjsuS30z5aK2Z2RT3QH6sef+1cq66f0kzOsTMv18g+47DFSGWUXSE4KWzkSaONKInc7h\nnblec8/0rXBHcokjWsqqxOQSc7T5g16XLmrZxinHSLI9Wu7qNrXx2WY8Msi5DEdsVjNzrHj+E2nK\nqsBvcEgN9s/epGEY6ejTm2d21shcBENphjwT3XP5VRqWlxCMrk8K30jtj/P7VxUqkbr26PKXumso\nNxJkqx8++McAVw3kgEjfMoMg/SiD/f8AzvX0sUrWj5+WDUrNnT16trfAxscZ53eVfTtO6itZbJ5J\npI5OyKp5JYZxx+v615vVxbpo9Ppn4Yb/AF620yGC1uGE6Tr9OVyF47n0ry2sS6HeyyK9iQEBYBCB\nuJA71xw807RrPwapnhtYg0db7FpGUTH1K2QB6/2/rWcyx+GYoxhT2x3xXuTlKKs+RJK9FQmJYruO\n3z9O/wD8UZb6ASZ2qeMHAq1ekQzT3kbZ4APABI71mkvRGAsJyB+VdIxAY7mQpuJA9SatiuQjBj3X\nOcedVx8Atju0RiXc4JyARVkpjuEdUm2+J3wM4PrXNprZGjlPM6s0cgJY8Kc8HFZWLs3fPGcE+Vd4\nqgXRqokRlkBBI8Qeg86vPhtcbonkGVzkkcAe9Zd2CK5WKQyKcMMJxnn1+9V+MsbDEi54JODj7f2o\nlbB04LkzDeUO4KFx/WtVwGgtVluQx2ndgHknJ9PY1wkqdA5r3DuZEaYgDkAdznsD+lOk0aKboZBT\n+GpHbtXRojOxb6g5hTAKgZ+oDBOfOupZySSWiRsysUyx3c4x615uPF2ToknyssbfUuQc5HY+VZJp\noLSBF+YfxMEA47D7/wCdq7QcnoqCWaGEu84mO36VXnJHmT6UITNJGx2JHIQWEQULnjkk988Vp1LY\nqyiC3ufmTPdxgR92DN+eOKl94u4sQoA5BXHA/wAxUck3SCKYJA+8RtggE4rC9gBJ41zLIF3ElWXk\n4/2rUZcF9lbokulyXMv/AKaUCIhQS5x+ePSrH0WzlikihvG8VBu2nseO1V52qSX8k5CC3XTbMi5g\njnjmUAkfiQn0PassFzFBbmIoQRzn1ziu0ZKatG1JMoku4mmOwABgAff1oRmLdvAIbtxW6ohZwiBg\ne3c5qmSRWfgefJFRdgaLK5YtnPC4omVgR+JefLtVewNcTeGokOeeM4pmELxKyqRIBhst3PtU6BQJ\nVRCSNxPtkVSWBZmccHtitAhbJADfSOwppGBVVzxSgbdF0TUNcvbXTNPj8W4uZNir/v8AbFfTdQ/Z\ny64Rd1rdaZN6YmZCfyK/71G0h5o89qHwG+JlgSZOnzLjn+HMhP6ZzWCX4W9eWylT0zdO4XeY4dsk\ngHrsUlv6UTT6JZzbjorq1NmzpXWANoyWs5ME+ePp7Vn1LRtR0zat3aTwkgcSRsp7e9VhSTGWe5CC\nCR2CJkFdxx6YxXPmszHKzwkc8qPSuUaTFhtVj3fXGN7DO4Hv7YrTHLPExxuVQcDBHIpLemC8yONy\nyptLcgnPNI0gAK7wqsS3fAA9KxRSvxlGZDkbe588+taILmUsoOWP8pA5B8qNeQdGWd00+C2lCqzA\n/UCMkA45/rWLwZDJlGBPljt965rRp9lkNjNcSOXIyqt+Mcj7Ctllo91GS21hLuO3BHI8vtRyS0d4\nQ6Z7TpsG1ljW9kKtJ+IEg4HpXtX06OBFeOdSuc5Zg2B6duK+XnlU9eT6eJe0a0trKW4DHYJGY4x3\nAx70dRgt4YECkMzSHLbf8964b5I34OfdESyGGOBCQuSGGM/auHc3UkLgQKpBzuUjufSvRi2qOc3x\nM8WpJK24wgSIB9TjOf8APyro3OpfvS3FjGskGxe48yR/zXWWOmn8GITTiU29hrGnSK4uXVc73UHP\nrXYgvxPIzEv9WBgqSDx/SueTjL3ROkG1pl1zb6VPhpImYhgoG0nn/POuBqXTEcjFYLQRqxOXqY8k\noPYyQUjiX3TQ0tDlSzN9ZOPX3rjWlxdK5KSMqA5yO3Pv2r3RkskbZ45/5Ju1DWW+QLIWZi/JOG4w\neMf715m61ic4tg5Khiw+rOCRUxY0eXLlc3bOdc3m8Z4x25NZ1vNnY8EfpXqjHRxJ882Rhx9QwT2r\nLPcPHL/3BkjsOKsY0wWRETg75grqO2fL0qfLsxBRQyg4P/zWroFm1kQoxHkD+VZpZ2QkEjFI7Aqy\ns+Oc+fetsE4VWC4wfU+VJIAunEiqUC+f1Y/3rFJKIwAQvPHfkVIrwQluMLuZ8BhkDPf/AI7VYLqT\nwxFEmCwxnHJGfX71pq+wPcyuluUViWzlie4NVW6eKf4zjPcc+dEqVlO1a3Py4GECkjkj/etF4YpY\nWcl2OeCGzivO1uyHHK55kcoVHmPxVtgM0qmFx9PkO4JPtW5LQNUK/gWXeGHGSp449PyroGdrS3dE\nBJbtgd8jv71xa2GrMEd8YrkiVuW8vOugssWwyzruUfTt4Arck10Q2ePZyWwMRChSBwfXy7dq0dJ9\nBdbfEHV7mw6N0C+1p7S2a9njtkyywKQC+M9gWUfc4qY73ZbLup/ht8T9F0bQ9buekb6TTdetmvNN\nuLdVuUuIlC7m/hFtoXeoIbBBPNeUmOqxWMU88EypP4hjndCFlVTgkE98cjjPIxXRQXknkxX921rD\naqoIeWEPgHB5JrTHfeFbrDdPtkiYsd31Yz/80nC0R7Kbm7BhMNqG5VmZnbB/KuQlzIspaJn4UNzz\nkccVrHHWwkda31hZIPAeD+H9SuTzjJ/pVmq2cDAXmnEEH6fD9G7/AKVmN45fRVpnLurCe0VTKwDH\n86Nt/Ek+rO0cnPnXoUk1aNC+Id2GHY1rttMedoZ5mIhclSRwRipKSirDNlwj22irbTqrSRztIrDG\nQpUDH9Af8NckuNgG0ZJzuBOcelIS5qx4K3aTac8qR3PlWjxHMKADDd60CqYnw1Kscef3qhVbHJ4F\nEAhyHLg4GasAWQkFvqHnVB+lvgL8MLrSNMXqzUURb66XbBHLGT4cf5Hgmvry/PiRctbIUYH8RBPP\nlkVzltlxrVmxLS617Vmm1G0mnYgM8qXJQhB37MormatoHS0Es+rW82qWTxI31vLuwoHmcPxx61zT\ncXSOtc9s+XXnVlzdiOXpjqO1gkUBP/WL4YdOcgkDknjv+tXz3GvuUW71fSrv5hA7/K3YVUPH0njv\nxXa68HN70j87TFpJpDKqKxbceOPXFCRVxmMKp7gjsa4fwYKnaKOHhT4mRyMHisrzFjjHI8qqQE8a\nTdmQncMYHc0WkLwYfBCc5xzWqADKzREpGxODnJ5xW7TfqEbSttycORzx/wA1mekaRbJE80ytHFJs\nIKplcnAzwcVbaS7SPFOzOQN3A7efpXN9FS2d60SCREYBWlYgDB4Bxk4I7+VaEnulmZZomiRMBQTk\n1wat0z1wfhHYsXlVGXwEctgqXPYedewbUNOuYlCxNC6qD9LNhj7+VeLNF2mj3YnqmUxX0xLRwyjf\nHjcpHI9x6jisbXlyJHgug6j+UjkN+XrzXHib5fBp0y5S4lMbYbyGGHY8DPmKya3YNaSpJbFGkBOY\n/T37/wCZrcHxnTM5FatHFS6soJv/AF0r7cZLLGcZ5/8AFdXRbuLULrEctn4aAKuCA7f8Y9K7zur8\nHDG0nxOndyxTgxQy/UD9RCDdz/tgUphitS7QvtKDc6n0PPH9K4xbSo9LVOylY4rOZZvCeNG77Tkj\nnn/5Fda2mSZWm3kgAY38kDt/Wk7aEWcvX76NI2leH6fwk7eMtxyP8718v1S7uIZpIML4bHa7AHA9\nq9PpVqmeH1rTpHHlmAiKmRseWe9cx5UUllOTk/VmvfBHzzFJcM4GD2zyTUVw5AD5Yc9+9dqoCOzM\npKvgYyBjGKMVu0iZm5cD6f8AzToCphhiJstznIyM1bFLPG2FcEtyR7VWgbVkmKbVXOcViuIpYpGM\nylcZAHr6ViNWCoSxoA4TJOQQa0WtwF4ck89j71trQLZ5QibV5bPOP71z5JkyVKZHqe+akUQVSCxU\nsFA/w10bG3ikcSSygqCMKDg8Uk6WimuRIAuYlDbfJud1VLbptUzEtxzjjBPl9q5ptIg0l4kZ8MgK\nrdx7etFrph9KksCe/njypxBmlWUSox3MqjOR5e1WreOq7Q43DnNVpSBrW5mZDIW3EjB+ry+9aoLn\nlVLqEU5BPfHuaw0qKXEQXoAQorxk7STnI9Oe9ZAzSK+wIHHfjIJqLrYP1F+zX8DtP6h6PPxFg0Xp\nr4n3CiaG/wCjDqb2V/ZQhtouFYHDOQGIVlAwQVYvwv6O+G/7SX7Knw16cfp8aFddBaj05bzI2mat\npZW/3LlnjEo3F3Yns7BjkZA8ukag1aM9H53+EH7aVh8E9f6v0zS9C1TXPh9qWoz3+gWEkiQ3OneJ\nJu8McsoRgxyufxKCMFmz7/oL409Iftd/tCaL0hP09Y2Hw30Oxvb6DQdUihT94X8sbRySSRglWk3X\nJZApJG13zknHRPRT4j+0N+yV8R/hN1cj6B01edT6RcW013aSaJp1xcLZxK5LLMoDGMIHXBZiCOd2\nc4/NU93Jeu38cLJ37dx7/wBKnHyyUWrPNE2Q7SFEzwOMeY9/Ov0v+yF1X0Xrdl1B0P1L8F+iNaPT\n3TOsdQxapf6eZby4khw6RSMTgoN+3gA4A5qxSCNPw06W0H9ozob4v6vadJ9BdGahC/Ta6dI7CxsN\nPBe4Wbw3fcYzII1zz9TYFfQul/gb0t0cfgD011LY9JdQXWudR6rBq99pkiXltqESFWhR5QAJAgOM\nHsQRWZRsHA/aG6dOm9EXkV/0t8BbS2mvYrdLnpAs2rQgOXHeQ7VITaxx54868P0d0X0tefsxfEzX\nJtDs59U0nUNGisL14g08CyTMHCv3AYdwO9ef8kuVPoW2zgfs2/By2+JnxjtLHWbF5undDgfXNWSK\nIyGS1gwzR7Ry3iNtjwOfryO1fdNY6B+HegftAdB6lqPw9i0voL4vaU1iuk31lsOj6k6CJo0Rh/Dk\nScwkOAOJWxxXW/yJF7EtP2cun7T9n3qXpHqDTIG+KNx+9db0vbFmcWelXMcEsSZ5/iYlZVH4wwPO\n2u30j8Lfh5pnxkt/g/a/DjpnV9V6T+G0lzfx39rG8d7r7JHLmZiVyB4iKCWG0MwyO9RexJIn0c/r\nf4UdMP0/0Ve/FP4P9GdCdY3vWmm2lnp2gXEbw6rpbyqJjJBHLKmwZA3FiScDgHByftGdKN0pYdcw\naJ0J+zrbaPYGe2tVsyw6hgiL7EKxiTCzqGyRtwMHjjFdISte4qL/AIqfs4/D7rPU+lpfhTo9nbdS\ndN2eh3XU/T0UQRb/AE658Mm+jQcMULMsvH4eTjC7/dzfs8/AnoNOuPiTd9E6JrN2vV1zoGl6ddvu\n06xwpky1urKp+ngIewCkYzmuvRabZR8Pvgj8K/iJ8VbDVYPhj0fp62uhXy3VikTNpt3chcxTNAxK\nxBOM7Tk5JJ7Y8p8UvgZqVsdFg1PpP4NWUAvDdrcdGWLx3QaNCoSYtO4MR8Tdtxy0a8gAg55aJKL6\nOgsNxZwRWcGBtUIJH8vy4yeKFx4dqY2l3EbiWJY/qecVzZ2XwizTurdLt1urZ54lM8eTJv4ABxt3\nZwOMmvnPxm6hjtrGOzsZCslyrB9rZ+gAn+tZjT2jtxlDUkfI+lbWW8mEEheAqhIMkZ/F5V1bmwvY\n9xeWN+6kk4GMDyPvmvSkeJvZ82udKu/pR02FslmY4JPPFc9I08PY7kgH6mHavFCfKOjRmuBlSEYn\nnA4rMlvKu2Rm49fSuqeiEIwBu2hRw2O5oNIghOxM84XPatFKVLRMzMOx7+9axc/RuViCvvg1JKwW\nxanfxM8UczKJOGjV8c4P/JpyzlVkZiwAyfq58sVhpI022a7GciTgumWBVh3z7V63TA90PEleYNz9\nTHOecD7Dv2rz5lSs9GB+6j0WnrscLsEg/m5B2++K3ahH4CJJLdQomcogBBOO/PPP5V8+TqR9CWla\nMV/qml2NxbTiaRZVXndjnnv6Ecg/lXIu9X1a/wBRRYVeKEuAsmcdvMDv/NWow57keeWV7jE7tw9t\naWCm3+WzKGDBndmaTPc47H2xiuRL1bYyzxyPAlouQx2Hbu47sRzj2wM4rEISntCWVY6ibWNh1BIj\npfRhJojJII12+EPU8+1cy66cvtEvYryBzPbtskhl5258uf0rtjlw9kiuPL3o9qNIkubKK5jmCXSY\nLGPnDY7EDsOaRlZ5ha6gUWYYAmjwpPsR+VedST6PUvhlFzDfSSFY3SRQeShyT/TijDcKm5ZC0bKB\nldvf3zW1UlSD9vZ5nXLm4toZo5r9cS/UQw4XPYH07j7V89vL93aXZMSjd892x5/1Ne7DFPaPmepb\n5bOTNNuDoCTgZHtWJ5CoO7B7E17oqjymaV/qPhkmjEAwG+QI2QRXQGkIRlGdWIPlVrRqVJ29u+PO\nubAsMcbF127M8hc+dDKQA7ZMlcEE9802QIvNyZyVPOMDyP8AXyrPIbmX6/qKg5A9feqlRRY0weTg\nj2rZCiefBb3o2QsFmwV2ildm/wBB7Ma5cwaGRTtHpzSLseTRBGzyBZ41UDIyPOtUsgihWFSM/wAz\nYo9sDxPJEPrz6qc00cqsN0ihVB4B86y15KZbpk5Cruyfqf09KRPolJc87d/9Owra6IdKASzxPyUJ\nAIBH2/8ANSO0to5f4jEAE9z3+9crrSBoSeGKIpDg7iMqwyOPSszSqX3AY9sd80in5KWxu8o3qTgD\ngDv9q7nT9j++NRsdFso0N3qE0dtEruAhaRgo3E9hkisz+ED+nv7NvQsf7L/wyvbT4uaj0doM13eN\ndi9jvwJZkKqBFKXRdzLj6QjMDu7A9/yR+378WPht8XOqulrf4f3a6ibKK6iv76LTDCzk+H4Y8ZwJ\nJFX6/pxtHJBOeNqSiuLeyM/NPTthfafeCG/RXgkUqmG4Bz+E5H3NbIlm6cvItR0yaSC7Mq3MUkbl\nXR1bIKkHIIIyD3FYlNSftB+4v2Tunfip+0joFx8SOrv2luvINPs9Sl059I0qY2jB4wrjfOcqwKyI\ncKmQDjcD2/IH7TXSPS/Q/wAb+ounul+mtY0Cw06aNWs9TuhPP4hRWMgk3OWSQFZQSzH+J3HAHfaQ\nZ8rkJZwschAXKkj7/wDBr2Xw7+JHUHwj1HVde0fTYLwdQaFe9Ps13G+xYp1VXdCpGXXHHceoouwh\ndA+I2s9K/D3qr4bLo8JtetJNNnuJZkcTR/KSSPGY+QCGMhzkHsMYr23R/wC0L1l0Ppvw/wBFh6b0\n6WT4dapd6hp8VxHKJria6bLRygEcDjbtAP3qNUKNvVXxr0TrzQr/AKdi+BfR2galeyLu1DTorkXc\nEglVm2h5SAW2lDkdmPnW34XfG/UPhh091B0Jqvw90TX7DXpbWe7tdYimA3wFvD+lHXzOefQV5p+2\nRk72uftP65ZdPXui/DLozRuh77XVtbW5vOnXuYboLDI0iLFJ4hZSxYBiOSoC147qn45/E/X/AIfw\n/DzrOa/1m7s9Zi1nTtV1O6uJtSs5wuzZHI7E7DydpyATkc0hNuinotW/ag+M+q/G3SPjrfdORQap\noVmtjFai1nWzNuFkWRWBbIDGWRj9XBIx2FeZ6S+OfWNn8Rer+ujptrqWrdb2ep6feQuruI1uzmQx\nqpBBUDCjkADkcV1kwx7T47dVaf0j030Lquh6fqbdEa7Fq2iXV4sgu7PbIrPaghhmFmUEoRkHsfpU\nD1XXPx1g67udV/e37P3RlrrnUSyNLqMdvdLeeNICDMgaUgtnOCQefKufKkDGvx1+IjfGHQ/jDpek\nNpur9P2trpLRWcErQTwQIIzFMpJJDpkMMjGQRggEfQNA/aT6pOudV6jrnSGk6npHVd4dQ1XQNQtH\na2SQnKyoc7o2HYNk+WckAjtjyt9i9nW6a/aQ1x+sdL6i6f6B6W0rTtPs7jR4LC2tXithFNzIZZAw\neRyMkZbzOACzE9PW/j3pWqaNFBYfDfRNFtINRUC/svG3TQ7XBQGRmB55OPNQPOk8ulRuLfknWus3\nWm6DBqcelXcpYxTxrGDzyDjgEkc84H5142X4y6NFqlsl5Y5XYPEkDn+FnG4Y2nJHIxmuMsnF9HRt\nJI6+r9ddGiwtdRtYYJWndPEDxrujQ8knyz28/OvmGv6pH1Nr6ziVWgRixB7Ko4CnOKqmpPRYtKJ0\n9YuP3XYwvbIkEhfG4Eg4OPTHl71xx1BdCVvEQPyD3Byc+e4GvVFJo4S0fPJLtOfmSZ0IO7GSMf8A\nNcK6lWNnS2DBXJCe4rw407oPozM6kjar5HLA+X2pGRmUjYQvoa9KFmdotvlkD1pTEXbIwMZIJHat\nIITw2I3nBGexphMA5GGCgBfp/wA+9R7KX20Yu5cNxuOSxHavWjQtK/d4uLZpZ3AHiYUbVPlyK4ZJ\nONJHWEU1bOZHAiP/AAcbQeAWBb7GvTWeo2kFsN8zllfOGzgc+VccickdcLUXbOsdZEESzQxIVJyz\nJ3H5Y7VTqmp2V3ZtK9rIpUjw3PJ/I+X2rx8XaaPTLInFo8sWN1qCQqz7X52kcAfzY47dxWrVNRSC\nNI45ZSEIZSvG05HufSvQk3JJHji6tlUOuSvIEaZwWOAwJBH5/rWe5ivDLLM0sM5YhkXHJIHJyPL+\n9WKWN7MOTfZTaXmuwGZyv0ybQ25SAwHbuO398VZqfW2s3dkmiw6k0lvGQQuDkkHI5/P7fpXX8cMk\nrWyrLKKpeT1XTvUOtaPpl3qd6LmR7lV8NfAb6mI4b0wBiudadWX6SLdTOZpDcEvkjj29/OvP+CLb\naO8s8oqKO1N1Xp1s0Ul9FIjTxBwYm5J8/vXMveufD3RrarslhxFLnhT55H34x7VYYJM6z9SqPJX3\nUt7fXpuHnAXCqQowDj27Vxrm4kYMqj8RzzXthjUaR4Jzc3bOXLIwJBbGO9JJMXXYGPHJr0JGRI5V\nGElCnvjFWTQRlA0UnGMlSeRVA8MRXCuWyf8ASKsTemQWx25/3rL2DZCmxSsSbmkGd2O3rWe5gRQN\nz4Yt3/Tisp7BXCoE5jVcDOCfatvhBoykQyF5XP8AakiMzzyKgYEfWBjbjzNVxpdOMInAxkdsGqqr\nYN0STQRfWcSE8jGCv3NZpWUrkIGZju59e1ZVN2iGl5kIXckYzzwMmuZezgy5ifzxyBVggi1LkEgu\nDhR2yTVkMjXIIYEKFbGR51qqKVXM0zr4awuETjdzzz6/entYwyq0h/FkDI7GnSBvgIUMC7E9lIHl\n9/Ko8WWO+XcW+ojtXPphGWASPMVCk5yq5NdKPTWaUs86LtHHPf8Aw5pOXEprDfLOsTNGP5c9z9xx\nTRXMkEsdza3jw3MbCWNoWKMrKeCCOQQec1y82D9pdHdW/sS9Y6t0pY650p1b1L1p1LNY2VzJfahe\nTLBezlY2Eksk6B0DucsFbgZA8q/TfU/7IfwJ13pHUemNP6E03Rp7238OHUreHdc2zjBV1dyWPIGR\nn6hkHvXWMIS2kD+Ymp9JapZ9daz0L0i1z1U+l3l1BFLY2Tu1zFbs2+ZY13ELtQtnOAOc+dchOnr2\n71LTre80y4tp9RdflXuAYEkDNtBDPhdu4/iJwOckYrz0420LP3b8Lv2Uf2iPgZo1t1F8LfiXpqan\nfKtxrHS2pox0+SXsVV1LAttCjcFQ5X8eDXw/9tbpLTrr5P4g9R/DbqbpLr7Vr4w6pZ3N4L3Tr+JY\ndvj2tyNy5XESiLcpUMMJgbq9Huitg/IJtH3JD4MiKxJ+pTxn/iv1bP0l8M+o/wBkP4UD4jfFG46N\nitNV142ssWgS6p8yzXADAhJE2bcLyc53e1dUD6Zqfwk0rrT9pz4f6wblNT6V6G+Heja1LczqtpHe\niEOLRW8U7YjLJ4ZKufwhwTxmuZ8VOhtb1b45fAr486rp2l2+pdQdS6NpXU0WlXkd1awatb3cQRhJ\nGzL/ABYAGC7iQI8HmqD4r1k6j9qnqhZRtDfEK7IIxnjU3/z9Kt/avCzftD9eMHAK6uwJJ5/AuP61\n5Jrt/ZEj2H7Nk1z018J/ir8VOi9NivOuOn4bCHT5Gt1nk061ldlnuYUOfq2g5bB2hOeCwPu/hr1n\n1L8Y/hRB1l8YbdbvUemuuunrbpTXp4VW4unmvY1ubUSBRvREy578nk/SMbinVeCop/ax+MV5pzfE\nHpzT/wBpzVbx5LybTm6O/wCkxHEkbTBJbcXpJ4SMud2Pq24GCa+T/sn/ABL0XoDTviB+97jX9BGs\nWtlawdZ6PpS3kmhOsrsVkDA7Vn4Bwcnw+OcMu1t2Tyfe4dH600PWet/jDP1XpXxE6ys+gNP1XonV\nYtHWCSWwkmkSW8a1IBFxGqg5O44cAk5K18o+EPxn+NHxP+JPwwtviFeXOtaPZ9Z2zWuq3OmoGW4J\nBaAXIQdlJbw93mCRwuJK1oH0fTOrI+l/hn8SdQf4yal8Nw/xevbddVsNHfUpJiYJT8uYkZSFO0vu\nzgGMDzrnfBP4q2Njrvxh646p6ruvijoNl0/pltNqGoWBspNRtJJ445k8FiShTxZFGTyUB4B4RpRV\nkPoPTnwp6P6b6D0XRotZg1noLrL4maVqGkXLyj/1FlLbMBby47OJEMTDgn2JwPkXX3x//aIuutOu\n/h1LY3B0qFb2wl6eGjRy29jp0e4bljCHaFj2uJc4wA2cYrnK4L2g+n/FP4sR9M9O/DLxf2lNa+Hs\nk/w80a6j0Sy6ekvorkmNwJjKjqFLFdm3HAjB86/DMutzapdy6teTmWa6kaR2ZhlnY8k+pJJNMibS\ndhmqbULjwTGk/wBDABmxjPI/SmtryWJSxuWdWbcCD5A//FcEqCNGva7qlxYwLBdThhMPrWQ5IIPf\nB4HA71yrfqPWPHWM35kLOqEOisRz7jNfQxtOKNS7Oa1xPAjhHKox7nkGssCS3Eqgld27IJPFckkt\nmfo1C2dMyPKHc8KF86xSPJJnLHCnj70i+RQFSv05yD5YwacRK31Mre/3raKGdFEYAVtzHCqB3NY2\nglO7aMDsQTzQo9om3grkk5DDg5rpWlxMAwTMWBkc4yf8NcplTNYs5Fk2x5kz9ZYNwuK6mn2Z8FJm\nhEwdsk5yUPv+lcJyOsIuzdfStAFCwmJAOGVhyc9wPSuNeXpKDfI5UNnaxIH9K4RVsuRtaMJ1NGuS\ny/SBHtG3JwPzNK00UxUCUOucsrkjdjPlXZJxOHI3C6hkCHw1RgAxVEwp8sE+lKLiSV03xBckqfpG\nAB79xXOnWxetFTsb6MoZJGjEm3d2GR6c8jvXd0DSdPsD+8r2Jc7RtD/UFwM+ecniujbjCkd8Si3c\nujv6t1zo01pNZeNc70xtKgqHwO3Hlxjmvly3Hih7dm27pc5J/FyeOfPmp6XFLHF8jXqM0crTib9T\ne4uYUtY48pAiqjg5OPP9awXt3JLFbJINojjwV9Tk4P6Yr1JHCXkwqyyN4DK0G0jk9z70JVmUuhI+\nnBGBzitHNnNNvLLKTtZeCcnIFVQRSTPsU44JzXW1RTbFp0YwGbe5zwOBirRZyRRgNsQNwcHP5Vhy\n3sEaaPcAm07RjnuD/wAVnWcYzxjG0HHf2qpA08hAckZXOAfKqpTL2UkqeQCeaIBUeHyV7jmtUDlg\nBhgDzj9aj2CqW2WR2niHIOeewxWqBS0aqPxgYx5msyeiGia2adAsf0sDyDzmufLAwJVSGUfzA9/f\n7cVmEvBChplPBA+o448qoESNKTvGRnjzrstFRU8m1ipbse44porp1YiNlKqOCatWU2yzLJbmYYVy\nACF/m/8ANSxkHirCWBU8kY7cedYrRDUzeHE0oTZn6RkVjSdvxBhzyOKkVaKbo2jYeKyBA3IYHJzT\nxOQzMZsBcE4+9ZrRCqS7XJZSSWHfP+ef96ujut+VkkznngZ/81eOijwajNazLLDcOHicNFKjEOrA\n5BB7g5/rX9Ivgh8Zet9D/ZA6o+MvXvxHXqLVYorhdOSaaKRrFx/AtopSg3eI8xVjvJYqyeeasVQL\nf2H/AIO6b8HujLX4l/EK6gs+pfiBLFaaYt04Vo7d1MkUK5//AMs2wyEd8BBwQQfpv7VXwT0j449E\nfuW1mtk6w0qKbUtCDyKsk2zaJYiCc+G5aNS3ZWMZPoa43CgeT6P/AGmOprH9liH4lw9HNr+u9Iud\nF6m0+e7a1ntZYP4bTODG7FsGF3TAwHc5Gw1/Pfqz4k9c9aWNjp/VfUl5qdlpUk0lhDcTNKtsJCpY\nIWywX6FwCcAKAMVym3pMqPKtq1tMpRo1J/Aecfb+1elmuurOrelNA6ENjql/o+mGW+0jTobJmCme\nfwpJIyi7nVphszkjeCo54rKUor2g7esdX/Grqbpq66YurnqC60m+s7Sxu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|
|
453 | 453 | "output_type": "pyout", |
|
454 | 454 | "prompt_number": 5, |
|
455 | 455 | "text": [ |
|
456 | 456 | "<IPython.core.display.Image at 0x10fb99b50>" |
|
457 | 457 | ] |
|
458 | 458 | } |
|
459 | 459 | ], |
|
460 | 460 | "prompt_number": 5 |
|
461 | 461 | }, |
|
462 | 462 | { |
|
463 | 463 | "cell_type": "markdown", |
|
464 | 464 | "metadata": {}, |
|
465 | 465 | "source": [ |
|
466 | 466 | "Here is today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connection, that should be different from the previous one. Notebooks saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline." |
|
467 | 467 | ] |
|
468 | 468 | }, |
|
469 | 469 | { |
|
470 | 470 | "cell_type": "code", |
|
471 | 471 | "collapsed": false, |
|
472 | 472 | "input": [ |
|
473 | 473 | "SoftLinked" |
|
474 | 474 | ], |
|
475 | 475 | "language": "python", |
|
476 | 476 | "metadata": {}, |
|
477 | 477 | "outputs": [ |
|
478 | 478 | { |
|
479 | 479 | "html": [ |
|
480 | 480 | "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />" |
|
481 | 481 | ], |
|
482 | 482 | "output_type": "pyout", |
|
483 | 483 | "prompt_number": 6, |
|
484 | 484 | "text": [ |
|
485 | 485 | "<IPython.core.display.Image at 0x10fb99b10>" |
|
486 | 486 | ] |
|
487 | 487 | } |
|
488 | 488 | ], |
|
489 | 489 | "prompt_number": 6 |
|
490 | 490 | }, |
|
491 | 491 | { |
|
492 | 492 | "cell_type": "markdown", |
|
493 | 493 | "metadata": {}, |
|
494 | 494 | "source": [ |
|
495 | 495 | "Of course, if you re-run this Notebook, the two images will be the same again." |
|
496 | 496 | ] |
|
497 | 497 | }, |
|
498 | 498 | { |
|
499 | 499 | "cell_type": "heading", |
|
500 | 500 | "level": 2, |
|
501 | 501 | "metadata": {}, |
|
502 | 502 | "source": [ |
|
503 | 503 | "Audio" |
|
504 | 504 | ] |
|
505 | 505 | }, |
|
506 | 506 | { |
|
507 | 507 | "cell_type": "markdown", |
|
508 | 508 | "metadata": {}, |
|
509 | 509 | "source": [ |
|
510 | 510 | "IPython makes it easy to work with sounds interactively. The `Audio` display class allows you to create an audio control that is embedded in the Notebook. The interface is analogous to the interface of the `Image` display class. All audio formats supported by the browser can be used. Note that no single format is presently supported in all browsers." |
|
511 | 511 | ] |
|
512 | 512 | }, |
|
513 | 513 | { |
|
514 | 514 | "cell_type": "code", |
|
515 | 515 | "collapsed": false, |
|
516 | 516 | "input": [ |
|
517 | 517 | "from IPython.display import Audio\n", |
|
518 | 518 | "Audio(url=\"http://www.nch.com.au/acm/8k16bitpcm.wav\")" |
|
519 | 519 | ], |
|
520 | 520 | "language": "python", |
|
521 | 521 | "metadata": {}, |
|
522 | 522 | "outputs": [ |
|
523 | 523 | { |
|
524 | 524 | "html": [ |
|
525 | 525 | "\n", |
|
526 | 526 | " <audio controls=\"controls\" >\n", |
|
527 | 527 | " <source src=\"http://www.nch.com.au/acm/8k16bitpcm.wav\" type=\"audio/x-wav\" />\n", |
|
528 | 528 | " Your browser does not support the audio element.\n", |
|
529 | 529 | " </audio>\n", |
|
530 | 530 | " " |
|
531 | 531 | ], |
|
532 | 532 | "metadata": {}, |
|
533 | 533 | "output_type": "pyout", |
|
534 | 534 | "prompt_number": 7, |
|
535 | 535 | "text": [ |
|
536 | 536 | "<IPython.lib.display.Audio at 0x111346750>" |
|
537 | 537 | ] |
|
538 | 538 | } |
|
539 | 539 | ], |
|
540 | 540 | "prompt_number": 7 |
|
541 | 541 | }, |
|
542 | 542 | { |
|
543 | 543 | "cell_type": "markdown", |
|
544 | 544 | "metadata": {}, |
|
545 | 545 | "source": [ |
|
546 | 546 | "A Numpy array can be auralized automatically. The Audio class normalizes and encodes the data and embed the result in the Notebook.\n", |
|
547 | 547 | "\n", |
|
548 | 548 | "For instance, when two sine waves with almost the same frequency are superimposed a phenomena known as [beats](https://en.wikipedia.org/wiki/Beat_%28acoustics%29) occur. This can be auralised as follows" |
|
549 | 549 | ] |
|
550 | 550 | }, |
|
551 | 551 | { |
|
552 | 552 | "cell_type": "code", |
|
553 | 553 | "collapsed": false, |
|
554 | 554 | "input": [ |
|
555 | 555 | "import numpy as np\n", |
|
556 | 556 | "max_time = 3\n", |
|
557 | 557 | "f1 = 220.0\n", |
|
558 | 558 | "f2 = 224.0\n", |
|
559 | 559 | "rate = 8000.0\n", |
|
560 | 560 | "L = 3\n", |
|
561 | 561 | "times = np.linspace(0,L,rate*L)\n", |
|
562 | 562 | "signal = np.sin(2*np.pi*f1*times) + np.sin(2*np.pi*f2*times)\n", |
|
563 | 563 | "\n", |
|
564 | 564 | "Audio(data=signal, rate=rate)" |
|
565 | 565 | ], |
|
566 | 566 | "language": "python", |
|
567 | 567 | "metadata": {}, |
|
568 | 568 | "outputs": [ |
|
569 | 569 | { |
|
570 | 570 | "html": [ |
|
571 | 571 | "\n", |
|
572 | 572 | " <audio controls=\"controls\" >\n", |
|
573 | 573 | " <source 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rLudBZKiidaExYN5ht2MwZbYo76z9sX22SDv0ARhGigvhELgU7Niim4Jd+17D31legV0H2r+XApNvDqjJloRifvV5enQaL3pq/Sc/pBliGuDOILWhDCLF5U+oj6yncTM2C7uHATvGfsunUI8VE9jYW8UeCN9Z37We4J1nWtzXmpO/ju+J0cSQfxU5izRbb2xq4KcVpCMh2iCE4GYg+OJxJPuoPywcsO/10ftYQNkGaMue0JQVJdj22+7ePJ9WH/gfJ92xWycX41PEj28KCgT//zr5pjRrL3Bq2ScDJAYh86BWIDBgveIyZLsn/qvdsLR1mzsoALBGCMuIEIcVItj92/9eFh+33+EfVt3k214YG9Q9T2aKfsTwv2Y5yzSI74ZrJqcH5AIh5yBBoBRgmyIKJI4nzmvrMED1qHr3AEJGHwtjUGhUyxjtW/beFZ+/H/AfbR3B24EYQ9Rpj5WKr8Uh/5b6ObS0b62rCKdjpBch9OBHYBJgkSI4ZHVnrquFsFZ1ebqFgE9F64sxEDiUntiF29UeOp9r3+Ufap3IG4/YWxRIj/vKnAVTf8w6cbTtL+XrfydWpEUiHKCn4CpgoCI9pHCnn+utMDT1D/qUABfFr4rxz/fUXphHm5rdxd9+H7/fDx33G0pYYRRaD9iKw4WEAAW6sjUy8C7riWfgJIviXmDioFygyCJaJIBn4quicBz1Kvpjv9xFasqlz6aUClgy2wfdt172X0DfGt2PW3AYFZRdz+vK5YW0gAL6+rVE8IgsJyg/5OqiuaE3oKihCOKNpOTn9uulsA61C7pz/51FHkpNz0WT4xeIWt0dD16UXyfejZ1QWwFYOJQTj/TKwgXjgEO7CzXi8PEsWCi1ZWGjLiGmoQ5homLYJR4oHOv3MAq1MnoFv5tEykoqDtUTaNcIGlpcjl4YnrVeJ9z6Gr2XiZQ7D7OK2EXQwIb7YrYMMWks22kAJi+ju6Iu4Y2iFKN5pWwoVKwW8FF1HzoZf1bEr4m7jlXS3Jay2YDcNN1DnimdqVxNGmVXSNPUD6eK6AX8AIx7gHa/8a9tcGmfppSkYWLQYmXinyPyJc6o3mxFMKK1EvovvxBETolCjghSftXJWRCbQxzV3UTdEtvJWfiW9lNej1DK8MXkgNO75Hb98gOuFqpS50/lHqOKYxbjQaSBJoXpeeyCMP71DboIfwiEJ8jADa2RkFVMWEqauhvQHIgcZJsvWTcWUhMaTy7KsoXKARv8DbdE8uTujSsZaCBl8yRcI9+kO2UmZxEp5y0NsSZ1T3okvv/DvAh0TMYREdS8l2+ZmpsyW7NbXxp/GGHV29KHTsHKrMXsQST8e7eU81JvUyvyaMWm3aVFJMAlDGYhZ/CqZe2n8Vk1mToEfvaDS8ggTFLQRFPa1oCY5Ro+Godagxm5V7iVFFIlzklKX4XKgW48rfgss8twKCycqf6nneZEpfcl86bx6KOrNi4Qsdc16nooPq2DGAeEy9QPqFLoFb4Xmpkz2YUZkNieVvvUe5F1jcWKCkXkgXb843iLtI8wyu2Xqspo8mdZpsQnMKfW6anr127H8mC2A7pQfqUC4MciiwtO/xHlFKkWvBfUWK2YSVevFewTkdD3TXZJrMW6AX79G/kxNRzxuq5ia+gp2miDKCZoAmkQKoLsyW+NcvW2ZTp9Pl3Cp0a6SnlNyVES04LVipbg10EXbVZsFMoS15AqjNvJR0WKwYW9lrmcNfNydi97rNarFSnAaVypaGocq63ti7BhM1X2zvqu/lfCa8YMid6NB9AykkxUR1WaFgEWPZUWE9YRzU9QDHYI2UVWQYp90voMNpIzfPBirhTsYSsQaqYqoWt77KqunfECdAE3QPrmPlQCLsWaSTwMPA7FUUbTMtQBVO6Uu1PuEpEQ845oC4UIowUcgY0+D/qAd3f0DbGV72GtvWxxq8GsLKys7ffvv3HxNLe3u3rivlLB8UUkSFMLZs3MUDMRjxLX00pTZ1K0kXuPio2zCslIJITdAY0+Tbs39+P1JzKUsLvu6K3jLW4tSS4urxUw73LstXj4Pjsk/lRBs8Srh6RKSUzITtKQXJFe0dXRwtFqkBaOk0yxCgLHnUSXwYo+ivuyOJV2CLPdceIwYe9jrupu9a9AcIGyLbP0tgS4yXutPlkBdsQwRvCJZEu6zWaO3Q/XEFIQTo/RjuLNTkuiyXHGzgRMwYO+x3wt+Us3MPTvcxOx57Dx8HUwcPDgsfyzOTTI9xr5XPv7fmFBOwOzxjkIeQpkzDBNUY5CjsCOzE5qDWFMPIpJCJaGdoP7gXk+wryq+gQ4HvYI9I6zeHJMcg0yOjJO80S0kXYoN/r5+LwPvq2AwMN2hX5HSIlHyvEL+4yiTSJNPMy1i9LK3olkB7HFlsOkAWr/O7zoOv/40XdpNdH00zQyM7Ezj3QJtNk19TcSeOR6nDyqPr5AiML5hIHGlEgkyWoKXIs3i3kLYcs1CniJdQg0xoOFL0MGQVf/cn1k+705x3iOt1w2djWhdV+1cDWPtni3I7hG+db7R30LPtOAk4J9Q8RFnMb9B9zI9clECcXJ/AlpyNPIAYc7hYzEQELiQQB/pj3gfHr6/7m4eKv34HdY9xc3Gndft+K4nDmEutI8On1yPu1AYUHCg0aEo8WSBoqHSIfJCApIDYfVB2VGhEX5hI2DicJ4QOP/ln5aPTg7+XrkugA5kDkXONZ4zPk4uVV6HbrK+9V89H3ffwxAcwFKQomDqcRkhTTFlsYIBkfGV0Y4Ba5FPsRvQ4aCzAHIAMJ/wv7RPfR88zwSu5c7A/raupu6hrrZOxA7pzwY/N/9tX5Sv3CACMEUwc5CsEM2Q5zEIURChIAEmoRUhDBDscMdgrhBx8FRgJu/6v8E/q697D1A/S+8unxhvGX8Rby/vJF9N31uPfF+fP7MP5oAIwCiwRWBuEHIgkQCqgK6ArQCmUKrQmwCHoHFQaOBPUCVQG9/zj+0vyW+4v6uPkh+cf4rPjL+CP5rPlf+jX7JPwk/Sr+Lf8kAAkB1AGBAgsDcAOvA8kDwAOXA1MD+AKNAhcCnQEkAbIATAD2/7H/gP9j/1v/Zf9//6X/1P8GADgAZQCJAJ8ApQCXAHYAQAD3/5z/Mv++/kT+y/1X/e/8mvxc/Dr8Ovxd/Kb8FP2n/Vz+Lv8YABMBGAIdAxkEAwXRBXsG+AZCB1MHKAe/BhkGNwUfBNgCaQHf/0T+pPwO+475NPgL9x72efUi9SD1dvUj9if3e/gX+vD7+v0kAGACmgTCBsQIkAoVDEUNFA54DmwO7Q37DJsL1gm3B0wFqALe/wP9Lfp19+/0svLQ8FzvZO7x7Qrusu7n76Hx1/N49nP5svwaAJQDBAdOClcNBhBEEv0TIBWjFX0VrRQ3EyMRfg5bC9EH+gPz/9r70ff282nwSe2u6rDoYefO5v/m9ees6RnsLO/O8uf2Vvv7/7EEVAm/Dc8RYRVZGJ0aGBy7HIAcZRtvGaoWKxMKD2QKXgUdAMv6j/WU8AHs/eeo5B7id+DB3wXgReF545Pmfuod70306fnF/7MFhwsRESYWnBpPHh8h9CK8I3AjDSKcHy0c2Re+EgMN0wZeANX5avNR7bvn0+LD3q3bqtnO2CLZp9pT3RXh0eVm66rxbPh6/5wGnA1DFFsatB8hJH4nrymfKkUqoCi6JaYhgxx2FqsPWAizAPn4ZPEx6pnj0N0F2WHVAdP80VzSINQ/16PbK+Gv5/7u4PYa/2sHkw9SF2oeoyTKKbYtRDBfMfswGC/CKxEnJSEsGloS6gkdATj4fu81557f9thy0z/PgsxQy7jLuM1D0UHWjtz6403sSPWm/h8IaRE7Gk8iZilGL8AzrTb1N4s3cDWwMWcsvCXfHQ0ViAubAZH3ue1f5M7bStQOzk7JMcbRxDzFcsdky/bQ/9dK4JnppfMg/rgIHRP8HAkm+i2RNJc55TxdPvE9ojt/N6YxQiqKIcEXMA0rAgb3Fuyy4SzYz8/eyJHDE8CDvu6+VcGnxcXLg9Ol3Obm+PGH/TYJrxSVH5MpWjKlOTg/5kKQRCZEqUEpPcc2sy4qJXMa4A7MApT2luov37rUicvmww2+L7psuNS4ZrsSwLTGHc8M2TbkRfDd/JsJHRYCIuwshTaAPp5ErEiKSiVKf0epQsc7DDO6KCAdlxB+Az32OenY3HvRfMcqv8e4ibSRsvGyqrWousfB0sqE1Yzhje4j/OUJaBdDJBIwdjodQ8NJMk5FUOlPH036R6BASDc4LMYfUBI/BAD2AOit2nDOqMOsusOzJa/3rE2tJ7BwtQO9psYR0uve0uxb+xUKjxhXJgEzKj55R6VOc1O9VW1VhFIYTU5FYzuhL2IiDBQNBdz16+ax2JzLE8BytgWvB6qip+un4KpvsG24nsK1zlXcF+uH+i0Kkhk8KLk1oEGRSz9TbFjsWqxaqlf9Uc1JWD/vMvAkxhXoBdH1++Xj1gDJvrx9spCqNaWYos+i3KWoqwe0vL51y8/ZXemn+SwKcBryKTg41ERiT45XF13QX6JfjFylVhdOJEMgNm0nfhfNBt31L+VG1Z7Gq7nRrmimsaDcnQCeHqEgp9ivBrtUyFvXqOe9+BQKKht3K306xkfpUo9bcmFkZEpkJmELWypSxEYwOdgpMRm7BwD2h+TY03fE3LZwq5CigJxymYCZqpzbouOrf7dVxfvU+eXL9+YJwBvMLIY8ckojVj5feWWjaKFocmUtXwBWMkocPCws2xqwCDn2A+Sc0o3CU7RdqAqfpJhelVOVhZjeniyoKrR8wrPSU+TT9qMJMhzwLVI+10wPWZhiKGmKbKJsbmkFY5dZbE3hPmcufByrCYb2ouOQ0d/AEbKZpdqbIZWkkX6Rs5Qsm7ekDLHMv4bQuOLX9UwJghzjLuE/9U6qW51lfmwXcEtwFm2QZupcblB8QYYwEB6oCuf2Y+O10G+/GLAnowKZ+pFFjgOON5HJl4ehJ65IvXbOLOHY9OIIsBymLzJByVDzXUhod29Gc5dzZnDKafZfNVPoQ4YylR+oC1n3RuML0D2+aK4HoYSWMI9Gi+aKFI64lJ+ef6v0uobMr9/Z82cIvBw4MEVCVFLpX5lqEXIVdoV2W3OxbLhivVUkRmU0CSGmDNz3SuOQz0m9Aq07n2CUxoypiCmITYv8kQOcF6nRuLnKRN7b8t0HqBybMBpDlVOLYY9sSnSBeBB583VBby1lBFgsSB82aSKjDW74beNFz5K856vEnZmSvopvhs+F5IiYj7aZ8abkthLJ79zh8UUHdhzPMLJDi1TXYiduInaIejh7K3h4cVJnCFr/SbM3tCOaDgz5r+Mozxm8FqujnDCRGImahNqD3YaOjbqXEaUttZLHsNvs8KAGJhzVMAxEN1XOY2FvlXcqfPt8AXpUcyVpxFuYSx455iSMD7b5DeQ5z927j6rWmyWQ14csg0uCOYXiixGWeaOxszzGitr/7/EFuhutMCpEmFVwZD1wpHhkfVZ+c3vRdKNqOF33TF46/iV1EGr6h+R3z927U6pgm3iP+oYmgiSB+oOUir6UKqJxshPFgNkb7zoFMxtbMA1EsFW8ZLpwT3k2fkl/gHzvdctrYV4YTnE7+iZTESX7GuXfzxi8X6o+myqPgoaJgWWAIYOmicKTKKFusRjElNhD7nsEkxrdL7VDgFWzZNlwlHmfftJ/JX2tdptsPV/7TlM81yclEub7xuVx0Iy8tKpxmzqPb4ZUgRGAroIZiR+Tc6CssE7Dxtd47bgD3Bk3LyRDCFVXZJtwdHmffvJ/ZH0IdxFtyl+dTwU9lCjoEqv8iOYq0Tm9T6v3m6iPwYaJgSaApILviNaSDKArsLXCGte87PECEBlqLlxCSVSnY/9v8Hg2fqh/O30BdyxtCWD8T4Q9LymcE3P9XucK0h2+MKzPnHKQeIcmgqWAAYMoieiS95/ur1HCkdYR7CoCMBh4LV5BRlOmYgdvCHhlffR+qXyXdu1s9l8YUM49pik9FDr+R+gO0zW/Va35nZiRkYgqg46BxoPDiVWTMqD0ryHCLdZ662MBPxdjLCxAAFJVYbRtvnYtfNd9sHvJdVJskl/vT+I99ynKFAD/QOk01IDAvK5xnxeTDIqWhN+C84TCih+UvqA/sCjC7tX36p4APhYsK8g+eVC2XwlsE3WOelJ8UHqZdFpr3V6BT789IipCFcL/SOp71fzBYrA3oe6U54tnhpiEh4YkjEOVnaHQsGfC19WL6uD/LxXXKTU9s07KXQZqCHOLeGZ6iXgGcwhq1V3NTmU9JSqjFX4AXOvf1qbDRrJHoxuXII6biLeGgIjojcSWzqKosd7C6dU26ib/FhRlKHQ7sUyWW69noXAmdhR4XnYScVpoe1zSTdI8/inrFTQBe+xe2HzFZrSfpZuZtZAxizqJ3YoMkJ+YUKTGso3DJdb76XX+8xLYJok5dkoaWQdl321gc191z3O+blJm0FqRTAU8rikZFuABoe332XvHvbY9qGyco5MnjiCMnI2QktOaJKYqtHfEi9ba6c39yRE0JXY3A0hbVg9ixWo8cEly4HALbPFj1FgKS/86MiksFoICzu6n26HJSrkdq4qf6JZ4kWWPvJBylWCdSKjUtZnFHNfV6TH9mhB6Iz41XUVaU8teV2e9bNVukW37aDlhiFY9ScA5iigiFhgD/+9r3evLCbw9rvOif5ojlQeTOpSvmESgvKrEt/XG2tft6aP8aA+tIeMyhkIcUD5bl2PmaAZr5mmRZSpe7VMrR0c4tyf7FZ8DMvFA31bO976ZsaKmZ54lmQOXEphGnH2jfa34uYvIxNgj6iP8NQ7PH2kwgT+kTG1XiV+8ZN5m4WXPYchaBVHURJU2tya2FRcEZPIl4d/QEsIttZWqmqJ4nVabQpwzoAini7BwvFnK2tl46rP7Aw3kHdItUjz1SFlTMVtAYGFihmG3XRRX0007Qqo0iiVRFX4ElfMW44PTVMX2uMeuFqcbovufxqBzpOOq47Mqv2DMHdvt6lX71AvtGyEr/DgTRQlPk1Z4W5Rd2VxOWRJTVkphP4gyMiTNFNMEwfQS5T/WvMjwvDWz1asHp/Ckm6UEqQyvgrckwp3Oi9yB6wr7qwruGVsogzUCQX9Ks1FoVnpY3VeXVMROlEZHPC8wrSIpFBUF6PUV5xDZRcwXwdq31LA6rC6qvarhrX6zaLtexRHRJt427NL6iAnoF4El6zHHPMFFlkwTURhTllKVTy5KjULvOKEt/CBjE0IFBvcd6fLb7M9mxbG8DravsbOvKLAHsze4j7/UyLrT7d8L7bD6bgjeFZciNy5kONJAQEeAS3JNCU1MSlJFRT5bNd4qIB9+ElkFG/gn6+PerNPaybbBfrtgt3m11rVxuDS998OEzJbW3eEB7qP6XwfUE6EfayrfM7c7t0GyRY1HO0fBRDZAvjmPMeonGx13EVsFJPkx7d7hg9duzuXGIMFJvXu7w7scvnDCm8hs0KPZ+OMY7636XAbKEaAciiY9L3U2/zuwP25BMEH4Ptw6/jSMLcUk7BpQEEUFIfo57+LkbNsf0znM7sZkw7XB68ECxObHeM2I1N/cOuZP8M/6ZgXFD5oZmiKAKhExHTZ9ORs77Tr2OEk1BjBWKXEhlRgJDxcFD/s88evnZN/n16zR48ytySHISMgfypTNidLX2EngpOim8Qj7gATFDZAWnB6uJZArFjAgM5g0dzTAMoIv2yrwJPIdGRaiDdIE7vs48/bqZuPB3DrX+dId0LnO1c5u0HPTzNdU3d3jNOsd81r7qQPNC4UTlhrMIPYl8CmeLOwt1C1aLIspgSVdIEkadxMdDHQEu/wr9f/tb+er4d7cLNmv1njVjNXp1oHZPN384Zrn5+2y9MT75QLgCX0QjBbdG0kgsSP8JRwnCifKJWkj/B+gG3oWshB5Cv4Ddv0S9wTxeuue5pPid99e3VjcaNyL3bbf1eLM5nzrvPBk9kb8MwL/B3sNgBLmFo4aXR1BHy4gHiAXHyEdURq+FoYSzQ24CG8DHv7t+AP0hu+X61To0uUk5FPjY+NP5A/mkejA64DvsvM0+OH8lQEsBoIKdg7sEckU+xZyGCcZFhlEGLkWhBS6EXIOyArbBsgCsv64+vf2jPOR8BvuOuz76mPqduov64bsbe7T8KPzxPYe+pX9CwFpBJQHcwrzDAEPjxCWEQ4S+BFYETUQmw6ZDEEKqAfjBAkCMv9y/N75i/eI9eTzqPLc8YPxnfEm8hbzZPQC9uL38/kj/GD+lwC4ArQEegb/BzkJIAqxCukKygpZCpsJmQheB/UFbQTSAjIBnP8Z/rb8fvt4+qn5F/nD+Kz40fgs+bn5cPpI+zn8Ov0//kL/OAAbAeQBjgIVA3cDswPKA74DkwNMA/AChAINApMBGwGpAEQA7/+s/33/Yv9b/2b/gf+p/9j/CgA8AGkAiwCgAKQAlQByADoA8P+T/yn/tP46/sH9Tv3n/JT8WPw5/Dv8Yvyt/B/9tf1s/kH/LAApAS4CMgMuBBUF4QWHBgAHRgdSByIHtAYIBiIFBgS6AkkBvv8h/oH87fpw+Rn49PYN9m71HvUk9YH1NvZA95v4PPoa/Cf+UwCQAskE7wbtCLMKMgxaDSAOfA5mDt0N4gx5C6wJhgcWBW0Cov/G/PL5Pfe89IbyrfBD71Xu7e0T7sfuB/DM8Qv0tfa2+fn8ZADfA0wHkgqUDTsQbhIbFDEVphVyFZUUERPwEEAOFAuCB6UDnP+D+3z3p/Mi8AvtfeqN6E3ny+YM5xPo2elU7HTvIvND97j7XgAVBbUJGg4gEqcVkRjEGi4cvxxxHEMbOxlnFtkSqw78CfAErf9a+iL1LvCm66/naeTy4V7gvd8W4Gvhs+Pf5trqhu/C9GT6QwAxBgEMgxGMFvMalB5QIQ8jwSNdI+MhXB/ZG3MXSRKDDEwG0/9K+eXy1exL53Tid95324zZydg32dXamd1x4UHm5us28gD5EQA0By8OyxTVGhwgdCS5J9AppSovKm4obiVCIQoc6xUUD7cHDgBV+MbwnukV41/drNgh1d7S9tF00lbUkdcO3K3hROih7473zP8bCD0Q8Bf4HhwlKir6LWowZTHhMN8uayueJpogjRmrETEJXwB798jui+YG33TYC9P2zlnMScvTy/TNoNG71iLdo+QH7Q32cf/oCCoS7xrxIvAptC8ONNk2/TdvNzA1TjHmKx8lKx1IFLcKxAC89uzsoOMj27jTms37yALGyMRaxbbHy8t+0aTYCOFp6oH0Av+ZCfYTxh2+JpQuDDXvORY9Zj7SPVs7EzcXMZQpwyDmFkkMPQEZ9jLr3eBt1yzPXMg0w9+/eL4Ov5/BGcZbzDnUdd3L5+vygP4vCp4VdCBbKgUzLjqaPx5Dm0QFRFxBszwrNvUtTySDGeINyAGR9ZvpRt7p09bKV8OnvfW5X7j1uLW7jMBXx+PP79kw5U7x7f2pCiIX9iLHLUA3FT8JRepIl0oCSixHKkIeOz8yzicdHIMPYwIk9Sno2tuX0LnGjr5XuEi0grIVs/+1LLt2wqfLedaZ4qvvSf0JC4IYSyX+MEA7v0M4SnZOVVDFT8hMckfrP2w2OyuvHikRDwPR9NvmnNl6zdbCBLpKs96u5axxrYCw/LW+vYrHFtMK4APulfxOC70Zcif/MwQ/KEgjT71Tz1VIVSlSiEyORHk6ky45IdESygOZ9LPljdeVyjK/vbWCrrqpjqcQqD6rArExuY7Dys+H3Vvs1Pt5C9MaaSnINohCTEzHU7xYAluHWktXZlEDSWE+0jG2I3kUkQR69LDkrtXpx867vLEEquKkgaL1oj2mQqzWtLm/mMwR27PqB/uMC8QbMCtXOctFKVAfWG1d6V99XylcB1ZETSJC9TQkJiAWZAV19NLj/9N4xa24Ba7TpVigwp0lnoKhwKewsA+8hcms2A7pLvqFC48cxiyrO8pIu1MoXM5hf2QlZMBgaFpOUbZF+TeAKMIXQgaH9BnjgtJCw9G1maryoSGcVZmlmRGdgaPDrJK4k8Za1m/nTPlnCzUdKi7CPYJLAFffX9tlwmh8aAplhV4dVRpJ2TrGKl4ZJwew9IbiNtFKwTyze6dknj+YPZV4le+YiJ8TqUa1xcMf1NflY/gzC7cdXS+bP/RN9llCY5BprWx+bARpWGKtWEtMkz31LPEaEwjv9BbiHdCPv++wrqQtm7eUgJGikR6V2pukpTCyH8H+0UnkdffqChQeXTA3QR1Qm1xOZutsPXAocKts4GX6W0ZPJEAJL3kcBAlC9crhNc8TvuuuMqJNmIqRHo4mjqOReph5olOvpL74z8jigvaNCk4eLDGTQvtR7V4Baepvb3N1c/pvF2kCXwZSiEL/MPMd+Amp9aHhf87WvDGtCqDHlbuOG4sHi4CObJWWn7GsWLwRzlXhjvUdCmYeyjGxQ5BT62BZa4lyQXZkdu9y/GvAYYlUvUTWMl4f7Qoh9pvh+s3Yu8KrNp6dk0yMeohJiLmLspL+nE6qPLpMzPPfmfSdCVweNjKPRNlUlGJVbcd0sXjyeId1i24xZMtWv0aJNLYg4Aup9rXhps0Zu5+quJzQkT6KPYbthVGJT5Czmi2oU7iryqXep/MNCTIecjIvRdZV52PzbqN2vHoce8B3wXBUZstYjUgXNvoh0QxA9+7hgc2ZusepkJtikJSIZYT1g0mHRo65mE+mobYwyWzdufJvCOkdfzKQRYlW5GQycBt4YHzgfJZ5nHImaIVaI0p+NycjvA3k90bijM1WujqpvppSj0+H9IJkgqOFmYwRl7mkKLXex0vc0PHGB4MdXjK0RfBWi2UTcS55nX0+fgp7GnSjafdbf0u7ODwkoQ6T+LvixM1RuvmoQpqhjm6G64E7gWKES4u+lWuj6bO3xkTb8PASBwAdDzKbRQxX22WUcdx5cn4zfxh8OXXLaiBdoEzMOTUlfA9L+UvjKc6IugGpHZpPjvOFS4F6gIeDW4rBlGii57K9xVnaGvBWBmMclTFHRd9W1mW2cSR63n6/f8B8+HWca/1dgk2uOhImTRAK+vXjuM76ulOpTZpcjt6FE4EjgBODzYkclLKhJLLyxIvZT++UBa4b8TC4RGlWfGV6cQd64X7hfwF9VnYVbIxeJk5hO88mERHQ+rbkcc+lu+2p0ZrIji2GRYE1gAWDoInRk0qhobFYxN7Yku7MBOEaJDDwQ6xVzWTgcIV5e36af9p8UnYzbM1eiE7iO2wnxhGY+43lUdCJvM2qqZuQj+KG4IGygGCD1YnfkzChYLHxw1LY5e0DBP8ZMS/xQqhUzWPpb594rH3pfkx863X3a75eqE4wPOcnaxJj/HnmV9GivfOr0py1kPmH44KXgSKEbYpJlGehYrG9w+nXSu04AwsZGS69QWFTe2KXblZ3dXzOfVZ7InVga19ehE5JPD4o/RIt/XbngdLwvlutS540knOJTITmgkuFaIsNle6hqLG+w6XXwexuAgUY3ixWQNhR2mDrbKt12XpMfPp59nNvaq9dHE4tPG8oexP1/YPozNNwwAWvE6AMlE6LHIachNuGxYwtlseiMrL2w4fXTuyoAfEWgyu+Pg5Q7V7naqFz13hiejd4aHIiaa5cb03aO3ko5BO6/p7pNtUfwu6wJqI7loiNT4i5htCIhI6nl/GjArNkxJDX8evmANAVCir4PAhOtVyOaDlxcnYTeBB2eXB7Z1xbfUxQO1woNRR4/8Xqvdb8wxKzgqS9mB2Q5Io6iSmLo5B7mWulF7QKxcLXq+srAKMUdSgGO8ZLNVrjZXZurXNhdYVzKm56ZblZRUuOOhYobhQuAPbrX9gDxnC1JaeRmw2T2Y0djOWNIZOomzancbXpxR3Yf+t5/28TxybqOExJcFfnYlpriXBNcppwfWshY8ZXyEmTOaYnjRTcAC7tGdozyAW4DKq0nlSWK5FgjwCR/JUtnlGpELcAx6LYbuvR/jQSAiWoNp5GaVSfX+lnCm3bbk9tdGhwYIRVBkhgOAsnkBR/AWvu6duHys26M60hou6Z1pQAk3mUM5kIobqr9LhPyFLZeOs1/vQQKCNCNL1DI1ENXCdkM2kNa6hpEGVqXfRSAEb0NkYmeBQVAqzvy93+zMW9lrDXpdmd2Jj7lk2Yw5w4pHCuHLvXyS3an+um/bMPPSG7Ma5Aok01WBVgB2XnZqhlVWESWhhQt0NRNVUlQhScAu7wvt+Uz+rAM7TQqRCiLZ1Mm3mcqaC5p3Kxhr2WyzPb5Osm/XEOQx8XL3M96kkbVLlbimBsYlJhRV1oVvFMLEF1Mzkk7xMUAy/yv+FG0jnEBrgKrpCm0aHwn/mg4qSLq760MsCNzWXcR+y2/DENPB1YLBE6/UXCTxZXwVugXalc41hvUoFJYD5jMfIifBN8A23zy+MR1a7HC7yAslWrwKbjpMqla6mpr1G4HsO6z8LdyexY/PYLKxuBKYo24UEwSzFSrlaHWLFXM1QsTstFVTscL38h6xLQA6b04OXy10bLPcAtt1qw9ashqueqQa4RtCm8R8Yc0krfau0N/MAKExmXJuMymT1oRg1NV1EmU25SOU+gSdJBDTifLOIfOhISBNj1++fl2vvOmsQOvJq1bbGlr02wX7PAuEPArcmz1P3gK+7V+5EJ9habIx8vKjlvQbFHwEuATeZM+EnQRJg9ijTvKRoeaRE+BAL3Gero3czSG8kewRG7Ibdrtfi1wrixvZ3ETc1819niC++z+20I1xSSIEMrlzRKPCBC70WbRxtHdES+PyA5zzANJykceBBWBCH4OOz34LTWvs1YxrrADr1tu+G7Zb7iwjLJI9F22t7kDPCn+1MHuRJ+HVEn5i/9NmA86D99QRNBsz5wOm003Sz8IxAaaA9XBDX5Vu4P5K/afdK3y5HGLsOnwQbCRMRNyADOL9We3QvnLPGx+0cGnRBjGk4jGiuMMXU2sTkpO9Q6uDjoNIQvuSi9IM8XOA5BBDr6b/At57neVdc30Y7Me8kTyF/IWcrvzQPTa9nz4F/pbPLS+0gFhg5DFz4fOCb+K2YwTzOlNGI0iTIsL2gqZSRSHWkV6QwUBDH7g/JN6s7iQNzT1q7S8c+tzunOoNDE0zfY1t1z5NjryvML/FoEdwwjFCQbRSFXJjcqxyz4LcItKyxBKR4l5B++Gd4SewvPAxf8jfRt7evmOuGE3OvYidZt1Z3VFNfF2ZjdbOIa6HTuR/Vc/HwDcQoFEQUXRBycIO0jICYmJ/smoiUqI6gfOhsEFjEQ8AlyA+z8jfaJ8AzrP+ZH4kDfPt1O3HbcsN3w3yLjKufn6zLx4PbF/LECdwjsDeQSPBfSGo8dXx82IBIg9h7uHAwaahYmEmMNSAj+Aq79gfie8yzvS+sW6KblCuRM427jbeQ95s/oC+zV7w/0lvhG/fkBiwbaCsUOLxL/FCIXiRgtGQwZKhiQFk4UeREoDncKhQZxAlz+Zfqq9kjzV/Dt7Rns5+pf6n/qRuup7JzuC/Hj8wr3Z/rf/VQBrwTUB6wKIw0nD6sQpRESEvARRBEXEHMOagwMCm4HpgTMAfb+Ofyq+V33YfXF85Py0PGB8aTxNvIu84P0KPYM+CD6UvyP/sUA5ALcBJ0GHAhPCTAKuQrqCsQKTAqHCYAIQQfWBUsErwIQAXr/+v2b/Gb7ZPqb+Q75v/it+Nb4NvnH+YH6XPtO/E/9Vf5X/0wALQHzAZsCHwN9A7YDygO7A44DRQPnAnoCAwKJAREBoAA8AOn/p/96/2H/W/9o/4T/rP/c/w4AQABsAI4AoQCkAJMAbgA1AOn/i/8f/6r+MP63/UX94PyO/FT8OPw9/Gb8tfwq/cP9ff5U/0EAPgFEAkgDQgQoBfAFkwYIB0kHUAcbB6gG9wUMBewDnQIpAZz//v1f/Mz6Uvn/99/2/fVk9Rz1KPWM9Un2Wve7+GL6RPxV/oMAvwL4BBsHFQnWCk4Mbw0sDn4OXw7MDcgMVwuBCVUH3wQzAmX/ify3+QX3ivRb8orwKu9H7uvtHO7c7ifw9/FA9PL2+vlB/a4AKQSUB9UK0Q1uEJcSOBRCFagVZhV7FOkSvBABDssKMgdQA0X/LPso91jz3O/P7E3qa+g758nmG+cx6Afqkey973bzn/ca/MMAeQUVCnQOcRLrFccY6hpCHMEcYRwgGwcZIhaFEkwOlAmBBDv/6fm19MjvS+ti5y3kx+FH4LvfKeCS4e7jLec36/HvNvXg+sEArwZ6DPQR8RZJG9gefyEoI8MjSCO3IRsfhBsMF9QRAgzDBUj/wPhf8lns3OYW4i3eQ9tx2cfYTtkF2+HdzuGy5mfsw/KV+aoAywfADlIVThuCIMQk8SfuKagqFio6KCAl3SCQG2AVew4WB2r/svcp8AvpkuLw3FTY5NS90vPRj9KO1OXXe9ww4troRvA7+HwAywjmEI0YhB+TJYgqPC6OMGkxxTCjLhErKSYNIOwY+xB3CKL/v/YT7uPlcN7116bSsM4zzEXL8cs0zv/RONe43U7lwu3T9joAsAnrEqIbkSN4Kh8wWTQCNwI4TzftNOkwYiuAJHYcgRPmCe//6PUf7OLiedoo0yjNq8jWxcPEe8X8xzbMCdJM2cfhO+te9eT/eQrOFI8ecSctL4Q1RDpFPWw+sD0RO6M2hTDkKPofChZgC08ALfVP6grgsdaMzt7H28Kuv3G+Mr/swY3G9Mzx1Ejesujf83r/JguMFlEhISuuM7M6+D9SQ6NE4EMMQTk8izU1LXMjkhjkDMMAjvSi6F7dGdMmysvCRL2+uVa4G7kJvAvB/cer0NXaK+ZY8v3+twsmGOgjny74N6c/cEUjSaFK3EnWRqZBcjpuMeAmFxtvDkgBC/Qa597atc/5xfW967cMtHeyPLNYtrS7KcN/zHDXqOPJ8G7+LQybGVAm6DEIPF5EqUq1TmFQnU9tTOZGMz+MNTwqlx0AEN8Bo/O45Y3Yh8wHwl+51LKbrtismq3esIy2fL5wyB7ULOE279D9hwzqGooo+zTaP9NInU8CVN5VH1XJUfRLy0OLOYMtDiCVEYUCV/N85GvWkclUvgy1A65yqX6nOqigq5qx+rmCxOLQut6g7SL9xgwTHJQq1DdtQwNNSlQHWRNbXVrnVspQNUhnPbMweiIrEzoDJfNm43rU1cbiugCxfKmUpG+iH6OjpuCsqbW6wL/NVdwK7Gf86gwWHWwsczq+RutQq1i+XfxfUl/CW2VVbUwbQcgz2CTAFPsDDfN34rvSVMS0tz2tQqUEoK2dUJ7soWWojLEbvbnK/9l26qD79gzzHRIu1jzKSYhUvFwlYpZk+mNVYMBZblCkRL42JSdSFsgEDvOt4S7REMLLtMapWaHHmz2Z0Jl+nSukp62oudTHvNfm6M766AypHoYv+z6PTNhXfGA3ZttoUmidZNddNVT/R5I5XinfF54FJ/MK4dPPCsApsp6mxJ3glyOVopVdmTig/qlnthHFjtVd5/T5www6H8cw4kAMT9ha52PyaclsVGyVaKdhvlcnS0E8gCtlGXwGWPOM4KzOQ77Rr8ejhJpSlGKRzJGOlY6clqZZs3bCeNPc5RP5iAylH9UxiUJAUYZd+2ZTbV1w/m86bCplBVsZTsg+iS3hGmAHnvMz4LfNu7zCrUKhnZcfkf2NT44UkjKZcaODsATAfdFm5C34NwzsH7Ay8UMpU+FftWlXcJJzTXOIb19oCF7SUCRBdi9QHEgI+PP+3/bMc7v+qxGfEZVLjveKL4vyjiaWkqDorb+9n8/94kP30wsPIFgzGUXHVOdhE2z7cmh2PXZ8ckFrwmBPU1FDRDGxHTIJZvTt32fMa7qHqjad4JLXi1OIb4gsjG6T/p2Kq6q74s2k4Vj2XAsPIM4zAUYYVphjFW4+ddp4zXgUdc5tMGONVU5F8DIBHx0K5fT+3wnMo7lcqbGbDZHFiRKGEYbDiQ2Rtpttqce5R8xd4G711QrtHxM0qUYeV/JkuW8ed+h6+HpNdwNwUWWJVxdHeDQ/IAYLdfUw4N3LG7l9qIKamY8XiDeEGIS6hwSPvZmSpxm40soq34b0PgqsHyc0EUfWV/Rl/XCaeJB8v3wled5xIWdBWalI2zVnIewLEvaB4OHL07jqp6uZhI7OhsOChIIUhleNFpj+paK2g8kO3qPzmglLHws0OkdDWKBm4nGxedB9H36aelxznmiyWgNKFDd3IswMvPbx4BTMyLijpyuZz43phbeBWIHShAiMw5axpGW1X8gK3cby6gjMHsEzJkdkWPVmZ3Jjeqh+Fn+qe310xmnaWyNLIzhvI6UNcfd94XXM+7iopwGZeo1rhROBlYD0gxeLxpWuo2S0Zscg3PLxMQgyHkoz1UY6WPNmjXKuehd/pX9UfD11mGq3XAZMBjlKJHUOL/gl4gLNa7n3py6ZhI1ThdmAO4B+g4aKH5X2oqCzmsZT2yjxbwd+HacySEbGV5tmU3KTehx/yn+XfJ51E2tJXatMujkJJTkP9Pjm4rrNFbqPqLGZ7Y2ghQmBS4Bug1eK0ZSMohuz/8Wk2mrwpwaxHNsxgUUKV+5lu3EUerh+hX90fJx1NGuMXQ9NPTqoJfAPvvm+45vO+LpvqYeatY5ShqGBxYDFg4mK3ZRvoteylMUV2rrv2wXOG+YwgUQGVu5kxXAveex91n7oezl1/GqCXTNNjzomJpgQjPqs5KLPE7yVqrGb2Y9oh6GCqIGEhB6LQpWiotSyW8Wo2RvvDQXWGswvS0O+VJxjc2/nd7d8v332enN0amonXRRNrTqCJi8RW/ut5c/QY70ArCudWJHiiAmE9IKqhRSMApYkoxSzV8Ve2Y3uPgTMGY0u4UEyU/phx209dhx7P3ydeUxzfWl9XLJMmDq6JrMRKfzA5h/S576srfSeMZO8iteFqIQ2h22NG5f2o5izh8U42RLucQOxGCwtREBlUQpgwmszdBx5WHred8NxNmiDWw1MTDrMJiQS9fzi55DTnMCZrwqhYZX2jAmIwoYniSaPj5gYpWC07sU52aztpwKIF6wreD5aT89dZ2nLcbl2DHi7ddlvlWY4WiNLyzm4Jn4SvP0R6R/Vf8LDsWuj5peMj56KQIl8iz+RXJqLpmy1isZh2V3t4gFTFg8qfzwSTUpbuWYHb/RzXHU1c5BtnGSeWPVJEzl8JsISfv5M6srWjsQntBKmvZp9kpKNIYwzjreTgpxNqLy2Xsex2SbtJQEUFVcoWjqSSoBYumPqa9FwS3JNcOpqSmK0VoJIIzgYJuwSN/+P647Yx8bDtv+o453FleOQYY9KkYyW/55eqlC4acgq2gjtcADNE4cmDjjbR3JVbWB3aFJt224Hbedno198VMxG/TaLJf0S5//Z7GnaJsmUuSysVaFimY+UAJO+lLyZ0aG9rCm6q8nM2gTtx/+AEqIknjXxRCVS1lyxZHppD2tlaYpkplz3UdJEnzXTJPMSigAo7lncqMuWvJivEKVQnZGY+JaOmEWd+KRor0O8JcuY2xztKP8wEakiCzPXQZxO+FicYE5l62ZpZdZgVlkmT5ZCCjTyI84SIgF571reSs7Hvz6zEKmLoeecR5u1nCShcKhesqC+1syO3FDtmP7fD6AgWTCRPtpK11Q8XNBgcmIYYc1ctlULTBlAPjLmIosSqwHK8GrgCtEiwxq3Ua0Qpo2h6Z8woValN6ydtT7BvM6v3aLtF/6ODokejC0iO+RGeFCUVwRcp11zXHNYyFGoSFw9PDCwISsSJAIa8ofi5NOkxiq7z7HZqn2m26T9pdepS7AjuRrE2dD73hHupv1ADWccpiqON71C3UuqUu9WkFiAV8tTj00ARWA6BS5QIKwRjAJm863k1dZJymi/hbbkr7WrGKoWq6WuqLTuvDTHKtNw4J/uR/33Cz0aqifYM2k+DEeATZZRL1NCUthODkkUQSg3myvGHg8R4QKs9Nvm2tkOztDDb7sqtS+xm694sLyzTLn6wIrKrtUP4kvv+/y0Cg0YnSQFMO05CUIeSPxLik2+TJ9JSUToPLYz/SgTHVMQIwPq9Q3p79zv0V/IicCouue2YLUethe5Mr5GxRjOZNjX4xbww/x6CdoVgSEYLE012TyGQihGpkf3RiNEQz9+OAwwLyY2G3gPUQMf90DrEeDn1RDNzsVZwNe8YrsDvLK+V8PNyd7RStvH5QHxofxKCKYTWh4VKI0wgTe+PB1Ah0H0QGo+ADrbMywsMSMzGX4OaQNJ+HTtPeP02d7ROcs3xvvCnMEjwonEt8iMztfVXt7e5wryk/wnB3QRKhsAJLErBTLLNuI5Mzu4Onc4hDQBLxkoByAIF2YNawNm+aTvb+YQ3sXWxdA9zE3JCch5yJbKTs6A0wLan+Eb6jLznfwRBkYP9hfdH8AmaiyzMHszrzRKNFAy1C70KdcjsRy5FC8MVgN1+s7xpek54sDbbdZm0sfPo87/ztbQFtSk2FreCuV97Hj0vfwKBSANwBSwG7whtiZ6Ku4sAS6uLfkr9Ci4JGkfMhlFEtoKKgN0+/Hz2+xp5szgLNys2GXWZNWw1ULXDNr23d7inOgC79z19fwTBAILixF9F6oc7SAnJEEmLifqJnkl6SJSH9IajRWvD2cJ5wJi/An2DvCe6uLl/eEL3x/dR9yG3NbdK+Bw44jnU+yo8V33RP0uA+8IWw5HE5AXFRu/HXofPSADINMeuBzFGRUWxRH5DNkHjAI+/RX4O/PT7v/q2+d85fLjRuN744zkbeYO6VfsLPBt9Pn4q/1cAuoGMgsTD3ESMxVHF54YMhkAGQ4YZhYXFDYR3A0lCi4GGQIG/hP6XvYF8x7wwO3569bqW+qK6l7rzuzL7kTxI/RQ97H6Kf6dAfUEFAjlClMNTA/FELQRFBLnETAR+A9MDjoM1gk0B2oEjwG6/gD8dvkv9zv1qPN+8sXxgPGs8UfyR/Ok9E72N/hO+oL8v/70ABADAwXABjkIZQk+CsAK6gq9Cj4KdAloCCQHtgUpBI0C7QBZ/9v9f/xP+1H6jfkF+bv4rvjc+EH51fmS+m/7Y/xl/Wv+bP9fAD4BAwKnAigDgwO5A8oDuQOJAz4D3wJwAvkBfwEHAZgANQDj/6P/d/9f/1z/av+H/7D/4f8TAEQAbwCQAKIAowCRAGoALwDi/4L/Fv+g/ib+rf08/dj8iPxR/Df8P/xs/L78Nf3R/Y7+Z/9VAFQBWQJdA1YEOgX/BZ8GEAdMB04HFAebBuYF9gTRA38CCQF6/9z9Pfyr+jT55PfJ9u71W/UZ9S31mfVc9nX32/iI+m/8gv6yAO8CJwVHBz0J+QpqDIINNw6ADlcOuw2tDDMLVgkjB6gE+AEo/0z8fPnO9lj0MPJp8BLvOu7q7Sfu8u5J8CTydvQv9z36if34AHIE2wcYCw0OoRDAElQUUBWpFVkVXxTBEocQwA2CCuIG+wLt/tX61PYK85bvlOwf6kvoKufI5irnUeg36s/sCPDL8/z3fPwnAd0FdQrNDsASLxb8GA8bVRzCHE4c+xrQGNsVMRLrDSoJEgTJ/nj5SfRk7/LqFufx457hMuC63z7gu+Er5Hvnlutd8Kz1XPtAAS0H8gxjElQXnRsZH60hQCPDIzEjiSHXHiwboxZdEYELOwW8/jX42/He62/muuHl3RHbV9nG2GfZN9sq3i7iJOfp7FDzK/pCAWIIUQ/YFcUb5yATJSgoCiqoKvspBCjQJHUgFBvTFOENdAbF/g73jO966BHig9z/16nUn9Ly0azSyNQ72OvctuJy6evw6fguAXsJjxEqGQ8gCCbkKnsurjBqMaYwZS61KrIlfh9KGEsQvQfk/gP2X+085dvdd9dE0mzOD8xEyxLMds5h0rfXUN775X7umfcEAXgKqxNUHC8k/SqIMKE0JzcEOC03pzSCMNwq3yO/G7oSFAkZ/xT1VOsm4tLZmtK5zF7IrsXAxJ/FRsijzJfS9tmI4g3sPPbFAFkLpBVWHyIowi/6NZU6cD1vPoo9xDowNvAvMSgvHywVdwpi/0H0bek53/bV7s1ix4XCgL9uvlm/PMIFx5DNrNUd35rp1PRyAB0MeRctIuUrUzQ1O1NAgkOnRLhDuEC8O+k0cSyVIp8X5Au//4vzqud43E3SeclDwuW8i7lRuEW5YLyNwabId9G82yjnYvMMAMUMKRnYJHUvrTg2QNRFWUmnSrFJfUYgQcI5mzDvJREaWg0tAPLyDebk2dfOPMVgvYO307NwsmiztLY/vN7DWs1p2Ljk6fGU/1ANsxpUJ9AyzDz5RBZL8E5oUHBPDUxXRnc+qjQ6KX0c1g6vAHXyl+SA15fLO8G+uGOyXa7QrMetQLEgtz2/Wcko1U/iavAK/74NFhygKfM1rUB6SRNQQ1TnVfFUZFFcSwRDmzhxLOIeVxBBARXyR+NM1ZHIer1ftImtL6l0p2ioB6w2sse6ecX80e/f5+5w/hEOUh28K904T0S2TchUTVkfWy1aflYrUGNHaTyRLz0h2xHjAdDxHuJJ08TF+rlHsPmoSqRhok+jDqeErYC2vsHozprdY+3H/UgOZx6lLYw7rUepUTJZCl4LYCJfVVu/VJFLEUCXMosjXxOSAqbxHeF50TTDvrZ5rLektZ+dnYCeWqIPqWyyKr7wy1Tb3+sS/WUOVR9cL/09xkpRVUxddmKnZMpj5V8TWYlPj0OANcgl4RRNA5bxQ+Dcz+HAyLP4qMagc5sqmQCa753bpJCuw7oYyR/ZX+pR/GgOGyDfMDBAmE2rWBRhjmbvaCFoKmQlXUlT30ZIOPQnYBYUBKDxkN9zzs6+G7HGpSidhpcNldOV0ZntoO+qi7dhxv/W5OiF+1IOuyAuMiRCIVC1W4ZkT2rgbCRsH2jvYMtW/knsOgkq1xfjBMHxBN8+zfq8t67louGZ85NJkfuRBJZHnY2nhrTQw/XUcOey+iUONCFJM9hDX1JtXqFntW12cM9vw2tvZAxa6ExqPQcsRxm6Bfrxnt49zGa7nqxXoPOWu5DijX6OjJLumW2kt7FowQTTBebY+eENhyExNEtFU1TQYGJqvXCvcx9zEG+gZwldmk+9P+otqxqXBknyXd5vyxO60KoenmCU4o3Zil2La4/mlpOhI68rvzDRp+T5+IgNtiHkNH5G+VXeYsdsZ3OHdhB2BHKAar5fEVLjQa8vAxx3B6zyQd7WygK5UKk7nCmSaYsxiJuIpYwwlAOfyqwcvXrPV+MY+BsNwCFkNW5HU1eWZM9urnX9eKF4m3QLbSliSlTZQ1QxSx1ZCCLzSd5wyjK4HaivmlCQU4nuhTyGPIrQkb6csao/u+bNF+I295wMpyGxNR5IYFj3ZXhwk3cOe8561XY/b0dkQ1adRdcygh47Carzct48yqK3N6d6mdeOoIcPhEGEM4jIj8ea2qiVuXbM6uBU9g0MbCHMNY5IH1n/ZsJxE3m5fJd8rXgZcRZm+FcsRzQ0pB8bCkH0vt45ylO3nqadmL2NU4aYgquCi4YcjiGZSKchuCvL0t929W4LESG2Nb1IkVmwZ6xyLnr8ffl9I3qYcpJnZ1mESGs1sSD3Cub0KN9nykO3U6YZmASNa4WJgX2BR4XLjM+X/KXmtgnK0d6d9MIKlyBwNa1ItlkJaDVz43rXfvN+NXu6c7toj1qiSXg2piHNC5j1sd/EynO3U6bsl6uM6YTjgLiAaITZi9CW+aTltRHJ6d3L8wsK/x/8NF9IkFkKaF1zMXtJf4R/4Xt8dI9pbVuFSlo3gSKbDFT2V+BPy9+3oKYWmLKMzoSmgFuA74NHiyiWQKQgtUbIHN0B80oJTB9bNNRHHlm1ZyZzGXtRf6t/J3zfdAtqAFwrSw84QCNgDRn3F+EGzIi4NqeWmBmNGYXTgGmA3YMVi9iV06OZtKjHa9xC8oIIfx6PMw1HY1gKZ5BynHrvfml/BnzgdC9qR1yTS5U44SMZDuX38OHnzGy5Fqhsmd+NyYVpgeCAMYREi+CVs6NRtDrH2tuQ8bQHmh2ZMg1GYFcKZptxuXklfr1+fnuAdPtpQFy6S+s4YyTEDrX44eLxzYi6PKmVmgKP3oZngsCB7YTUi0GW4aNKtP3GaNvs8OIGnxx8MdZEFla4ZEpwcnjzfKl9j3q/c21p6luhSw45xCRgD4j55uMhz9u7qaoQnIGQVojNgwmDD4bHjPyWXqSFtPPGGNtZ8A4GkBs5MGhDiFQUY51uyXZZeyx8OnmccoZoRltFS/84AiXqD1z6/uR10GK9WKzbnVuSMIqZhbqEl4cajhCYKqUCtRzH7NrX7zoFcBrTLsdBuFIiYZdsv3RbeUd6f3cYcUVnU1qnSrs4HCViEDD7J+bs0Ry/Sa70n4yUaozKh9GGhInOj32ZRabCtXrH5Npp72gEPxlNLfU/p1DjXjtqVnL4dv53YHU0b6tlEFnFSUM4EiXGEAD8XueC0wbBeLBYohOXAY9dikyJ1YvikUObr6fFtg3IAtsQ75kDARinK/Q9Wk5bXIpnkW81dFF13nLxbLljflehSJU34CQUEcz8o+g21R3D4rIEpe6Z85FRjSuMh45UlGGdaakLuNbIR9vN7tECtxbmKcg700uLWYdkc2wScUJy+29Qam9hnlU5R7E2iCRLEZH98ekF117FhrX2pxidPZWikGmPmpEil9afcKuUudXJs9uj7g8CZRULKHI5FEl4VjZh/miTbdVuumxUZ9BecFOORZc1CCRpEU7+SOvr2MfHX7grq4+g3JhNlASTCpVLmqCixK1huwvLSNyR7lcBCxQZJvY2IUYjU5pdNmW8aQxrHGn/Y9xb9VChQ0Y0XyNuEQH/pOzo2lXKa7uerk+kzZxQmPuW1JjNnb2lZLBvvXbMBd2a7qoArBITJFg0/UKST7dZHWGPZepmJWVSYJZYME5yQcAyjSJYEaj/BO733ATNpr5MslWoC6GnnEib9pykoSupTrO+vxjO7N2+7goASxH7IZkxqz/HS49VuVwQYXJi2WBRXABVIUsDPwMxkiEmEUEAZu8X39LPDcIztp2slKVNoeifbaHOpeisgbZNwu/P+9797nj/6Q/UH70uMDzHRyhRDVhDXKpdOVz+Vx1Ry0dUPBIvbSDYEMwAx/BE4bvSnMVMuiKxYqpAptikNaZIqvGw+rkaxfrRNeBa7/T+iQ6hHcgrjziVQ4ZMHlMsV5NYS1deU+9MMERoOe0sHx9tEEcBJvJ847zVT8mWvuG1cq95qxOqSasOr0S1t70kyDnUl+HU74L+LQ1lG7woyzQ1P6xH703RUTRTEVJzTnlIUkBBNpQqqR3kD7EBgPO85dHYI80Kw9S6vrT2sJavprAdtNy5tcFpy6vWIuNs8CH+1gsiGZ0l6DCsOqBChkg0TJBNkkxCSb9DNDzfMgooCRw9DwgC0/QB6PjbE9Gmx/i/Q7qwtlq1R7Zvube+8sXnzk7Z1eQi8dT9hwraFm8i6yz/NWU96EJdRq1H0EbPQ8Q+2TdGL08lQhp4DkwCHfZK6i3fHdVlzEjF+r+kvFu7KbwCv9DDasqb0iDcsOb28Zr9QQmSFDQf1ygwMQI4GD1PQI5B0UAePo05RTN4K2UiVBiVDXsCXveT7G3iOtlB0b7K4MXLwpXBRMLRxCTJGs+C1iHfsejo8nb9BghKEvAbsCRGLHoyHjcPOjs7mTozOB00ei54J08fQBaTDJQCkvjZ7rTlad041lbQ7sshyQLIlsjWyq/O/tOa2k3i2Or582f92QYGEKcYeyBFJ9Ms/TCkM7Y0LzQUMnkufSlIIw4cBxR0C5gCufka8f/opOFD2wrWINKgz5zOGM8O0WvUFNng3qLlI+0n9W/9uQXIDVsVOhwxIhMnvCoTLQguly3FK6UoUSTtHqQYqxE3CoUC0fpU80vs6eVf4Nbbb9hD1l7VxdVy11XaVd5R4x/pkO9y9o39qQSSCxAS8xcPHT0hXyRhJjQn1iZNJaYi+h5oGhUVLQ/eCFsC2PuF9ZTvMuqG5bXh194D3ULcl9z+3Wjgv+Po58DsHvLZ98L9qwNnCckOqRPjF1cb7R2UH0Eg8x+vHoEcfhm+FWMRjwxpBxoCzfyq99jye+616qDnUuXb40LjieOs5J7mTumj7IPwzPRc+Q/+vwJJB4kLYQ+yEmcVaxeyGDUZ9BjyFzsW3xPzEJAN0gnYBcIBsP3B+RP2wvLm75Tt2+vF6ljqlep36/Ps/O5+8WX0l/f6+nP+5gE6BVQIHQuBDXEP3hDBERYS3REbEdkPIw4KDKAJ+gYtBFIBf/7I+0P5AvcW9YvzavK78X/xtfFY8mHzxPR09mL4fPqx/O/+IgE7AysF4gZVCHsJTQrHCuoKtgowCmAJTwgHB5YFBwRqAssAOP+9/WT8N/s++n/5/Pi3+LD44/hL+eP5o/qD+3j8e/2B/oH/cwBQARICswIxA4kDvAPKA7YDgwM3A9YCZwLvAXUB/QCPAC0A3f+e/3T/Xv9c/2z/iv+0/+X/FwBIAHMAkgCjAKMAjwBmACkA2v96/wz/lv4b/qP9M/3Q/IL8Tfw2/EH8cfzG/EH94P2f/nr/agBpAW8CcwNqBEsFDgaqBhcHTgdMBwwHjgbUBd8EtwNhAugAV/+5/Rv8i/oW+cv3tPbf9VP1GPUz9ab1cfaQ9/34rvqa/LD+4gAfA1UFcgdlCRoLhQyVDUEOgQ5ODqkNkgwPCyoJ8AZwBL0B6/4P/EH5l/Yn9AbySPD77i7u6e0y7grvbPBR8qz0bveC+tH9QgG8BCMIWgtIDtMQ5xJvFF4VqRVLFUMUlxJREIANOAqRBqYClv5/+oH2vfJR71rs8eks6BvnyeY753PoaOoO7VPwIPRZ+N78jAFABtUKJQ8PE3EWLxkyG2ccwRw7HNUamRiUFdsRig3BCKIDWP4I+d3zAO+Z6szmt+N34R7gvN9U4ObhaeTM5/bryfAi9tj7vwGqB2oN0hK3F+8bWh/YIVUjwiMYI1ohkh7UGjkW5RD+CrEEMf6s91fxZOsD5l/hnt3h2j/ZyNiC2Wvbdt6P4pjnbO3f88D62wH4COEPXRY7HEkhYCVcKCQqpirdKcsnfiQMIJYaRRRHDdIFIP5r9vDu6ueR4RjcrNdx1IPS9NHL0gXVk9hc3T3jCuqR8Zj54AEqCjYSxBmYIHsmPiu4Ls0waDGEMCQuVyo4Je4epheZDwIHJv5H9avsl+RJ3fzW5NErzu/LRcs1zLvOxtI42OreqeY872D4zwFAC2oUBR3LJIEr7jDnNEo3AjgHN140FzBTKjwjBhvxEUEIQv5A9Inqa+Es2Q/STMwUyInFwcTGxZLIE80n06LaS+Ph7Bv3qAE5DHoWHCDRKFUwbDbkOpc9bz5hPXQ6uzVZL30nYh5NFI0JdP5W84zoad4+1VPN6cYywla/br6Dv5DCgMcuzmnW89+E6sn1bAEUDWUYByOmLPY0tDuqQK5DqESMQ2FAPDtENKwrtSGrFuQKuv6J8rPmlNuC0c7IvsGJvFy5ULhyubq8EsJSyUXSptwm6G30HAHSDSsaxiVIMF85wkA0RotJqUqCSR9GlkAQOcUv/SQIGUQME//a8QHl7Nj7zYLEz7wet5+zbrKYsxW3zryXxDfOZdnL5QnzuQByDskbVii1M409kUV/SydPbFA/T6lLw0W4PcUzNShhG6wNgP9J8XbjddaqynPAIbj2sSSuy6z5raaxuLcCwEbKNdZ0457xRAD1DkAdtSrpNn1BHUqFUH9U7FW+VPxQwEo5Qqc3XCu0HRkP/v/U8BPiLtSTx6O8trMTrfCobqecqHKs1rKXu3TGGdMm4S7wvv9cD5Ae4izjOSxFZE5CVY9ZJlv5WRBWh0+NRmg7bC79H4oQiwB88NjgGtK2xBW5k697qAakWaKEo36nLK5at8XCFNDi3rzuKP+mD7cf3S6hPJhIY1K0WVFeFGDtXuNaE1SxSgQ/ZDE7Iv0RKAFA8MXfOdAXwsy1uqsxpGyfk522ns6ivalQsz6/Ks2s3ErthP7UD7UgozAhP75LFVbWXcNismSUY29fYlihTnZCPzRqJG8T0wEf8Nrejc62v8qyL6g3oCSbHpk2mmaekKV9r+G7XsqF2tnr0/3oD4whNjJjQZxOelmmYeBm/WjrZ7FjblxYUrxF+zaHJt4UigIY8BjeFc2VvRCw8qSSnDKX/pQJlkuap6Hjq7O4tMdy2GzqF/3hDzoikzNkQzBRjVwgZaVq8Wzua6RnM2DSVdFIlDmQKEkWSwMs8H3d0su0u6GtCKJEmZqTN5ExkoCWBp6IqLe1LcV01gXpUfzCD8EiuzQkRXpTTl9CaBBuinCab0ZrrmMNWbNLBzyCKqwXFQRX8ArdxMoVun6rcZ9Oll2QzY2zjgqTsZpvpfCyzsKO1Kbng/uKDyEjrzWiRndVumEKax5xxXPqcpFu3GYFXF5OUj5bLAUZ5gSa8L3c7Mm4uKepMJ20k3+NwYqRi+qPq5eaomKwmcDD0lLmsPo8D1sjbTbeRydX0GN2bcxzoXbddYRxuWm2Xs9QcEAXLlMavAXy8JfcSMmctx6oRZt4kQGLFojOiCSN+JQNoA+ukr4W0Qvl2PnaDm8j9jbYSIpYj2WEbxh2GXlveBx0QmwdYQNTYEK1L5MblQZf8ZXc2cjDtuOmspmZj+eI0IVthruKmZLLnfururyIz9Pj/vhjDl4jTDeQSZ1Z9mYycQF4LnueelZ2dW45Y/hUH0QyMcMccAff8bfcncgttvald5gajjCH74NwhLKIk5DXmyeqFbsdzqziI/jaDSsjbjcGSmNaBWiBcoV523xofC94T3AGZapWqkWLMuAdSghw8vzclMjXtVillZf8jN+FdILZggmH5o4ympeopLnWzJnhSvdBDdUiXjc7Stpaumhvc6R6In7MfaZ5znGCZhhYAEe/M+keIQkR82LdvcjDtQelDJc/jPOEYoGpgcSFlY3fmEynari3y5vgdPaZDGAiHTcwSgRbF2n8c1x7/37Ifrl68HKrZz9ZHUjKNNwf9Qm/8+fdFsnutQSl25bii26EuoDhgOOEoozgl0imarfAyrTfpPXlC8shrDblSeFaHGkodK57c39cf2d7tXN/aB5aAEmsNbYgwQp69IrenslYtk2lA5fni1CEeoCCgGiEDYw3l46lpLb0yefe2/QlCxkhDDZcSXJayWjzc5h7fn+Gf7B7GXT9aLNaqEliNnYhhgs/9UrfVMoAt+KlgZdLjJmEpICNgFKE2Ivklh+lG7ZUyTXeG/RcCkwgQDWWSLhZIGhecx17H39Gf5J7HnQlafxaEkrqNhkiQQwL9iTgNsvjt8GmVZgQjUeFOIEBgaSEBIzplvyk0LXjyKDdZ/OMCWUfSTSWR7RYIWdrcjx6V36efg17wXP0aPlaPUpDN54i7wzf9hfhQcwAueinfpkyjlqGNILegVyFkYxGlyalxbWiyCvdv/K2CGceKjNcRmlXzmUacfd4J32MfSF6BHNraKhaKUpsNwQjkA229yDidc1Wulap+pqxj9GHmIMlg3uGf437l52l+rWSyNXcJvLdB1Qd4zHrRNlVKWRtb053kHsRfNB45nGJZwpa00ljN0kjIQ6Q+D3jzs7huwirx5yLkaqJYoXShP+Hzo4KmWOmcLa0yKLcnfECBy0ceDBGQwVUNWJnbUV1k3kwehl3Z3BOZh1ZPUknN2sjoQ5r+W3kS9Cgvf2s456+k+SLkYfnhuiJfJBxmnanKLcKyZHcJvEoBvUa6i5uQfFR818Ia9xyMnfqd/90iG67ZOJXZEi4NmkjDg9E+q3l6dGQvzGvSqFHlnyOI4pfiTSMipIwnNmoIriTyaXcxPBQBa4ZPS1nP55PZl1VaBZwb3Q/dYFyTGzQYllWSEcUNkMjZg8a+/vmpdOuwaKx+6MkmW+RFo07jOKO9pRGnomqXrlRyt/cdvB9BFoYcisyPRBNkVpPZfZsTXEzcqNvsmmPYIJU60U8NfYiqQ/r+1ToftX5w02086ZSnLqUZpB2j/CRvpeyoIas3LpFyz/dPvCvA/sWjCnTOklKeFf6YYBpz23JbmZsvGb4XV9STEQuNIMi1A+1/LfpcNdsxi+3LqrNn1yYEpQPk1uV4Jpzo9CunLxtzMbdH/DpApQVjidMOE1HHVRZXrVl92kCa85obmMOW/BPa0LrMugh6A92/SLredkFyUS6qK2So0+cFZgDlyCZWp6GpmSxnb7KzXTeGPAtAicUeyWiNR9Eg1BwWpphymXiZtxkyV/RVzZNSkBzMSYh4Q8t/pHsltvBy4q9X7Gep5GgbJxOmz2dKqLrqUK038Bdz0vfLPB8AbYSVCPWMsJAsExDVjJdSmFtYpRgz1tGVDRK6T3HLzsgwA/Y/gPuxd2czvzAT7Xtqx2lE6Hsn6+hTKadrWi3X8Mj0UngWvDYAEQRHiHsLzs9pkjUUYJYfFynXfpbhVdtUOtGSjvmLSgfhA91/3bvA+CU0ZjEc7l5sPCpB6bapHGmvqqcsdS6HcYe03DhpPBCANIP2h7nLIw5aUQqTY5TZFeSWBBX7VJKTF1DbTjSK+0dLA8CAOfwTOKk1FnIx71AtQSvQqsUqoGre6/jtYO+F8lL1cDiC/G8/2IOjBzLKbo1/j9ISFpOB1I1U9xRCk7fR40/VjWLKYoctw6AAFTyn+TL1zvMSMI9ule0wbCUr9mwgbRvunPCS8yq1zfkjvFH//cMNRqbJskxaTsyQ+tIaEySTWFM4kgxQ347BTIUJ/8aJg7tALzz+OYD2zvQ8MZqv+G5frZXtXW2zLk+v6HGuM862tXlLvLk/pML2hdaI7strjbuPUZDjkawR6RGd0NCPjI3fi5sJE0Zdw1GARz1VelL3lTUvMvExJ+/dLxYu1K8Vr9MxArLWtP53Jvn7PKU/jcKfBUNIJcp0jGAOHA9fUCSQapAzj0XOa0ywiqXIXQXqgyMAXP2s+ue4YPYp9BFyozFn8KRwWnCHMWUyavPL9fk34bpx/NY/uUIHxO1HF4l2SztMm43Ojo/O3c67De0M/Et1CaVHncVwAu+Ab/3D+765MTcrdXpz6LL+cj+x7bIGcsSz3/UNdv74pbrwPQx/qAHxBBXGRYhyCc6LUUxyzO7NBE01TEcLgQptyJpG1UTuQraAf74Z/Ba6BLhyNqp1dzRfM+YzjPPSNHC1IXZaN885srt1vUg/mgGbw72FcMcpCJtJ/sqNS0MLn0tjytUKOgjbx4WGBARlQngAS76ufK762rl9N+C2zXYI9Za1dzVpNeg2rfexeOj6R/wCPcl/kAFIQyUEmgYcR2KIZUkfiY4J8EmHyViIqEe/RmcFKkOVAjPAU/7AvUb78fpLOVu4abe6Nw+3KvcKN6m4BHkSegu7ZbyVvhB/igE3gk3DwoUNBiXGxoerB9EIOIfiR5JHDQZZxUAESMM+AaoAV78P/d28iXubOpn5yvlxeM/45njzuTR5o/p8ezb8Cv1wPl0/iIDpwfgC60P8hKYFY0XxRg3GeUY1BcPFqYTrxBDDX8JgQVqAVr9b/nI9YDyr+9p7b3rtepX6qLqkesZ7S3vuPGm9N33RPu+/i8CfgWSCFQLrw2UD/YQzhEXEtIRBRG4D/oN2QtpCb8G8QMVAUP+kPsQ+db28fRu81fysvF/8b/xa/J78+b0m/aO+Kv64fwe/1ABZgNSBQMHcAiPCVoKzQroCq0KIQpMCTUI6gZ1BeUDRwKpABj/n/1J/CH7LPpy+fT4tPiy+On4Vvny+bX6lvuN/JH9l/6W/4YAYQEgAr8COgOPA78DygOzA34DMAPNAl0C5QFqAfQAhgAmANf/mv9x/13/Xf9u/43/uP/p/xsATAB2AJQApACiAIwAYgAjANP/cf8D/4v+Ef6Z/Sr9yfx9/Er8NvxE/Hf8z/xN/e79sP6N/38AfwGFAogDfQRdBR0GtQYdB1AHSQcEB4EGwgXJBJwDQwLIADX/lv35+2r6+fix96D20PVK9Rb1OfWz9YX2q/ce+dX6xfze/hEBTwOEBZ4HjAk8C58MqA1LDoEORQ6WDXUM6gr+CL0GOASBAa7+0/sG+WD29vPd8Sfw5e4j7urtP+4i74/wf/Lj9Kz3xvoa/o0BBgVpCJsLgg4EEQ0TiRRrFagVOxUlFGwSGhA+De0JPwZQAj7+KPou9nDyDe8h7MXpDugM58vmTueV6JnqTu2f8Hf0t/hB/fEBpAY0C30PXROyFmIZVBt3HL4cJRyuGmAYSxWFESgNVggzA+b9l/hx853uQuqC5n/jUeEN4L/fbOAT4qnkHehX7DfxmfZV/D4CJwjiDUATGBhBHJgfAiJpI74j/SIpIUseehrOFWwQewooBKX9IvfT8OvqmOUG4Vrds9oq2czYn9mh28Pe8eIN6PDtbvRX+3MCjglwEOEWrxyrIasljig7KqIqvSmRJyokoR8XGrUTrAwvBXv9yfVV7lznE+Gv21vXO9Rp0vjR7dJE1e3Yz93G46XqOPJH+pEC2QrdEl4aICHsJpUr8i7oMGQxYDDgLfYpvSRcHgEX5g5HBmj9jPT56/LjuNyD1ofR7M3Ry0rLXMwDzy3Tu9iF31nn+u8n+ZkCBwwoFbMdZiUCLFExKjVqN/433zYSNKovyCmXIkwaJxFuB2z9bfPA6bHgiNiG0ePLzcdnxcXE8cXiyIbNutNQ2xDktu3694oCGA1PF98gfinmMNw2Lzu8PWs+NT0gOkI1vy7GJpMdbROiCIX9a/Ks55vdiNS7zHPG4sEvv3K+sb/owv7H0M4p18zgbuu/9mYCCg5QGeAjZS2WNTA8/kDXQ6VEXEMGQLg6mzPjKtMgthXjCbT9iPG+5bHautAnyDzBMbwwuVO4o7kYvZvCAcoV05HdJul59SwC3g4rG7ImGTEOOklBkUa5SaZKUEm9RQhAWjjtLggk/xctC/j9w/D34/bXIc3Mw0G8vrZus3CyzLN6t2C9VMUYz2Pa3uYq9N8BlA/eHFUplzRLPiRG40taT2pQCk9CSyxF9jzdMi8nRBqADE/+HPBX4mzVv8muv4e3jbHvrcysL64RslS4y8A1y0TXm+TT8n4BLBBpHscr3DdJQrxK8lC3VO1Vh1SOUB9KakGxNkQqhBzaDbn+k+/h4BPTmMbQuxGzoqy1qG2n1KjirHqza7xxxzjUX+J38QwBphDLHwYu5joGRg9PuFXLWShbwFmeVd5OtEVkOkUtvB45DzT/KO+T3+7QrMM1uOOuAqjHo1aivaPzp9iuObjQw0PRLOAX8IgAAxEFIREwsz1/SRhTMlqTXhhgs15sWmNTzUnzPS4w6SCaEL//2u5u3v3O/cDftACrr6Mnn46d8J5Ho3GqObRVwGfOBd617vb/QhEUIugxQkCyTNVWXF4KY7hkWWP1XqtXtE1aQfwyCSP8EVgAqO5z3UDNjr7QsWqnrp/bmhaZcZrjnkmmbrADvajL7dtU7Vb/ZhH7IoozkUKcT0NaM2IsZwVpsGczY7FbYlGVRKs1GCVcE/8Aku6h3LrLX7wLrySkAZzklvSURJbKmmai3azfuQrJ59n166n+bxG4I/U0n0Q8UmBdtWX2avxss2skZ3Ff1VShRzk4FSe4FLIBl+7422nKcrqQrDChrJhGkyuRbZICl8qeiKnsto7G9deb6vH9XRFNJCs2bEaQVCpg3mhmbpdwXm/DauhiClh6SqI6+ygPFm8Cte5420/Jx7hiqpGesJUFkL6N7o6Nk3mbdaYttDjEGtZJ6S/9MxG5JCo39UeXVp9irGt5cdVzr3INbhJm/FoeTeM8yipdFzQD7O4g22vIX7eCqEecD5Mija+Ky4tvkHaYpaOmsQzCWdT/52f88BD+JPM3O0lRWL1kHm4rdLR2o3X/cO1oqF2IT/o+fiyiGAAEOu/u2r3HO7bwplWazJCgigKICImqjcWVHaFZrwvAs9LB5pj7lxAcJYY4Pkq7WYNmMnB8di95NniWc3RrDGC3UeRAFC7ZGdAEnu/k2kXHWbWtpbuY6I6BiLmFpYZBi2mT3p5IrTm+LdGQ5cb6KRAUJeQ4/krWWvBn5nFpeEZ7Z3rQdaVtJWKoU55Ciy8CG6QFFvD+2gHHu7S6pHqXZI3GhtSDp4Q3iWOR7Jx4q5i8x89w5PL5pw/oJA05e0uiWwRpOXPxefd8M3yqd39v8GNXVSVE3zAaHHgGoPA82/LGX7QWpJOWQYxxhVeCDYOOh7aPSJvqqSq7hM5h4x75FA+YJAM5tksfXL9pLHQTe0B+mX0ief5wa2XEVnhFDzIfHUsHPPGd2xXHRrTAowWWgIuChEOB24FHhmWO9pmgqPO5Z81m4kz4cA4mJMY4r0tNXCBqvHTPeyB/l343eiFylGbqV5RGGTMQHhsI5/Ef3GvHbbS5o9GVIIv6g5eAEYFkhXCN9pidp/O4ccyB4X73vg2VI1g4Z0stXChq63QjfJd/LX/neudyamfKWHhH+jPpHucIoPLA3PHH1bQApPWVIYvZg1WAr4DnhNqMS5jipiy4pcu04Lb2/wzkIro34ErAW9hpuXQRfKV/Wn8ye05z6mdgWSFIsTSpH6wJZfN/3abIe7WTpHGWhIsfhHyAt4DPhKOM9pdwpqG3BMsB4PX1NQwXIu82G0oHWzBpJ3SYe0h/HX8Xe1VzFGitWY1IPDVPIGgKM/Ra3ojJXrZxpUWXRozLhA2BKYEdhcuM95dKplO3kMpp3z71YwsvIfc1GkkEWjFoNXO5eoN+d36Vevxy52etWb1ImTXYIBoLCfVP35XKfLeZpm6YaI3dhQeCBILShVSNUJhvpkO3Ssrv3pL0igouINU030e4WN9m5HF1eVV9aH2teUNyY2diWa1IxzVCIb8L5fVc4MzL1LgIqOqZ545Th2mDR4Pthj6OAZnhpnK3NMqU3vPzrAkWH4oza0YmVzllOHDNd7978XtgeClxhmbJWF5IxDWOIVYMxfZ+4SnNY7q9qbmbwZAriTKF8oRtiIiPCZqgp+K3T8pZ3mTzygjpHRoywURPVUJjMG7EdcR5EnqtdrBvUWXjV85HkDW3Id4Mp/e14qzOJ7y2q9ed9ZJli1+HA4dSijGRaputqJK4nMpA3uXy6AepHIYw5EI2U/1g0Gtbc2V3z3eXdNdtxWOwVv5GKjW/IVQNifj941HQHb7vrUKggJX8jfCJeYmZjDmTIp0HqoK5HMtK3njyBwdZG9Au1UDdUG1eGmmVcKN0J3UecqBr4mEwVe1FkTSjIbcNaflV5RbSQ8BmsPeiYJjwkOGMUYxDj56VMJ+tq7W6z8t53h/yKAb7GfwsmD5JTpNbEmZ0bYJxHnJFbw1pqV9iU5pEwzNiIQYORvq55vnTlsIYs/SlkZs9lDGQio9Lkl+Yk6GhrSi8t8zM3tvxTgWQGAsrMDx6S3NYuWL8aQVut24NbB9mG11JUQZDwjL8ID8OHfsp6PfVFMUCtjWpEZ/hl9yTIJOxlXqbS6Tfr9y90s1F367xewQcFwEpnzl1SBFVE18vZi1q82p6aNhiOlrlTjJBjTFwIGAO7Pug6QzYuMchubes26LWm9+XEZdymeyeVadostC/Ic/l35jxrwOhFeEm6DY9RXBRJVsRYgBm1maNZDpfCFc4TB8/JDC9H2oOs/wf6zjagMpxvHew7aYboDacWZuKnbSir6o6tQPCpNCr4Jvx7gIhFKwkEDTWQZRN8VamXYBhY2JLYElbh1NCScw8hy7jHloObv2h7HXcac3vv2+0QaurpN6g9Z/2oc6mV65TuHTEW9KZ4bjxOQKdEmYiGDFCPoBJfFLyWLFcn122WwdXuU8GRjw6tyziHTAOHf4l7sPeb9CXw5241a+CqdOl4aSzpjirSrKxuyPHRNSu4u/xkAEZEREgBC6HOjlFyk35U5hXjFjRVndSoUuGQm83tCq5HOsNv/6p7x7hj9Nlx/y8pLScrg+rGaq9q+2vhrZTvw3KYNbq40Ly9gCWD7Ed2CqnNsNA4EjATjlSMFOjUZ1NQkfFPmk0gChpG4sNUf8q8YPjxtZWy4nBqbnzs5CwmK8Qseq0B7s0wzDNrNhN5bDybAAXDkgblyemMiI8wUNMSZhMkE0tTH1IoELEOikxHCbzGQ4N0/+m8u/lEdplzz7G4L6DuU+2WbWntiy6yr9Tx4vQKNvX5jvz9P+eDNgYRCSJLlo3cz6gQ7tGr0d1RhtDvT2HNrMtiCNWGHUMQQAc9GHoa92P0xfLRMRIv0i8Wbt+vK2/y8StyxvU092H6OPzjv8sC2YW4yBUKnAy+zjEPadAkkGAQHs9njgSMgoqxyCTFr8LngCJ9dTq0eDP1xDQ0Mk8xXbCkcGQwmvFBso+0N7XquBc6qf0O//ECfMTeB0KJmktXTO6N2E6QDtSOqI3RzNmLS4m2h2sFOwK5wDs9kbtQeQh3CTVfs9Zy9PI/MfZyF/LeM8D1dHbrONV7Ij1/P5nCIIRBRqwIUkony2KMe4zvDTxM5QxvC2JKCUixBqhEv0JHAFD+LXvtueC4E7aS9Wb0VrPls5Sz4XRHNX42fHf1uZx7oX20v4XBxUPjhZKHRUjxSc4K1QtDi5hLVcrASh9I+8dhhd0EPIIOwGM+R/yLevs5IvfMNv81wXWWNX21djX7doZ3zvkKOqv8J73vv7VBbAMFxPcGNId1iHJJJkmOiepJu8kGyJGHpEZIhQlDssHRAHF+n/0o+5d6dTkKeF33s/cPdzA3FPe5+Bj5Kzone0O89P4wP6kBFQKow9qFIUY1RtFHsIfRiDOH2IeDxzqGA4VnBC3C4gGNwHu+9b2FfLP7SXqMOcF5bLjPuOr4/HkBOfR6UDtM/GL9SP62f6EAwQINQz4DzETyRWvF9YYOBnWGLUX4RVsE2oQ9gwsCSsFEwEF/R75fvVA8nnvP+2h66fqV+qw6qzrQO1f7/Px6PQl+I77CP93AsMF0QiKC9wNtw8OEdkRFhLGEe4Qlw/QDagLMgmEBrQD2AAI/lj73fiq9s30U/NF8qnxgPHJ8X7ylvMH9cP2ufjZ+hH9Tv9+AZEDeAUlB4sIpAlnCtMK5wqlChIKNwkcCMwGVQXDAyQChgD3/oH9L/wK+xr6Zfns+LL4tPjw+GH5AfrG+qr7o/yn/az+q/+ZAHIBLwLLAkIDlAPBA8kDrwN4AygDxAJTAtoBYAHqAH4AHgDR/5b/b/9d/17/cP+R/7z/7f8fAFAAeQCWAKQAoQCJAF0AHQDL/2j/+f6B/gf+kP0h/cL8d/xH/Db8R/x9/Nj8Wf39/cL+of+UAJUBmwKdA5EEbgUrBr8GJAdSB0UH+wZzBq8FsQSBAyUCpwAT/3P91/tK+tz4mPeM9sL1Q/UW9UD1wvWb9sf3QPn9+vD8DP9BAX4DsgXJB7IJXAu5DLkNVA6ADjsOgg1YDMUK0QiKBgAERgFx/pb7zPgq9sbztPEI8NDuGe7s7UzuO++08K3yG/Xs9wv7Y/7XAU8FsAjdC7wONREyE6IUdhWlFSoVBxRAEuIP+wyiCe0F+gHn/dL52/Uk8sru6eua6fLnAOfO5mLnuejN6o/t7fDO9Bb5pP1VAgcHkwvUD6kT8haTGXQbhRy6HA4chBolGAEVLRHFDOsHwgJ0/Sf4B/M77uvpO+ZI4y3h/d/D34bgQeLr5HDoueyl8RH30vy8AqMIWA6tE3gYkBzVHyoieiO5I+Ei9SADHh4aYhXyD/cJngMZ/Zn2UfBz6i7lruAX3YfaFtnS2L/Z2dsT31bjg+h17v707fsLAyQK/hBkFyIdCiL0Jb4oUCqcKpspVCfUIzQflxklEw8MjATW/Cb1u+3O5pfgSNsM1wfUUtL/0RLThtVK2UTeUORA6+Dy9vpDA4gLgxP2GqYhXCfqKyovATFdMTkwmi2TKUAkxx1bFjIOiwWq/NHzR+tP4yncDNYs0bDNtstRy4XMTc+W00DZI+AK6Lrw7/ljA84M5RVhHv4lgCyyMWo1hzf3N7M2wzM7Lzsp8CGRGVwQmgaV/Jry+Oj53+fX/9B8y4nHSMXNxB7GNcn7zU/UANzW5Izu2fhtA/YNIhiiISkqdDFJN3c73T1kPgU9yTnHNCIuDCbDHIwStweX/ILxzebP3NTTJcwAxpbBDL95vuO/QsN/yHPP69em4VrstvdfA/8OORq2JCIuMzapPE5B/UOeRClDpz8yOvAyGSrvH8AU4Qiv/IjwyuTR2fTPgse9wN27CblauNi5er0nw7PK6NN/3ibqhvY9A+oPKRycJ+gxujrOQelG4kmgShlJWEV3P6E3ES4RI/MWFgrd/K3v7eID10rMGMO3u2G2QrN2sgS04rf3vRPG+89j2/PnTPUFA7UQ8R1SKnY1Bj+0RkRMiE9lUNFO1kqRRDA88jEmJiUZVAsf/fHuOuFl1NjI7L7ytiixvq3RrGqugLL0uJfBKMxW2MPlCfS5AmERkB/WLMw4EkNYS1tR6lToVUtUHFB7SZhAtzUrKVMbmgx0/VTusN/70aDFALtxsjWsgKhwpxGpVq0jtEO9csha1ZnjwPJaAu8RBSEnL+Y73Ua1TylWA1olW4NZJ1UxTtZEXDkcLHkd5g3c/dXtUN7Ez6TCWLc4ro2njaNZovyjbKiIrxy53sR00nfhcvHpAV4SUSJEMcI+Y0rJU6pa0F4XYHNe8FmvUuZI3jz2LpYfNg9V/nXtGt3Czee/9bNKqjOj6J6OnTCfxKMpqya1b8Gnz2DfIfBoAbASciMqM2BBok2QV9xeS2O5ZBljdV7wVsJMOUC2MaYhhxDe/jLtDtz2y2q92rCqpiqfl5oVmbKaZJ8Ip2SxKb71zFfd0O7YAOQSaCTbNL1DmFAIW7ticmcIaW9nsGLwWmhQakNYNKcj2BF2/w3tLdthyi67Ca5ao3abm5bxlIaWT5sqo9utD7tiyl7bgO05APwSNCVVNtdFQ1MvXkRmQmsAbXFrnmarXtRTbEbaNpclJxMZAAPtddoDyTS5hKtdoBmY+ZIlka6SiZeTn46qJbjyx3nZM+yQ//gS1iWXN7BHolUBYXRptm6fcB1vO2odYgFXPUk5OXIncRTJABTt6Nndx363TKm2nRaVs4+1jS+PFpRGnICnbrWmxanX7Orb/toSTyaiOERJs1d+Y0lszXHfc25yg21DZe5Z2UtyOzYptBWCAT7thNntxgu2Yqdkm3CSy4ykigyM+ZBHmbak7rKBw/HVreke/qMSnyZ2OZRKdVmkZcFuhHTAdmJ1dHAaaJVcPU6BPeEq7xZEAoLtSNk1xt20yKVrmSeQRYr0h0eJNY6ZljGiprCIwVTUeOhZ/VQSxyYSOqBL6FpxZ9pw2XY+efd3CnOfavZeZ1BkP3AsHhgLA9ztNNm0xfOzfaTKlz2OIoioheSGzYs+lPafm668v9TST+eP/O4RyCZ5OmhMClzlaJNyynhYeyl6RHXPbAxhVFIZQeEtQBnXA03uRtloxU6zg6ODlrSMY4bBg+SEw4k5kgaezqwfvnPRNObC+3MRoiapOuxM3Fz+aexzVnoMffd7HneobtViAFSdQjEvUxqlBNHuftlTxeyy2aKWlY2LCoVBgkmDGYiNkGScQqu1vDTQKuXz+uUQWCalOixNXl2+auJ0fHtYfl99mHgncE9ka1XtQ14wVBt0BWjv2tlxxc2yfqIElceKGIQqgRSC0YY7jxKb+ql/uxrPMuQl+kYQ6yVsOilNkV0ja3d1O3w7f19+rnlLcXllkVYIRWUxQhxCBhDwWNrDxfGydKLMlGSKjIN7gEiB7IVFjhKa9qh/uiXOT+NZ+ZYPXCUBOuVMdF0va6l1kny1f/d+YHoTck9mcVfrRUYyGh0MB8fw99pGxlWzt6LtlGKKaYM2gOSAbYWtjWWZOqi4uVnNguKR+NgOrSRmOWBMCl3hanp1gnzFfyd/rXp8ctJmCViVRv4y2x3RB4vxttv6xvqzSaNolcOKrINbgOmAUoVzjQ2ZxqcrubbMzuHP9w4O4COaOJxLUlw6aul0DHxrf+1+lXqGcv9mWFgFR4szgx6PCFvykdzdx920JqQ6loOLVoTqgFiBnYWZjQuZnKfauD/MNOEW9zoN9iKhN5tKT1s9afhzLnuofkl+F3oxctVmXVg4R+wzDx9ECTTzid3syP21TqVil6SMZoXhgTCCT4YejmCZvafGuPXLteBm9l0M8iF9Nl5JAlrqZ6ly7Hl8fT19Mnl8cVVmFlgtRx80fx/uCRT0md4lyle3v6bfmCKO24ZBg3CDZocDjwyaKqjvuNnLVODC9XoL1iAuNedHblhDZvxwRnjoe8l76XdncH5lg1flRiM00B+LCvr0wd+Iy+m4d6ivmv2Ps4gIhRiF4ohHkA6b4qhXue3LE+Ar9ZIKox+5MzlGk1ZKZPNuPXbvee55O3bzbk9kpFZdRvczAiAbC+P1/+AQzbK6c6rQnDKS7IozhyaHworrkWic6Kn/uTLM8d+k9KgJXB4eMlZEdlQCYpJs1HORd613KXQgbcpieVWVRZkzEyCaC872T+K8zq+8saw+n7+UhI3DiZiJBY3tkxmeOavnuqjM8d8t9L0IAx1hMEFCGFJuX9ppDnHRdAl1tXHvau9gAlSNRAozAiAIDLj3sOOK0Ny+Lq/4oaGXeJCzjG6MqY9Llh+g16wPvFDNFODJ89MHmhuDLvw/fU+PXM5m7G2xcQNy4W5jaL5ePlJFQ0kyzR9iDKD4H+V30jjB57H7pNaaxpMCkKOPrZIFmXqiwK53vSvOW+B48+0GJBqILIo9p0xqWXJjcmo0bp5urmt8ZTlcL1C9QVQxdB+oDIT5m+aA1L/D2bRCqFmea5eskzeTDpYZnCil9LAevznPxuA98wwGoxhyKu86mUkCVshfo2Zeat1qIGg8YmJZ1032Py0w9h7ZDGL6Ieii1m7GAbjLqymiY5uulyWXyZmEnyiocbMFwXrQV+EY8zIFGhdEKCw4WEZZUtVbgmIwZsNmOWSnXjpWNUvwPdIuUx7yDDj7runb2ELJXLuSr0Cmq58GnGqb251Eo3irNrYqw+7RDeIK82AEihUBJkc15UJ0TptXFF6wYVNi/F++WsNSTEisO0UtiR3zDAX8QOso2zjM5b6Ts5uqPqSuoASgQqJVpxWvQrmNxZTT6uIW85kD9hOrI0EyRj9XSiBTXVnhXJFdbFuEVgBPHkUrOYYrmhzbDMb81eyG3U3PmcLLtzavGamjpe2k+aa2q/2yk7wsyGzV7eM6894CYBJGIR4vfjsGRmZOYFTGV4JYjlb9UfRKrEFvNpUphBupDHv9a+7y333SdcY1vAy0N67hqiKq/qtjsC23JsAFy3bXFuV58zACyhDUHuIrkDeEQXRJIk9mUihTZVEsTaFG+T15M3MnSBpdDCH+APBp4sTVdMrNwBq5k7NjsJ+vS7FXtaK7+MMYzrDZZebT85IBNw9YHJAogTPXPExEqEnETIlN9EsVSAtCBzpLMCIl5hj1C7j+kfHp5CDZks6OxVq+Krkktl+13baQulnACMhh0Rjc2udJ9AMBqA3VGSslVS8DOPU+90PlRqpHQka8QjU92jXnLKIiXhdyCz3/HPNu543cy9J1ysfD9L4gvF27rrwIwE3FUszf1K/edOna9IYAIQxOF7ghDysMM3M5FD7OQI9BUkAlPSI4dDFPKfYfsRXTCrH/oPT26QbgHNd7z13J78RQwpTBu8K8xXzK09CP2HHhMuuH9RwAogrFFDketCb3LcozBDiFOj07KjpVN9gy2CyHJR4d4RMYChEAGvZ/7IrjgNue1BfPE8uxyP7H/siny+HPiNVv3F7kFe1Q9sb/LQk+ErIaSCLIKAEuzDEPNLs0zTNQMVotCyiQIR0a7RFBCV4AifcF7xTn89/X2e/UXdE7z5fOcs/E0XjVbdp84HPnGu8194T/xQe6DyYX0B2FIxsocitxLQ0uQy0cK6wnECNuHfUW1w9OCJYA6viF8aDqcOQj3+Daxtfq1VjVEtYP2Dzbft+y5K7qQPE1+Fb/awY9DZkTThkyHh8i+ySyJjknjya9JNMh6h0kGacToQ1AB7gAPfr+8yzu9Oh85OXgSd643D3c2NyB3ijht+QP6QzuhvNR+T//IAXKCg8QyRTTGBIcbh7XH0UguR85HtMbnhi1FDgQSwsXBsUAf/ts9rTxe+3e6fnm4OSf4z/jvuMW5TnnFeqP7Yzx6/WH+j3/5gNhCIoMQxBvE/kVzxflGDcZxRiVF7MVMRMkEKgM2AjUBLsAsPzO+DX1//FE7xftheua6ljqvurI62ntku8v8iv1bPjX+1L/vwIGBg4JwAsJDtkPJBHkERUSuRHWEHYPpQ12C/sISQZ3A5sAzf0h+6v4f/ap9DjzNPKh8YLx1PGR8rLzKvXr9uX4CPtB/X3/qwG8A54FRQemCLcJdArYCuQKnAoDCiEJAQiuBjQFoQMCAmQA1/5j/RT89PoJ+lj55fiw+Lf4+Pht+RD62Pq++7j8vP3C/r//rACDAT0C1gJLA5oDwwPIA6wDcgMgA7sCSQLQAVYB4QB1ABcAy/+S/23/XP9f/3L/lP/A//L/JABUAHwAmAClAJ8AhgBZABcAxP9g/+/+d/79/Yb9Gf27/HL8Rfw2/Er8g/zh/GX9Df7T/rT/qQCrAbECsgOkBH8FOQbKBioHUwdBB/IGZQacBZoEZQMGAoYA8P5R/bX7Kvq/+ID3efa09Tz1FvVH9dD1sfbk92P5JPsc/Tv/cQGuA+AF9AfYCX0L0gzKDVwOfw4wDm0NOwyfCqMIVgbHAwoBNP5a+5L49PWW843x6e+87hDu7u1b7lXv2fDd8lT1LPhR+6z+IQKZBfYIHQz1DmQRVxO6FIEVoRUZFecTExKpD7gMVgmbBaQBj/17+Yn12PGH7rLrcOnW5/Tm0+Z3597oAevR7TvxJvV1+Qf+ugJqB/ELKxD1EzEXwxmTG5IctBz2G1oa6he1FNQQYgx/B1ICAv24953y2u2W6fTlEuMK4e7fyt+h4HHiLuXE6BztFPKJ90/9OwMgCc4OGRTWGN4cECBQIoojsiPCIsAguR3BGfQUdw9zCRQDjvwQ9s/v/OnG5Fjg1txe2gXZ2tjg2RPcZN+84/vo++6P9YT8pAO5CowR5heUHWgiOybsKGMqkyp3KRUnfCPGHhUZkxJzC+kDMfyF9CLtQuYc4OLav9bV0z7SCNI508nVqdm73tzk3euJ86b79QM2DCgUjRsqIsknPCxgLxcxUzEPMFItLSnAIzIdsxV9Dc8E7PsX85fqruKb25jV1NB3zZ7LW8uxzJrPAtTI2cLgveh68bj6LgSUDaEWDR+VJv0sETKnNaE37TeFNnIzyS6rKEch0xiRD8YFv/vI8THoQ99H13zQGMtIxyzF18RPxovJdM7m1LLcneVj77n5TwTUDvUYYiLRKgAysze8O/o9WT7SPG85STSDLVEl8RuqEcsGqfuY8PDlBNwj05PLkMVNwe2+g74YwKDDA8ka0K/YguJH7a34WQT0DyIbiiXdLs42Hj2bQR9Ek0TyQkY/qDlCMkwpCR/IE98HqvuI79fj89gxz+DGQsCMu+W4ZbgRuuC9tsNpy73Ubt8p65P3TQT1ECcdhCizMmM7T0I+RwhKlUrfSO9E4j7lNjQtGCLnFf4IwvuX7ubhEdZ2y2jCMLsIthqzgLJAtE+4kb7WxuHQZdwK6W/2KwTVEQMfTStTNr0/QEehTLNPW1CTTmZK8kNmOwUxGyUFGCgK7vvG7R7gYdPzxy6+YLbHsJKt2qyprvOymLlnwh3Nadnt5kD18wOWErYg5C25OddD70u/URlV31ULVKZP00jDP7o0DiggGloLMPwV7YHe5NCrxDW61LHNq0+oeadSqc+t0LQfvnbJf9bV5Ar0qAM3Ez4iRjDiPK9HV1CVVjZaHVtAWatUgE31Q1I47yo1HJMMhPyE7A7dnc6gwX+2ka0dp1ejYKI/pOqoPrADuu/FqNPE4s/ySgO5E5sjczLOP0JLdVQeWwdfEGAvXnBZ9lH6R8c7ui1BHtEN7PwR7Mfbi8zUvg+zmKm7oq6elJ12n0ek5asWto3C6dC94I/x2gIcFM0kajR6Qo5OR1hXX4djtGTTYvBdMFbNSxY/bDBCIBIPZP2+66var8pJvOiv7qWrnliaGZn5muufy6deslK/Rc7D3k3wWgJhFNMlKTbkRJBRyFs9Y7NnBWkoZydiKVpqTztCAjM1IlQQ6/2I67rZDMkAugytlqLwmliW85TNltmb86PdrkO8vsvY3AzvywGIFK4msTcMR0ZU+F7NZodrAG0qaxJm313NUjNFeTUXJJURgf5w6/XYoMf6t3yqkJ+Ml7GSJZH2kheYYaCXq2K5WMn+2sztLwGSFF4nADnwSK9W02EEagBvoHDVbqxpTGH0VftHzTfnJdISJP9z61rYbcY4tjqo35yDlGaPs413j6aUGZ2QqLS2Fsc52ZHshwCBFOMnFzqPSspYWGTfbBty43MncvNsb2TbWJBK/TmhJwoU0v+S6+rXcsW7tEemhprWkXuMn4pTjIqRHZrLpTq0+sSL113r1f9VFD4o9jrpS5VahWZdb9d0xnYcdeNvQ2d+W+5MBDxDKTsViADL66TXsMSDs6SkhZiHj/CJ7YeOiceOcpdLo/ixCMP21TDqGv8PFHAonDv+TA9cWWh8cTB3R3mxd3hyxWnaXRJP4T3KKmIWRgEc7IfXJsSRslKj3paYjcmHnoUph1+MGZUTofKvQsF91A/pWP6yE3koCjzOTTld02k7cyV5ZHvkebJ09GvtX/tQkD80LH0XCwKF7JHX08PksVGikZUKjAaGtIMnhVWKFZMmnyiuqr8i0/vnkv0/E1soQjxYThJe82qYdLV6Gn20e412zG21YaVSEEF/LYoY0wID7cLXt8N8saGhoJTeiqqEMoKLg6qIaZGFnZ+sQ77n0fXmyPy2EhcoQzyeTplet2uTdd57aX4dfQd4S28uYw1UXkKpLocZnQOV7RnY0MNYsUKhCZQVirSDF4FUgmGHF5AznFirD73P0AHm/fsbEq4nDzygTtBeIWwrdqB8Tn8gfh55cHBXZDNVd0OvL3MaaAQ67pTYHsR4sTOhzZOuiSaDZoCFgXuGII8zm1SqELzczx/lNPtuESInqDtfTrZeL2xgdvt8y3+7ftN5OHEvZRNWW0SPMEobMAXv7jHZn8TasXSh65Oqif+CH4AfgfmFho6EmpepSLsPz1LkbPqxEHUmDjvcTU5e5Gszdu183X/tfiJ6pHGzZa1WBkVIMQsc9gWz7+7ZUsV+sgOiZJQIikCDQYAigdyFSo4qmiGpubprzp3jqvnmD6clQzoZTZhdP2uldXl8hn+1fg16sXHjZf9WeEXXMbUctQaE8MvaNMZgs+CiNZXHiuiDzYCOgSSGbI4lmvSoZbrxzQDj7vgQD7wkSTkXTJVcQmq1dJ57xX4VfpJ5X3G+ZQdXr0U8MkUdbQdf8cTbRceBtAmkXZbmi/aEwoFjgtKG7Y51mhCpTLqizX3iOvgwDrUjIjjYSkdb72hnc116nH0MfbF4rnBCZcZWqkV0MrodHAhE8tncgsjdtXul2pdkjWqGIIOgg+WHzo8cm3epcLqBzRfikfdHDZQi0DZfSbFZR2e6cbd4C3ybe2x3nm9wZDlWZ0V/MhIewAgv8wbe6clztzWnrJk/j0CI5IREhV2JDZEZnCqq0bqOzc7h8/ZZDFshVTWtR9NXTWWxb692E3rDecJ1MG5IY2FV50RaMkseVwkg9Erfd8tBuTWpz5t1kXmKDodPhzmLq5JsnSercbvKzaThY/ZnCw0gtDPERbJVAmNObUd0t3eGd7RzY2zKYT5UKEQGMmUe3wkT9aLgKs1Du3erQJ4ElBGNnIm/iXeNp5QVn3CsT7w2zprh4/VyCqse7zGoQ09TamCUaoBx+XTldEVxOWr2X89SKkOBMV8eVwoI9g3iAc94vfqt/qDplgaQi4yRjBaQ/5YToQWubb3UzrLhc/V+CTgdCDBcQa1Qh12GZ11u2nHicXZus2fOXRVR7UHLMDYevgr89ofj99Dcv7qwBqQgmlWT2I/DjxWTspllo+Ovyb6jz+zhFvWLCLcbAi7hPtBNXFomZOJqXm6Abklr02RSWxFPcUDjL+odEQvt9w/lC9NtwrWzU6eonfyWgpNTk3CWvpwKpgyyZcCj0EnizfSdByka4Ss7PLpK7VZ4YBFniGrDasFnnGGFWMRMtj7KLnodUAvZ+KLmOtUnxea246p7ofaahJc+lyWaIaAAqX60PsLW0cvimfS0BpEYpiltOW5HPVN/XO9iW2arZt9jDl5nVS9Kvjx+LecceQu++T7ogNcHyEq6sq6YpUCf25uBmzKe2KNFrDa3VcQ603Hje/TSBfIWVCd7NvFDUE9AWH5e22E+YqhfLVr7UVNHiDoBLC4ciwuc+uDp3NkLy969vLL5qdejg6AXoJOi4afXrzW6qcbQ1DzkdPT5BE0V7yRoM0dAKku+U8NZC11/XR5b/FVETjJEFzhSKlAbhgtv+4frStwuzp/B/baarrWoeaX+pESnOay0s3i9OMmX1i3lh/QsBKUTeSI2MHI8z0b+TsJU8FdyWEZWflFDSs5AazVzKE0aZws2/C/tx95t0YfFcrt4s9etuKoxqkOs3bDYt/zAAcyO2EPmsvRrA/0R9h/qLHY4QkIESoBPj1IbUyJRtkz8RSo9hjJkJiUZLwvx/NfuUeHF1JTJFcCOuDizO7Crr4qxyLVBvMDEAs+12n7n9/S3AlUQZx2HKVk0ij3URAFK60x+TbhLqUdyQUc5aS8mJNcX3Aqd/X3w4+My2MHN4sTWvdS4/rVptRa397rrwMDIOdIK3d7oV/UTArIO0BoRJh0wqTh0P0tEC0ehRwtGWUKpPCo1Fyy6IWUWbwo4/h7yfeax2wvS1clNw6S++7tlu+K8ZsDSxfvMpdWM32Lq0fWAARUNNRiLIscrpTPnOWE+8kCIQSFAzDykN9QwkygjH84U5wnD/rfzGuk932zW6c7tyKXELsKawerCEcb0ymzRQtk64grsZ/b+AH8LlxX4Hlwngi41NEo4pjo4O/45BTdmMkgs3SRgHBQTRAk8/0n1uOvV4uHaGtSyztDKkcgDyCfJ8stM0BDWD90R5dbtGPePAPMJ+RJdG94iRSlgLgwyLTS3NKczCjH1LIwn+iB1GTgRhQih/8/2Ve5z5mbfYtmV1CHRH8+bzpbPBtLW1eTaCOEQ6MPv5fc0AHIIXxC8F1Me8iNvKKorjC0KLiIt3ypUJ6Ei6xxiFjoPqwfy/0n47PAV6vbjvt6S2pLX0dVb1TDWR9iM2+TfK+U169HxzPjv/wAHyg0aFL8Zjx5nIislySY3J3QmiSSJIYwdtRgrExsNtgYtALT5ffO37Y3oJ+Sk4B3eo9w/3PHcsN5s4Q3ldOl97v/zz/m9/5wFPgt6ECYVIRlNHJUe6h9DIKIfDh6XG1EYWhTSD94KpgVTABD7BPZV8SftmenF5r3kj+NB49LjPOVv51nq4O3m8Uv26/qi/0gEvQjeDIwQrBMnFu0X9Bg1GbMYcxeDFfUS3g9ZDIQIfQRkAFv8fvjs9MDxEO/v7Gvrjupa6s/q5euS7cXvbPJu9bT4Ifyc/wcDSgZLCfULNA75DzkR7RETEqsRvRBTD3oNRAvDCA4GOgNeAJP96vp6+FT2h/Qe8yPymvGE8eDxpvLO8031E/cR+Tf7cP2t/9kB5gPEBWUHwAjKCX8K3AriCpIK8wkMCecHkAYTBX8D3wFCALf+Rv36+976+PlM+d74rvi6+AD5efkf+uv60vvO/NL91/7U/78AlAFLAuECUwOeA8UDxwOoA2wDGQOyAj8CxgFMAdcAbQAQAMb/jv9r/1z/YP91/5f/xP/2/ygAVwB/AJoApQCeAIMAVAARALz/V//l/m3+8/18/RD9tPxt/EL8NvxN/In86/xy/Rz+5f7I/74AwQHGAscDuASQBUcG1AYvB1QHPQfpBlcGiAWCBEoD5wFkAM7+Lv2T+wv6ovhn92X2p/U29Rf1T/Xg9cf2AfiG+Uz7SP1p/6AB3QMNBh4I/gmcC+oM2g1jDn0OJA5YDRwMeAp1CCIGjgPOAPf9HftY+L/1Z/Nl8cvvqO4I7vLtau5x7//wDfON9Wz4l/v1/msC4gU8CV0MLQ+TEXoT0RSKFZ0VBRXGE+URbw90DAkJSAVOATj9Jfk49Y7xRu5860fpvOfq5tnmjucF6TfrFO6K8X711Plr/h8DzAdODIAQQBRvF/EZsRudHK0c3BsuGqwXaRR6EP0LEwfiAZH8SPcz8nrtQumv5d/i6eDi39Lfv+Cj4nLlGumA7YXyAfjN/boDnAlED4QUNBkrHUogdSKYI6gjoiKJIG0dYhmGFPwO7giKAgL8h/VO74bpYOQE4JfcNtr22OTYBNpP3LffI+R06YPvIPYb/TwETgsZEmYYBB7EIn8mFyl0KogqUSnUJiIjVR6RGAES1QpFA4z74/OJ7Lflo99/2nXWptMs0hTSYtMQ1graNN9q5XvsM/RX/KYE4wzMFCMcrCI0KI0ski8rMUcx4y8HLcYoPyOaHAoVyAwSBC77XvLn6Q7iENsl1X7QQM2Jy2jL4Mzqz3DUUtpk4XDpO/KA+/gEWg5cF7cfKSd3LWwy4TW4N983UzYdM1QuGSicIBUYxA7xBOn69/Br54/eqtb6z7fKCscTxeXEg8bjye/OgNVm3WbmO/Ca+jEFsQ/GGSEjeCuIMho4/jsVPks+nDwSOccz4SyUJB4bxxDfBbv6sO8U5TvbdNICyyTFCMHQvpK+UMABxIvJw9B22WDjNu6k+VMF6BAIHF0mlC9lN5A95EE9RIVEt0LgPhs5kjF9KCIezxLcBqX6ie7l4hbYcc5Cxsq/P7vFuHO4TrpJvknEIcyV1V/gLOyh+F0F/xEjHmopfDMJPMxCj0cqSodKoEiCREo+JjZULB0h2RTlB6f6gu3g4CLVpcq7wa66tLX3so6ygLTAuC6/nMfJ0WndIuqS91AF9RITIEYsLDdxQMlH+UzYT01QUU7ySU9DmjoUMA4k4xb6CL76newE31/SEcdzvdK1a7Bqreis7a5qsz+6OcMVzn/aGOh49i4FyhPaIe8uojqYRIJMH1JDVdJVxlMsTyZI6T67M/Am6xgYCuv61+tT3dHPucNsuTyxaasjqIanmKlNroG1/r59yqXXEuZV9fYEfxR1I2Mx3D1+SPRQ/FZlWhBb+VgrVMtMEENEN8Ep7ho/Cy37M+vO23jNn8Cqte6ssqYno2yiiKRtqfew7boEx9/UE+Qs9KsEExXjJKAz1kAdTB1VjVs6XwVg5V3qWDlRCkesOn0s6hxrDIL7r+p22lbLxb0tsuyoSaJ6np+dwJ/PpKesC7euwy7SHOL98k0EiBUmJqc1kEN1T/hYzV++Y6pkiGJmXWtV00ruPSEv2x6cDen7SupJ2WvJLLv7rjilMZ4fmiKZRJt3oJOoXLN/wJfPMeDL8d0D3RU8J3U3CEaDUoNcumPuZ/1o22aZYV5ZZ04JQaoxwCDODmH8BepJ2LnH1bgTrNahb5oalvqUGpdpnMKk5K96vR3NU96Y8F0DExYmKAs5PEhEVbxfUWfGa/ls3WqBZQ1dw1H3QxU0lSIBEOj83ul210DGw7Z4qceeBZdvkiuRQ5OpmDWhpqyjusLKhtxm788CKxbkKGc6LEq4V6BijmpEb5twiG4YaXZg41S2Rl82WSQyEX791OnO1gHF9rQspw+c9ZMgj7eNxI87lfGdpan9t4rIzNo37jMCJhZ1KYk71kvcWS1lcG1kcuBz2XFdbJRjw1dDSYU4CSZfEiD+5+lS1vvDb7Mwpa6ZQpExjKGKoIwhkvma5qaKtXfGKNkN7YsBBRbbKXM8Ok2wW2Fn9G8jdcZ2z3RLb2VmYVqaS4Q6oieFE8z+FeoC1i7DLrKFo6aX7o6iieyH2olfj1GYaqRPs4zEm9fq69oAyhUXKiI9WE4yXTxpGHKAd0l5ZXfgceVouVy6TVo8ISmkFIL/Xerb1ZvCM7EroviV+ox3h5qFdYf4jPqVNqJNscvCKdbR6iAAdRUpKpk9ME9jXr1q3HN5eWh7mXkZdBJryV6eTwQ+hSq4FT4Avure1UHCf7AjoaaUZ4uwha6DcoXtiveTSqCHrzjB1NTC6WL/CRUSKtg9wU9CX+FrPnUNeyF9anv0delsj2BEUYA/zCvAFgABNusJ1h7CEbBuoK6TN4pQhCmC04NCiUySq54ArtS/ndPB6J3+hhTTKd89DFDOX6tsPXY6fHJ+1nxvd2huB2KrUstA8iy5F8YBw+ta1jLC6K8KoBOTaYlXgwyBm4L4h/mQWp26rKK+iNLQ59b97xNvKa89ElAJYBht2Hb/fFt/2n2IeI5vMWPQU+NB9i2iGI0CZOzR1nzCBLD3n9SS/4jFgliAyoEQhwGQWZy3q6S9ltHw5g/9RBPmKEs91U/0XyptEXdcfdp/d34/eVhwCWSxVMdC1i54GVUDGO1s1/vCY7A2oO+S+Iicgg6AYYGMhmWPqZv4qty8ydAk5kj8iBI6KLI8VE+NX+Fs53ZSfe9/rH6RecZwj2RMVXRDjy86GhoE2+0p2K3DBbHDoGWTU4nbgi6AYYFshiePTZuAqku8I9Bt5YX7vRFsJ+g7kk7YXj5sWnbffJt/d35+edZwwmShVehDITDmGtsEre4G2Y/E6LGfoTWUEYqAg7eAyoGxhkaPRJtQqvO7pc/N5Mb65RCAJu06j03WXUJrbHUGfNx+2n0GeYhwoGStVSNEiTB5G5YFi+8C2qLFCbPIol2VL4uNhKqBnIJch8OPkJtoqta7U89G5A/6ARB2JcQ5T0yHXO9pHnTHerV91HwpeNtvKmRxVSNExzDzG0oGdPAa2+LGaLQ8pNuWrIz/hQWD1oNriJ+QMpzJqvS7K8/a42D5FA9QJG4400rvWkZocnIjeSZ8ZnvodtBuXWPqVOdD2DBRHPQGZvFM3E3IAbb4pa6YiI7Vh8iEeIXeidmRKZ11q068Mc+K47v4Hw4RI+42HEkPWUpmaHAcdzF6kXlCdWdtPGIZVG5DuzCTHJIHXfKX3eHJ1Lf8p9Oav5ANivCGf4e2i3GTdZ5rrOa8Zc9Y4yP4JQ28IUc1L0fpVv1jBG6zdNd3V3c6c6BrxWD+UrdCcDC2HCQIWvP33pvL3LlDqkidT5OljHuJ64nvjWeVF6Csrbu9yM9E45n3JwxRIHozDEWBVGFhSGvscRp1unTQcHxp+V6YUcNB9S+6HKcIWPRr4HrNGLzLrAqgNpaaj2mMuoyJkLiXDaI3r86+WtBQ4x73KAvUHooxuELZUXleN2jJbv1xu3EGbv5m2VzoT5FASy+dHBkJWPXw4XrPhL6SrxajcJnqkrWP6Y+Ck2OaVqQLsR/AHdF+47T2KQpIHXovNED0Tklb1GRNa4JuXG7faiZkZ1rvTSE/cC5eHHoJVfaE45nRH8GUsmmm+5ySll6TdpPYlmid8aYps67BENLO4132LQmtG00thD3WS9RXImF7Z61qompcZ/Zgo1etS3M9ZC39G8cJUPcl5dTT5MPOtQCq06COml+XXZeHmsKg3amOtXrDNNNA5Br2NQgHGgUrqzqBSB1UJV1WY4BmjmaAY3BdkFQkSYk7KCx5GwAKRfjP5ijW0MY8udat9aTanrabnJuOnnGkF606uIPFidTW5Oz1QwdYGKUorDf6RChQ4FjiXgBiJGJPX5hZL1FVRmI5uirRGiMKM/mC6JPY4MncvOmxW6l0o16gMKDponKonrAsu8jHDtaQ5dT1WQajFjEmizREQflLWFQkWjFdaF3LWnBVg01CQwA3HSkFGi8KGPo66hDbEc2owDO2A65WqFSlFKWUp8Gsb7RgvkfKxNdu5tP1eQXpFKsjSzFiPZNHkU8gVRVYXlj5VftQjkntP2Q0TycVGSQK8/r0657dX9CdxLK66LJ8rZOqQ6qNrFuxh7jWwf/Mqdlx5+v1pQQuExUh7y1aOf1CkErZT7NSCVPbUD1MVEVYPJAxUyUAGAAKwfuw7TrgyNO4yGC/Brjhshewu6/OsT2247yKxe7PvduY6Bv23QNzEXQefCouNTk+WEVWSg9Nb013SzlH1kCEOIUuKCPHFsMJgvxp7+DiRtf0zDnEV72BuNu1drVUt2K7gMF7yRTT/t3j6WX2IwO7D8ob9CbjMEw57j+aRCxHlEfRRfNBGjx3NEYr0SBqFWwJNP0g8Y3l1tpN0TnJ18JXvtq7cLsavcjAW8amzW3Wa+BR68r2eQIIDhoZWyN9LDs0WTqrPhJBfUHtP288IjcxMNQnTh7qE/oI1f3Q8j/odt6+1VrOgchexA/Co8Ebw2nGb8sG0vfZBOPj7Ej34AFbDGcWth8BKAovnDSOOMQ6LzvPObI28jG2KzIkoRtHEm8IZf549PPqIeJE2pnTUM6QynXIC8hTyUDMutCa1rHdxeWX7uH3WgG4CrMTBhxyI78pvS5IMkg0sDR+M8EwjiwKJ2IgyxiCEMgH4/4W9qbt1OXb3u/YPtTo0AXPoc68z0rSNtZd25bhruht8JX45gAgCQIRURjVHl0kwSjgK6QtBC7/LJ8q+yYwImcczxWcDgcHTf+o91Xwiul941reRtpg17vVYdVR1oLY39tM4KXlvetk8mT5hgCUB1YOmhQvGuserSJZJd4mMidWJlMkPSEtHUUYrxKWDCsGov8t+f3yQu0n6NPjZODz3ZDcRNwM3eHeseFk5drp7+559E36OwAXBrML4xCCFW0Zhxy7HvsfPyCJH+IdWBsDGP8TbA9xCjUF4/+i+pz19vDV7Fbpkeab5IDjRePo42Plp+ef6jHuQfKs9k/7BQCqBBkJMg3UEOcTVBYLGAEZMhmfGFAXUhW3EpcPCgwvCCYEDQAG/C/4pfSC8d3uyexT64PqXerg6gPsvO3676nysvX8+Gz85v9OA40GiAkpDF8OGRBOEfYRDxKcEaQQMA9ODRELiwjTBf0CIgBY/bT6Sfgq9mX0BfMT8pTxiPHs8bvy6/Nw9Tz3Pvlm+6D93P8GAhAE6QWFB9kI3QmKCuAK3gqHCuIJ9QjMB3IG8gRcA7wBIQCX/ij94fvJ+uf5QfnY+K34vvgI+YX5L/r9+uf74/zo/e3+6P/SAKQBWQLsAloDowPGA8YDpANmAxEDqQI1ArwBQgHOAGQACQDA/4r/af9b/2H/d/+b/8j/+v8sAFsAgQCbAKUAnQCAAE8ACgC0/07/3P5j/un9c/0I/a38afxA/Df8UfyQ/PX8f/0s/vf+3P/TANYB3ALcA8sEoQVUBt0GNQdUBzkH3wZIBnUFagQuA8gBQwCr/gv9cvvr+Yb4UPdT9pv1MPUY9Vj18PXe9h/4qvl1+3T9mP/QAQ0EOwZICCMKuwsCDeoNaQ56DhcOQg39C1AKRgjtBVUDkgC6/eH6H/iK9TnzP/Gu75buAO727Xvuje8n8T/zx/Wt+N37Pv+2AisGgQmdDGQPwBGcE+YUkhWWFfEUpBO2ETQPLwy8CPUE9wDg/ND45vRD8QXuR+sg6aPn4ebg5qXnLelu61nu2vHX9TT6z/6DAy8IqwzVEIoUqxceGs0bpxykHMAbABpuFxsUIBCYC6cGcQEf/Nn2yvEa7e/oa+Ws4srg19/c397g1uK45XHp5u328nv4S/44BBcKuA/uFJAZdh2CIJcipCOdI38iUSAfHQIZFRR/DmgI/wF3+//0ze4S6frjsd9Z3BDa6djw2CnajdwM4I3k7+kL8LL2sv3UBOMLpRLlGHIeHiPCJkApgip7KigpkCbGIuMdDBhtETcKoQLn+kPz8ust5SzfHtos1nnTHNIi0o7TWNZt2q/f+eUa7d30B/1YBZANbxW3HCwjnCjaLMMvPDE4MbQvuSxcKLsiARxgFBIMVQNw+qXxOelw4YbatdQq0A3Nd8t3yxLNPNDh1N7aB+Im6v3ySvzCBR4PFRhgILsn7i3FMhg2zDfPNx82xjLdLYUn8B9VF/YNHAQS+ibwpubc3Q7We89Yys/G/sT2xLrGP8ptzxzWHN4x5xTxe/sTBo0QlRrdIxwsDjN+OD08LD45PmI8sjhDMz0s1CNJGuMP8gTN+cjuOeR12sfRdcq6xMbAuL6kvozAZsQVym/RPto/5CXvnPpMBtsR7hwuJ0ow+jf/PSpCV0RyRHlCeD6LON4wqyc4HdUR2AWh+Yvt9eE817PNpsVWv/W6qbiFuI66tr7fxNvMb9ZS4THtr/ltBggTHR9OKkM0rDxGQ9xHSEp0Sl5IEUSuPWQ1cSshIMoTzAaM+W7s29801NbJEsEuumO117KhssS0NLnPv2XItNJv3jvrtfh2BhMUIiE8LQM4IUFNSE5N+k86UAtOekmpQso5IS//IsEVzAeO+XTr7N1g0TLGvLxItROwRq37rDWv5bPruhDEEM+X20XpsPdoBv0U/CL3L4k7VkURTXtSaFW/VXxTrU52Rw0+uDLQJbUX1win+ZvqKNzAzsvCqLiosAqr/KeYp+Opz642tuG/hsvO2FHnofZFBsUVqSR8MtI+SUmOUV9Xjlr/WqxYplMSTChCMzaQKKYZ6gnV+ePpkdpWzKK/2LRQrEum/KJ9otak9am1sdu7G8gX1mPlifUMBmwWKibLNNtB9UzAVfdbZ1/0X5ddYFh3UBZGjTk8K5EbBQsY+k3pJ9kjyrm8ULFEqNuhSp6vnRCgXKVsrQS408R2033jbPS/BfIWfifhNqNEWVClWT5g8GOaZDdi11yiVNVJxDzSLXMdJQxu+tfo6tcqyBK6Ea6HpL2d7JkxmZabCKFgqV+0sMHt0KDhSvNgBVcXpCi+OChHclM5XTJkJGjuaIlmBmGOWGBN0z9OMEkfSA3W+oLo29Zpxq+3HqsbofSZ45UIlWyX/pyVpe+wtb5/ztHfJvLvBJwXnClhOmlJPlZ7YM9nAGzsbIpq6mQ3XLRQt0KtMhIhbQ5P+03o+dXjxJG1eagEnoSWM5I3kZaTQpkOormt6LsvzBDeAfFuBMMXZyrKO2RLvFhnYxNrgm+QcDRuf2ibX8xTbUXtNMoikQ/Y+zboRdWXw7izJKZDm26T4I7AjRiQ1pXPnr+qSrkAymHc3u/fA8oXBSv4PBlN6Vr8ZfptpXLXc4ZxwWu1YqZW8kcJN28kshBu/D3ovdSGwieyHqTbmLWQ7YupivSMvpLbmwWo37b2x8bav+5CA7UXdivsPYdOxlw4aIRwaXW/dnt0rm6CZT9ZQ0oBOf8lzxEQ/WDoYtSwwd2wa6LMlluOWonyhy2K/Y81mY6lqbQSxkLZpe2bAoQXuyulPq5PUF4aaq5yyndFeRJ3QnEAaJNbXEzQOnYn5RK9/Z/oMtQUwdqvCqEYlWGMK4eehceHl43gll2jrLJYxNfXk+zqATcX1iskP41QiF+ga3d0x3lme0h5enMraqBdPE51PNQo8hNy/vjoLdSywB6v+5+/k8qKYYWvg8OFjIvflHSh6rDJwofWi+sxAdIWxitqPyVRbWDKbN11XnsifRp7VnUBbGRf4E/tPRYq9RQu/2rpUdSJwKquQJ/DkpWJ/YMngiOE4Yk1k9efZq9pwVXVj+pyAFUWjSt3P3ZR/2CYbeB2jnx2fod80XaAbdtgRVE1Pzgr6hXw//LpntSYwHyu154kksSIAYMIgemClYjikYaeIa45wELUoemw/8EVLStMP4FRPmEKboB3V31hf4597HembgRiaVJMQDos0BazAJDqEdXewJSuwZ7gkVaIbIJRgBaCrIfpkIWdHq08v1LTw+jq/hoVpyrqPkZRK2Efbrx3t33jfy1+pHhyb95iSlMvQRotpRd5AUHrqtVawfGu/J75kUyIQIIEgKqBJYdLkNScX6xzvoTS9+ck/l8U/SlUPsdQyGDYbZR3r336f2R++Hjhb2Zj51PdQdQtaBg+AgXsZtYLwpGviJ9tkqWIfIIhgKiBA4cJkHWc5Kvgvd3RP+dg/ZQTLymKPQZQFGA3bQl3P32ofzJ+6Hj0b5xjP1RUQmguFRkBA9jsRNfuwnOwZKA7k2GJIIOogA6CRYclkGmcsKuFvV3RnOaf/LkSQSiOPARPEl88bB12aHztfph9dHiqb35jT1STQtQurBm/A7ntQtgCxJaxjaFjlH6KKoSZgd2C7IefkLGcxKtjvQXREebk+9IRNCdjO8JNwl3patB0KnvIfZV8m3cCbwxjF1SYQhcvKxp3BKbuXdlExfayAqPhlfuLm4XxghOE94h2kU2dIKx8vdjQn+Uw++AQCiYKOkJMKFw/aSNzh3k7fCp7Xnb7bUVillNiQi4vkBonBZ3vldq0xpO0wKS1l9aNb4eyhLGFZoqrkj6exazPvdfQSOWE+uUPxiSFOIhKRVpBZxlxgXdIell5vXSYbCphzVLxQRkv2RrOBZzw5ttNyGq2x6bcmQ6Qp4nYhraHOYw9lISftK1fvgLRDeXk+eMOaSPXNpVIHFjyZLRuGXXwdyN3uXLXarpfuVFDQdcuBRtoBqHxTt0Pyni4E6lUnJ+SPoxiiR6KbY4slh6h7K4rv1vR8ORP+dsN9iECNWxGrlVSYvdrUnI1dYl0VHC6aPZdXVBZQGcuFBv1Bqnyy972y7u6oasan4iVNI9NjOmMApF2mAujbbAzwOPR8eTJ+NEMbyAJMxBEAFNmX+NoL28Zco1xkG1DZt9bt04xP8gtAxt0B7TzW+AAzjC9bq4rosaYhZKYjxWQ9ZMam0ulN7J5wZnSEuVT+McL1x7vMIRBFFAxXH1lsmugbjJubmpyY3ZZyUzNPfos0RriB7/0++Eq0NS/eLGEpVScLpY/k56TRZcXnt2nSbT7wn/TVOXu970KLx22Lso+7ky2WMdh3mfMantq8WZLYLxWk0otPPwrfxo+CMf1qeNx0qPCu7QhqTCgK5o/l4KX75ppob6qo7a6xJXUt+Wc97YJextiLOY7kEn4VMZdt2OgZmtmHGPOXLRTFkhQOs8qChqGCMz2YuXS1JvFM7j/rFakep6Vm76b754Qpe6tQrm0xtrVPeZd97QIvRn0Kdo4/kX7UHxZQl8hYgVi8V7/WF5QVEU5OHIpcxm6CMr3JedL17nI3bsascOoFqM9oE6gRKMHqWmxJrzpyE/X5eY097kH+BdwJ6w1PULDTO5UgVpRXUxdc1rgVL5MT0LmNeUnuRjZCMH47ujZ2fjLtb9utXGt+6czpS6l6adNrS61TL9Yy/PYsecg98YGLBbaJF0yTz5USCBQeVU2WEVYp1V0UNVICD9bMyom3BfhCK/5uup43FXPt8P2uV2yJK1zqluq26zesTm5s8IAzsXaoOgk994FXhQzIvIuOjqzQxdLLlDTUvNSkFC/S6dEgjuYMEAk2xbRCJL6iewl383S38evvoK3jrL4r9CvFrK2tom9WMbe0Mbcs+lA9wIFkBKAH24rADbkPthFpkouTVxNM0vFRjdAvzefLSkithWpCGj7V+7e4VzWKcyTw9u8M7i9tYi1lbfRuxnCOcrx0/Pe6ep09zMEwxDCHNUnpjHrOWZA5kRKR4RHk0WJQYg7wTNyKuYfbxRoCC/8IvCf5P7ZkdCfyGTCDr69u3+7Vb0twebGU84310zhQuzC93ID+g7+GSokMS3ONMc68T4uQW9BtT8PPJ02iy8TJ3gdBRMNCOj86fFm57HdE9XOzRfIG8T0wbDBUMPExu3Lo9Kv2s/jve0p+MICNw02F3IgpCiQLwA1zjjeOiM7njlcNnsxIiuEI+AaeRGZB4/9qPMv6m/hqtka0/DNU8pbyBbIgsmRzCrRJtdU3nvmWu+r+CMCfAtsFK4cBCQ3KhcvgjJgNKY0UzN1MCUshybIHyAYyw8LByX+XfX47DblUd5/2OnTsdDuzqrO5M+R0pjW2Nsm4k7pGPFG+ZcBzAmlEeUYVh/HJBApEyy6Lfwt2SxeKp8mviHiGzoV/Q1iBqj+CPe+7wHpBuP43f3ZMden1WjVdNa+2DTctuAg5kbs9vL8+R4BKAjiDhgVnBpFH/EihSXxJisnNiYcJO8gzBzUFzESDwygBRf/pfh98s7sw+eA4ybgy91/3ErcKd0U3/jhvOVB6mHv8/TL+rkAkQYmDEwR3RW3Gb8c3x4KIDogbx+0HRkbtBeiEwUPAwrEBHL/NPo09ZnwhOwT6V/me+Ry40rjAOSM5eDn5eqE7pzyDve0+2kACwV0CYQNHBEhFIAWJxgMGS0ZihgsFyAVehJPD7sL2wfOA7f/svvg9130RPGr7qPsO+t56mLq8uoi7OftL/Dm8vb1RPm2/C8AlgPPBsQJXQyJDjgQYRH9EQsSjRGJEAsPIg3eClMIlwXAAub/Hv1++hn4APZD9O3yBPKP8Yzx+fHR8gj0lPVl92v5lfvQ/QoAMwI5BA4GpAfyCO4JlQrjCtoKfQrRCd8IsQdTBtEEOgOaAQAAd/4L/cj7tPrX+Tb50vis+ML4EPmS+T/6D/v7+/n8/v0C//3/5AC1AWcC9wJiA6cDxwPEA6ADYAMJA6ACKwKyATgBxQBcAAIAu/+H/2f/W/9i/3n/nv/M//7/MABeAIQAnQClAJsAfQBKAAQArP9E/9L+Wf7f/Wn9//ym/GT8Pvw4/FX8l/z//Iz9O/4J//D/6ADsAfIC8APeBLEFYgbnBjkHVAc0B9UGOAZhBVEEEQOpASIAif7p/FD7zPlr+Dj3QfaP9Sv1GvVh9QD29vY9+M75nvug/cf/AAI8BGgGcghICtoLGQ35DW8Odg4KDisN3QsoChcIuAUcA1YAff2l+ub3VvUL8xnxku+E7vrt/O2M7qrvT/Fx8wH27/gk/Ij/AAN0BsYJ2wybD+0RvRP7FJkVjxXcFIEThhH4DukLbgiiBKAAifx6+Jb0+vDF7RPr+eiM59nm6ea/51bppeue7iryMfaU+jP/6AORCAgNKRHTFOYXShrnG7AcmhyjG9EZLhfME8QPMgs6BgABrvtr9mLxvOyd6Cjle+Kt4M7f6N/+4AvjAObJ6UzuZ/P0+Mn+twSSCiwQVxXrGcAduCC4Iq4jkCNbIhYg0BygGKQTAQ7iB3QB6/p49E7unuiX42DfHtzs2d7Y/9hR2s3cYuD35GvqlPBF90r+bQV3DDATYxnfHnYjAydoKY4qayr9KEsmaCJvHYYX2BCYCf0BQvqj8lvrpeS23r7Z5tVP0w/SM9K906PW0tos4Inmuu2I9bj9CQY8DhEWSR2rIwMpJi3wL0oxJjGDL2ks8Cc2ImYbtRNaC5gCs/nt8Izo0+D/2UfU2c/bzGfListGzZHQVNVs26vi3OrA8xP9jAbjD84YBiFMKGMuGzNNNt03uzfnNWwyYy3vJkEfkxYoDUYDPPlW7+LlK9111f/O/MmXxuzECsX0xp7K7c+71tXe/efu8Vz89QZoEWQbmCS9LJIz3zh4PD8+JT4lPE84vDKWKxMjchn+DgYE4Pjh7WDjsNkc0evJVMSHwKO+ub7MwM7Eosoe0gnbIOUV8JX7RQfNEtId/Cf9MIs4az5sQm5EXUQ3Qgs+9zcoMNgmTRzaENUEnPiN7AfhZNb4zA7F5b6vupG4nLjSuia/eMWZzUzXR+I37r76fAcQFBYgMCsGNUs9vEMlSGJKXkoXSJ1DDz2fNIwqIh+6ErIFcfhb69jeSdMKyWzAs7kWtbuyt7INtay5dMAxyaLTd99V7Nr5mwcxFS8iMS7XOM5BzkieTRdQJFDBTf5I/0H3OCsu7iGcFJ0GXvhM6tXcYtBXxQm8w7S/ryetEa2Br2W0mrvpxA3Qsdxz6un4ogcvFhwk/TBtPBBGnE3SUolVqVUuUypOwkYtPbMxrSR+FpQHY/hf6f7asc3gwee3GLCvqtmnr6czqlWv77bHwJPM+dmS6O33kgcLF9wlkzPEPw9KI1K9V7Ja6FpbWB1TVEs7QR81XSddGJUIfviU6FXZNsunvgu0tqvppdWilKIopYGqd7LNvDbJUte15uj2bAfEF28n8jXcQshNX1ZcXI9f3l9DXdFXsU8fRWw4+ik3Gp0Jr/js59nX9Miwu3ewoKdzoSCexZ1koO2lNq4BufrFwNTf5Nz1MQdbGNMoGDiyRThRTVqqYBxkhWThYUNc01PTSJY7gSwJHK0K9Phm54zW68b8uC2t2qNOnb6ZRpnsm5+hMqpltePCRNIS48r04gbRGAkqAzpFSFxU612kZFRo2mgyZm5guVdVTJk+8C7RHcELTPkB527VHcWMti+qZqB/mbGVG5XEl5mdbab/sfS/489Q4bTzgQYlGRArtDuSSjNXNWFIaDRs2Wwxak5kXFugT3NBQzGMH9cMt/m95n7UicNitH+nRp0Ilv6RSJHvk9+Z7KLQrjC9n82c353yDgZZGegrKj2ZTLtZKWSSa7pvf3Dbbd9nul6xUiBEeDM4Ie8NMvqZ5r3TMcJ/siClfprskqeO0Y1xkHaWsp/dq5u6esv43YbxiwVtGZIsZD5YTvFbxmZ/buFyyHMscR9r0GGFVZ1GizXTIgUPvPqU5irTFcHjsBKjDpgtkK+Lt4pOjWCTwpwpqTe4eMln3HHw+gRjGQ8tYj/QT9ddCWkPcal1snYidApummQZWOdIezdZJBgQVPut5sTSNcCPr1ah+JXOjRiJ/oeHiqGQH5q3pgi2nMfs2mHvXAQ8GV4tJUD/UGlf8Wo+cw54Onm5dp1wFGdpWvtKQznJJSUR9/vj5ovSkL+Eru2fPZTPi+aGqIUgiDuOzZeJpBC06MWI2VfuswP4GIEtrEDmUadgfWwLdQ56XnvveNVyPmlyXNdM4johJysSpfw0537SJr/Crdme35IzihiFt4MahjGMzZWkolKyXsQ92FXtAQOaGHgt+UCFUpJhrW12dql7HH3DerF0E2s0XndOVjxdKCgTW/2f55zS975HrRie3pH6iLGDLIJ5hIWKI5QIodCwAcMP117sRwIiGEUtC0HbUipigG59d9x8cn4yfC12kmyqX9pPmz19KRkUGP4i6OTSAb8UraqdOpEliLGCCoE9gzmJ0JK4n42v1MH/1XPriAGTF+os5UDqUm1i9W4heKh9YH87fUl3uG3TYP1QsT58Kv0U2v696FPTQ78prZCd85CzhxqCUYBogk6I1pG2noqu18AQ1ZfqxQDuFmYsh0CzUl5iDm9geAt+5H/cfQN4hW6tYd9RlD9bK9EVnv9s6erTvb+DrcidCZGnh+uBAYD6gcWHNpEDnsmtDsBD1MvpAAA=\" type=\"audio/wav\" />\n", |
|
574 | 574 | " Your browser does not support the audio element.\n", |
|
575 | 575 | " </audio>\n", |
|
576 | 576 | " " |
|
577 | 577 | ], |
|
578 | 578 | "metadata": {}, |
|
579 | 579 | "output_type": "pyout", |
|
580 | 580 | "prompt_number": 8, |
|
581 | 581 | "text": [ |
|
582 | 582 | "<IPython.lib.display.Audio at 0x111353e10>" |
|
583 | 583 | ] |
|
584 | 584 | } |
|
585 | 585 | ], |
|
586 | 586 | "prompt_number": 8 |
|
587 | 587 | }, |
|
588 | 588 | { |
|
589 | 589 | "cell_type": "heading", |
|
590 | 590 | "level": 2, |
|
591 | 591 | "metadata": {}, |
|
592 | 592 | "source": [ |
|
593 | 593 | "Video" |
|
594 | 594 | ] |
|
595 | 595 | }, |
|
596 | 596 | { |
|
597 | 597 | "cell_type": "markdown", |
|
598 | 598 | "metadata": {}, |
|
599 | 599 | "source": [ |
|
600 | 600 | "More exotic objects can also be displayed, as long as their representation supports the IPython display protocol. For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other hosted content is trivial):" |
|
601 | 601 | ] |
|
602 | 602 | }, |
|
603 | 603 | { |
|
604 | 604 | "cell_type": "code", |
|
605 | 605 | "collapsed": false, |
|
606 | 606 | "input": [ |
|
607 | 607 | "from IPython.display import YouTubeVideo\n", |
|
608 | 608 | "# a talk about IPython at Sage Days at U. Washington, Seattle.\n", |
|
609 | 609 | "# Video credit: William Stein.\n", |
|
610 | 610 | "YouTubeVideo('1j_HxD4iLn8')" |
|
611 | 611 | ], |
|
612 | 612 | "language": "python", |
|
613 | 613 | "metadata": {}, |
|
614 | 614 | "outputs": [ |
|
615 | 615 | { |
|
616 | 616 | "html": [ |
|
617 | 617 | "\n", |
|
618 | 618 | " <iframe\n", |
|
619 | 619 | " width=\"400\"\n", |
|
620 | 620 | " height=\"300\"\n", |
|
621 | 621 | " src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n", |
|
622 | 622 | " frameborder=\"0\"\n", |
|
623 | 623 | " allowfullscreen\n", |
|
624 | 624 | " ></iframe>\n", |
|
625 | 625 | " " |
|
626 | 626 | ], |
|
627 | 627 | "output_type": "pyout", |
|
628 | 628 | "prompt_number": 7, |
|
629 | 629 | "text": [ |
|
630 | 630 | "<IPython.lib.display.YouTubeVideo at 0x10fba2190>" |
|
631 | 631 | ] |
|
632 | 632 | } |
|
633 | 633 | ], |
|
634 | 634 | "prompt_number": 7 |
|
635 | 635 | }, |
|
636 | 636 | { |
|
637 | 637 | "cell_type": "markdown", |
|
638 | 638 | "metadata": {}, |
|
639 | 639 | "source": [ |
|
640 | 640 | "Using the nascent video capabilities of modern browsers, you may also be able to display local\n", |
|
641 | 641 | "videos. At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n", |
|
642 | 642 | "we will continue testing this and looking for ways to make it more robust. \n", |
|
643 | 643 | "\n", |
|
644 | 644 | "The following cell loads a local file called `animation.m4v`, encodes the raw video as base64 for http\n", |
|
645 | 645 | "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n", |
|
646 | 646 | "bar at the bottom with a play/pause button and a location slider." |
|
647 | 647 | ] |
|
648 | 648 | }, |
|
649 | 649 | { |
|
650 | 650 | "cell_type": "code", |
|
651 | 651 | "collapsed": false, |
|
652 | 652 | "input": [ |
|
653 | 653 | "from IPython.display import HTML\n", |
|
654 | 654 | "from base64 import b64encode\n", |
|
655 | 655 | "video = open(\"animation.m4v\", \"rb\").read()\n", |
|
656 | 656 | "video_encoded = b64encode(video)\n", |
|
657 | 657 | "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n", |
|
658 | 658 | "HTML(data=video_tag)" |
|
659 | 659 | ], |
|
660 | 660 | "language": "python", |
|
661 | 661 | "metadata": {}, |
|
662 | 662 | "outputs": [ |
|
663 | 663 | { |
|
664 | 664 | "html": [ |
|
665 | 665 | "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n", |
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750 | 750 | "nWc1SmpHm2zHMBcUjYLDZ5gL5vdfxn0V8FFw66G88c/LN4I5icUa7xf4fcSBKywU0ajbp1P+aJYj\n", |
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753 | 753 | "a+Kcs/n0KLCJdTilyaGadopLeaAn3eYvWTeHcucMM1Fp1KgHD1tiFeO6HvobLkZlRximsA3/7Mio\n", |
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754 | 754 | "hYklLIcJrZL22BH+6W9d6kZsYIsej9RM681nU6mWNjepBAfAfTbrGRrVB/h2DxC5B8YyRjgSIzQj\n", |
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760 | 760 | "ZG+W/ar/WGlzDa1xPWnPRsEdrIcZlEVGV/jGmbirkxw1lyUYoqj8Vv7Bxube9XPQlBkXOV6Lc1LT\n", |
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761 | 761 | "2IzNq0V7WwVhF0kA6yxfAsFxc9krNEH8vGGntTWI608ovjatXc/CKKXw7AjJSftlTcLI0hIIGXbR\n", |
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763 | 763 | "/H2mmGEvOzPBie1D0YT7Jh19vxa4Dd3SQ1FrDfmSUpvv4DjbYcZ2PrPpFpWtMjWqHBeoyMiZf6RP\n", |
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765 | 765 | "RQuDMGGS7B2zuf/0GbJyRhUO48UbMrqnILMrbQg1LF00Q3pH9nbGEK/RRQpRN3T/J/4IZQjwW2Ft\n", |
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767 | 767 | "BBtony2wK9T2Imj+NCziOSEL7Q7VuIU8kclUHrJJsSneFcxGRgIgGGUEQM8/pklwTOqab7mMmJeR\n", |
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768 | 768 | "iaBrjJDEnDpkR4Vz3qXxgyn4/5x24FuTMNVPwQAAAhtBmqVJ4Q8mUwIr/wApcLwPT0/Xh9UdWqWX\n", |
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769 | 769 | "Is8Wbj5K1hivmN6qIQnq+aolcegdlM/63MbHsdC6xYZC1e/Q8UjQCt9N/Ejqwms8DzeWv2qxskel\n", |
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771 | 771 | "9zVqWyLck315GFmXxQKIM8pICQc8Q5es34LH1+DmnMnW8kQpVGrztQcDXhjCU3F0fOgoSsXSVWCj\n", |
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861 | 861 | "AgABAAAAAAJ1bWRpYQAAACBtZGhkAAAAAHwlsIB8JbCAAAAAGQAAABRVxAAAAAAALWhkbHIAAAAA\n", |
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864 | 864 | "AAAAAAAAAQAAAKRhdmMxAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAAY4BhgBIAAAASAAAAAAAAAAB\n", |
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866 | 866 | "2UGQz6mhAAADAAEAAAMAMg8WLZYBAAZo6+PLIsAAAAAcdXVpZGtoQPJfJE/FujmlG88DI/MAAAAA\n", |
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868 | 868 | "AAABAAAAFAAAAAIAAAAcc3RzYwAAAAAAAAABAAAAAQAAAAEAAAABAAAAZHN0c3oAAAAAAAAAAAAA\n", |
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870 | 870 | "/QAAAUEAAAEaAAABKQAAAQAAAADlAAAAzQAAAGBzdGNvAAAAAAAAABQAAAAsAAANZQAAEA4AABJt\n", |
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871 | 871 | "AAAUgAAAFwsAABkqAAAbWQAAHOEAAB48AAAfdQAAINAAACIUAAAjegAAJHcAACW4AAAm0gAAJ/sA\n", |
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872 | 872 | "ACj7AAAp4AAAAGF1ZHRhAAAAWW1ldGEAAAAAAAAAIWhkbHIAAAAAAAAAAG1kaXJhcHBsAAAAAAAA\n", |
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873 | 873 | "AAAAAAAALGlsc3QAAAAkqXRvbwAAABxkYXRhAAAAAQAAAABMYXZmNTIuMTExLjA=\n", |
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874 | 874 | "\">" |
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875 | 875 | ], |
|
876 | 876 | "output_type": "pyout", |
|
877 | 877 | "prompt_number": 8, |
|
878 | 878 | "text": [ |
|
879 | 879 | "<IPython.core.display.HTML at 0x10fba28d0>" |
|
880 | 880 | ] |
|
881 | 881 | } |
|
882 | 882 | ], |
|
883 | 883 | "prompt_number": 8 |
|
884 | 884 | }, |
|
885 | 885 | { |
|
886 | 886 | "cell_type": "heading", |
|
887 | 887 | "level": 2, |
|
888 | 888 | "metadata": {}, |
|
889 | 889 | "source": [ |
|
890 | 890 | "HTML" |
|
891 | 891 | ] |
|
892 | 892 | }, |
|
893 | 893 | { |
|
894 | 894 | "cell_type": "markdown", |
|
895 | 895 | "metadata": {}, |
|
896 | 896 | "source": [ |
|
897 | 897 | "Python objects can declare HTML representations that will be displayed in the Notebook. If you have some HTML you want to display, simply use the `HTML` class." |
|
898 | 898 | ] |
|
899 | 899 | }, |
|
900 | 900 | { |
|
901 | 901 | "cell_type": "code", |
|
902 | 902 | "collapsed": false, |
|
903 | 903 | "input": [ |
|
904 | 904 | "from IPython.display import HTML" |
|
905 | 905 | ], |
|
906 | 906 | "language": "python", |
|
907 | 907 | "metadata": {}, |
|
908 | 908 | "outputs": [], |
|
909 | 909 | "prompt_number": 3 |
|
910 | 910 | }, |
|
911 | 911 | { |
|
912 | 912 | "cell_type": "code", |
|
913 | 913 | "collapsed": false, |
|
914 | 914 | "input": [ |
|
915 | 915 | "s = \"\"\"<table>\n", |
|
916 | 916 | "<tr>\n", |
|
917 | 917 | "<th>Header 1</th>\n", |
|
918 | 918 | "<th>Header 2</th>\n", |
|
919 | 919 | "</tr>\n", |
|
920 | 920 | "<tr>\n", |
|
921 | 921 | "<td>row 1, cell 1</td>\n", |
|
922 | 922 | "<td>row 1, cell 2</td>\n", |
|
923 | 923 | "</tr>\n", |
|
924 | 924 | "<tr>\n", |
|
925 | 925 | "<td>row 2, cell 1</td>\n", |
|
926 | 926 | "<td>row 2, cell 2</td>\n", |
|
927 | 927 | "</tr>\n", |
|
928 | 928 | "</table>\"\"\"" |
|
929 | 929 | ], |
|
930 | 930 | "language": "python", |
|
931 | 931 | "metadata": {}, |
|
932 | 932 | "outputs": [], |
|
933 | 933 | "prompt_number": 4 |
|
934 | 934 | }, |
|
935 | 935 | { |
|
936 | 936 | "cell_type": "code", |
|
937 | 937 | "collapsed": false, |
|
938 | 938 | "input": [ |
|
939 | 939 | "h = HTML(s); h" |
|
940 | 940 | ], |
|
941 | 941 | "language": "python", |
|
942 | 942 | "metadata": {}, |
|
943 | 943 | "outputs": [ |
|
944 | 944 | { |
|
945 | 945 | "html": [ |
|
946 | 946 | "<table>\n", |
|
947 | 947 | "<tr>\n", |
|
948 | 948 | "<th>Header 1</th>\n", |
|
949 | 949 | "<th>Header 2</th>\n", |
|
950 | 950 | "</tr>\n", |
|
951 | 951 | "<tr>\n", |
|
952 | 952 | "<td>row 1, cell 1</td>\n", |
|
953 | 953 | "<td>row 1, cell 2</td>\n", |
|
954 | 954 | "</tr>\n", |
|
955 | 955 | "<tr>\n", |
|
956 | 956 | "<td>row 2, cell 1</td>\n", |
|
957 | 957 | "<td>row 2, cell 2</td>\n", |
|
958 | 958 | "</tr>\n", |
|
959 | 959 | "</table>" |
|
960 | 960 | ], |
|
961 | 961 | "output_type": "pyout", |
|
962 | 962 | "prompt_number": 5, |
|
963 | 963 | "text": [ |
|
964 | 964 | "<IPython.core.display.HTML at 0x1087a0c10>" |
|
965 | 965 | ] |
|
966 | 966 | } |
|
967 | 967 | ], |
|
968 | 968 | "prompt_number": 5 |
|
969 | 969 | }, |
|
970 | 970 | { |
|
971 | 971 | "cell_type": "markdown", |
|
972 | 972 | "metadata": {}, |
|
973 | 973 | "source": [ |
|
974 | 974 | "Pandas makes use of this capability to allow `DataFrames` to be represented as HTML tables." |
|
975 | 975 | ] |
|
976 | 976 | }, |
|
977 | 977 | { |
|
978 | 978 | "cell_type": "code", |
|
979 | 979 | "collapsed": false, |
|
980 | 980 | "input": [ |
|
981 | 981 | "import pandas" |
|
982 | 982 | ], |
|
983 | 983 | "language": "python", |
|
984 | 984 | "metadata": {}, |
|
985 | 985 | "outputs": [], |
|
986 | 986 | "prompt_number": 6 |
|
987 | 987 | }, |
|
988 | 988 | { |
|
989 | 989 | "cell_type": "markdown", |
|
990 | 990 | "metadata": {}, |
|
991 | 991 | "source": [ |
|
992 | "By default, `DataFrames` will be represented as text; to enable HTML representations we need to set a print option:" | |
|
993 | ] | |
|
994 | }, | |
|
995 | { | |
|
996 | "cell_type": "code", | |
|
997 | "collapsed": false, | |
|
998 | "input": [ | |
|
999 | "pandas.core.format.set_printoptions(notebook_repr_html=True)" | |
|
1000 | ], | |
|
1001 | "language": "python", | |
|
1002 | "metadata": {}, | |
|
1003 | "outputs": [], | |
|
1004 | "prompt_number": 9 | |
|
1005 | }, | |
|
1006 | { | |
|
1007 | "cell_type": "markdown", | |
|
1008 | "metadata": {}, | |
|
1009 | "source": [ | |
|
1010 | 992 | "Here is a small amount of stock data for APPL:" |
|
1011 | 993 | ] |
|
1012 | 994 | }, |
|
1013 | 995 | { |
|
1014 | 996 | "cell_type": "code", |
|
1015 | 997 | "collapsed": false, |
|
1016 | 998 | "input": [ |
|
1017 | 999 | "%%file data.csv\n", |
|
1018 | 1000 | "Date,Open,High,Low,Close,Volume,Adj Close\n", |
|
1019 | 1001 | "2012-06-01,569.16,590.00,548.50,584.00,14077000,581.50\n", |
|
1020 | 1002 | "2012-05-01,584.90,596.76,522.18,577.73,18827900,575.26\n", |
|
1021 | 1003 | "2012-04-02,601.83,644.00,555.00,583.98,28759100,581.48\n", |
|
1022 | 1004 | "2012-03-01,548.17,621.45,516.22,599.55,26486000,596.99\n", |
|
1023 | 1005 | "2012-02-01,458.41,547.61,453.98,542.44,22001000,540.12\n", |
|
1024 | 1006 | "2012-01-03,409.40,458.24,409.00,456.48,12949100,454.53" |
|
1025 | 1007 | ], |
|
1026 | 1008 | "language": "python", |
|
1027 | 1009 | "metadata": {}, |
|
1028 | 1010 | "outputs": [ |
|
1029 | 1011 | { |
|
1030 | 1012 | "output_type": "stream", |
|
1031 | 1013 | "stream": "stdout", |
|
1032 | 1014 | "text": [ |
|
1033 | 1015 | "Writing data.csv\n" |
|
1034 | 1016 | ] |
|
1035 | 1017 | } |
|
1036 | 1018 | ], |
|
1037 | 1019 | "prompt_number": 11 |
|
1038 | 1020 | }, |
|
1039 | 1021 | { |
|
1040 | 1022 | "cell_type": "markdown", |
|
1041 | 1023 | "metadata": {}, |
|
1042 | 1024 | "source": [ |
|
1043 | 1025 | "Read this as into a `DataFrame`:" |
|
1044 | 1026 | ] |
|
1045 | 1027 | }, |
|
1046 | 1028 | { |
|
1047 | 1029 | "cell_type": "code", |
|
1048 | 1030 | "collapsed": false, |
|
1049 | 1031 | "input": [ |
|
1050 | 1032 | "df = pandas.read_csv('data.csv')" |
|
1051 | 1033 | ], |
|
1052 | 1034 | "language": "python", |
|
1053 | 1035 | "metadata": {}, |
|
1054 | 1036 | "outputs": [], |
|
1055 | 1037 | "prompt_number": 12 |
|
1056 | 1038 | }, |
|
1057 | 1039 | { |
|
1058 | 1040 | "cell_type": "markdown", |
|
1059 | 1041 | "metadata": {}, |
|
1060 | 1042 | "source": [ |
|
1061 | 1043 | "And view the HTML representation:" |
|
1062 | 1044 | ] |
|
1063 | 1045 | }, |
|
1064 | 1046 | { |
|
1065 | 1047 | "cell_type": "code", |
|
1066 | 1048 | "collapsed": false, |
|
1067 | 1049 | "input": [ |
|
1068 | 1050 | "df" |
|
1069 | 1051 | ], |
|
1070 | 1052 | "language": "python", |
|
1071 | 1053 | "metadata": {}, |
|
1072 | 1054 | "outputs": [ |
|
1073 | 1055 | { |
|
1074 | 1056 | "html": [ |
|
1075 | 1057 | "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n", |
|
1076 | 1058 | "<table border=\"1\">\n", |
|
1077 | 1059 | " <thead>\n", |
|
1078 | 1060 | " <tr>\n", |
|
1079 | 1061 | " <th></th>\n", |
|
1080 | 1062 | " <th>Date</th>\n", |
|
1081 | 1063 | " <th>Open</th>\n", |
|
1082 | 1064 | " <th>High</th>\n", |
|
1083 | 1065 | " <th>Low</th>\n", |
|
1084 | 1066 | " <th>Close</th>\n", |
|
1085 | 1067 | " <th>Volume</th>\n", |
|
1086 | 1068 | " <th>Adj Close</th>\n", |
|
1087 | 1069 | " </tr>\n", |
|
1088 | 1070 | " </thead>\n", |
|
1089 | 1071 | " <tbody>\n", |
|
1090 | 1072 | " <tr>\n", |
|
1091 | 1073 | " <td><strong>0</strong></td>\n", |
|
1092 | 1074 | " <td> 2012-06-01</td>\n", |
|
1093 | 1075 | " <td> 569.16</td>\n", |
|
1094 | 1076 | " <td> 590.00</td>\n", |
|
1095 | 1077 | " <td> 548.50</td>\n", |
|
1096 | 1078 | " <td> 584.00</td>\n", |
|
1097 | 1079 | " <td> 14077000</td>\n", |
|
1098 | 1080 | " <td> 581.50</td>\n", |
|
1099 | 1081 | " </tr>\n", |
|
1100 | 1082 | " <tr>\n", |
|
1101 | 1083 | " <td><strong>1</strong></td>\n", |
|
1102 | 1084 | " <td> 2012-05-01</td>\n", |
|
1103 | 1085 | " <td> 584.90</td>\n", |
|
1104 | 1086 | " <td> 596.76</td>\n", |
|
1105 | 1087 | " <td> 522.18</td>\n", |
|
1106 | 1088 | " <td> 577.73</td>\n", |
|
1107 | 1089 | " <td> 18827900</td>\n", |
|
1108 | 1090 | " <td> 575.26</td>\n", |
|
1109 | 1091 | " </tr>\n", |
|
1110 | 1092 | " <tr>\n", |
|
1111 | 1093 | " <td><strong>2</strong></td>\n", |
|
1112 | 1094 | " <td> 2012-04-02</td>\n", |
|
1113 | 1095 | " <td> 601.83</td>\n", |
|
1114 | 1096 | " <td> 644.00</td>\n", |
|
1115 | 1097 | " <td> 555.00</td>\n", |
|
1116 | 1098 | " <td> 583.98</td>\n", |
|
1117 | 1099 | " <td> 28759100</td>\n", |
|
1118 | 1100 | " <td> 581.48</td>\n", |
|
1119 | 1101 | " </tr>\n", |
|
1120 | 1102 | " <tr>\n", |
|
1121 | 1103 | " <td><strong>3</strong></td>\n", |
|
1122 | 1104 | " <td> 2012-03-01</td>\n", |
|
1123 | 1105 | " <td> 548.17</td>\n", |
|
1124 | 1106 | " <td> 621.45</td>\n", |
|
1125 | 1107 | " <td> 516.22</td>\n", |
|
1126 | 1108 | " <td> 599.55</td>\n", |
|
1127 | 1109 | " <td> 26486000</td>\n", |
|
1128 | 1110 | " <td> 596.99</td>\n", |
|
1129 | 1111 | " </tr>\n", |
|
1130 | 1112 | " <tr>\n", |
|
1131 | 1113 | " <td><strong>4</strong></td>\n", |
|
1132 | 1114 | " <td> 2012-02-01</td>\n", |
|
1133 | 1115 | " <td> 458.41</td>\n", |
|
1134 | 1116 | " <td> 547.61</td>\n", |
|
1135 | 1117 | " <td> 453.98</td>\n", |
|
1136 | 1118 | " <td> 542.44</td>\n", |
|
1137 | 1119 | " <td> 22001000</td>\n", |
|
1138 | 1120 | " <td> 540.12</td>\n", |
|
1139 | 1121 | " </tr>\n", |
|
1140 | 1122 | " <tr>\n", |
|
1141 | 1123 | " <td><strong>5</strong></td>\n", |
|
1142 | 1124 | " <td> 2012-01-03</td>\n", |
|
1143 | 1125 | " <td> 409.40</td>\n", |
|
1144 | 1126 | " <td> 458.24</td>\n", |
|
1145 | 1127 | " <td> 409.00</td>\n", |
|
1146 | 1128 | " <td> 456.48</td>\n", |
|
1147 | 1129 | " <td> 12949100</td>\n", |
|
1148 | 1130 | " <td> 454.53</td>\n", |
|
1149 | 1131 | " </tr>\n", |
|
1150 | 1132 | " </tbody>\n", |
|
1151 | 1133 | "</table>\n", |
|
1152 | 1134 | "</div>" |
|
1153 | 1135 | ], |
|
1154 | 1136 | "output_type": "pyout", |
|
1155 | 1137 | "prompt_number": 14, |
|
1156 | 1138 | "text": [ |
|
1157 | 1139 | " Date Open High Low Close Volume Adj Close\n", |
|
1158 | 1140 | "0 2012-06-01 569.16 590.00 548.50 584.00 14077000 581.50\n", |
|
1159 | 1141 | "1 2012-05-01 584.90 596.76 522.18 577.73 18827900 575.26\n", |
|
1160 | 1142 | "2 2012-04-02 601.83 644.00 555.00 583.98 28759100 581.48\n", |
|
1161 | 1143 | "3 2012-03-01 548.17 621.45 516.22 599.55 26486000 596.99\n", |
|
1162 | 1144 | "4 2012-02-01 458.41 547.61 453.98 542.44 22001000 540.12\n", |
|
1163 | 1145 | "5 2012-01-03 409.40 458.24 409.00 456.48 12949100 454.53" |
|
1164 | 1146 | ] |
|
1165 | 1147 | } |
|
1166 | 1148 | ], |
|
1167 | 1149 | "prompt_number": 14 |
|
1168 | 1150 | }, |
|
1169 | 1151 | { |
|
1170 | 1152 | "cell_type": "heading", |
|
1171 | 1153 | "level": 2, |
|
1172 | 1154 | "metadata": {}, |
|
1173 | 1155 | "source": [ |
|
1174 | 1156 | "External sites" |
|
1175 | 1157 | ] |
|
1176 | 1158 | }, |
|
1177 | 1159 | { |
|
1178 | 1160 | "cell_type": "markdown", |
|
1179 | 1161 | "metadata": {}, |
|
1180 | 1162 | "source": [ |
|
1181 | 1163 | "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n", |
|
1182 | 1164 | "page for mobile users:" |
|
1183 | 1165 | ] |
|
1184 | 1166 | }, |
|
1185 | 1167 | { |
|
1186 | 1168 | "cell_type": "code", |
|
1187 | 1169 | "collapsed": false, |
|
1188 | 1170 | "input": [ |
|
1189 | 1171 | "from IPython.display import HTML\n", |
|
1190 | 1172 | "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')" |
|
1191 | 1173 | ], |
|
1192 | 1174 | "language": "python", |
|
1193 | 1175 | "metadata": {}, |
|
1194 | 1176 | "outputs": [ |
|
1195 | 1177 | { |
|
1196 | 1178 | "html": [ |
|
1197 | 1179 | "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>" |
|
1198 | 1180 | ], |
|
1199 | 1181 | "output_type": "pyout", |
|
1200 | 1182 | "prompt_number": 9, |
|
1201 | 1183 | "text": [ |
|
1202 | 1184 | "<IPython.core.display.HTML at 0x1094900d0>" |
|
1203 | 1185 | ] |
|
1204 | 1186 | } |
|
1205 | 1187 | ], |
|
1206 | 1188 | "prompt_number": 9 |
|
1207 | 1189 | }, |
|
1208 | 1190 | { |
|
1209 | 1191 | "cell_type": "heading", |
|
1210 | 1192 | "level": 2, |
|
1211 | 1193 | "metadata": {}, |
|
1212 | 1194 | "source": [ |
|
1213 | 1195 | "LaTeX" |
|
1214 | 1196 | ] |
|
1215 | 1197 | }, |
|
1216 | 1198 | { |
|
1217 | 1199 | "cell_type": "markdown", |
|
1218 | 1200 | "metadata": {}, |
|
1219 | 1201 | "source": [ |
|
1220 | 1202 | "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n", |
|
1221 | 1203 | "in the browser thanks to the [MathJax library](http://mathjax.org)." |
|
1222 | 1204 | ] |
|
1223 | 1205 | }, |
|
1224 | 1206 | { |
|
1225 | 1207 | "cell_type": "code", |
|
1226 | 1208 | "collapsed": false, |
|
1227 | 1209 | "input": [ |
|
1228 | 1210 | "from IPython.display import Math\n", |
|
1229 | 1211 | "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')" |
|
1230 | 1212 | ], |
|
1231 | 1213 | "language": "python", |
|
1232 | 1214 | "metadata": {}, |
|
1233 | 1215 | "outputs": [ |
|
1234 | 1216 | { |
|
1235 | 1217 | "latex": [ |
|
1236 | 1218 | "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$" |
|
1237 | 1219 | ], |
|
1238 | 1220 | "output_type": "pyout", |
|
1239 | 1221 | "prompt_number": 10, |
|
1240 | 1222 | "text": [ |
|
1241 | 1223 | "<IPython.core.display.Math at 0x10fba26d0>" |
|
1242 | 1224 | ] |
|
1243 | 1225 | } |
|
1244 | 1226 | ], |
|
1245 | 1227 | "prompt_number": 10 |
|
1246 | 1228 | }, |
|
1247 | 1229 | { |
|
1248 | 1230 | "cell_type": "markdown", |
|
1249 | 1231 | "metadata": {}, |
|
1250 | 1232 | "source": [ |
|
1251 | 1233 | "With the `Latex` class, you have to include the delimiters yourself. This allows you to use other LaTeX modes such as `eqnarray`:" |
|
1252 | 1234 | ] |
|
1253 | 1235 | }, |
|
1254 | 1236 | { |
|
1255 | 1237 | "cell_type": "code", |
|
1256 | 1238 | "collapsed": false, |
|
1257 | 1239 | "input": [ |
|
1258 | 1240 | "from IPython.display import Latex\n", |
|
1259 | 1241 | "Latex(r\"\"\"\\begin{eqnarray}\n", |
|
1260 | 1242 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1261 | 1243 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1262 | 1244 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1263 | 1245 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", |
|
1264 | 1246 | "\\end{eqnarray}\"\"\")" |
|
1265 | 1247 | ], |
|
1266 | 1248 | "language": "python", |
|
1267 | 1249 | "metadata": {}, |
|
1268 | 1250 | "outputs": [ |
|
1269 | 1251 | { |
|
1270 | 1252 | "latex": [ |
|
1271 | 1253 | "\\begin{eqnarray}\n", |
|
1272 | 1254 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1273 | 1255 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1274 | 1256 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1275 | 1257 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n", |
|
1276 | 1258 | "\\end{eqnarray}" |
|
1277 | 1259 | ], |
|
1278 | 1260 | "output_type": "pyout", |
|
1279 | 1261 | "prompt_number": 11, |
|
1280 | 1262 | "text": [ |
|
1281 | 1263 | "<IPython.core.display.Latex at 0x10fba2c10>" |
|
1282 | 1264 | ] |
|
1283 | 1265 | } |
|
1284 | 1266 | ], |
|
1285 | 1267 | "prompt_number": 11 |
|
1286 | 1268 | }, |
|
1287 | 1269 | { |
|
1288 | 1270 | "cell_type": "markdown", |
|
1289 | 1271 | "metadata": {}, |
|
1290 | 1272 | "source": [ |
|
1291 | 1273 | "Or you can enter latex directly with the `%%latex` cell magic:" |
|
1292 | 1274 | ] |
|
1293 | 1275 | }, |
|
1294 | 1276 | { |
|
1295 | 1277 | "cell_type": "code", |
|
1296 | 1278 | "collapsed": false, |
|
1297 | 1279 | "input": [ |
|
1298 | 1280 | "%%latex\n", |
|
1299 | 1281 | "\\begin{align}\n", |
|
1300 | 1282 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1301 | 1283 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1302 | 1284 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1303 | 1285 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", |
|
1304 | 1286 | "\\end{align}" |
|
1305 | 1287 | ], |
|
1306 | 1288 | "language": "python", |
|
1307 | 1289 | "metadata": {}, |
|
1308 | 1290 | "outputs": [ |
|
1309 | 1291 | { |
|
1310 | 1292 | "latex": [ |
|
1311 | 1293 | "\\begin{align}\n", |
|
1312 | 1294 | "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n", |
|
1313 | 1295 | "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n", |
|
1314 | 1296 | "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n", |
|
1315 | 1297 | "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n", |
|
1316 | 1298 | "\\end{align}" |
|
1317 | 1299 | ], |
|
1318 | 1300 | "metadata": {}, |
|
1319 | 1301 | "output_type": "display_data", |
|
1320 | 1302 | "text": [ |
|
1321 | 1303 | "<IPython.core.display.Latex at 0x106c04dd0>" |
|
1322 | 1304 | ] |
|
1323 | 1305 | } |
|
1324 | 1306 | ], |
|
1325 | 1307 | "prompt_number": 12 |
|
1326 | 1308 | } |
|
1327 | 1309 | ], |
|
1328 | 1310 | "metadata": {} |
|
1329 | 1311 | } |
|
1330 | 1312 | ] |
|
1331 | 1313 | } No newline at end of file |
@@ -1,487 +1,490 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "name": "" |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "heading", |
|
12 | 12 | "level": 1, |
|
13 | 13 | "metadata": {}, |
|
14 | 14 | "source": [ |
|
15 | 15 | "Using Parallel Magics" |
|
16 | 16 | ] |
|
17 | 17 | }, |
|
18 | 18 | { |
|
19 | 19 | "cell_type": "markdown", |
|
20 | 20 | "metadata": {}, |
|
21 | 21 | "source": [ |
|
22 | 22 | "IPython has a few magics for working with your engines.\n", |
|
23 | 23 | "\n", |
|
24 | 24 | "This assumes you have started an IPython cluster, either with the notebook interface,\n", |
|
25 | 25 | "or the `ipcluster/controller/engine` commands." |
|
26 | 26 | ] |
|
27 | 27 | }, |
|
28 | 28 | { |
|
29 | 29 | "cell_type": "code", |
|
30 | 30 | "collapsed": false, |
|
31 | 31 | "input": [ |
|
32 | 32 | "from IPython import parallel\n", |
|
33 | 33 | "rc = parallel.Client()\n", |
|
34 | 34 | "dv = rc[:]\n", |
|
35 | 35 | "rc.ids" |
|
36 | 36 | ], |
|
37 | 37 | "language": "python", |
|
38 | 38 | "metadata": {}, |
|
39 | 39 | "outputs": [] |
|
40 | 40 | }, |
|
41 | 41 | { |
|
42 | 42 | "cell_type": "markdown", |
|
43 | 43 | "metadata": {}, |
|
44 | 44 | "source": [ |
|
45 | 45 | "Creating a Client registers the parallel magics `%px`, `%%px`, `%pxresult`, `pxconfig`, and `%autopx`. \n", |
|
46 | 46 | "These magics are initially associated with a DirectView always associated with all currently registered engines." |
|
47 | 47 | ] |
|
48 | 48 | }, |
|
49 | 49 | { |
|
50 | 50 | "cell_type": "markdown", |
|
51 | 51 | "metadata": {}, |
|
52 | 52 | "source": [ |
|
53 | 53 | "Now we can execute code remotely with `%px`:" |
|
54 | 54 | ] |
|
55 | 55 | }, |
|
56 | 56 | { |
|
57 | 57 | "cell_type": "code", |
|
58 | 58 | "collapsed": false, |
|
59 | 59 | "input": [ |
|
60 | 60 | "%px a=5" |
|
61 | 61 | ], |
|
62 | 62 | "language": "python", |
|
63 | 63 | "metadata": {}, |
|
64 | 64 | "outputs": [] |
|
65 | 65 | }, |
|
66 | 66 | { |
|
67 | 67 | "cell_type": "code", |
|
68 | 68 | "collapsed": false, |
|
69 | 69 | "input": [ |
|
70 |
"%px print |
|
|
70 | "%px print(a)" | |
|
71 | 71 | ], |
|
72 | 72 | "language": "python", |
|
73 | 73 | "metadata": {}, |
|
74 | 74 | "outputs": [] |
|
75 | 75 | }, |
|
76 | 76 | { |
|
77 | 77 | "cell_type": "code", |
|
78 | 78 | "collapsed": false, |
|
79 | 79 | "input": [ |
|
80 | 80 | "%px a" |
|
81 | 81 | ], |
|
82 | 82 | "language": "python", |
|
83 | 83 | "metadata": {}, |
|
84 | 84 | "outputs": [] |
|
85 | 85 | }, |
|
86 | 86 | { |
|
87 | 87 | "cell_type": "code", |
|
88 | 88 | "collapsed": false, |
|
89 | 89 | "input": [ |
|
90 | 90 | "with dv.sync_imports():\n", |
|
91 | 91 | " import sys" |
|
92 | 92 | ], |
|
93 | 93 | "language": "python", |
|
94 | 94 | "metadata": {}, |
|
95 | 95 | "outputs": [] |
|
96 | 96 | }, |
|
97 | 97 | { |
|
98 | 98 | "cell_type": "code", |
|
99 | 99 | "collapsed": false, |
|
100 | 100 | "input": [ |
|
101 | "%px print >> sys.stderr, \"ERROR\"" | |
|
101 | "%px from __future__ import print_function\n", | |
|
102 | "%px print(\"ERROR\", file=sys.stderr)" | |
|
102 | 103 | ], |
|
103 | 104 | "language": "python", |
|
104 | 105 | "metadata": {}, |
|
105 | 106 | "outputs": [] |
|
106 | 107 | }, |
|
107 | 108 | { |
|
108 | 109 | "cell_type": "markdown", |
|
109 | 110 | "metadata": {}, |
|
110 | 111 | "source": [ |
|
111 | 112 | "You don't have to wait for results. The `%pxconfig` magic lets you change the default blocking/targets for the `%px` magics:" |
|
112 | 113 | ] |
|
113 | 114 | }, |
|
114 | 115 | { |
|
115 | 116 | "cell_type": "code", |
|
116 | 117 | "collapsed": false, |
|
117 | 118 | "input": [ |
|
118 | 119 | "%pxconfig --noblock" |
|
119 | 120 | ], |
|
120 | 121 | "language": "python", |
|
121 | 122 | "metadata": {}, |
|
122 | 123 | "outputs": [] |
|
123 | 124 | }, |
|
124 | 125 | { |
|
125 | 126 | "cell_type": "code", |
|
126 | 127 | "collapsed": false, |
|
127 | 128 | "input": [ |
|
128 | 129 | "%px import time\n", |
|
129 | 130 | "%px time.sleep(5)\n", |
|
130 | 131 | "%px time.time()" |
|
131 | 132 | ], |
|
132 | 133 | "language": "python", |
|
133 | 134 | "metadata": {}, |
|
134 | 135 | "outputs": [] |
|
135 | 136 | }, |
|
136 | 137 | { |
|
137 | 138 | "cell_type": "markdown", |
|
138 | 139 | "metadata": {}, |
|
139 | 140 | "source": [ |
|
140 | 141 | "But you will notice that this didn't output the result of the last command.\n", |
|
141 | 142 | "For this, we have `%pxresult`, which displays the output of the latest request:" |
|
142 | 143 | ] |
|
143 | 144 | }, |
|
144 | 145 | { |
|
145 | 146 | "cell_type": "code", |
|
146 | 147 | "collapsed": false, |
|
147 | 148 | "input": [ |
|
148 | 149 | "%pxresult" |
|
149 | 150 | ], |
|
150 | 151 | "language": "python", |
|
151 | 152 | "metadata": {}, |
|
152 | 153 | "outputs": [] |
|
153 | 154 | }, |
|
154 | 155 | { |
|
155 | 156 | "cell_type": "markdown", |
|
156 | 157 | "metadata": {}, |
|
157 | 158 | "source": [ |
|
158 | 159 | "Remember, an IPython engine is IPython, so you can do magics remotely as well!" |
|
159 | 160 | ] |
|
160 | 161 | }, |
|
161 | 162 | { |
|
162 | 163 | "cell_type": "code", |
|
163 | 164 | "collapsed": false, |
|
164 | 165 | "input": [ |
|
165 | 166 | "%pxconfig --block\n", |
|
166 | 167 | "%px %matplotlib inline" |
|
167 | 168 | ], |
|
168 | 169 | "language": "python", |
|
169 | 170 | "metadata": {}, |
|
170 | 171 | "outputs": [] |
|
171 | 172 | }, |
|
172 | 173 | { |
|
173 | 174 | "cell_type": "code", |
|
174 | 175 | "collapsed": false, |
|
175 | 176 | "input": [ |
|
176 | 177 | "%%px\n", |
|
177 | 178 | "import numpy as np\n", |
|
178 | 179 | "import matplotlib.pyplot as plt" |
|
179 | 180 | ], |
|
180 | 181 | "language": "python", |
|
181 | 182 | "metadata": {}, |
|
182 | 183 | "outputs": [] |
|
183 | 184 | }, |
|
184 | 185 | { |
|
185 | 186 | "cell_type": "markdown", |
|
186 | 187 | "metadata": {}, |
|
187 | 188 | "source": [ |
|
188 | 189 | "`%%px` can also be used as a cell magic, for submitting whole blocks.\n", |
|
189 | 190 | "This one acceps `--block` and `--noblock` flags to specify\n", |
|
190 | 191 | "the blocking behavior, though the default is unchanged.\n" |
|
191 | 192 | ] |
|
192 | 193 | }, |
|
193 | 194 | { |
|
194 | 195 | "cell_type": "code", |
|
195 | 196 | "collapsed": false, |
|
196 | 197 | "input": [ |
|
197 | 198 | "dv.scatter('id', dv.targets, flatten=True)\n", |
|
198 | 199 | "dv['stride'] = len(dv)" |
|
199 | 200 | ], |
|
200 | 201 | "language": "python", |
|
201 | 202 | "metadata": {}, |
|
202 | 203 | "outputs": [] |
|
203 | 204 | }, |
|
204 | 205 | { |
|
205 | 206 | "cell_type": "code", |
|
206 | 207 | "collapsed": false, |
|
207 | 208 | "input": [ |
|
208 | 209 | "%%px --noblock\n", |
|
209 | 210 | "x = np.linspace(0,np.pi,1000)\n", |
|
210 | 211 | "for n in range(id,12, stride):\n", |
|
211 |
" print |
|
|
212 | " print(n)\n", | |
|
212 | 213 | " plt.plot(x,np.sin(n*x))\n", |
|
213 | 214 | "plt.title(\"Plot %i\" % id)" |
|
214 | 215 | ], |
|
215 | 216 | "language": "python", |
|
216 | 217 | "metadata": {}, |
|
217 | 218 | "outputs": [] |
|
218 | 219 | }, |
|
219 | 220 | { |
|
220 | 221 | "cell_type": "code", |
|
221 | 222 | "collapsed": false, |
|
222 | 223 | "input": [ |
|
223 | 224 | "%pxresult" |
|
224 | 225 | ], |
|
225 | 226 | "language": "python", |
|
226 | 227 | "metadata": {}, |
|
227 | 228 | "outputs": [] |
|
228 | 229 | }, |
|
229 | 230 | { |
|
230 | 231 | "cell_type": "markdown", |
|
231 | 232 | "metadata": {}, |
|
232 | 233 | "source": [ |
|
233 | 234 | "It also lets you choose some amount of the grouping of the outputs with `--group-outputs`:\n", |
|
234 | 235 | "\n", |
|
235 | 236 | "The choices are:\n", |
|
236 | 237 | "\n", |
|
237 | 238 | "* `engine` - all of an engine's output is collected together\n", |
|
238 | 239 | "* `type` - where stdout of each engine is grouped, etc. (the default)\n", |
|
239 | 240 | "* `order` - same as `type`, but individual displaypub outputs are interleaved.\n", |
|
240 | 241 | " That is, it will output the first plot from each engine, then the second from each,\n", |
|
241 | 242 | " etc." |
|
242 | 243 | ] |
|
243 | 244 | }, |
|
244 | 245 | { |
|
245 | 246 | "cell_type": "code", |
|
246 | 247 | "collapsed": false, |
|
247 | 248 | "input": [ |
|
248 | 249 | "%%px --group-outputs=engine\n", |
|
249 | 250 | "x = np.linspace(0,np.pi,1000)\n", |
|
250 | 251 | "for n in range(id+1,12, stride):\n", |
|
251 |
" print |
|
|
252 | " print(n)\n", | |
|
252 | 253 | " plt.figure()\n", |
|
253 | 254 | " plt.plot(x,np.sin(n*x))\n", |
|
254 | 255 | " plt.title(\"Plot %i\" % n)" |
|
255 | 256 | ], |
|
256 | 257 | "language": "python", |
|
257 | 258 | "metadata": {}, |
|
258 | 259 | "outputs": [] |
|
259 | 260 | }, |
|
260 | 261 | { |
|
261 | 262 | "cell_type": "markdown", |
|
262 | 263 | "metadata": {}, |
|
263 | 264 | "source": [ |
|
264 | 265 | "When you specify 'order', then individual display outputs (e.g. plots) will be interleaved.\n", |
|
265 | 266 | "\n", |
|
266 | 267 | "`%pxresult` takes the same output-ordering arguments as `%%px`, \n", |
|
267 | 268 | "so you can view the previous result in a variety of different ways with a few sequential calls to `%pxresult`:" |
|
268 | 269 | ] |
|
269 | 270 | }, |
|
270 | 271 | { |
|
271 | 272 | "cell_type": "code", |
|
272 | 273 | "collapsed": false, |
|
273 | 274 | "input": [ |
|
274 | 275 | "%pxresult --group-outputs=order" |
|
275 | 276 | ], |
|
276 | 277 | "language": "python", |
|
277 | 278 | "metadata": {}, |
|
278 | 279 | "outputs": [] |
|
279 | 280 | }, |
|
280 | 281 | { |
|
281 | 282 | "cell_type": "heading", |
|
282 | 283 | "level": 2, |
|
283 | 284 | "metadata": {}, |
|
284 | 285 | "source": [ |
|
285 | 286 | "Single-engine views" |
|
286 | 287 | ] |
|
287 | 288 | }, |
|
288 | 289 | { |
|
289 | 290 | "cell_type": "markdown", |
|
290 | 291 | "metadata": {}, |
|
291 | 292 | "source": [ |
|
292 | 293 | "When a DirectView has a single target, the output is a bit simpler (no prefixes on stdout/err, etc.):" |
|
293 | 294 | ] |
|
294 | 295 | }, |
|
295 | 296 | { |
|
296 | 297 | "cell_type": "code", |
|
297 | 298 | "collapsed": false, |
|
298 | 299 | "input": [ |
|
300 | "from __future__ import print_function\n", | |
|
301 | "\n", | |
|
299 | 302 | "def generate_output():\n", |
|
300 | 303 | " \"\"\"function for testing output\n", |
|
301 | 304 | " \n", |
|
302 | 305 | " publishes two outputs of each type, and returns something\n", |
|
303 | 306 | " \"\"\"\n", |
|
304 | 307 | " \n", |
|
305 | 308 | " import sys,os\n", |
|
306 | 309 | " from IPython.display import display, HTML, Math\n", |
|
307 | 310 | " \n", |
|
308 |
" print |
|
|
309 |
" print |
|
|
311 | " print(\"stdout\")\n", | |
|
312 | " print(\"stderr\", file=sys.stderr)\n", | |
|
310 | 313 | " \n", |
|
311 | 314 | " display(HTML(\"<b>HTML</b>\"))\n", |
|
312 | 315 | " \n", |
|
313 |
" print |
|
|
314 |
" print |
|
|
316 | " print(\"stdout2\")\n", | |
|
317 | " print(\"stderr2\", file=sys.stderr)\n", | |
|
315 | 318 | " \n", |
|
316 | 319 | " display(Math(r\"\\alpha=\\beta\"))\n", |
|
317 | 320 | " \n", |
|
318 | 321 | " return os.getpid()\n", |
|
319 | 322 | "\n", |
|
320 | 323 | "dv['generate_output'] = generate_output" |
|
321 | 324 | ], |
|
322 | 325 | "language": "python", |
|
323 | 326 | "metadata": {}, |
|
324 | 327 | "outputs": [] |
|
325 | 328 | }, |
|
326 | 329 | { |
|
327 | 330 | "cell_type": "markdown", |
|
328 | 331 | "metadata": {}, |
|
329 | 332 | "source": [ |
|
330 | 333 | "You can also have more than one set of parallel magics registered at a time.\n", |
|
331 | 334 | "\n", |
|
332 | 335 | "The `View.activate()` method takes a suffix argument, which is added to `'px'`." |
|
333 | 336 | ] |
|
334 | 337 | }, |
|
335 | 338 | { |
|
336 | 339 | "cell_type": "code", |
|
337 | 340 | "collapsed": false, |
|
338 | 341 | "input": [ |
|
339 | 342 | "e0 = rc[-1]\n", |
|
340 | 343 | "e0.block = True\n", |
|
341 | 344 | "e0.activate('0')" |
|
342 | 345 | ], |
|
343 | 346 | "language": "python", |
|
344 | 347 | "metadata": {}, |
|
345 | 348 | "outputs": [] |
|
346 | 349 | }, |
|
347 | 350 | { |
|
348 | 351 | "cell_type": "code", |
|
349 | 352 | "collapsed": false, |
|
350 | 353 | "input": [ |
|
351 | 354 | "%px0 generate_output()" |
|
352 | 355 | ], |
|
353 | 356 | "language": "python", |
|
354 | 357 | "metadata": {}, |
|
355 | 358 | "outputs": [] |
|
356 | 359 | }, |
|
357 | 360 | { |
|
358 | 361 | "cell_type": "code", |
|
359 | 362 | "collapsed": false, |
|
360 | 363 | "input": [ |
|
361 | 364 | "%px generate_output()" |
|
362 | 365 | ], |
|
363 | 366 | "language": "python", |
|
364 | 367 | "metadata": {}, |
|
365 | 368 | "outputs": [] |
|
366 | 369 | }, |
|
367 | 370 | { |
|
368 | 371 | "cell_type": "markdown", |
|
369 | 372 | "metadata": {}, |
|
370 | 373 | "source": [ |
|
371 | 374 | "As mentioned above, we can redisplay those same results with various grouping:" |
|
372 | 375 | ] |
|
373 | 376 | }, |
|
374 | 377 | { |
|
375 | 378 | "cell_type": "code", |
|
376 | 379 | "collapsed": false, |
|
377 | 380 | "input": [ |
|
378 | 381 | "%pxresult --group-outputs order" |
|
379 | 382 | ], |
|
380 | 383 | "language": "python", |
|
381 | 384 | "metadata": {}, |
|
382 | 385 | "outputs": [] |
|
383 | 386 | }, |
|
384 | 387 | { |
|
385 | 388 | "cell_type": "code", |
|
386 | 389 | "collapsed": false, |
|
387 | 390 | "input": [ |
|
388 | 391 | "%pxresult --group-outputs engine" |
|
389 | 392 | ], |
|
390 | 393 | "language": "python", |
|
391 | 394 | "metadata": {}, |
|
392 | 395 | "outputs": [] |
|
393 | 396 | }, |
|
394 | 397 | { |
|
395 | 398 | "cell_type": "heading", |
|
396 | 399 | "level": 2, |
|
397 | 400 | "metadata": {}, |
|
398 | 401 | "source": [ |
|
399 | 402 | "Parallel Exceptions" |
|
400 | 403 | ] |
|
401 | 404 | }, |
|
402 | 405 | { |
|
403 | 406 | "cell_type": "markdown", |
|
404 | 407 | "metadata": {}, |
|
405 | 408 | "source": [ |
|
406 | 409 | "When you raise exceptions with the parallel exception,\n", |
|
407 | 410 | "the CompositeError raised locally will display your remote traceback." |
|
408 | 411 | ] |
|
409 | 412 | }, |
|
410 | 413 | { |
|
411 | 414 | "cell_type": "code", |
|
412 | 415 | "collapsed": false, |
|
413 | 416 | "input": [ |
|
414 | 417 | "%%px\n", |
|
415 | 418 | "from numpy.random import random\n", |
|
416 | 419 | "A = random((100,100,'invalid shape'))" |
|
417 | 420 | ], |
|
418 | 421 | "language": "python", |
|
419 | 422 | "metadata": {}, |
|
420 | 423 | "outputs": [] |
|
421 | 424 | }, |
|
422 | 425 | { |
|
423 | 426 | "cell_type": "heading", |
|
424 | 427 | "level": 2, |
|
425 | 428 | "metadata": {}, |
|
426 | 429 | "source": [ |
|
427 | 430 | "Remote Cell Magics" |
|
428 | 431 | ] |
|
429 | 432 | }, |
|
430 | 433 | { |
|
431 | 434 | "cell_type": "markdown", |
|
432 | 435 | "metadata": {}, |
|
433 | 436 | "source": [ |
|
434 | 437 | "Remember, Engines are IPython too, so the cell that is run remotely by %%px can in turn use a cell magic." |
|
435 | 438 | ] |
|
436 | 439 | }, |
|
437 | 440 | { |
|
438 | 441 | "cell_type": "code", |
|
439 | 442 | "collapsed": false, |
|
440 | 443 | "input": [ |
|
441 | 444 | "%%px\n", |
|
442 | 445 | "%%timeit\n", |
|
443 | 446 | "from numpy.random import random\n", |
|
444 | 447 | "from numpy.linalg import norm\n", |
|
445 | 448 | "A = random((100,100))\n", |
|
446 | 449 | "norm(A, 2)" |
|
447 | 450 | ], |
|
448 | 451 | "language": "python", |
|
449 | 452 | "metadata": {}, |
|
450 | 453 | "outputs": [] |
|
451 | 454 | }, |
|
452 | 455 | { |
|
453 | 456 | "cell_type": "heading", |
|
454 | 457 | "level": 2, |
|
455 | 458 | "metadata": {}, |
|
456 | 459 | "source": [ |
|
457 | 460 | "Local Execution" |
|
458 | 461 | ] |
|
459 | 462 | }, |
|
460 | 463 | { |
|
461 | 464 | "cell_type": "markdown", |
|
462 | 465 | "metadata": {}, |
|
463 | 466 | "source": [ |
|
464 |
"As of IPython 0 |
|
|
467 | "As of IPython 1.0, you can instruct `%%px` to also execute the cell locally.\n", | |
|
465 | 468 | "This is useful for interactive definitions,\n", |
|
466 | 469 | "or if you want to load a data source everywhere,\n", |
|
467 | 470 | "not just on the engines." |
|
468 | 471 | ] |
|
469 | 472 | }, |
|
470 | 473 | { |
|
471 | 474 | "cell_type": "code", |
|
472 | 475 | "collapsed": false, |
|
473 | 476 | "input": [ |
|
474 | 477 | "%%px --local\n", |
|
475 | 478 | "import os\n", |
|
476 | 479 | "thispid = os.getpid()\n", |
|
477 |
"print |
|
|
480 | "print(thispid)" | |
|
478 | 481 | ], |
|
479 | 482 | "language": "python", |
|
480 | 483 | "metadata": {}, |
|
481 | 484 | "outputs": [] |
|
482 | 485 | } |
|
483 | 486 | ], |
|
484 | 487 | "metadata": {} |
|
485 | 488 | } |
|
486 | 489 | ] |
|
487 | 490 | } No newline at end of file |
@@ -1,101 +1,102 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 |
"name": " |
|
|
3 | "name": "" | |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "markdown", |
|
12 | 12 | "metadata": {}, |
|
13 | 13 | "source": [ |
|
14 | 14 | "# Distributed hello world\n", |
|
15 | 15 | "\n", |
|
16 | 16 | "Originally by Ken Kinder (ken at kenkinder dom com)" |
|
17 | 17 | ] |
|
18 | 18 | }, |
|
19 | 19 | { |
|
20 | 20 | "cell_type": "code", |
|
21 | 21 | "collapsed": true, |
|
22 | 22 | "input": [ |
|
23 | "from __future__ import print_function\n", | |
|
23 | 24 | "from IPython.parallel import Client" |
|
24 | 25 | ], |
|
25 | 26 | "language": "python", |
|
26 | 27 | "metadata": {}, |
|
27 | 28 | "outputs": [], |
|
28 | 29 | "prompt_number": 1 |
|
29 | 30 | }, |
|
30 | 31 | { |
|
31 | 32 | "cell_type": "code", |
|
32 | 33 | "collapsed": true, |
|
33 | 34 | "input": [ |
|
34 | 35 | "rc = Client()\n", |
|
35 | 36 | "view = rc.load_balanced_view()" |
|
36 | 37 | ], |
|
37 | 38 | "language": "python", |
|
38 | 39 | "metadata": {}, |
|
39 | 40 | "outputs": [], |
|
40 | 41 | "prompt_number": 2 |
|
41 | 42 | }, |
|
42 | 43 | { |
|
43 | 44 | "cell_type": "code", |
|
44 | 45 | "collapsed": true, |
|
45 | 46 | "input": [ |
|
46 | 47 | "def sleep_and_echo(t, msg):\n", |
|
47 | 48 | " import time\n", |
|
48 | 49 | " time.sleep(t)\n", |
|
49 | 50 | " return msg" |
|
50 | 51 | ], |
|
51 | 52 | "language": "python", |
|
52 | 53 | "metadata": {}, |
|
53 | 54 | "outputs": [], |
|
54 | 55 | "prompt_number": 3 |
|
55 | 56 | }, |
|
56 | 57 | { |
|
57 | 58 | "cell_type": "code", |
|
58 | 59 | "collapsed": true, |
|
59 | 60 | "input": [ |
|
60 | 61 | "world = view.apply_async(sleep_and_echo, 3, 'World!')\n", |
|
61 | 62 | "hello = view.apply_async(sleep_and_echo, 2, 'Hello')" |
|
62 | 63 | ], |
|
63 | 64 | "language": "python", |
|
64 | 65 | "metadata": {}, |
|
65 | 66 | "outputs": [], |
|
66 | 67 | "prompt_number": 4 |
|
67 | 68 | }, |
|
68 | 69 | { |
|
69 | 70 | "cell_type": "code", |
|
70 | 71 | "collapsed": false, |
|
71 | 72 | "input": [ |
|
72 |
"print |
|
|
73 |
"print |
|
|
73 | "print(\"Submitted tasks:\", hello.msg_ids + world.msg_ids)\n", | |
|
74 | "print(hello.get(), world.get())" | |
|
74 | 75 | ], |
|
75 | 76 | "language": "python", |
|
76 | 77 | "metadata": {}, |
|
77 | 78 | "outputs": [ |
|
78 | 79 | { |
|
79 | 80 | "output_type": "stream", |
|
80 | 81 | "stream": "stdout", |
|
81 | 82 | "text": [ |
|
82 | 83 | "Submitted tasks: ['04670c2d-b2fd-4b6b-a5ac-dee15e533683', 'fc802284-507b-4c29-a526-67396e17718c']\n", |
|
83 | 84 | "Hello World!\n" |
|
84 | 85 | ] |
|
85 | 86 | } |
|
86 | 87 | ], |
|
87 | 88 | "prompt_number": 6 |
|
88 | 89 | }, |
|
89 | 90 | { |
|
90 | 91 | "cell_type": "code", |
|
91 | 92 | "collapsed": false, |
|
92 | 93 | "input": [], |
|
93 | 94 | "language": "python", |
|
94 | 95 | "metadata": {}, |
|
95 | 96 | "outputs": [] |
|
96 | 97 | } |
|
97 | 98 | ], |
|
98 | 99 | "metadata": {} |
|
99 | 100 | } |
|
100 | 101 | ] |
|
101 | 102 | } No newline at end of file |
@@ -1,140 +1,141 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "name": "task1" |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "markdown", |
|
12 | 12 | "metadata": {}, |
|
13 | 13 | "source": [ |
|
14 | 14 | "# Simple task farming example" |
|
15 | 15 | ] |
|
16 | 16 | }, |
|
17 | 17 | { |
|
18 | 18 | "cell_type": "code", |
|
19 | 19 | "collapsed": true, |
|
20 | 20 | "input": [ |
|
21 | "from __future__ import print_function\n", | |
|
21 | 22 | "from IPython.parallel import Client" |
|
22 | 23 | ], |
|
23 | 24 | "language": "python", |
|
24 | 25 | "metadata": {}, |
|
25 | 26 | "outputs": [], |
|
26 | 27 | "prompt_number": 1 |
|
27 | 28 | }, |
|
28 | 29 | { |
|
29 | 30 | "cell_type": "markdown", |
|
30 | 31 | "metadata": {}, |
|
31 | 32 | "source": [ |
|
32 | 33 | "A `Client.load_balanced_view` is used to get the object used for working with load balanced tasks." |
|
33 | 34 | ] |
|
34 | 35 | }, |
|
35 | 36 | { |
|
36 | 37 | "cell_type": "code", |
|
37 | 38 | "collapsed": true, |
|
38 | 39 | "input": [ |
|
39 | 40 | "rc = Client()\n", |
|
40 | 41 | "v = rc.load_balanced_view()" |
|
41 | 42 | ], |
|
42 | 43 | "language": "python", |
|
43 | 44 | "metadata": {}, |
|
44 | 45 | "outputs": [], |
|
45 | 46 | "prompt_number": 2 |
|
46 | 47 | }, |
|
47 | 48 | { |
|
48 | 49 | "cell_type": "markdown", |
|
49 | 50 | "metadata": {}, |
|
50 | 51 | "source": [ |
|
51 | 52 | "Set the variable `d` on all engines:" |
|
52 | 53 | ] |
|
53 | 54 | }, |
|
54 | 55 | { |
|
55 | 56 | "cell_type": "code", |
|
56 | 57 | "collapsed": true, |
|
57 | 58 | "input": [ |
|
58 | 59 | "rc[:]['d'] = 30" |
|
59 | 60 | ], |
|
60 | 61 | "language": "python", |
|
61 | 62 | "metadata": {}, |
|
62 | 63 | "outputs": [], |
|
63 | 64 | "prompt_number": 3 |
|
64 | 65 | }, |
|
65 | 66 | { |
|
66 | 67 | "cell_type": "markdown", |
|
67 | 68 | "metadata": {}, |
|
68 | 69 | "source": [ |
|
69 | 70 | "Define a function that will be our task:" |
|
70 | 71 | ] |
|
71 | 72 | }, |
|
72 | 73 | { |
|
73 | 74 | "cell_type": "code", |
|
74 | 75 | "collapsed": true, |
|
75 | 76 | "input": [ |
|
76 | 77 | "def task(a):\n", |
|
77 | 78 | " return a, 10*d, a*10*d" |
|
78 | 79 | ], |
|
79 | 80 | "language": "python", |
|
80 | 81 | "metadata": {}, |
|
81 | 82 | "outputs": [], |
|
82 | 83 | "prompt_number": 4 |
|
83 | 84 | }, |
|
84 | 85 | { |
|
85 | 86 | "cell_type": "markdown", |
|
86 | 87 | "metadata": {}, |
|
87 | 88 | "source": [ |
|
88 | 89 | "Run the task once:" |
|
89 | 90 | ] |
|
90 | 91 | }, |
|
91 | 92 | { |
|
92 | 93 | "cell_type": "code", |
|
93 | 94 | "collapsed": true, |
|
94 | 95 | "input": [ |
|
95 | 96 | "ar = v.apply(task, 5)" |
|
96 | 97 | ], |
|
97 | 98 | "language": "python", |
|
98 | 99 | "metadata": {}, |
|
99 | 100 | "outputs": [], |
|
100 | 101 | "prompt_number": 5 |
|
101 | 102 | }, |
|
102 | 103 | { |
|
103 | 104 | "cell_type": "markdown", |
|
104 | 105 | "metadata": {}, |
|
105 | 106 | "source": [ |
|
106 | 107 | "Print the results:" |
|
107 | 108 | ] |
|
108 | 109 | }, |
|
109 | 110 | { |
|
110 | 111 | "cell_type": "code", |
|
111 | 112 | "collapsed": false, |
|
112 | 113 | "input": [ |
|
113 |
"print |
|
|
114 | "print(\"a, b, c: \", ar.get())" | |
|
114 | 115 | ], |
|
115 | 116 | "language": "python", |
|
116 | 117 | "metadata": {}, |
|
117 | 118 | "outputs": [ |
|
118 | 119 | { |
|
119 | 120 | "output_type": "stream", |
|
120 | 121 | "stream": "stdout", |
|
121 | 122 | "text": [ |
|
122 | 123 | "a, b, c: [5, 300, 1500]\n" |
|
123 | 124 | ] |
|
124 | 125 | } |
|
125 | 126 | ], |
|
126 | 127 | "prompt_number": 6 |
|
127 | 128 | }, |
|
128 | 129 | { |
|
129 | 130 | "cell_type": "code", |
|
130 | 131 | "collapsed": false, |
|
131 | 132 | "input": [], |
|
132 | 133 | "language": "python", |
|
133 | 134 | "metadata": {}, |
|
134 | 135 | "outputs": [] |
|
135 | 136 | } |
|
136 | 137 | ], |
|
137 | 138 | "metadata": {} |
|
138 | 139 | } |
|
139 | 140 | ] |
|
140 | 141 | } No newline at end of file |
@@ -1,125 +1,126 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 |
"name": " |
|
|
3 | "name": "" | |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "markdown", |
|
12 | 12 | "metadata": {}, |
|
13 | 13 | "source": [ |
|
14 | 14 | "# Load balanced map and parallel function decorator" |
|
15 | 15 | ] |
|
16 | 16 | }, |
|
17 | 17 | { |
|
18 | 18 | "cell_type": "code", |
|
19 | 19 | "collapsed": true, |
|
20 | 20 | "input": [ |
|
21 | "from __future__ import print_function\n", | |
|
21 | 22 | "from IPython.parallel import Client" |
|
22 | 23 | ], |
|
23 | 24 | "language": "python", |
|
24 | 25 | "metadata": {}, |
|
25 | 26 | "outputs": [], |
|
26 | 27 | "prompt_number": 1 |
|
27 | 28 | }, |
|
28 | 29 | { |
|
29 | 30 | "cell_type": "code", |
|
30 | 31 | "collapsed": false, |
|
31 | 32 | "input": [ |
|
32 | 33 | "rc = Client()\n", |
|
33 | 34 | "v = rc.load_balanced_view()" |
|
34 | 35 | ], |
|
35 | 36 | "language": "python", |
|
36 | 37 | "metadata": {}, |
|
37 | 38 | "outputs": [], |
|
38 | 39 | "prompt_number": 2 |
|
39 | 40 | }, |
|
40 | 41 | { |
|
41 | 42 | "cell_type": "code", |
|
42 | 43 | "collapsed": false, |
|
43 | 44 | "input": [ |
|
44 | 45 | "result = v.map(lambda x: 2*x, range(10))\n", |
|
45 |
"print |
|
|
46 | "print(\"Simple, default map: \", list(result))" | |
|
46 | 47 | ], |
|
47 | 48 | "language": "python", |
|
48 | 49 | "metadata": {}, |
|
49 | 50 | "outputs": [ |
|
50 | 51 | { |
|
51 | 52 | "output_type": "stream", |
|
52 | 53 | "stream": "stdout", |
|
53 | 54 | "text": [ |
|
54 | 55 | "Simple, default map: " |
|
55 | 56 | ] |
|
56 | 57 | }, |
|
57 | 58 | { |
|
58 | 59 | "output_type": "stream", |
|
59 | 60 | "stream": "stdout", |
|
60 | 61 | "text": [ |
|
61 | 62 | "[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n" |
|
62 | 63 | ] |
|
63 | 64 | } |
|
64 | 65 | ], |
|
65 | 66 | "prompt_number": 3 |
|
66 | 67 | }, |
|
67 | 68 | { |
|
68 | 69 | "cell_type": "code", |
|
69 | 70 | "collapsed": false, |
|
70 | 71 | "input": [ |
|
71 | 72 | "ar = v.map_async(lambda x: 2*x, range(10))\n", |
|
72 |
"print |
|
|
73 | "print(\"Submitted tasks, got ids: \", ar.msg_ids)\n", | |
|
73 | 74 | "result = ar.get()\n", |
|
74 |
"print |
|
|
75 | "print(\"Using a mapper: \", result)" | |
|
75 | 76 | ], |
|
76 | 77 | "language": "python", |
|
77 | 78 | "metadata": {}, |
|
78 | 79 | "outputs": [ |
|
79 | 80 | { |
|
80 | 81 | "output_type": "stream", |
|
81 | 82 | "stream": "stdout", |
|
82 | 83 | "text": [ |
|
83 | 84 | "Submitted tasks, got ids: ['d482fcb3-f8e9-41ff-ba16-9fd4118324f1', 'e4fe38dd-8a4d-4f3a-a111-e4c9fdbea7c3', '580431f4-ac66-4517-b03e-a58aa690a87b', '19a012cf-5d9d-4cf3-9656-d56263958c0e', '012ebbb5-5def-47ad-a247-20f88d2c8980', '0dea6cdb-5b22-4bac-a1bb-7544c0ef44e6', '909d073f-7eee-42a7-8f3b-8f7aa32e7639', 'be6c7466-d541-47a0-b12d-bc408d40ad77', 'b97b5967-a5a3-45c5-95cc-44e0823fd646', '69b06902-9526-42d9-bda6-c943be19cc5a']\n", |
|
84 | 85 | "Using a mapper: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n" |
|
85 | 86 | ] |
|
86 | 87 | } |
|
87 | 88 | ], |
|
88 | 89 | "prompt_number": 4 |
|
89 | 90 | }, |
|
90 | 91 | { |
|
91 | 92 | "cell_type": "code", |
|
92 | 93 | "collapsed": false, |
|
93 | 94 | "input": [ |
|
94 | 95 | "@v.parallel(block=True)\n", |
|
95 | 96 | "def f(x): return 2*x\n", |
|
96 | 97 | "\n", |
|
97 | 98 | "result = f.map(range(10))\n", |
|
98 |
"print |
|
|
99 | "print(\"Using a parallel function: \", result)" | |
|
99 | 100 | ], |
|
100 | 101 | "language": "python", |
|
101 | 102 | "metadata": {}, |
|
102 | 103 | "outputs": [ |
|
103 | 104 | { |
|
104 | 105 | "output_type": "stream", |
|
105 | 106 | "stream": "stdout", |
|
106 | 107 | "text": [ |
|
107 | 108 | "Using a parallel function: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n" |
|
108 | 109 | ] |
|
109 | 110 | } |
|
110 | 111 | ], |
|
111 | 112 | "prompt_number": 5 |
|
112 | 113 | }, |
|
113 | 114 | { |
|
114 | 115 | "cell_type": "code", |
|
115 | 116 | "collapsed": false, |
|
116 | 117 | "input": [], |
|
117 | 118 | "language": "python", |
|
118 | 119 | "metadata": {}, |
|
119 | 120 | "outputs": [] |
|
120 | 121 | } |
|
121 | 122 | ], |
|
122 | 123 | "metadata": {} |
|
123 | 124 | } |
|
124 | 125 | ] |
|
125 | 126 | } No newline at end of file |
@@ -1,269 +1,269 b'' | |||
|
1 | 1 | { |
|
2 | 2 | "metadata": { |
|
3 | 3 | "name": "" |
|
4 | 4 | }, |
|
5 | 5 | "nbformat": 3, |
|
6 | 6 | "nbformat_minor": 0, |
|
7 | 7 | "worksheets": [ |
|
8 | 8 | { |
|
9 | 9 | "cells": [ |
|
10 | 10 | { |
|
11 | 11 | "cell_type": "heading", |
|
12 | 12 | "level": 1, |
|
13 | 13 | "metadata": {}, |
|
14 | 14 | "source": [ |
|
15 | 15 | "Basic Output" |
|
16 | 16 | ] |
|
17 | 17 | }, |
|
18 | 18 | { |
|
19 | 19 | "cell_type": "code", |
|
20 | 20 | "collapsed": false, |
|
21 | 21 | "input": [ |
|
22 | 22 | "from IPython.display import display" |
|
23 | 23 | ], |
|
24 | 24 | "language": "python", |
|
25 | 25 | "metadata": {}, |
|
26 | 26 | "outputs": [] |
|
27 | 27 | }, |
|
28 | 28 | { |
|
29 | 29 | "cell_type": "code", |
|
30 | 30 | "collapsed": false, |
|
31 | 31 | "input": [ |
|
32 |
"print |
|
|
32 | "print('hi')" | |
|
33 | 33 | ], |
|
34 | 34 | "language": "python", |
|
35 | 35 | "metadata": {}, |
|
36 | 36 | "outputs": [] |
|
37 | 37 | }, |
|
38 | 38 | { |
|
39 | 39 | "cell_type": "code", |
|
40 | 40 | "collapsed": false, |
|
41 | 41 | "input": [ |
|
42 | 42 | "display('hi')" |
|
43 | 43 | ], |
|
44 | 44 | "language": "python", |
|
45 | 45 | "metadata": {}, |
|
46 | 46 | "outputs": [] |
|
47 | 47 | }, |
|
48 | 48 | { |
|
49 | 49 | "cell_type": "code", |
|
50 | 50 | "collapsed": false, |
|
51 | 51 | "input": [ |
|
52 | 52 | "1" |
|
53 | 53 | ], |
|
54 | 54 | "language": "python", |
|
55 | 55 | "metadata": {}, |
|
56 | 56 | "outputs": [] |
|
57 | 57 | }, |
|
58 | 58 | { |
|
59 | 59 | "cell_type": "code", |
|
60 | 60 | "collapsed": false, |
|
61 | 61 | "input": [ |
|
62 | 62 | "%matplotlib inline\n", |
|
63 | 63 | "import matplotlib.pyplot as plt\n", |
|
64 | 64 | "plt.plot([1,3,2])" |
|
65 | 65 | ], |
|
66 | 66 | "language": "python", |
|
67 | 67 | "metadata": {}, |
|
68 | 68 | "outputs": [] |
|
69 | 69 | }, |
|
70 | 70 | { |
|
71 | 71 | "cell_type": "code", |
|
72 | 72 | "collapsed": false, |
|
73 | 73 | "input": [ |
|
74 | 74 | "%%javascript\n", |
|
75 | 75 | "console.log(\"I ran!\");" |
|
76 | 76 | ], |
|
77 | 77 | "language": "python", |
|
78 | 78 | "metadata": {}, |
|
79 | 79 | "outputs": [] |
|
80 | 80 | }, |
|
81 | 81 | { |
|
82 | 82 | "cell_type": "code", |
|
83 | 83 | "collapsed": false, |
|
84 | 84 | "input": [ |
|
85 | 85 | "%%html\n", |
|
86 | 86 | "<b>bold</b>" |
|
87 | 87 | ], |
|
88 | 88 | "language": "python", |
|
89 | 89 | "metadata": {}, |
|
90 | 90 | "outputs": [] |
|
91 | 91 | }, |
|
92 | 92 | { |
|
93 | 93 | "cell_type": "code", |
|
94 | 94 | "collapsed": false, |
|
95 | 95 | "input": [ |
|
96 | 96 | "%%latex\n", |
|
97 | 97 | "$$\n", |
|
98 | 98 | "a = 5\n", |
|
99 | 99 | "$$" |
|
100 | 100 | ], |
|
101 | 101 | "language": "python", |
|
102 | 102 | "metadata": {}, |
|
103 | 103 | "outputs": [] |
|
104 | 104 | }, |
|
105 | 105 | { |
|
106 | 106 | "cell_type": "heading", |
|
107 | 107 | "level": 1, |
|
108 | 108 | "metadata": {}, |
|
109 | 109 | "source": [ |
|
110 | 110 | "input_request" |
|
111 | 111 | ] |
|
112 | 112 | }, |
|
113 | 113 | { |
|
114 | 114 | "cell_type": "code", |
|
115 | 115 | "collapsed": false, |
|
116 | 116 | "input": [ |
|
117 | 117 | "raw_input(\"prompt > \")" |
|
118 | 118 | ], |
|
119 | 119 | "language": "python", |
|
120 | 120 | "metadata": {}, |
|
121 | 121 | "outputs": [] |
|
122 | 122 | }, |
|
123 | 123 | { |
|
124 | 124 | "cell_type": "heading", |
|
125 | 125 | "level": 1, |
|
126 | 126 | "metadata": {}, |
|
127 | 127 | "source": [ |
|
128 | 128 | "set_next_input" |
|
129 | 129 | ] |
|
130 | 130 | }, |
|
131 | 131 | { |
|
132 | 132 | "cell_type": "code", |
|
133 | 133 | "collapsed": false, |
|
134 | 134 | "input": [ |
|
135 | 135 | "%%writefile tst.py\n", |
|
136 | 136 | "def foo():\n", |
|
137 | 137 | " pass\n" |
|
138 | 138 | ], |
|
139 | 139 | "language": "python", |
|
140 | 140 | "metadata": {}, |
|
141 | 141 | "outputs": [] |
|
142 | 142 | }, |
|
143 | 143 | { |
|
144 | 144 | "cell_type": "code", |
|
145 | 145 | "collapsed": false, |
|
146 | 146 | "input": [ |
|
147 | 147 | "%load tst.py" |
|
148 | 148 | ], |
|
149 | 149 | "language": "python", |
|
150 | 150 | "metadata": {}, |
|
151 | 151 | "outputs": [] |
|
152 | 152 | }, |
|
153 | 153 | { |
|
154 | 154 | "cell_type": "heading", |
|
155 | 155 | "level": 1, |
|
156 | 156 | "metadata": {}, |
|
157 | 157 | "source": [ |
|
158 | 158 | "Pager in execute_reply" |
|
159 | 159 | ] |
|
160 | 160 | }, |
|
161 | 161 | { |
|
162 | 162 | "cell_type": "code", |
|
163 | 163 | "collapsed": false, |
|
164 | 164 | "input": [ |
|
165 | 165 | "plt?" |
|
166 | 166 | ], |
|
167 | 167 | "language": "python", |
|
168 | 168 | "metadata": {}, |
|
169 | 169 | "outputs": [] |
|
170 | 170 | }, |
|
171 | 171 | { |
|
172 | 172 | "cell_type": "heading", |
|
173 | 173 | "level": 1, |
|
174 | 174 | "metadata": {}, |
|
175 | 175 | "source": [ |
|
176 | 176 | "object_info" |
|
177 | 177 | ] |
|
178 | 178 | }, |
|
179 | 179 | { |
|
180 | 180 | "cell_type": "code", |
|
181 | 181 | "collapsed": false, |
|
182 | 182 | "input": [ |
|
183 | "# press tab after parentheses\n", | |
|
183 | "# press shift-tab after parentheses\n", | |
|
184 | 184 | "int(" |
|
185 | 185 | ], |
|
186 | 186 | "language": "python", |
|
187 | 187 | "metadata": {}, |
|
188 | 188 | "outputs": [] |
|
189 | 189 | }, |
|
190 | 190 | { |
|
191 | 191 | "cell_type": "heading", |
|
192 | 192 | "level": 1, |
|
193 | 193 | "metadata": {}, |
|
194 | 194 | "source": [ |
|
195 | 195 | "complete" |
|
196 | 196 | ] |
|
197 | 197 | }, |
|
198 | 198 | { |
|
199 | 199 | "cell_type": "code", |
|
200 | 200 | "collapsed": false, |
|
201 | 201 | "input": [ |
|
202 | "# pres tab after f\n", | |
|
202 | "# press tab after f\n", | |
|
203 | 203 | "f" |
|
204 | 204 | ], |
|
205 | 205 | "language": "python", |
|
206 | 206 | "metadata": {}, |
|
207 | 207 | "outputs": [] |
|
208 | 208 | }, |
|
209 | 209 | { |
|
210 | 210 | "cell_type": "heading", |
|
211 | 211 | "level": 1, |
|
212 | 212 | "metadata": {}, |
|
213 | 213 | "source": [ |
|
214 | 214 | "clear_output" |
|
215 | 215 | ] |
|
216 | 216 | }, |
|
217 | 217 | { |
|
218 | 218 | "cell_type": "code", |
|
219 | 219 | "collapsed": false, |
|
220 | 220 | "input": [ |
|
221 | "import sys\n", | |
|
221 | "import sys, time\n", | |
|
222 | 222 | "from IPython.display import clear_output" |
|
223 | 223 | ], |
|
224 | 224 | "language": "python", |
|
225 | 225 | "metadata": {}, |
|
226 | 226 | "outputs": [] |
|
227 | 227 | }, |
|
228 | 228 | { |
|
229 | 229 | "cell_type": "code", |
|
230 | 230 | "collapsed": false, |
|
231 | 231 | "input": [ |
|
232 | 232 | "for i in range(10):\n", |
|
233 | 233 | " clear_output()\n", |
|
234 | 234 | " time.sleep(0.25)\n", |
|
235 |
" print |
|
|
235 | " print(i)\n", | |
|
236 | 236 | " sys.stdout.flush()\n", |
|
237 | 237 | " time.sleep(0.25)\n" |
|
238 | 238 | ], |
|
239 | 239 | "language": "python", |
|
240 | 240 | "metadata": {}, |
|
241 | 241 | "outputs": [] |
|
242 | 242 | }, |
|
243 | 243 | { |
|
244 | 244 | "cell_type": "code", |
|
245 | 245 | "collapsed": false, |
|
246 | 246 | "input": [ |
|
247 | 247 | "for i in range(10):\n", |
|
248 | 248 | " clear_output(wait=True)\n", |
|
249 | 249 | " time.sleep(0.25)\n", |
|
250 |
" print |
|
|
250 | " print(i)\n", | |
|
251 | 251 | " sys.stdout.flush()\n" |
|
252 | 252 | ], |
|
253 | 253 | "language": "python", |
|
254 | 254 | "metadata": {}, |
|
255 | 255 | "outputs": [] |
|
256 | 256 | }, |
|
257 | 257 | { |
|
258 | 258 | "cell_type": "code", |
|
259 | 259 | "collapsed": false, |
|
260 | 260 | "input": [], |
|
261 | 261 | "language": "python", |
|
262 | 262 | "metadata": {}, |
|
263 | 263 | "outputs": [] |
|
264 | 264 | } |
|
265 | 265 | ], |
|
266 | 266 | "metadata": {} |
|
267 | 267 | } |
|
268 | 268 | ] |
|
269 | 269 | } No newline at end of file |
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