Mercurial > hg > orthanc-book
annotate Sphinx/source/plugins/python.rst @ 590:404aca6160f0
warning about deadlock in python
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Thu, 07 Jan 2021 09:03:34 +0100 |
parents | 090cc988c35e |
children | 2397b0e12bc8 |
rev | line source |
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1 .. _python-plugin: |
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2 |
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3 |
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4 Python plugin for Orthanc |
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5 ========================= |
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6 |
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7 .. contents:: |
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8 |
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10 Overview |
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11 -------- |
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12 |
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13 This plugin can be used to write :ref:`Orthanc plugins |
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14 <creating-plugins>` using the `Python programming language |
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15 <https://en.wikipedia.org/wiki/Python_(programming_language)>`__ |
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16 instead of the more complex C/C++ programming languages. |
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17 |
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18 Python plugins have access to more features and a more consistent SDK |
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19 than :ref:`Lua scripts <lua>`. The Python API is automatically |
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20 generated from the `Orthanc plugin SDK in C |
568 | 21 <https://hg.orthanc-server.com/orthanc/file/Orthanc-1.8.2/OrthancServer/Plugins/Include/orthanc/OrthancCPlugin.h>`__ |
345 | 22 using the `Clang <https://en.wikipedia.org/wiki/Clang>`__ compiler |
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23 front-end. |
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24 |
462 | 25 As of release 2.0 of the plugin, the coverage of the C SDK is about |
26 75% (119 functions are automatically wrapped in Python out of a total | |
27 of 157 functions in the Orthanc SDK 1.7.2). | |
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28 |
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29 |
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30 Source code |
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31 ----------- |
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32 |
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33 * Link to the `official releases of this plugin |
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34 <https://www.orthanc-server.com/browse.php?path=/plugin-python>`__. |
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35 |
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36 * Link to the `code repository |
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37 <https://hg.orthanc-server.com/orthanc-python/>`__. |
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38 |
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39 |
353 | 40 Licensing |
41 --------- | |
42 | |
43 Pay attention to the fact that this plugin is licensed under the terms | |
44 of the `AGPL license | |
45 <https://en.wikipedia.org/wiki/GNU_Affero_General_Public_License>`__. | |
46 | |
47 This has an important consequence: If you distribute Orthanc to | |
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48 clients together with one Python script, or if you put an Orthanc |
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49 server equipped with one Python script on a Web portal, you **must** |
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50 disclose the source code of your Python script to the Orthanc |
354 | 51 community under the terms of the AGPL license. |
52 | |
53 We suggest you to put the source code of your Python scripts on the | |
54 dedicated `"OrthancContributed" repository on GitHub | |
55 <https://github.com/jodogne/OrthancContributed/tree/master/Plugins>`__, | |
56 and/or to send it to the `Orthanc Users | |
57 <https://groups.google.com/forum/#!forum/orthanc-users>`__ discussion | |
58 group. | |
353 | 59 |
60 Check out the :ref:`FAQ about licensing <licensing>` for more context. | |
61 | |
62 | |
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63 Usage |
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64 ----- |
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65 |
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66 Docker |
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67 ...... |
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68 |
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69 .. highlight:: json |
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70 |
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71 The most direct way of starting Orthanc together with the Python |
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72 plugin is through :ref:`Docker <docker>`. Let's create the file |
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73 ``/tmp/hello.py`` that contains the following basic Python script:: |
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74 |
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75 print('Hello world!') |
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76 |
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77 .. highlight:: json |
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78 |
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79 Let's also create the file ``/tmp/orthanc.json`` that contains the |
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80 following minimal :ref:`configuration for Orthanc <configuration>`:: |
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81 |
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82 { |
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83 "StorageDirectory" : "/var/lib/orthanc/db", |
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84 "RemoteAccessAllowed" : true, |
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85 "Plugins" : [ |
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86 "/usr/local/share/orthanc/plugins" |
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87 ], |
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88 "PythonScript" : "/etc/orthanc/hello.py" |
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89 } |
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90 |
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91 .. highlight:: bash |
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92 |
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93 Given these two files, Orthanc can be started as follows:: |
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94 |
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95 $ docker run -p 4242:4242 -p 8042:8042 --rm \ |
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96 -v /tmp/orthanc.json:/etc/orthanc/orthanc.json:ro \ |
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97 -v /tmp/hello.py:/etc/orthanc/hello.py:ro \ |
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98 jodogne/orthanc-python |
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99 |
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100 .. highlight:: text |
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101 |
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102 You'll see the following excerpt in the log, which indicates that the Python plugin is properly loaded:: |
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103 |
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104 W0331 15:48:12.990661 PluginsManager.cpp:269] Registering plugin 'python' (version mainline) |
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105 W0331 15:48:12.990691 PluginsManager.cpp:168] Python plugin is initializing |
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106 W0331 15:48:12.990743 PluginsManager.cpp:168] Using Python script "hello.py" from directory: /etc/orthanc |
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107 W0331 15:48:12.990819 PluginsManager.cpp:168] Program name: /usr/local/sbin/Orthanc |
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108 Hello world! |
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109 |
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110 |
405 | 111 `Here <https://bitbucket.org/osimis/orthanc-setup-samples/src/master/docker/python/>`__ is a full example |
112 of a more complex setup using the :ref:`osimis/orthanc <docker-osimis>` images. | |
113 | |
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114 Compiling from source |
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115 ..................... |
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116 |
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117 .. highlight:: bash |
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118 |
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119 The procedure to compile this plugin from source is similar to that |
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120 for the :ref:`core of Orthanc <compiling>`. The following commands |
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121 should work for most UNIX-like distribution (including GNU/Linux):: |
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122 |
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123 $ mkdir Build |
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124 $ cd Build |
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125 $ cmake .. -DPYTHON_VERSION=3.7 -DSTATIC_BUILD=ON -DCMAKE_BUILD_TYPE=Release |
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126 $ make |
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127 |
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128 Before running CMake, make sure that the Python interpreter and its |
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129 associated development library are installed. On Ubuntu 18.04 LTS, you |
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130 would for instance install packages ``libpython3.7-dev`` and |
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131 ``python3.7``. |
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132 |
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133 The compilation will produce the shared library ``OrthancPython``, |
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134 that can be loaded by properly setting the ``Plugins`` |
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135 :ref:`configuration option <configuration>` of Orthanc. |
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136 |
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137 **Warning:** The shared library is only compatible with the Python |
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138 interpreter whose version corresponds to the value of the |
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139 ``PYTHON_VERSION`` argument that was given to CMake. |
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140 |
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141 **Note for OS X:** As indicated by `Stephen Douglas Scotti |
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142 <https://groups.google.com/g/orthanc-users/c/RnmZKFv8FaY/m/HhvOD2A2CAAJ>`__, |
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143 here is a sample invocation of CMake to force the version of Python to |
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144 be used on OS X:: |
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145 |
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146 $ cmake .. -DPYTHON_VERSION=3.8 -DSTATIC_BUILD=ON -DCMAKE_BUILD_TYPE=Release \ |
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147 -DPYTHON_LIBRARY=/usr/local/Cellar/python@3.8/3.8.5/Frameworks/Python.framework/Versions/3.8/lib/libpython3.8.dylib \ |
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148 -DPYTHON_INCLUDE_DIR=/usr/local/Cellar/python@3.8/3.8.5/Frameworks/Python.framework/Versions/3.8/include/python3.8/ |
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149 |
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150 |
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151 Microsoft Windows |
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152 ................. |
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153 |
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154 Pre-compiled binaries for Microsoft Windows `are also available |
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155 <https://www.orthanc-server.com/browse.php?path=/plugin-python>`__. |
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156 |
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157 Beware that one version of the Python plugin can only be run against |
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158 one version of the Python interpreter. This version is clearly |
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159 indicated in the filename of the precompiled binaries. |
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160 |
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161 .. highlight:: text |
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162 |
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163 You are of course free to compile the plugin from sources. You'll have |
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164 to explicitly specify the path to your Python installation while |
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165 invoking CMake. For instance:: |
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166 |
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167 C:\orthanc-python\Build> cmake .. -DPYTHON_VERSION=2.7 -DPYTHON_WINDOWS_ROOT=C:/Python27 \ |
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168 -DSTATIC_BUILD=ON -DCMAKE_BUILD_TYPE=Release -G "Visual Studio 15 2017" |
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169 |
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170 **Note about debug builds**: Usually, building Python modules such as the Python |
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171 plugin for Orthanc in debug mode (where ``_DEBUG`` is defined) leads to a module |
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172 (``.exe`` or ``.dll``) that requires a debug build of Python, and debug versions of all |
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173 the Python libraries. This is quite cumbersome, for it requires building Python |
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174 on your own or downloading additional debug files. |
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175 |
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176 Since using a debug build of Python is only necessary in very specific cases |
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177 (such as the debugging of code at the boundary between Python and an extension), |
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178 we have changed the default behavior to use the release Python library by default. |
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179 |
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180 This means that you are able to build this plugin in debug mode with the |
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181 standard Python distribution. |
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182 |
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183 In case you need to use the Python debug libraries, you can instruct the build |
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184 system to do so by setting the ``PYTHON_WINDOWS_USE_RELEASE_LIBS`` CMake option, |
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185 that is ``ON`` by default, to ``OFF``. The previous build example would then be, |
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186 should you require a full debug build:: |
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187 |
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188 C:\orthanc-python\Build> cmake .. -DPYTHON_VERSION=2.7 -DPYTHON_WINDOWS_ROOT=C:/Python27 \ |
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189 -DSTATIC_BUILD=ON -DPYTHON_WINDOWS_USE_RELEASE_LIBS=OFF \ |
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190 -DCMAKE_BUILD_TYPE=Debug -G "Visual Studio 15 2017" |
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191 |
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192 Please note that this CMake option only impacts **debug** builds under Windows, |
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193 when using (any version of) the Microsoft Visual Studio compiler. |
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194 |
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195 The precompiled binaries all use release (i.e. non-debug) versions of Python. |
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196 |
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197 |
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198 Configuration options |
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199 --------------------- |
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200 |
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201 The only two configuration options that are available for this plugin |
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202 are the following: |
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203 |
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204 * ``PythonScript`` indicates where the Python script is located. If |
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205 this configuration option is not provided, the Python plugin is not |
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206 started. |
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207 |
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208 * ``PythonVerbose`` is a Boolean value to make the Python interpreter |
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209 verbose. |
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210 |
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211 |
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212 Samples |
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213 ------- |
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214 |
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215 Extending the REST API |
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216 ...................... |
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217 |
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218 .. highlight:: python |
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219 |
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220 Here is a basic Python script that registers two new routes in the |
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221 REST API:: |
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222 |
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223 import orthanc |
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224 import pprint |
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225 |
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226 def OnRest(output, uri, **request): |
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227 pprint.pprint(request) |
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228 print('Accessing uri: %s' % uri) |
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229 output.AnswerBuffer('ok\n', 'text/plain') |
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230 |
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231 orthanc.RegisterRestCallback('/(to)(t)o', OnRest) |
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232 orthanc.RegisterRestCallback('/tata', OnRest) |
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233 |
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234 .. highlight:: json |
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235 |
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236 Here is the associated minimal configuration file for Orthanc |
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237 (provided the Python script is saved as ``rest.py``):: |
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238 |
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239 { |
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240 "Plugins" : [ "." ], |
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241 "PythonScript" : "rest.py", |
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242 "PythonVerbose" : false |
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243 } |
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244 |
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245 .. highlight:: bash |
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246 |
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247 The route can then be accessed as:: |
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248 |
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249 $ curl http://localhost:8042/toto |
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250 ok |
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251 |
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252 |
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253 .. _python-changes: |
345 | 254 |
255 Listening to changes | |
256 .................... | |
257 | |
346
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258 .. highlight:: python |
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259 |
345 | 260 This sample uploads a DICOM file as soon as Orthanc is started:: |
261 | |
262 import orthanc | |
263 | |
264 def OnChange(changeType, level, resource): | |
265 if changeType == orthanc.ChangeType.ORTHANC_STARTED: | |
266 print('Started') | |
267 | |
268 with open('/tmp/sample.dcm', 'rb') as f: | |
269 orthanc.RestApiPost('/instances', f.read()) | |
270 | |
271 elif changeType == orthanc.ChangeType.ORTHANC_STOPPED: | |
272 print('Stopped') | |
273 | |
274 elif changeType == orthanc.ChangeType.NEW_INSTANCE: | |
275 print('A new instance was uploaded: %s' % resource) | |
276 | |
277 orthanc.RegisterOnChangeCallback(OnChange) | |
278 | |
279 | |
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280 |
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281 .. warning:: |
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282 Your callback function will be called synchronously with |
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283 the core of Orthanc. This implies that deadlocks might emerge if |
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284 you call other core primitives of Orthanc in your callback (such |
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285 deadlocks are particular visible in the presence of other plugins |
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286 or Lua scripts). It is thus strongly advised to avoid any call to |
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287 the REST API of Orthanc in the callback. If you have to call other |
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288 primitives of Orthanc, you should make these calls in a separate |
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289 thread, passing the pending events to be processed through a |
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290 message queue. |
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291 |
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292 |
345 | 293 Accessing the content of a new instance |
346
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294 ....................................... |
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295 |
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296 .. highlight:: python |
345 | 297 |
298 :: | |
299 | |
300 import orthanc | |
301 import json | |
302 import pprint | |
303 | |
304 def OnStoredInstance(dicom, instanceId): | |
305 print('Received instance %s of size %d (transfer syntax %s, SOP class UID %s)' % ( | |
306 instanceId, dicom.GetInstanceSize(), | |
307 dicom.GetInstanceMetadata('TransferSyntax'), | |
308 dicom.GetInstanceMetadata('SopClassUid'))) | |
309 | |
310 # Print the origin information | |
311 if dicom.GetInstanceOrigin() == orthanc.InstanceOrigin.DICOM_PROTOCOL: | |
312 print('This instance was received through the DICOM protocol') | |
313 elif dicom.GetInstanceOrigin() == orthanc.InstanceOrigin.REST_API: | |
314 print('This instance was received through the REST API') | |
315 | |
316 # Print the DICOM tags | |
317 pprint.pprint(json.loads(dicom.GetInstanceSimplifiedJson())) | |
318 | |
319 orthanc.RegisterOnStoredInstanceCallback(OnStoredInstance) | |
346
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320 |
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321 |
590
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322 .. warning:: |
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323 Your callback function will be called synchronously with |
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324 the core of Orthanc. This implies that deadlocks might emerge if |
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325 you call other core primitives of Orthanc in your callback (such |
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326 deadlocks are particular visible in the presence of other plugins |
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327 or Lua scripts). It is thus strongly advised to avoid any call to |
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328 the REST API of Orthanc in the callback. If you have to call other |
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329 primitives of Orthanc, you should make these calls in a separate |
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330 thread, passing the pending events to be processed through a |
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331 message queue. |
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332 |
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333 |
346
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334 Calling pydicom |
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335 ............... |
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336 |
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337 .. highlight:: python |
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338 |
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339 Here is a sample Python plugin that registers a REST callback to dump |
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340 the content of the dataset of one given DICOM instance stored in |
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341 Orthanc, using `pydicom <https://pydicom.github.io/>`__:: |
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342 |
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343 import io |
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344 import orthanc |
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345 import pydicom |
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346 |
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347 def DecodeInstance(output, uri, **request): |
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348 if request['method'] == 'GET': |
347 | 349 # Retrieve the instance ID from the regular expression (*) |
346
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350 instanceId = request['groups'][0] |
347 | 351 # Get the content of the DICOM file |
346
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352 f = orthanc.GetDicomForInstance(instanceId) |
347 | 353 # Parse it using pydicom |
346
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354 dicom = pydicom.dcmread(io.BytesIO(f)) |
347 | 355 # Return a string representation the dataset to the caller |
346
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356 output.AnswerBuffer(str(dicom), 'text/plain') |
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357 else: |
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358 output.SendMethodNotAllowed('GET') |
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359 |
347 | 360 orthanc.RegisterRestCallback('/pydicom/(.*)', DecodeInstance) # (*) |
346
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361 |
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362 .. highlight:: bash |
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363 |
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364 This can be called as follows:: |
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365 |
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366 $ curl http://localhost:8042/pydicom/19816330-cb02e1cf-df3a8fe8-bf510623-ccefe9f5 |
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367 |
347 | 368 |
369 Auto-routing studies | |
370 .................... | |
371 | |
372 .. highlight:: python | |
373 | |
374 Here is a sample Python plugin that routes any :ref:`stable study | |
375 <lua-callbacks>` to a modality named ``samples`` (as declared in the | |
376 ``DicomModalities`` configuration option):: | |
377 | |
378 import orthanc | |
379 | |
380 def OnChange(changeType, level, resourceId): | |
381 if changeType == orthanc.ChangeType.STABLE_STUDY: | |
382 print('Stable study: %s' % resourceId) | |
383 orthanc.RestApiPost('/modalities/sample/store', resourceId) | |
384 | |
385 orthanc.RegisterOnChangeCallback(OnChange) | |
348 | 386 |
387 | |
539 | 388 Note that, if you want to use an orthanc plugin to transfer the study, |
389 you should use the ``RestApiPostAfterPlugins()`` method:: | |
390 | |
391 import orthanc | |
392 | |
393 def OnChange(changeType, level, resourceId): | |
394 if changeType == orthanc.ChangeType.STABLE_STUDY: | |
395 print('Stable study: %s' % resourceId) | |
396 orthanc.RestApiPostAfterPlugins('/dicom-web/servers/sample/store', resourceId) | |
397 | |
398 orthanc.RegisterOnChangeCallback(OnChange) | |
399 | |
400 | |
352 | 401 Rendering a thumbnail using PIL/Pillow |
402 ...................................... | |
348 | 403 |
404 .. highlight:: python | |
405 | |
406 :: | |
407 | |
408 from PIL import Image | |
409 import io | |
410 import orthanc | |
411 | |
412 def DecodeInstance(output, uri, **request): | |
413 if request['method'] == 'GET': | |
414 # Retrieve the instance ID from the regular expression (*) | |
415 instanceId = request['groups'][0] | |
416 | |
417 # Render the instance, then open it in Python using PIL/Pillow | |
418 png = orthanc.RestApiGet('/instances/%s/rendered' % instanceId) | |
419 image = Image.open(io.BytesIO(png)) | |
420 | |
421 # Downsize the image as a 64x64 thumbnail | |
422 image.thumbnail((64, 64), Image.ANTIALIAS) | |
423 | |
424 # Save the thumbnail as JPEG, then send the buffer to the caller | |
425 jpeg = io.BytesIO() | |
426 image.save(jpeg, format = "JPEG", quality = 80) | |
427 jpeg.seek(0) | |
428 output.AnswerBuffer(jpeg.read(), 'text/plain') | |
429 | |
430 else: | |
431 output.SendMethodNotAllowed('GET') | |
432 | |
433 orthanc.RegisterRestCallback('/pydicom/(.*)', DecodeInstance) # (*) | |
351 | 434 |
435 | |
369
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436 .. _python-introspection: |
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437 |
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438 Inspecting the available API |
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439 ............................ |
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440 |
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441 .. highlight:: python |
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442 |
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443 Thanks to Python's introspection primitives, it is possible to inspect |
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444 the API of the ``orthanc`` module in order to dump all the available |
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445 features:: |
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446 |
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447 import inspect |
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448 import numbers |
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449 import orthanc |
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450 |
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451 # Loop over the members of the "orthanc" module |
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452 for (name, obj) in inspect.getmembers(orthanc): |
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453 if inspect.isroutine(obj): |
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454 print('Function %s():\n Documentation: %s\n' % (name, inspect.getdoc(obj))) |
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455 |
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456 elif inspect.isclass(obj): |
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457 print('Class %s:\n Documentation: %s' % (name, inspect.getdoc(obj))) |
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458 |
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459 # Loop over the members of the class |
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460 for (subname, subobj) in inspect.getmembers(obj): |
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461 if isinstance(subobj, numbers.Number): |
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462 print(' - Enumeration value %s: %s' % (subname, subobj)) |
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463 elif (not subname.startswith('_') and |
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464 inspect.ismethoddescriptor(subobj)): |
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465 print(' - Method %s(): %s' % (subname, inspect.getdoc(subobj))) |
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466 print('') |
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467 |
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468 |
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469 .. _python-scheduler: |
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470 |
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471 Scheduling a task for periodic execution |
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472 ........................................ |
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473 |
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474 .. highlight:: python |
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475 |
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476 The following Python script will periodically (every second) run the |
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477 function ``Hello()`` thanks to the ``threading`` module:: |
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478 |
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479 import orthanc |
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480 import threading |
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481 |
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482 TIMER = None |
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483 |
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484 def Hello(): |
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485 global TIMER |
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486 TIMER = None |
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487 orthanc.LogWarning("In Hello()") |
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488 # Do stuff... |
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489 TIMER = threading.Timer(1, Hello) # Re-schedule after 1 second |
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490 TIMER.start() |
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491 |
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492 def OnChange(changeType, level, resource): |
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493 if changeType == orthanc.ChangeType.ORTHANC_STARTED: |
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494 orthanc.LogWarning("Starting the scheduler") |
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495 Hello() |
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496 |
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497 elif changeType == orthanc.ChangeType.ORTHANC_STOPPED: |
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498 if TIMER != None: |
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499 orthanc.LogWarning("Stopping the scheduler") |
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500 TIMER.cancel() |
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501 |
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502 orthanc.RegisterOnChangeCallback(OnChange) |
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503 |
378
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504 |
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505 .. _python-metadata: |
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506 |
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507 Filtering and returning metadata |
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508 ................................ |
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509 |
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510 Besides the main DICOM tags, Orthanc associates some metadata to each |
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511 resource it stores (this includes the date of last update, the |
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512 transfer syntax, the remote AET...). People are often interested in |
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513 getting such metadata while calling the ``/tools/find`` route in the |
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514 :ref:`REST API <rest-find>`, or even in filtering this metadata the |
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515 same way they look for DICOM tags. |
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516 |
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517 This feature is not built in the core of Orthanc, as metadata is not |
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518 indexed in the Orthanc database, contrarily to the main DICOM |
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519 tags. Filtering metadata requires a linear search over all the |
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520 matching resources, which induces a cost in the performance. |
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521 |
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522 .. highlight:: python |
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523 |
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524 Nevertheless, here is a full sample Python script that overwrites the |
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525 ``/tools/find`` route in order to give access to metadata:: |
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526 |
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527 import json |
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528 import orthanc |
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529 import re |
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530 |
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531 # Get the path in the REST API to the given resource that was returned |
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532 # by a call to "/tools/find" |
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533 def GetPath(resource): |
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534 if resource['Type'] == 'Patient': |
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535 return '/patients/%s' % resource['ID'] |
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536 elif resource['Type'] == 'Study': |
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537 return '/studies/%s' % resource['ID'] |
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538 elif resource['Type'] == 'Series': |
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539 return '/series/%s' % resource['ID'] |
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540 elif resource['Type'] == 'Instance': |
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541 return '/instances/%s' % resource['ID'] |
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542 else: |
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543 raise Exception('Unknown resource level') |
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544 |
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545 def FindWithMetadata(output, uri, **request): |
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546 # The "/tools/find" route expects a POST method |
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547 if request['method'] != 'POST': |
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548 output.SendMethodNotAllowed('POST') |
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549 else: |
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550 # Parse the query provided by the user, and backup the "Expand" field |
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551 query = json.loads(request['body']) |
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552 |
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553 if 'Expand' in query: |
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554 originalExpand = query['Expand'] |
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555 else: |
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556 originalExpand = False |
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557 |
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558 # Call the core "/tools/find" route |
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559 query['Expand'] = True |
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560 answers = orthanc.RestApiPost('/tools/find', json.dumps(query)) |
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561 |
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562 # Loop over the matching resources |
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563 filteredAnswers = [] |
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564 for answer in json.loads(answers): |
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565 try: |
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566 # Read the metadata that is associated with the resource |
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567 metadata = json.loads(orthanc.RestApiGet('%s/metadata?expand' % GetPath(answer))) |
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568 |
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569 # Check whether the metadata matches the regular expressions |
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570 # that were provided in the "Metadata" field of the user request |
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571 isMetadataMatch = True |
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572 if 'Metadata' in query: |
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573 for (name, pattern) in query['Metadata'].items(): |
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574 if name in metadata: |
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575 value = metadata[name] |
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576 else: |
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577 value = '' |
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578 |
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579 if re.match(pattern, value) == None: |
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580 isMetadataMatch = False |
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581 break |
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582 |
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583 # If all the metadata matches the provided regular |
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584 # expressions, add the resource to the filtered answers |
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585 if isMetadataMatch: |
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586 if originalExpand: |
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587 answer['Metadata'] = metadata |
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588 filteredAnswers.append(answer) |
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589 else: |
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590 filteredAnswers.append(answer['ID']) |
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591 except: |
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592 # The resource was deleted since the call to "/tools/find" |
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593 pass |
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594 |
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595 # Return the filtered answers in the JSON format |
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596 output.AnswerBuffer(json.dumps(filteredAnswers, indent = 3), 'application/json') |
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597 |
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598 orthanc.RegisterRestCallback('/tools/find', FindWithMetadata) |
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599 |
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600 |
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601 **Warning:** In the sample above, the filtering of the metadata is |
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602 done using Python's `library for regular expressions |
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603 <https://docs.python.org/3/library/re.html>`__. It is evidently |
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604 possible to adapt this script in order to use the DICOM conventions |
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605 about `attribute matching |
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606 <http://dicom.nema.org/medical/dicom/2019e/output/chtml/part04/sect_C.2.2.2.html>`__. |
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607 |
469
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608 .. highlight:: bash |
378
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609 |
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610 Here is a sample call to retrieve all the studies that were last |
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611 updated in 2019 thanks to this Python script:: |
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612 |
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613 $ curl http://localhost:8042/tools/find -d '{"Level":"Study","Query":{},"Expand":true,"Metadata":{"LastUpdate":"^2019.*$"}}' |
369
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614 |
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615 |
469
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616 .. _python-paging: |
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617 |
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618 Implementing basic paging |
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619 ......................... |
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620 |
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621 .. highlight:: python |
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622 |
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623 As explained in the FAQ, the :ref:`Orthanc Explorer interface is |
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624 low-level <improving-interface>`, and is not adapted for |
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625 end-users. One common need is to implement paging of studies, which |
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626 calls for server-side sorting of studies. This can be done using the |
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627 following sample Python plugin that registers a new route |
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628 ``/sort-studies`` in the REST API of Orthanc:: |
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629 |
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630 import json |
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631 import orthanc |
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632 |
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633 def GetStudyDate(study): |
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634 if 'StudyDate' in study['MainDicomTags']: |
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635 return study['MainDicomTags']['StudyDate'] |
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636 else: |
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637 return '' |
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638 |
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639 def SortStudiesByDate(output, uri, **request): |
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640 if request['method'] == 'GET': |
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641 # Retrieve all the studies |
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642 studies = json.loads(orthanc.RestApiGet('/studies?expand')) |
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643 |
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644 # Sort the studies according to the "StudyDate" DICOM tag |
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645 studies = sorted(studies, key = GetStudyDate) |
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646 |
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647 # Read the limit/offset arguments provided by the user |
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648 offset = 0 |
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649 if 'offset' in request['get']: |
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650 offset = int(request['get']['offset']) |
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651 |
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652 limit = 0 |
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653 if 'limit' in request['get']: |
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654 limit = int(request['get']['limit']) |
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655 |
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656 # Truncate the list of studies |
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657 if limit == 0: |
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658 studies = studies[offset : ] |
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659 else: |
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660 studies = studies[offset : offset + limit] |
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661 |
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662 # Return the truncated list of studies |
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663 output.AnswerBuffer(json.dumps(studies), 'application/json') |
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664 else: |
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665 output.SendMethodNotAllowed('GET') |
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666 |
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667 orthanc.RegisterRestCallback('/sort-studies', SortStudiesByDate) |
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668 |
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669 |
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670 .. highlight:: bash |
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671 |
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672 Here is a sample call to this new REST route, that could be issued by |
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673 any JavaScript framework (the ``json_pp`` command-line pretty-prints a |
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674 JSON file):: |
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675 |
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676 $ curl http://localhost:8042/sort-studies | json_pp |
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677 |
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678 This route also implement paging (i.e. it can limit and offset the |
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679 returned studies):: |
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680 |
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681 $ curl 'http://localhost:8042/sort-studies?offset=2&limit=2' | json_pp |
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682 |
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683 Obviously, this basic sample can be improved in many ways. To improve |
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684 performance, one could for instance cache the result of |
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685 ``/studies?expand`` in memory by :ref:`listening to changes |
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686 <python-changes>` in the list of studies |
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687 (cf. ``orthanc.ChangeType.NEW_STUDY`` and |
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688 ``orthanc.ChangeType.DELETED``). |
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689 |
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690 |
551
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691 .. _python_excel: |
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692 |
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693 Creating a Microsoft Excel report |
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694 ................................. |
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695 |
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696 .. highlight:: python |
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697 |
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698 As Orthanc plugins have access to any installed Python module, it is |
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699 very easy to implement a server-side plugin that generates a report in |
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700 the Microsoft Excel ``.xls`` format. Here is a working example:: |
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701 |
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702 import StringIO |
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703 import json |
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704 import orthanc |
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705 import xlwt |
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706 |
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707 def CreateExcelReport(output, uri, **request): |
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708 if request['method'] != 'GET' : |
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709 output.SendMethodNotAllowed('GET') |
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710 else: |
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711 # Create an Excel writer |
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712 excel = xlwt.Workbook() |
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713 sheet = excel.add_sheet('Studies') |
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714 |
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715 # Loop over the studies stored in Orthanc |
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716 row = 0 |
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717 studies = orthanc.RestApiGet('/studies?expand') |
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718 for study in json.loads(studies): |
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719 sheet.write(row, 0, study['PatientMainDicomTags'].get('PatientID')) |
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720 sheet.write(row, 1, study['PatientMainDicomTags'].get('PatientName')) |
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Python plugin: excel generation example
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721 sheet.write(row, 2, study['MainDicomTags'].get('StudyDescription')) |
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Python plugin: excel generation example
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722 row += 1 |
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|
723 |
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724 # Serialize the Excel workbook to a string, and return it to the caller |
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725 # https://stackoverflow.com/a/15649139/881731 |
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726 b = StringIO.StringIO() |
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Python plugin: excel generation example
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727 excel.save(b) |
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Python plugin: excel generation example
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728 output.AnswerBuffer(b.getvalue(), 'application/vnd.ms-excel') |
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Python plugin: excel generation example
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|
729 |
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730 orthanc.RegisterRestCallback('/report.xls', CreateExcelReport) |
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Python plugin: excel generation example
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|
731 |
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732 If opening the ``http://localhost:8042/report.xls`` URI, this Python |
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733 will generate a workbook with one sheet that contains the list of |
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Python plugin: excel generation example
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734 studies, with the patient ID, the patient name and the study |
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Python plugin: excel generation example
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|
735 description. |
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Python plugin: excel generation example
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|
736 |
469
46949efa5818
Implementing basic paging using a Python script
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737 |
556
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738 .. _python_authorization: |
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|
739 |
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740 Forbid or allow access to REST resources (authorization) |
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741 ........................................................ |
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742 |
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743 .. highlight:: python |
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744 |
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745 The following Python script installs a callback that is triggered |
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746 whenever the HTTP server of Orthanc is accessed:: |
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Python sample: "Forbid or allow access to REST resources (authorization)", deprecating advanced authorization plugin
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|
747 |
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748 import orthanc |
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749 import pprint |
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|
750 |
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751 def Filter(uri, **request): |
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752 print('User trying to access URI: %s' % uri) |
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753 pprint.pprint(request) |
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754 return True # False to forbid access |
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|
755 |
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756 orthanc.RegisterIncomingHttpRequestFilter(Filter) |
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|
757 |
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758 If access is not granted, the ``Filter`` callback must return |
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759 ``False``. As a consequence, the HTTP status code would be set to |
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760 ``403 Forbidden``. If access is granted, the ``Filter`` must return |
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761 ``true``. The ``request`` argument contains more information about the |
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762 request (such as the HTTP headers, the IP address of the caller and |
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763 the GET arguments). |
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764 |
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765 Note that this is similar to the ``IncomingHttpRequestFilter()`` |
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766 callback that is available in :ref:`Lua scripts <lua-filter-rest>`. |
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|
767 |
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768 Thanks to Python, it is extremely easy to call remote Web services for |
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769 authorization. Here is an example using the ``requests`` library:: |
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|
770 |
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771 import json |
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772 import orthanc |
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773 import requests |
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774 |
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775 def Filter(uri, **request): |
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776 body = { |
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777 'uri' : uri, |
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778 'headers' : request['headers'] |
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779 } |
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780 r = requests.post('http://localhost:8000/authorize', |
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781 data = json.dumps(body)) |
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782 return r.json() ['granted'] # Must be a Boolean |
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783 |
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784 orthanc.RegisterIncomingHttpRequestFilter(Filter) |
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|
785 |
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786 .. highlight:: javascript |
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787 |
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788 This filter could be used together with the following Web service |
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789 implemented using `Node.js |
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790 <https://en.wikipedia.org/wiki/Node.js>`__:: |
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|
791 |
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792 const http = require('http'); |
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793 |
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794 const requestListener = function(req, res) { |
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795 let body = ''; |
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796 req.on('data', function(chunk) { |
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797 body += chunk; |
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798 }); |
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799 req.on('end', function() { |
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800 console.log(JSON.parse(body)); |
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801 var answer = { |
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802 'granted' : false // Forbid access |
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803 }; |
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804 res.writeHead(200); |
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805 res.end(JSON.stringify(answer)); |
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806 }); |
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807 } |
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808 |
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809 http.createServer(requestListener).listen(8000); |
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810 |
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811 |
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812 |
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813 |
351 | 814 Performance and concurrency |
815 --------------------------- | |
816 | |
471
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817 **Important:** This section only applies to UNIX-like systems. The |
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818 ``multiprocessing`` package will not work on Microsoft Windows as the |
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819 latter OS has a different model for `forking processes |
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820 <https://en.wikipedia.org/wiki/Fork_(system_call)>`__. |
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821 |
555
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822 Using slave processes |
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823 ..................... |
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824 |
351 | 825 .. highlight:: python |
826 | |
827 Let us consider the following sample Python script that makes a | |
828 CPU-intensive computation on a REST callback:: | |
829 | |
830 import math | |
831 import orthanc | |
832 import time | |
833 | |
834 # CPU-intensive computation taking about 4 seconds | |
835 def SlowComputation(): | |
836 start = time.time() | |
837 for i in range(1000): | |
838 for j in range(30000): | |
839 math.sqrt(float(j)) | |
840 end = time.time() | |
841 duration = (end - start) | |
842 return 'computation done in %.03f seconds\n' % duration | |
843 | |
844 def OnRest(output, uri, **request): | |
845 answer = SlowComputation() | |
846 output.AnswerBuffer(answer, 'text/plain') | |
847 | |
848 orthanc.RegisterRestCallback('/computation', OnRest) | |
849 | |
850 | |
851 .. highlight:: text | |
852 | |
853 Calling this REST route from the command-line returns the time that is | |
854 needed to compute 30 million times a squared root on your CPU:: | |
855 | |
856 $ curl http://localhost:8042/computation | |
857 computation done in 4.208 seconds | |
858 | |
859 Now, let us call this route three times concurrently (we use bash):: | |
860 | |
861 $ (curl http://localhost:8042/computation & curl http://localhost:8042/computation & curl http://localhost:8042/computation ) | |
862 computation done in 11.262 seconds | |
863 computation done in 12.457 seconds | |
864 computation done in 13.360 seconds | |
865 | |
866 As can be seen, the computation time has tripled. This means that the | |
867 computations were not distributed across the available CPU cores. | |
868 This might seem surprising, as Orthanc is a threaded server (in | |
869 Orthanc, a pool of C++ threads serves concurrent requests). | |
870 | |
871 The explanation is that the Python interpreter (`CPython | |
872 <https://en.wikipedia.org/wiki/CPython>`__ actually) is built on the | |
873 top of a so-called `Global Interpreter Lock (GIL) | |
874 <https://en.wikipedia.org/wiki/Global_interpreter_lock>`__. The GIL is | |
875 basically a mutex that protects all the calls to the Python | |
876 interpreter. If multiple C++ threads from Orthanc call a Python | |
353 | 877 callback, only one can proceed at any given time. Note however that |
878 the GIL only applies to the Python script: The baseline REST API of | |
879 Orthanc is not affected by the GIL. | |
351 | 880 |
881 .. highlight:: python | |
882 | |
883 The solution is to use the `multiprocessing primitives | |
884 <https://docs.python.org/3/library/multiprocessing.html>`__ of Python. | |
885 The "master" Python interpreter that is initially started by the | |
886 Orthanc plugin, can start several `children processes | |
887 <https://en.wikipedia.org/wiki/Process_(computing)>`__, each of these | |
888 processes running a separate Python interpreter. This allows to | |
889 offload intensive computations from the "master" Python interpreter of | |
890 Orthanc onto those "slave" interpreters. The ``multiprocessing`` | |
891 library is actually quite straightforward to use:: | |
892 | |
893 import math | |
894 import multiprocessing | |
895 import orthanc | |
896 import signal | |
897 import time | |
898 | |
899 # CPU-intensive computation taking about 4 seconds | |
900 # (same code as above) | |
901 def SlowComputation(): | |
902 start = time.time() | |
903 for i in range(1000): | |
904 for j in range(30000): | |
905 math.sqrt(float(j)) | |
906 end = time.time() | |
907 duration = (end - start) | |
908 return 'computation done in %.03f seconds\n' % duration | |
909 | |
910 # Ignore CTRL+C in the slave processes | |
911 def Initializer(): | |
912 signal.signal(signal.SIGINT, signal.SIG_IGN) | |
913 | |
914 # Create a pool of 4 slave Python interpreters | |
915 POOL = multiprocessing.Pool(4, initializer = Initializer) | |
916 | |
917 def OnRest(output, uri, **request): | |
918 # Offload the call to "SlowComputation" onto one slave process. | |
919 # The GIL is unlocked until the slave sends its answer back. | |
920 answer = POOL.apply(SlowComputation) | |
921 output.AnswerBuffer(answer, 'text/plain') | |
922 | |
923 orthanc.RegisterRestCallback('/computation', OnRest) | |
924 | |
925 .. highlight:: text | |
926 | |
927 Here is now the result of calling this route three times concurrently:: | |
928 | |
929 $ (curl http://localhost:8042/computation & curl http://localhost:8042/computation & curl http://localhost:8042/computation ) | |
930 computation done in 4.211 seconds | |
931 computation done in 4.215 seconds | |
932 computation done in 4.225 seconds | |
933 | |
934 As can be seen, the calls to the Python computation now fully run in | |
935 parallel (the time is cut down from 12 seconds to 4 seconds, the same | |
936 as for one isolated request). | |
937 | |
938 Note also how the ``multiprocessing`` library allows to make a fine | |
939 control over the computational resources that are available to the | |
940 Python script: The number of "slave" interpreters can be easily | |
941 changed in the constructor of the ``multiprocessing.Pool`` object, and | |
942 are fully independent of the threads used by the Orthanc server. | |
943 | |
555
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944 Obviously, an in-depth discussion about the ``multiprocessing`` |
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945 library is out of the scope of this document. There are many |
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946 references available on Internet. Also, note that ``threading`` is not |
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947 useful here, as Python multithreading is also limited by the GIL, and |
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948 is more targeted at dealing with costly I/O operations or with the |
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949 :ref:`scheduling of commands <python-scheduler>`. |
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950 |
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951 |
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952 Slave processes and the "orthanc" module |
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953 ........................................ |
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954 |
352 | 955 .. highlight:: python |
956 | |
555
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957 Very importantly, pay attention to the fact that **only the "master" |
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958 Python interpreter has access to the Orthanc SDK**. The "slave" |
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959 processes have no access to the ``orthanc`` module. |
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960 |
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961 You must write your Python plugin so as that all the calls to |
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962 ``orthanc`` are moved from the slaves process to the master |
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963 process. For instance, here is how you would parse a DICOM file in a |
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964 slave process:: |
352 | 965 |
966 import pydicom | |
967 import io | |
968 | |
969 def OffloadedDicomParsing(dicom): | |
970 # No access to the "orthanc" library here, as we are in the slave process | |
971 dataset = pydicom.dcmread(io.BytesIO(dicom)) | |
972 return str(dataset) | |
973 | |
974 def OnRest(output, uri, **request): | |
975 # The call to "orthanc.RestApiGet()" is only possible in the master process | |
976 dicom = orthanc.RestApiGet('/instances/19816330-cb02e1cf-df3a8fe8-bf510623-ccefe9f5/file') | |
977 answer = POOL.apply(OffloadedDicomParsing, args = (dicom, )) | |
978 output.AnswerBuffer(answer, 'text/plain') | |
979 | |
980 Communication primitives such as ``multiprocessing.Queue`` are | |
981 available to exchange messages from the "slave" Python interpreters to | |
555
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982 the "master" Python interpreter for more advanced scenarios. |
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983 |
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984 NB: Starting with release 3.0 of the Python plugin, it is possible to |
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985 call the REST API of Orthanc from a slave process in a more direct |
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986 way. The function ``orthanc.GenerateRestApiAuthorizationToken()`` can |
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987 be used to create an authorization token that provides full access to |
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988 the REST API of Orthanc (without have to set credentials in your |
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989 plugin). Any HTTP client library for Python, such as `requests |
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990 <https://requests.readthedocs.io/en/master/>`__, can then be used to |
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991 access the REST API of Orthanc. Here is a minimal example:: |
352 | 992 |
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993 import json |
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994 import multiprocessing |
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995 import orthanc |
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996 import requests |
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997 import signal |
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998 |
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999 TOKEN = orthanc.GenerateRestApiAuthorizationToken() |
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1000 |
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1001 def SlaveProcess(): |
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1002 r = requests.get('http://localhost:8042/instances', |
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1003 headers = { 'Authorization' : TOKEN }) |
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1004 return json.dumps(r.json()) |
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1005 |
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1006 def Initializer(): |
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1007 signal.signal(signal.SIGINT, signal.SIG_IGN) |
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1008 |
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1009 POOL = multiprocessing.Pool(4, initializer = Initializer) |
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1010 |
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1011 def OnRest(output, uri, **request): |
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1012 answer = POOL.apply(SlaveProcess) |
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1013 output.AnswerBuffer(answer, 'text/plain') |
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1014 |
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1015 orthanc.RegisterRestCallback('/computation', OnRest) |