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        "author": "Mike C. Fletcher",
        "author_email": "mcfletch@vrplumber.com",
        "bugtrack_url": null,
        "classifiers": [
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "RunSnakeRun\n===========\n\nprofile-viewer (RunSnakeRun) is a small GUI utility that allows you to\nview (Python) cProfile or Profile profiler dumps in a sortable GUI view.\n\u00a0It allows you to explore the profiler information using a \u201csquare map\u201d\nvisualization or sortable tables of data.\u00a0 It also (experimentally)\nallows you to view the output of the Meliae \u201cmemory analysis\u201d tool using\nthe same basic visualisations.\n\nFeatures\n--------\n\nRunSnakeRun is a simple program, it doesn\u2019t provide all the\nbells-and-whistles of a program like KCacheGrind, it\u2019s intended to allow\nfor profiling your Python programs, and just your Python programs. \u00a0What\nit does provide, for profile viewing:\n\n-  sortable data-grid views for raw profile information\n\n-  identity: function name, file-name, directory name\n-  time-spent: cumulative, cumulative-per, local and local-per time\n\n-  overall data-grid view\n-  (all) callers-of-this-function, (all) callees-of-this-function views\n\n-  squaremap view of call tree\n\n-  size proportional to amount of time spent by the given parent in the\n   given function\n\n-  squaremap view of packages/modules/functions\n\n-  size proportional to time spent in each package/module/function\n\n-  basic navigation (home, back, up)\n\nFor `Meliae <https://launchpad.net/meliae>`__ memory-dump viewing, it\nprovides:\n\n-  sortable data-grid views\n-  squaremap of memory-usage\n-  basic navigation\n\nInstallation\n------------\n\nYou will need to have all of wxPython,\n`SquareMap <http://pypi.python.org/pypi/SquareMap/>`__ and\n`RunSnakeRun <http://pypi.python.org/pypi/RunSnakeRun>`__ installed to\nuse RunSnakeRun. \u00a0You may also need the \u201cpython-profiler\u201d package for\nyour platform, which provides the pstats view.\u00a0 You will likely want to\nuse your platform wxPython package (i.e.\u00a0a pre-built binary). For\nDebian/Ubuntu distributions the prerequisite setup looks like this:\nRunSnakeRun and SquareMap will install well in a VirtualEnv if you would\nlike to keep them isolated (normally you do not want to use the\n``--no-site-packages`` flag if you are doing this).\u00a0 I recommend this\napproach rather than using easy\\_install directly on your Linux/OS-X\nhost.\n\n::\n\n    virtualenv runsnake\n    source runsnake/bin/activate\n\nIf you already have Python pip installed (a.k.a.\n`pip <https://github.com/pypa/pip>`__), you should be able to install\nthe Python packages with:\n\n::\n\n    pip install profile-viewer\n\nYou will require a modern `wxPython\n(e.g.\u00a04.0) <http://www.wxpython.org/>`__ and Python 3.x (e.g.\u00a03.3\nthrough 3.6 installation. \u00a0The setup will create a script named\n\u201crunsnake\u201d on Linux machines which launches the profile viewer.\u00a0 On OS-X\nmachines a wrapper script runsnake is created that runs the runsnake32\nexecutable with a flag to tell Python to use the 32-bit implementation\n(for wxPython compatibility).\u00a0 On Win32 machines, a\nScripts:raw-latex:`\\runsnake`.exe executable is created.\u00a0 If you have\nadded your scripts directory to the PATH then this will be available\nfrom the command-line.\n\nUsage\n-----\n\nIf you are new to profiling you may wish to check out:\n\n-  my (`Mike Fletcher <http://www.vrplumber.com/>`__\\ \u2019s) `presentation\n   at PyCon\n   2009 <http://blip.tv/pycon-us-videos-2009-2010-2011/introduction-to-python-profiling-1966784>`__\n   which tries to explain the use of profiling as a tool for\n   optimization in Python\n\n-  `W. Matthew Wilson\u2019s presentation at\n   PyOhio <http://blip.tv/file/3988199>`__ on optimizing Python code\n\ncProfile Viewing\n~~~~~~~~~~~~~~~~\n\nTo use cProfile to capture your application\u2019s profile data, either using\nthe command-line, like so:\n\n::\n\n    $ python -m cProfile -o <outputfilename> <script-name> <options>\n\nOr in code, like so:\n\n::\n\n    import cProfile\n    command = \"\"\"reactor.run()\"\"\"\n    cProfile.runctx( command, globals(), locals(), filename=\"OpenGLContext.profile\" )</pre>\n\nTo view the results of your run:\n\n::\n\n    python runsnake.py OpenGLContext.profile\n\nThere will be a brief delay as the application is created and begins the\nloading process, then you should see something like this:\n\n.. figure:: https://cloud.githubusercontent.com/assets/15351036/25775877/29669478-3275-11e7-9795-69c8218043d0.png\n   :alt: Screenshot of the application viewing a HotShot profile\n\n   Screenshot of the application viewing a HotShot profile\n\nClick on any column title to sort by that property within that list.\n\u00a0Select a record in the left-most list view to see a breakdown of that\nrecord in the right-side list views. \u00a0Choose the appropriate view on the\nright via the tabs. \u00a0You can resize the borders between the lists and\nsquare-map views. \u00a0You can select a package/module/function hierarchic\nview via the menus. \u00a0You can also toggle use of percentage displays\nthere.\n\nMeliae Memory Analysis\n~~~~~~~~~~~~~~~~~~~~~~\n\nNote: this feature is considered experimental, the memory consumed\nloading even a tiny meliae dump is enormous, so real-world programs will\nmake RunSnakeRun quite slow and require a very large amount of RAM (far\nmore than the process being viewed).\n\nTo install `Meliae <https://launchpad.net/meliae>`__, you will need a\nworking C extension compilation environment (Meliae uses a Cython\nextension):\n\n::\n\n    easy_install meliae\n\nNow instrument your application to be able to trigger a memory dump at\nthe moment you would like to capture, like so:\n\n::\n\n    from meliae import scanner\n    scanner.dump_all_objects( filename ) # you can pass a file-handle if you prefer\n\nThe memory dump will generally be quite large (e.g.\u00a02MB to describe an\napplication with 200KB of user-controllable memory usage (i.e.\u00a0not the\ninterpreter itself)) and for any real application will take an extremely\nlong time to load (multiple minutes for 16MB dumps).\n\n::\n\n    $ runsnakemem <filename>\n\n.. figure:: https://cloud.githubusercontent.com/assets/15351036/25775876/200c1290-3275-11e7-9fe7-6f943714bb11.png\n   :alt: Screenshot of a meliae memory view\n\n   Screenshot of a meliae memory view\n\nThe Meliae loader in RunSnakeRun performs the following simplifications:\n\n-  only displays memory which is reachable from a module (there is\n   normally > 1MB of unreachable objects included in a meliae dump)\n\n-  treats modules as memory-cost barriers, so referencing a module does\n   not cost the referrer anything\n-  treats all (reachable) references to an instance as sharing the cost\n   of the instance equally\n-  treats loops as being a separate object which holds all objects in\n   the loop, breaking inter-loop references but retaining child\n   references, all references to the loop members become references to\n   the loop\n-  eliminates dictionary objects from modules (always) and from types\n   and classes when the dictionary is only referenced by the class/type,\n   the cost of the dictionary is folded into the cost of the parent\n   object (note: this means that function **globals** references are\n   \u201c0-cost\u201d and do not create loops)\n-  compresses large numbers (>=10 currently) of \u201csimple\u201d objects of the\n   same type held by a single parent into a \u201c\u201d object with the type as\n   the name\n\nEven with those simplifications, however, the program is tracking most\nints, strings, tuples, lists, etc. separately, which uses a large amount\nof RAM and slows down the GUI substantially.\n\nCode Access and Contributions\n-----------------------------\n\nRunSnakeRun is reasonably stable. \u00a0I don\u2019t tend to do much work on it,\nas it tends to just work. \u00a0My (personal) current wish list for the\nproject follows:\n\n-  Speed up and reduce memory requirements for meliae loading\n-  Clean up the meliae loader (was grown organically from a quick hack\n   and doesn\u2019t particularly invite further hacking)\n\nIf you have an idea, feel free to check out the code and\u00a0implement the\nnew\u00a0feature. \u00a0I\u2019m certainly willing to entertain new features or bug-fix\nrequests as well. \u00a0The code is available in bzr here:\n\n::\n\n    git clone https://github.com/xoviat/profile-viewer.git\n    cd profile-viewer\n    pip install -e .\n\nYou can `contact me directly <mailto:mcfletch@vrplumber.com>`__ if you\u2019d\nlike to contribute. \u00a0Or you can just set up a bzr branch on LaunchPad\nand request a merge.\n\nRoadmap/Wish-list\n-----------------\n\nThis is just a listing of things that either I or others have requested\nas features:\n\n-  provide comparison views and \u201cprogress\u201d views that compare across\n   multiple profiles\n-  (re)support\u00a0Hotshot profile dumps (removed because Hotshot itself was\n   deprecated)\n-  support\u00a0Robert Kern\u2019s line\\_profiler module (line and import timings)\n-  support\u00a0IronPython profiles (with cleanup on load to remove \u201cnoise\u201d\n   functions)\n-  with a line-profiling module, allow per-line profile views\n-  support\u00a0(C)\u00a0calltree/cachegrind files (as used by kcachegrind)\n-  clean up the UI code (very hacky)\n-  configuration/storage of preferences such as column widths, rounded\n   corners, padding, etc.\n-  utility functions for capturing data\n\nOther Tools\n-----------\n\nRunSnakeRun is by no means a comprehensive tool-set for profiling, you\nmay want to have any or all of these other tools available for your\nprofiling needs:\n\n-  `Gprof2Dot <http://code.google.com/p/jrfonseca/wiki/Gprof2Dot>`__ \u2013\n   Converts various Profile formats into dot-format graphs\n\n-  Robert Kern\u2019s\n   `line\\_profiler <http://pypi.python.org/pypi/line_profiler/>`__ \u2013\n   Cython based Python profiler with line timings\n-  KCacheGrind \u2013 KDE viewer for CacheGrind C-level profiler or converted\n   Python profiles (via\n   `pyprof2calltree <http://pypi.python.org/pypi/pyprof2calltree/>`__),\n   KCacheGrind is basically what RunSnakeRun started off trying to\n   imitate save that RunSnakeRun was intended to be Python specific and\n   cross-platform\n-  `profilehooks <http://pypi.python.org/pypi/profilehooks>`__ \u2013 specify\n   which function to profile by using a decorator on a particular\n   function\n\nCopyright 2005-2017 Contributors\n\n",
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