Mercurial > hg > orthanc-book
annotate Sphinx/source/plugins/python.rst @ 703:a589668768d7
moving python samples in separate files (2)
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Fri, 11 Jun 2021 10:07:12 +0200 |
parents | 6e02cd89eb6a |
children | ba2403ebd4b7 |
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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9 |
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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 |
678 | 21 <https://hg.orthanc-server.com/orthanc/file/Orthanc-1.9.3/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:: python |
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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 Here is a basic Python script that registers two new routes in the |
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219 REST API: |
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220 |
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221 .. literalinclude:: python/extending-rest-api.py |
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222 :language: python |
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223 |
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224 .. highlight:: json |
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225 |
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226 Here is the associated minimal configuration file for Orthanc |
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227 (provided the Python script is saved as ``rest.py``):: |
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228 |
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229 { |
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230 "Plugins" : [ "." ], |
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231 "PythonScript" : "rest.py", |
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232 "PythonVerbose" : false |
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233 } |
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234 |
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235 .. highlight:: bash |
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236 |
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237 The route can then be accessed as:: |
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238 |
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239 $ curl http://localhost:8042/toto |
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240 ok |
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241 |
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242 |
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243 .. _python-changes: |
345 | 244 |
245 Listening to changes | |
246 .................... | |
247 | |
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248 This sample uploads a DICOM file as soon as Orthanc is started: |
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250 .. literalinclude:: python/listening-changes.py |
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251 :language: python |
345 | 252 |
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253 |
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254 .. warning:: |
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255 In releases <= 3.0 of the Python plugin, deadlocks might emerge if |
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256 you call other core primitives of Orthanc (such as the REST API) in |
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257 your callback function. This issue has been `fixed in release 3.1 |
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258 <https://hg.orthanc-server.com/orthanc-python/rev/46fe70776d61>`__. |
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259 |
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260 As a **temporary workaround** against such deadlocks in releases <= |
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261 3.0, if you have to call other primitives of Orthanc, you should make |
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262 these calls in a separate thread, passing the pending events to be |
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263 processed through a message queue. Here is the template of a possible |
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264 solution to postpone such deadlocks as much as possible by relying on |
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265 the multithreading primitives of Python: |
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266 |
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267 .. literalinclude:: python/changes-deadlock-3.0.py |
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268 :language: python |
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269 |
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270 Beware that **this workaround is imperfect** and deadlocks have been |
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271 observed even if using it! Make sure to upgrade your plugin to solve |
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272 this issue for good. Note that this temporary workaround is not needed |
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273 in releases >= 3.1 of the plugin. |
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274 |
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275 |
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276 |
345 | 277 Accessing the content of a new instance |
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278 ....................................... |
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279 |
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280 .. literalinclude:: python/accessing-new-instance.py |
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281 :language: python |
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282 |
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283 .. warning:: |
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284 Your callback function will be called synchronously with |
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285 the core of Orthanc. This implies that deadlocks might emerge if |
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286 you call other core primitives of Orthanc in your callback (such |
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287 deadlocks are particular visible in the presence of other plugins |
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288 or Lua scripts). It is thus strongly advised to avoid any call to |
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289 the REST API of Orthanc in the callback. If you have to call other |
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290 primitives of Orthanc, you should make these calls in a separate |
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291 thread, passing the pending events to be processed through a |
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292 message queue. |
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293 |
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294 |
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295 Calling pydicom |
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296 ............... |
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297 |
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298 Here is a sample Python plugin that registers a REST callback to dump |
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299 the content of the dataset of one given DICOM instance stored in |
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300 Orthanc, using `pydicom <https://pydicom.github.io/>`__: |
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301 |
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302 .. literalinclude:: python/pydicom.py |
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303 :language: python |
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304 |
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305 .. highlight:: bash |
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306 |
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307 This callback can be called as follows:: |
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308 |
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309 $ curl http://localhost:8042/pydicom/19816330-cb02e1cf-df3a8fe8-bf510623-ccefe9f5 |
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310 |
347 | 311 |
312 Auto-routing studies | |
313 .................... | |
314 | |
315 Here is a sample Python plugin that routes any :ref:`stable study | |
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316 <stable-resources>` to a modality named ``samples`` (as declared in the |
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317 ``DicomModalities`` configuration option): |
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319 .. literalinclude:: python/autorouting-1.py |
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320 :language: python |
348 | 321 |
539 | 322 Note that, if you want to use an orthanc plugin to transfer the study, |
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323 you should use the ``RestApiPostAfterPlugins()`` method: |
539 | 324 |
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325 .. literalinclude:: python/autorouting-2.py |
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326 :language: python |
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327 |
539 | 328 |
352 | 329 Rendering a thumbnail using PIL/Pillow |
330 ...................................... | |
348 | 331 |
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332 .. literalinclude:: python/pil.py |
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333 :language: python |
351 | 334 |
335 | |
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336 .. _python-introspection: |
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337 |
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338 Inspecting the available API |
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339 ............................ |
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340 |
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341 Thanks to Python's introspection primitives, it is possible to inspect |
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342 the API of the ``orthanc`` module in order to dump all the available |
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343 features: |
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344 |
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345 .. literalinclude:: python/inspect-api.py |
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346 :language: python |
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347 |
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348 |
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349 .. _python-scheduler: |
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350 |
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351 Scheduling a task for periodic execution |
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352 ........................................ |
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353 |
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354 .. highlight:: python |
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355 |
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356 The following Python script will periodically (every second) run the |
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357 function ``Hello()`` thanks to the ``threading`` module:: |
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358 |
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359 import orthanc |
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360 import threading |
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361 |
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362 TIMER = None |
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363 |
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364 def Hello(): |
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365 global TIMER |
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366 TIMER = None |
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367 orthanc.LogWarning("In Hello()") |
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368 # Do stuff... |
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369 TIMER = threading.Timer(1, Hello) # Re-schedule after 1 second |
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370 TIMER.start() |
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371 |
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372 def OnChange(changeType, level, resource): |
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373 if changeType == orthanc.ChangeType.ORTHANC_STARTED: |
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374 orthanc.LogWarning("Starting the scheduler") |
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375 Hello() |
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376 |
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377 elif changeType == orthanc.ChangeType.ORTHANC_STOPPED: |
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378 if TIMER != None: |
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379 orthanc.LogWarning("Stopping the scheduler") |
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380 TIMER.cancel() |
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381 |
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382 orthanc.RegisterOnChangeCallback(OnChange) |
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383 |
378
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384 |
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385 .. _python-metadata: |
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386 |
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387 Filtering and returning metadata |
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388 ................................ |
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389 |
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390 Besides the main DICOM tags, Orthanc associates some metadata to each |
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391 resource it stores (this includes the date of last update, the |
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392 transfer syntax, the remote AET...). People are often interested in |
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393 getting such metadata while calling the ``/tools/find`` route in the |
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394 :ref:`REST API <rest-find>`, or even in filtering this metadata the |
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395 same way they look for DICOM tags. |
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396 |
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397 This feature is not built in the core of Orthanc, as metadata is not |
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398 indexed in the Orthanc database, contrarily to the main DICOM |
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399 tags. Filtering metadata requires a linear search over all the |
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400 matching resources, which induces a cost in the performance. |
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401 |
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402 .. highlight:: python |
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403 |
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404 Nevertheless, here is a full sample Python script that overwrites the |
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405 ``/tools/find`` route in order to give access to metadata:: |
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406 |
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407 import json |
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408 import orthanc |
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409 import re |
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410 |
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411 # Get the path in the REST API to the given resource that was returned |
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412 # by a call to "/tools/find" |
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413 def GetPath(resource): |
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414 if resource['Type'] == 'Patient': |
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415 return '/patients/%s' % resource['ID'] |
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416 elif resource['Type'] == 'Study': |
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417 return '/studies/%s' % resource['ID'] |
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418 elif resource['Type'] == 'Series': |
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419 return '/series/%s' % resource['ID'] |
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420 elif resource['Type'] == 'Instance': |
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421 return '/instances/%s' % resource['ID'] |
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422 else: |
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423 raise Exception('Unknown resource level') |
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424 |
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425 def FindWithMetadata(output, uri, **request): |
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426 # The "/tools/find" route expects a POST method |
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427 if request['method'] != 'POST': |
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428 output.SendMethodNotAllowed('POST') |
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429 else: |
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430 # Parse the query provided by the user, and backup the "Expand" field |
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431 query = json.loads(request['body']) |
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432 |
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433 if 'Expand' in query: |
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434 originalExpand = query['Expand'] |
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435 else: |
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436 originalExpand = False |
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437 |
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438 # Call the core "/tools/find" route |
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439 query['Expand'] = True |
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440 answers = orthanc.RestApiPost('/tools/find', json.dumps(query)) |
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441 |
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442 # Loop over the matching resources |
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443 filteredAnswers = [] |
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444 for answer in json.loads(answers): |
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445 try: |
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446 # Read the metadata that is associated with the resource |
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447 metadata = json.loads(orthanc.RestApiGet('%s/metadata?expand' % GetPath(answer))) |
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448 |
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449 # Check whether the metadata matches the regular expressions |
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450 # that were provided in the "Metadata" field of the user request |
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451 isMetadataMatch = True |
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452 if 'Metadata' in query: |
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453 for (name, pattern) in query['Metadata'].items(): |
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454 if name in metadata: |
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455 value = metadata[name] |
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456 else: |
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457 value = '' |
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458 |
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459 if re.match(pattern, value) == None: |
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460 isMetadataMatch = False |
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461 break |
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462 |
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463 # If all the metadata matches the provided regular |
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464 # expressions, add the resource to the filtered answers |
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465 if isMetadataMatch: |
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466 if originalExpand: |
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467 answer['Metadata'] = metadata |
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468 filteredAnswers.append(answer) |
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469 else: |
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470 filteredAnswers.append(answer['ID']) |
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471 except: |
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472 # The resource was deleted since the call to "/tools/find" |
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473 pass |
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474 |
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475 # Return the filtered answers in the JSON format |
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476 output.AnswerBuffer(json.dumps(filteredAnswers, indent = 3), 'application/json') |
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477 |
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478 orthanc.RegisterRestCallback('/tools/find', FindWithMetadata) |
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479 |
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480 |
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481 **Warning:** In the sample above, the filtering of the metadata is |
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482 done using Python's `library for regular expressions |
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483 <https://docs.python.org/3/library/re.html>`__. It is evidently |
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484 possible to adapt this script in order to use the DICOM conventions |
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485 about `attribute matching |
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486 <http://dicom.nema.org/medical/dicom/2019e/output/chtml/part04/sect_C.2.2.2.html>`__. |
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487 |
469
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488 .. highlight:: bash |
378
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489 |
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490 Here is a sample call to retrieve all the studies that were last |
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491 updated in 2019 thanks to this Python script:: |
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492 |
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493 $ curl http://localhost:8042/tools/find -d '{"Level":"Study","Query":{},"Expand":true,"Metadata":{"LastUpdate":"^2019.*$"}}' |
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494 |
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495 |
469
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496 .. _python-paging: |
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497 |
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498 Implementing basic paging |
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499 ......................... |
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500 |
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501 .. highlight:: python |
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502 |
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503 As explained in the FAQ, the :ref:`Orthanc Explorer interface is |
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504 low-level <improving-interface>`, and is not adapted for |
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505 end-users. One common need is to implement paging of studies, which |
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506 calls for server-side sorting of studies. This can be done using the |
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507 following sample Python plugin that registers a new route |
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508 ``/sort-studies`` in the REST API of Orthanc:: |
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509 |
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510 import json |
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511 import orthanc |
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512 |
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513 def GetStudyDate(study): |
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514 if 'StudyDate' in study['MainDicomTags']: |
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515 return study['MainDicomTags']['StudyDate'] |
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516 else: |
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517 return '' |
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518 |
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519 def SortStudiesByDate(output, uri, **request): |
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520 if request['method'] == 'GET': |
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521 # Retrieve all the studies |
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522 studies = json.loads(orthanc.RestApiGet('/studies?expand')) |
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523 |
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524 # Sort the studies according to the "StudyDate" DICOM tag |
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525 studies = sorted(studies, key = GetStudyDate) |
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526 |
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527 # Read the limit/offset arguments provided by the user |
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528 offset = 0 |
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529 if 'offset' in request['get']: |
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530 offset = int(request['get']['offset']) |
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531 |
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532 limit = 0 |
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533 if 'limit' in request['get']: |
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534 limit = int(request['get']['limit']) |
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535 |
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536 # Truncate the list of studies |
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537 if limit == 0: |
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538 studies = studies[offset : ] |
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539 else: |
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540 studies = studies[offset : offset + limit] |
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541 |
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542 # Return the truncated list of studies |
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543 output.AnswerBuffer(json.dumps(studies), 'application/json') |
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544 else: |
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545 output.SendMethodNotAllowed('GET') |
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546 |
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547 orthanc.RegisterRestCallback('/sort-studies', SortStudiesByDate) |
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548 |
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549 |
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550 .. highlight:: bash |
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551 |
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552 Here is a sample call to this new REST route, that could be issued by |
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553 any JavaScript framework (the ``json_pp`` command-line pretty-prints a |
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554 JSON file):: |
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555 |
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556 $ curl http://localhost:8042/sort-studies | json_pp |
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557 |
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558 This route also implement paging (i.e. it can limit and offset the |
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559 returned studies):: |
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560 |
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561 $ curl 'http://localhost:8042/sort-studies?offset=2&limit=2' | json_pp |
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562 |
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563 Obviously, this basic sample can be improved in many ways. To improve |
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564 performance, one could for instance cache the result of |
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565 ``/studies?expand`` in memory by :ref:`listening to changes |
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566 <python-changes>` in the list of studies |
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567 (cf. ``orthanc.ChangeType.NEW_STUDY`` and |
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568 ``orthanc.ChangeType.DELETED``). |
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569 |
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570 |
551
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571 .. _python_excel: |
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572 |
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573 Creating a Microsoft Excel report |
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574 ................................. |
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575 |
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576 .. highlight:: python |
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577 |
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578 As Orthanc plugins have access to any installed Python module, it is |
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579 very easy to implement a server-side plugin that generates a report in |
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580 the Microsoft Excel ``.xls`` format. Here is a working example:: |
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581 |
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582 import StringIO |
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583 import json |
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584 import orthanc |
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585 import xlwt |
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586 |
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587 def CreateExcelReport(output, uri, **request): |
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588 if request['method'] != 'GET' : |
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589 output.SendMethodNotAllowed('GET') |
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590 else: |
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591 # Create an Excel writer |
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592 excel = xlwt.Workbook() |
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593 sheet = excel.add_sheet('Studies') |
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594 |
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595 # Loop over the studies stored in Orthanc |
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596 row = 0 |
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597 studies = orthanc.RestApiGet('/studies?expand') |
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598 for study in json.loads(studies): |
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599 sheet.write(row, 0, study['PatientMainDicomTags'].get('PatientID')) |
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600 sheet.write(row, 1, study['PatientMainDicomTags'].get('PatientName')) |
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601 sheet.write(row, 2, study['MainDicomTags'].get('StudyDescription')) |
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602 row += 1 |
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603 |
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604 # Serialize the Excel workbook to a string, and return it to the caller |
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605 # https://stackoverflow.com/a/15649139/881731 |
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606 b = StringIO.StringIO() |
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607 excel.save(b) |
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608 output.AnswerBuffer(b.getvalue(), 'application/vnd.ms-excel') |
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609 |
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610 orthanc.RegisterRestCallback('/report.xls', CreateExcelReport) |
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611 |
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612 If opening the ``http://localhost:8042/report.xls`` URI, this Python |
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613 will generate a workbook with one sheet that contains the list of |
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614 studies, with the patient ID, the patient name and the study |
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615 description. |
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616 |
469
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617 |
556
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618 .. _python_authorization: |
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619 |
697
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Handling DICOM SCP requests using a Python plugin
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620 Forbid or allow access to REST resources (authorization, new in 3.0) |
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621 .................................................................... |
556
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622 |
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623 .. highlight:: python |
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624 |
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625 The following Python script installs a callback that is triggered |
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626 whenever the HTTP server of Orthanc is accessed:: |
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627 |
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628 import orthanc |
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629 import pprint |
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630 |
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631 def Filter(uri, **request): |
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632 print('User trying to access URI: %s' % uri) |
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633 pprint.pprint(request) |
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634 return True # False to forbid access |
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635 |
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636 orthanc.RegisterIncomingHttpRequestFilter(Filter) |
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637 |
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638 If access is not granted, the ``Filter`` callback must return |
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639 ``False``. As a consequence, the HTTP status code would be set to |
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640 ``403 Forbidden``. If access is granted, the ``Filter`` must return |
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641 ``true``. The ``request`` argument contains more information about the |
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642 request (such as the HTTP headers, the IP address of the caller and |
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643 the GET arguments). |
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644 |
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645 Note that this is similar to the ``IncomingHttpRequestFilter()`` |
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646 callback that is available in :ref:`Lua scripts <lua-filter-rest>`. |
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647 |
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648 Thanks to Python, it is extremely easy to call remote Web services for |
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649 authorization. Here is an example using the ``requests`` library:: |
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650 |
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651 import json |
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652 import orthanc |
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653 import requests |
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654 |
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655 def Filter(uri, **request): |
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656 body = { |
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657 'uri' : uri, |
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658 'headers' : request['headers'] |
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659 } |
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660 r = requests.post('http://localhost:8000/authorize', |
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661 data = json.dumps(body)) |
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662 return r.json() ['granted'] # Must be a Boolean |
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663 |
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664 orthanc.RegisterIncomingHttpRequestFilter(Filter) |
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665 |
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666 .. highlight:: javascript |
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667 |
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668 This filter could be used together with the following Web service |
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669 implemented using `Node.js |
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670 <https://en.wikipedia.org/wiki/Node.js>`__:: |
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671 |
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672 const http = require('http'); |
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673 |
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674 const requestListener = function(req, res) { |
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675 let body = ''; |
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676 req.on('data', function(chunk) { |
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677 body += chunk; |
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678 }); |
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679 req.on('end', function() { |
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680 console.log(JSON.parse(body)); |
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681 var answer = { |
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682 'granted' : false // Forbid access |
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683 }; |
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684 res.writeHead(200); |
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685 res.end(JSON.stringify(answer)); |
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686 }); |
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687 } |
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688 |
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689 http.createServer(requestListener).listen(8000); |
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690 |
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691 |
695
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692 .. _python_create_dicom: |
556
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693 |
696 | 694 Creating DICOM instances (new in 3.2) |
695
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695 ..................................... |
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696 |
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697 .. highlight:: python |
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698 |
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699 The following sample Python script will write on the disk a new DICOM |
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700 instance including the traditional Lena sample image, and will decode |
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701 the single frame of this DICOM instance:: |
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702 |
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703 import json |
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704 import orthanc |
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705 |
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706 def OnChange(changeType, level, resource): |
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707 if changeType == orthanc.ChangeType.ORTHANC_STARTED: |
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708 tags = { |
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709 'SOPClassUID' : '1.2.840.10008.5.1.4.1.1.1', |
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710 'PatientID' : 'HELLO', |
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711 'PatientName' : 'WORLD', |
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712 } |
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713 |
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714 with open('Lena.png', 'rb') as f: |
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715 img = orthanc.UncompressImage(f.read(), orthanc.ImageFormat.PNG) |
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716 |
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717 s = orthanc.CreateDicom(json.dumps(tags), img, orthanc.CreateDicomFlags.GENERATE_IDENTIFIERS) |
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718 |
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719 with open('/tmp/sample.dcm', 'wb') as f: |
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720 f.write(s) |
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721 |
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722 dicom = orthanc.CreateDicomInstance(s) |
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723 frame = dicom.GetInstanceDecodedFrame(0) |
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724 print('Size of the frame: %dx%d' % (frame.GetImageWidth(), frame.GetImageHeight())) |
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725 |
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726 orthanc.RegisterOnChangeCallback(OnChange) |
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727 |
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728 |
697
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729 .. _python_dicom_scp: |
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730 |
697
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731 Handling DICOM SCP requests (new in 3.2) |
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732 ........................................ |
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733 |
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734 .. highlight:: python |
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735 |
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736 Starting with release 3.2 of the Python plugin, it is possible to |
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737 replace the C-FIND SCP and C-MOVE SCP of Orthanc by a Python |
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738 script. This feature can notably be used to create a custom DICOM |
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739 proxy. Here is a minimal example:: |
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740 |
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741 import json |
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742 import orthanc |
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743 import pprint |
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744 |
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745 def OnFind(answers, query, issuerAet, calledAet): |
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746 print('Received incoming C-FIND request from %s:' % issuerAet) |
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747 |
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748 answer = {} |
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749 for i in range(query.GetFindQuerySize()): |
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750 print(' %s (%04x,%04x) = [%s]' % (query.GetFindQueryTagName(i), |
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751 query.GetFindQueryTagGroup(i), |
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752 query.GetFindQueryTagElement(i), |
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753 query.GetFindQueryValue(i))) |
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754 answer[query.GetFindQueryTagName(i)] = ('HELLO%d-%s' % (i, query.GetFindQueryValue(i))) |
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755 |
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756 answers.FindAddAnswer(orthanc.CreateDicom( |
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757 json.dumps(answer), None, orthanc.CreateDicomFlags.NONE)) |
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758 |
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759 def OnMove(**request): |
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760 orthanc.LogWarning('C-MOVE request to be handled in Python: %s' % |
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761 json.dumps(request, indent = 4, sort_keys = True)) |
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762 |
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763 orthanc.RegisterFindCallback(OnFind) |
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764 orthanc.RegisterMoveCallback(OnMove) |
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765 |
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766 .. highlight:: text |
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767 |
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768 In this sample, the C-FIND SCP will send one single answer that |
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769 reproduces the values provided by the SCU:: |
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770 |
699 | 771 $ findscu localhost 4242 -S -k QueryRetrieveLevel=STUDY -k PatientName=TEST -k SeriesDescription= |
697
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772 I: --------------------------- |
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773 I: Find Response: 1 (Pending) |
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774 I: |
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775 I: # Dicom-Data-Set |
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776 I: # Used TransferSyntax: Little Endian Explicit |
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777 I: (0008,0005) CS [ISO_IR 100] # 10, 1 SpecificCharacterSet |
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778 I: (0008,0052) CS [HELLO0-STUDY] # 12, 1 QueryRetrieveLevel |
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779 I: (0008,103e) LO [HELLO1- ] # 8, 1 SeriesDescription |
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780 I: (0010,0010) PN [HELLO2-TEST ] # 12, 1 PatientName |
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781 I: |
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782 |
698 | 783 A more realistic Python script could for instance call the route |
784 ``/modalities/{...}/query`` in the :ref:`REST API <rest-find-scu>` of | |
785 Orthanc using ``orthanc.RestApiPost()``, in order to query the content | |
786 a remote modality through a second C-FIND SCU request (this time | |
787 issued by Orthanc as a SCU). | |
788 | |
697
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789 The C-MOVE SCP can be invoked as follows:: |
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790 |
699 | 791 $ movescu localhost 4242 -aem TARGET -aec SOURCE -aet MOVESCU -S -k QueryRetrieveLevel=IMAGE -k StudyInstanceUID=1.2.3.4 |
697
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792 |
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793 The C-MOVE request above would print the following information in the |
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794 Orthanc logs:: |
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795 |
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796 W0610 18:30:36.840865 PluginsManager.cpp:168] C-MOVE request to be handled in Python: { |
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797 "AccessionNumber": "", |
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798 "Level": "INSTANCE", |
699 | 799 "OriginatorAET": "MOVESCU", |
697
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800 "OriginatorID": 1, |
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801 "PatientID": "", |
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802 "SOPInstanceUID": "", |
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803 "SeriesInstanceUID": "", |
699 | 804 "SourceAET": "SOURCE", |
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805 "StudyInstanceUID": "1.2.3.4", |
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806 "TargetAET": "TARGET" |
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807 } |
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808 |
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809 It is now up to your Python callback to proces the C-MOVE SCU request, |
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810 for instance by calling the route ``/modalities/{...}/store`` in the |
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811 :ref:`REST API <rest-store-scu>` of Orthanc using |
700
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812 ``orthanc.RestApiPost()``. It is highly advised to create a Python |
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813 thread to handle the request, in order to avoid blocking Orthanc as |
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814 much as possible. |
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815 |
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816 |
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817 .. _python_worklists: |
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818 |
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819 Handling worklist SCP requests (new in 3.2) |
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820 ........................................... |
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821 |
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822 Starting with release 3.2 of the Python plugin, it is possible to |
701
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823 answer :ref:`worklist queries <worklist>` using a Python script. This |
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824 is especially useful to easily create a bridge between Orthanc, |
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825 HL7/FHIR messages and RIS systems. Indeed, Python provides many tools |
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826 to handle HL7 such as `python-hl7 library |
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827 <https://python-hl7.readthedocs.io/en/latest/>`__. |
700
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828 |
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829 The following Python script reproduces features similar to the |
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830 :ref:`sample modality worklists plugin <worklists-plugin>`: |
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831 |
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832 .. literalinclude:: python/worklist.py |
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833 :language: python |
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834 |
701
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835 .. highlight:: text |
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836 |
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837 Here is the result of this plugin on a sample call:: |
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838 |
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839 $ findscu -W -k "ScheduledProcedureStepSequence[0].Modality=MR" 127.0.0.1 4242 |
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840 I: --------------------------- |
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841 I: Find Response: 1 (Pending) |
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842 I: |
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843 I: # Dicom-Data-Set |
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844 I: # Used TransferSyntax: Little Endian Explicit |
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845 I: (0008,0005) CS [ISO_IR 100] # 10, 1 SpecificCharacterSet |
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846 I: (0040,0100) SQ (Sequence with explicit length #=1) # 18, 1 ScheduledProcedureStepSequence |
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847 I: (fffe,e000) na (Item with explicit length #=1) # 10, 1 Item |
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848 I: (0008,0060) CS [MR] # 2, 1 Modality |
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849 I: (fffe,e00d) na (ItemDelimitationItem for re-encoding) # 0, 0 ItemDelimitationItem |
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850 I: (fffe,e0dd) na (SequenceDelimitationItem for re-encod.) # 0, 0 SequenceDelimitationItem |
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851 I: |
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852 I: --------------------------- |
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853 I: Find Response: 2 (Pending) |
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854 I: |
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855 I: # Dicom-Data-Set |
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856 I: # Used TransferSyntax: Little Endian Explicit |
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857 I: (0008,0005) CS [ISO_IR 100] # 10, 1 SpecificCharacterSet |
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858 I: (0040,0100) SQ (Sequence with explicit length #=1) # 18, 1 ScheduledProcedureStepSequence |
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859 I: (fffe,e000) na (Item with explicit length #=1) # 10, 1 Item |
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860 I: (0008,0060) CS [MR] # 2, 1 Modality |
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861 I: (fffe,e00d) na (ItemDelimitationItem for re-encoding) # 0, 0 ItemDelimitationItem |
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862 I: (fffe,e0dd) na (SequenceDelimitationItem for re-encod.) # 0, 0 SequenceDelimitationItem |
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863 I: |
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864 |
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865 |
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866 |
351 | 867 Performance and concurrency |
868 --------------------------- | |
869 | |
471
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870 **Important:** This section only applies to UNIX-like systems. The |
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871 ``multiprocessing`` package will not work on Microsoft Windows as the |
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872 latter OS has a different model for `forking processes |
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873 <https://en.wikipedia.org/wiki/Fork_(system_call)>`__. |
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874 |
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875 Using slave processes |
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876 ..................... |
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877 |
351 | 878 Let us consider the following sample Python script that makes a |
702
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879 CPU-intensive computation on a REST callback: |
351 | 880 |
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881 .. literalinclude:: python/multiprocessing-1.py |
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882 :language: python |
351 | 883 |
884 .. highlight:: text | |
885 | |
886 Calling this REST route from the command-line returns the time that is | |
887 needed to compute 30 million times a squared root on your CPU:: | |
888 | |
889 $ curl http://localhost:8042/computation | |
890 computation done in 4.208 seconds | |
891 | |
892 Now, let us call this route three times concurrently (we use bash):: | |
893 | |
894 $ (curl http://localhost:8042/computation & curl http://localhost:8042/computation & curl http://localhost:8042/computation ) | |
895 computation done in 11.262 seconds | |
896 computation done in 12.457 seconds | |
897 computation done in 13.360 seconds | |
898 | |
899 As can be seen, the computation time has tripled. This means that the | |
900 computations were not distributed across the available CPU cores. | |
901 This might seem surprising, as Orthanc is a threaded server (in | |
902 Orthanc, a pool of C++ threads serves concurrent requests). | |
903 | |
904 The explanation is that the Python interpreter (`CPython | |
905 <https://en.wikipedia.org/wiki/CPython>`__ actually) is built on the | |
906 top of a so-called `Global Interpreter Lock (GIL) | |
907 <https://en.wikipedia.org/wiki/Global_interpreter_lock>`__. The GIL is | |
908 basically a mutex that protects all the calls to the Python | |
909 interpreter. If multiple C++ threads from Orthanc call a Python | |
353 | 910 callback, only one can proceed at any given time. Note however that |
911 the GIL only applies to the Python script: The baseline REST API of | |
912 Orthanc is not affected by the GIL. | |
351 | 913 |
914 The solution is to use the `multiprocessing primitives | |
915 <https://docs.python.org/3/library/multiprocessing.html>`__ of Python. | |
916 The "master" Python interpreter that is initially started by the | |
917 Orthanc plugin, can start several `children processes | |
918 <https://en.wikipedia.org/wiki/Process_(computing)>`__, each of these | |
919 processes running a separate Python interpreter. This allows to | |
920 offload intensive computations from the "master" Python interpreter of | |
921 Orthanc onto those "slave" interpreters. The ``multiprocessing`` | |
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922 library is actually quite straightforward to use: |
351 | 923 |
702
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924 .. literalinclude:: python/multiprocessing-2.py |
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925 :language: python |
351 | 926 |
927 .. highlight:: text | |
928 | |
929 Here is now the result of calling this route three times concurrently:: | |
930 | |
931 $ (curl http://localhost:8042/computation & curl http://localhost:8042/computation & curl http://localhost:8042/computation ) | |
932 computation done in 4.211 seconds | |
933 computation done in 4.215 seconds | |
934 computation done in 4.225 seconds | |
935 | |
936 As can be seen, the calls to the Python computation now fully run in | |
937 parallel (the time is cut down from 12 seconds to 4 seconds, the same | |
938 as for one isolated request). | |
939 | |
940 Note also how the ``multiprocessing`` library allows to make a fine | |
941 control over the computational resources that are available to the | |
942 Python script: The number of "slave" interpreters can be easily | |
943 changed in the constructor of the ``multiprocessing.Pool`` object, and | |
944 are fully independent of the threads used by the Orthanc server. | |
945 | |
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946 Obviously, an in-depth discussion about the ``multiprocessing`` |
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947 library is out of the scope of this document. There are many |
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948 references available on Internet. Also, note that ``threading`` is not |
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949 useful here, as Python multithreading is also limited by the GIL, and |
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950 is more targeted at dealing with costly I/O operations or with the |
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951 :ref:`scheduling of commands <python-scheduler>`. |
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952 |
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953 |
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954 Slave processes and the "orthanc" module |
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955 ........................................ |
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956 |
352 | 957 .. highlight:: python |
958 | |
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959 Very importantly, pay attention to the fact that **only the "master" |
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960 Python interpreter has access to the Orthanc SDK**. The "slave" |
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961 processes have no access to the ``orthanc`` module. |
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962 |
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963 You must write your Python plugin so as that all the calls to |
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964 ``orthanc`` are moved from the slaves process to the master |
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965 process. For instance, here is how you would parse a DICOM file in a |
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966 slave process: |
352 | 967 |
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968 .. literalinclude:: python/multiprocessing-3.py |
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969 :language: python |
352 | 970 |
971 Communication primitives such as ``multiprocessing.Queue`` are | |
972 available to exchange messages from the "slave" Python interpreters to | |
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973 the "master" Python interpreter for more advanced scenarios. |
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974 |
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975 NB: Starting with release 3.0 of the Python plugin, it is possible to |
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976 call the REST API of Orthanc from a slave process in a more direct |
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977 way. The function ``orthanc.GenerateRestApiAuthorizationToken()`` can |
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978 be used to create an authorization token that provides full access to |
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979 the REST API of Orthanc (without have to set credentials in your |
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980 plugin). Any HTTP client library for Python, such as `requests |
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981 <https://requests.readthedocs.io/en/master/>`__, can then be used to |
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982 access the REST API of Orthanc. Here is a minimal example: |
352 | 983 |
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984 .. literalinclude:: python/multiprocessing-4.py |
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985 :language: python |