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        "author": "Xiaowei Zhan",
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        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Other Environment",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License (GPL)",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 3",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development :: Testing",
            "Topic :: System :: Monitoring"
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        "description": "Monitor Process Resources Usage\n===============================\n\n| Bench aims to be a handy tool with these functions:\n|  - Monitor CPU time (user time, system time, real time)\n|  - Monitor memory usage (virtual memory usage, resident memory usage)\n|  - Output to TSV(tab-delimited files)\n|  - Output benchmark metrics\n|  - Visualize performance metrics (memory consumptions) over time\n\nExamples\n========\n\nWe showed several examples below. **Please note that all output are\ntabularized for demonstration purpose.**\n\n-  Example 1: simple command.\n\n| This will start the process *sleep* for 2 seconds. The tabular output\n  below was from the actual command:\n  ``monitor.py sleep 2 2>&1 |column -t -s $'\\t'``.\n| If you simply run ``monitor.py sleep 2``, you will get tab-deliminated\n  outputs in standard error (stderr).\n\n::\n\n        $> monitor.py sleep 2\n        pid     ppid    utime  stime  rtime         rss     vms      maxRss  maxVms   avgRss    avgVms     cwd                                cmd\n        133692  133675  0.0    0.0    1.9368159771  774144  6066176  774144  6066176  774144.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 2\n\n-  Example 2: complex shell commands with sampling interval equaling to\n   0.1 second\n\nThis example will use shell to start 3 processes: ``sleep 2``,\n``sleep 4`` and ``seq 1000000``. You can see bench can monitor all 4\nprocesses all together.\n\n::\n\n        $> monitor.py sh -c 'sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait'\n        pid     ppid    utime  stime  rtime            rss     vms      maxRss  maxVms   avgRss    avgVms     cwd                                cmd\n        135004  134985  0.0    0.0    3.9532430172     798720  4558848  798720  4558848  798720.0  4558848.0  /home/zhanxw/mycode/bench/scripts  sh -c sleep 2 & sleep 4 & seq 10000000 >/dev/null & wait\n        135006  135004  0.0    0.0    3.95348381996    655360  6066176  655360  6066176  655360.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 4\n        135005  135004  0.0    0.0    1.83160495758    774144  6066176  774144  6066176  774144.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 2\n        135007  135004  0.05   0.0    0.0599648952484  720896  6090752  720896  6090752  720896.0  6090752.0  /home/zhanxw/mycode/bench/scripts  seq 10000000\n\n-  Example 3: generate performance metrics to external file\n\nHere we used a small program, burnCpu. It will keep CPU running for\nseveral seconds. Its source code is under src/.\n\nThe option ``-t`` will enable outputting traces. That means at several\ntime stops, performance metrics of each processes will be outputted to\nthe standard error as well as a separate comma-separated file,\n``$prefix.trace.csv``.\n\nThe option ``-g`` will generate a graph which contains several\nsub-figures, including timings for each processes, memory consumption\nfor each processes, and memory consumption over the processing running\ntime.\n\nThe option ``-o`` will specify the output prefix. The default value will\nbe ``bench``, meaning, you will get ``bench.csv``. You can overwrite\nthis value by using ``-o`` option.\n\n::\n\n        $> monitor.py -t -g -o burnCpu ./burnCpu\n        pid     ppid    utime  stime  rtime            rss      vms       cwd                                cmd\n        135471  135454  0.04   0.0    0.0441780090332  1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu\n        135471  135454  0.2    0.0    0.205282926559   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu\n        135471  135454  0.38   0.0    0.381079912186   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu\n        ...\n\nAdditional result are stored in *burnCpu.csv*, *burnCpu.trace.csv* in\nthe Comma-separated format (CSV).\n\n*burnCpu.csv* file content\n\n::\n\n    pid,ppid,utime,stime,rtime,rss,vms,maxRss,maxVms,avgRss,avgVms,cwd,cmd\n    144433,144416,5.4,0.0,5.40555810928,1404928,12984320,1404928,12984320,1404928.0,12984320.0,/home/zhanxw/mycode/bench/scripts,../src/burnCpu\n\n*burnCpu.trace.csv* file content\n\n::\n\n    pid,ppid,utime,stime,rtime,rss,vms,cwd,cmd\n    144433,144416,0.03,0.0,0.0423669815063,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu\n    144433,144416,0.19,0.0,0.20046210289,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu\n    144433,144416,0.36,0.0,0.373480081558,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu\n    ...\n\nWhen ``-g`` optioned is specified, bench will generate several\nperformance metrics in the file *burnCpu.trace.csv*:\n\n|image|\n\nNotes\n=====\n\n| To benchmark a complex command or combinations of commands, you can\n  use shell (sh or bash) . For example, you can use \"sh -c 'command arg1\n  arg2 ... '\" (see Example 2).\n| Bench requires `psutil <https://pypi.python.org/pypi/psutil>`__ to\n  collect basic performance metrics, and\n| requires `numpy <http://www.numpy.org/>`__ and\n  `pandas <http://pandas.pydata.org/>`__ for statistical calculations.\n| In this release, we used psutil 3.1.1, numpy 1.8.2, pandas 0.16.2 and\n  matplotlib 1.4.3.\n\nContact\n=======\n\n| For questions or commend, please visit bench github repo:\n| `repo <https://github.com/zhanxw/bench>`__\n\n| or email to:\n| Xiaowei Zhan \n\n.. |image| image:: http://zhanxw.com/bench/burnCpu.png",
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