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enh: clean up documentation
- point to michael's tutorials - reorganize display of workflows and interfaces
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doc/documentation.rst

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Previous versions: `0.12.0 <http://nipype.readthedocs.io/en/0.12.0/>`_ `0.11.0 <http://nipy.org/nipype/0.11.0>`_
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.. container:: doc2
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.. admonition:: Michael Notter's Nipype guide
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Be sure to read `Michael's excellent tutorials <https://miykael.github.io/nipype_tutorial/>`_.
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.. admonition:: Guides
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.. hlist::

doc/links_names.txt

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.. _pythonxy: https://python-xy.github.io/
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.. _EPD: http://www.enthought.com/products/epd.php
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.. _Traits: http://code.enthought.com/projects/traits/
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.. _Anaconda: https://www.continuum.io/downloads
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.. _Canopy: https://www.enthought.com/products/canopy/
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.. _Miniconda: https://conda.io/miniconda.html
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.. Python imaging projects
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.. _PyMVPA: http://www.pymvpa.org

doc/quickstart.rst

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:maxdepth: 1
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users/install
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users/vagrant
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Beginner's guide
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================
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Beginner's tutorials (IPython Notebooks). `Available here`__
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Michael Notter's Nipype tutorial. `Available here`__
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Michael Notter's Nipype guide. `Available here`__
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__ https://miykael.github.io/nipype_tutorial/
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Dissecting Nipype Workflows. `Available here`__
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Nipype workshop materials
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=========================
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Introductory slides [older]. `Available here`__
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Self-assessment questionnaire with links to learning about each piece. `Available here`__
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__ https://github.com/mwaskom/nipype_concepts
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__ http://miykael.github.com/nipype-beginner-s-guide/index.html
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__ http://slideviewer.herokuapp.com/url/raw.github.com/nipy/nipype/master/examples/nipype_tutorial.ipynb?theme=sky
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__ http://satra.github.com/intro2nipype
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Lecture slides `Available here`__
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User guides
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===========
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__ http://nipy.org/workshops/2017-03-boston/review.html
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__ http://nipy.org/workshops/2017-03-boston/index.html
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.. toctree::
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:maxdepth: 1
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`Docker containers <https://hub.docker.com/r/nipype/workshops/tags/>`_
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`Github project for lectures <https://github.com/nipy/workshops/tree/gh-pages/2017-03-boston>`_
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`Github project for dockerfiles + notebooks <https://github.com/nipy/workshops/tree/master/170327-nipype>`_
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users/interface_tutorial
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users/pipeline_tutorial
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users/plugins
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users/debug
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`All notebooks visualized <http://nbviewer.jupyter.org/github/nipy/workshops/tree/master/170327-nipype/notebooks/>`_
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Developer guides
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================
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:maxdepth: 1
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devel/writing_custom_interfaces
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devel/gitwash/index
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.. include:: links_names.txt
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Useful links for beginners
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===========================
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Getting started with Python - Tutorials. `Available here`__
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Python for Beginners `Available here`__
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__ http://www.codecademy.com/en/tracks/python
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__ https://www.python.org/about/gettingstarted/

doc/users/index.rst

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:maxdepth: 2
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install
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vagrant
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interface_tutorial
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caching_tutorial
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.. toctree::
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:maxdepth: 1
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pipeline_tutorial
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plugins
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config_file
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debug

doc/users/install.rst

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Nipype for users
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----------------
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Using conda
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~~~~~~~~~~~
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Installing nipype from the conda-forge channel can be achieved by adding conda-forge to your channels with::
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conda config --add channels conda-forge
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Using docker
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~~~~~~~~~~~~
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You can follow the `Nipype tutorial <https://miykael.github.io/nipype_tutorial/>`_
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Once the conda-forge channel has been enabled, nipype can be installed with::
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Using conda
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~~~~~~~~~~~
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conda install nipype
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Installing nipype from the conda-forge channel can be achieved by::
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conda install --channel conda-forge nipype
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It is possible to list all of the versions of nipype available on your platform with::
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If you already have a Python environment set up, you can do::
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easy_install nipype
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or::
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pip install nipype
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If you want to install all the optional features of ``nipype``,
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use the following command (only for ``nipype>=0.13``)::
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use the following command::
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pip install nipype[all]
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Available options are::
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'doc': ['Sphinx>=1.4', 'matplotlib', 'pydotplus'],
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'tests': TESTS_REQUIRES,
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'nipy': ['nitime', 'nilearn', 'dipy', 'nipy', 'matplotlib'],
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'profiler': ['psutil'],
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'duecredit': ['duecredit'],
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'xvfbwrapper': ['xvfbwrapper'],
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Debian and Ubuntu
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~~~~~~~~~~~~~~~~~
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Mac OS X
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~~~~~~~~
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The easiest way to get nipype running on Mac OS X is to install Anaconda_ or
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Canopy_ and then add nipype by executing::
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The easiest way to get nipype running on Mac OS X is to install Miniconda_ and
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follow the instructions above. If you have a non-conda environment you can
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install nipype by typing::
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easy_install nipype
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pip install nipype
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Note that the above procedure may require availability of gcc on your system
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path to compile the traits package.
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From source
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``nipype-x.y`` directory and install nipype using::
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python setup.py install
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pip install .
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**Note:** Depending on permissions you may need to use ``sudo``.
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Testing the install
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The best way to test the install is checking nipype's version ::
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The best way to test the install is checking nipype's version and then running
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the tests::
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python -c "import nipype; print(nipype.__version__)"
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python -c "import nipype; nipype.test()"
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Installation for developers
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---------------------------
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Developers should start `here <../devel/testing_nipype.html>`_.
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Recommended Software
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------------
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--------------------
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Strong Recommendations
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~~~~~~~~~~~~~~~~~~~~~~
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IPython_ 0.10.2 - 1.0.0
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Interactive python environment. This is necessary for some parallel
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components of the pipeline engine.
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IPython_
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Interactive python environment.
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Matplotlib_ 1.0 - 1.2
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Matplotlib_
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`RDFLib <http://rdflib.readthedocs.org/en/latest/>`_ 4.1
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RDFLibrary required for provenance export as RDF
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Required for building the documentation
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`Graphviz <http://www.graphviz.org/>`_
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Required for building the documentation. The python wrapper package (``graphviz``)
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and the program itself both need to be installed.
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Required for building the documentation.
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Interface Dependencies
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0.4 or later
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Nitime_
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(optional)

doc/users/resource_sched_profiler.rst

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.. _resource_sched_profiler:
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============================================
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=============================================
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Resource Scheduling and Profiling with Nipype
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=============================================
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The latest version of Nipype supports system resource scheduling and profiling.
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These features allows users to ensure high throughput of their data processing
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while also controlling the amount of computing resources a given workflow will

tools/interfacedocgen.py

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mvalues = m.split('.')
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if len(mvalues) > 3:
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index_prefix = '.'.join(mvalues[1:3])
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index_dir = os.path.join(outdir,
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index_prefix)
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index_file = index_dir + self.rst_extension
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if not os.path.exists(index_dir):
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os.makedirs(index_dir)
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header = """.. AUTO-GENERATED FILE -- DO NOT EDIT!
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{name}
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{underline}
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.. toctree::
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:maxdepth: 1
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:glob:
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{name}/*
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""".format(name=index_prefix,
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underline='='*len(index_prefix))
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with open(index_file, 'wt') as fp:
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fp.write(header)
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m = os.path.join(index_prefix,
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'.'.join(mvalues[3:]))
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outfile = os.path.join(outdir,
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m + self.rst_extension)
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fileobj = open(outfile, 'wt')

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