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        "author": "Andrew Alcock, Aviser LLP, Singapore",
        "author_email": "dovetail@aviser.asia",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Topic :: Software Development :: Build Tools"
        ],
        "description": "Introducing Dovetail\n====================\n\nDovetail is a light-weight, multi-platform build tool for Python with\nContinuous Integration servers like Jenkins in mind.\n\n-----\n\n    **TL;DR**\n\n    Builds are complex, integrate many tools and sometimes must run on\n    many platforms. Writing good build scripts is hard.\n\n    Dovetail helps in all these areas, and is not a rip'n'replace for your\n    existing tools. You can readily automate a build using Dovetail.\n\n-----\n\nBuilding an application is not just running::\n\n    > python setup.py sdist\n\nWhat about:\n\n    * Building binary distributions *for several target platforms*\n    * Building the user documentation *and* the API docs?\n    * Running your unit tests, sometimes using several test frameworks?\n    * Installing your application in a clean virtual environment and running\n      user tests?\n    * Running code quality tools like\n      `Coverage <http://http://nedbatchelder.com/code/coverage/>`_ and\n      `Pylint <http://pypi.python.org/pypi/pylint/>`_?\n    * Tagging your code in your DVCS?\n    * Uploading the artifacts to a repository? That's probably at least an Egg,\n      a source distribution, documentation and your web site\n\n**How can you guarantee everyone, especially the new team members, are\nbuilding in the same way?**\n\nMany teams solve this by writing scripts, but that raises more questions:\n\n    * Do you have a *lot of scripts* lying around, each doing their\n      own thing, and little shared code?\n    * Do you have *operating system specific scripts* that do the same\n      thing, but on different operating systems?\n    * Are your scripts *reliable* and *maintainable*?\n\nIf you need to improve in these areas, **Dovetail can help**. Dovetail:\n\n    * Is **pure Python**, so the build runs everywhere and is maintainable\n    * Provides a **simple API** to externalize many common build\n      requirements\n    * There are **no new configuration file formats** or 4GLs of abstruse XML\n      or other syntaxes\n    * Makes it simple to **query the build environment** and adjust\n      the build appropriately\n    * **Audits all the build steps and decisions**\n    * Properly **catches build errors** and displays the details of what went wrong\n    * Makes it terribly easy to **automate the build** in a tool like\n      `Jenkins <http://jenkins-ci.org/>`_.\n\nA nice unexpected benefit for the maintainer was that it has become easier\nto build in my IDE; I also get precisely the same build from the command line.\n\nDovetail does not replace `Setuptools <http://pypi.python.org/pypi/setuptools/>`_\nor `distutils <http://docs.python.org/distutils/introduction.html>`_ -\nthese are the perfect tools for the specific build step of creating a distributable\npackage.\n\nFunctionality\n-------------\n\nA Dovetail build script is *a standard Python script*. Functions are declared to\nbe *tasks* in the build by decorating them. Further decorators declare:\n\n    * *Task dependencies*, with the same build script or across related files\n    * *Required packages*, which are downloaded and installed if not present\n    * *Conditions*, such as tests on environment variables or the file system.\n    * Build *directory structure*\n    * *Error conditions*, such as a non-zero return or output in stderr.\n\nDovetail works with numerous other tools to automate build steps, and has built-in\nintegration with `Virtualenv <http://http://www.virtualenv.org/>`_. Any build can\nbe run in either the Python version on the path, or any nominated virtual environment.\n\nDovetail installs packages as required, even in the middle of a build. This means that\nyou run a simple task in a complex build without installing all the documentation\nand test packages.\n\nExample\n-------\n\nA trivial example of a Dovetail build script is given below. It uses\n`Sphinx <http://sphinx.pocoo.org/>`_ to build the project documentation::\n\n    from dovetail import task, requires, check_result, call, mkdirs, do_if, IsDir\n    from os import path\n    from shutil import rmtree\n\n    DOCSOURCE = path.abspath(path.join(path.dirname(__file__), \"source\"))\n    BUILD     = path.abspath(path.join(path.dirname(__file__), \"..\", \"build\"))\n\n    @task                  # Declares the function clean() is a build task\n    @do_if(IsDir(BUILD))   # Only run if the build directory exists\n    def clean():\n        \"\"\"Clean the project of all build artifacts\"\"\"\n        rmtree(BUILD)\n\n    @task                  # Declares the function clean() is a build task\n    @requires('sphinx')    # Ensures the sphinx package is installed\n    @mkdirs(BUILD)         # Make the build directory if it doesn't exist\n    @check_result          # Fails the build if sphinx fails\n    def doc():\n        \"\"\"Builds the Sphinx User documentation\"\"\"\n        return call(\"sphinx-build {0} {1}\".format(DOCSOURCE, BUILD).split(' '))\n\nBuilds are run simply from the OS command line::\n\n    $ dovetail clean doc",
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        "license": "GPLv3+",
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        "name": "Dovetail",
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