{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "WARNING: pylab import has clobbered these variables: ['datetime']\n",
        "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from vizgrimoire.metrics.query_builder import SCRQuery\n",
      "from vizgrimoire.metrics.metrics_filter import MetricFilters\n",
      "import vizgrimoire.metrics.scr_metrics as scr"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#database object\n",
      "user=\"root\"\n",
      "password=\"\"\n",
      "scr_db = \"wikimedia_gerrit_20150224\"\n",
      "identities_db =\"wikimedia_git_20150224\"\n",
      "people_out = [\"Translation updater bot\", \"\", \"\", \"\"]\n",
      "dbcon=SCRQuery(user, password, scr_db, identities_db)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#metrics filter object\n",
      "period = MetricFilters.PERIOD_MONTH\n",
      "startdate=\"'2013-01-01'\"\n",
      "enddate=\"'2015-03-01'\"\n",
      "\n",
      "filters = MetricFilters(period, startdate, enddate, [\"autoreviews\", \"fake\"])\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "reviewers = scr.ActiveCoreReviewers(dbcon, filters)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "reviewers.get_agg()\n",
      "#get query: reviewers._get_sql(False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "{'core_reviewers': 295L}"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from datetime import datetime\n",
      "dates = []\n",
      "unixtime = reviewers.get_ts()[\"unixtime\"]\n",
      "for i in unixtime:\n",
      "    dates.append(datetime.fromtimestamp(float(i)))\n",
      "ts = reviewers.get_ts()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure()\n",
      "plot(dates, ts[\"core_reviewers\"])\n",
      "fig.autofmt_xdate()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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LoqOj4efnB2dnZ8TExMDJyQl+fn4KDZYTOWOMFVepRG5kZISuXbsCABo0aAAL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\nMcY0HCdyxhjTcJzIGWNMw3EiZ4wxDff/THKlWBjKPxwAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f03af5433d0>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "period = MetricFilters.PERIOD_MONTH\n",
      "startdate=\"'2015-01-24'\"\n",
      "enddate=\"'2015-02-24'\"\n",
      "\n",
      "filters = MetricFilters(period, startdate, enddate, [\"autoreviews\", \"fake\"])\n",
      "reviewers = scr.ActiveCoreReviewers(dbcon, filters)\n",
      "\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "list_reviewers = reviewers.get_list()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "select up.id as id , up.identifier as identifier , count(distinct(ch.id)) as reviews from issues_ext_gerrit ieg , issues i , changes ch , wikimedia_git_20150224.upeople up , people_upeople pup where field = 'Code-Review' and changed_on < '2015-02-24' and ieg.issue_id = i.id and changed_on >= '2015-01-24' and ch.issue_id = i.id and pup.upeople_id = up.id and (ch.new_value = -2 or ch.new_value = 2) and ch.changed_by  = pup.people_id and ieg.branch like '%master%' and i.id not in\n",
        "                       (select distinct(i.id) as issue_id\n",
        "                       from issues i,\n",
        "                            changes ch\n",
        "                       where i.submitted_by = ch.changed_by and\n",
        "                             i.id = ch.issue_id and\n",
        "                             ch.field = 'status' and\n",
        "                             ch.new_value = 'MERGED')\n",
        "                     group by up.id, up.identifier order by count(distinct(ch.id)) desc \n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#Now adding to the query the affiliation\n",
      "query = \"\"\"select up.id as id , up.identifier as identifier , c.name as company, count(distinct(ch.id)) as reviews\n",
      "           from issues_ext_gerrit ieg , issues i , changes ch , \n",
      "                wikimedia_git_20150224.upeople up , people_upeople pup, \n",
      "                wikimedia_git_20150224.upeople_companies upc, wikimedia_git_20150224.companies c\n",
      "           where field = 'Code-Review' and changed_on < '2015-02-24' and ieg.issue_id = i.id and changed_on >= '2015-01-24' and \n",
      "                 ch.issue_id = i.id and pup.upeople_id = up.id and (ch.new_value = -2 or ch.new_value = 2) and \n",
      "                 ch.changed_by  = pup.people_id and ieg.branch like '%master%' and \n",
      "                 up.id = upc.upeople_id and upc.company_id = c.id and\n",
      "                 i.id not in\n",
      "                       (select distinct(i.id) as issue_id\n",
      "                       from issues i,\n",
      "                            changes ch\n",
      "                       where i.submitted_by = ch.changed_by and\n",
      "                             i.id = ch.issue_id and\n",
      "                             ch.field = 'status' and\n",
      "                             ch.new_value = 'MERGED')\n",
      "                     group by up.id, up.identifier order by count(distinct(ch.id)) desc \n",
      "        \"\"\"\n",
      "list_affs = reviewers.db.ExecuteQuery(query)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for i in range(0,len(list_affs[\"id\"])):\n",
      "    identifier = list_affs[\"identifier\"][i]\n",
      "    company = list_affs[\"company\"][i]\n",
      "    reviews = list_affs[\"reviews\"][i]\n",
      "    print identifier.split('@')[0] + \",\" + company + \",\" + str(reviews)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "legoktm,Independent,214\n",
        "jforrester,Unknown,118\n",
        "Catrope,Wikimedia Foundation,111\n",
        "hoo,Unknown,80\n",
        "Ed S,Unknown,74\n",
        "Bartosz Dziewo\u0144ski,Independent,68\n",
        "Adrian Lang,Unknown,58\n",
        "Trevor Parscal,Wikimedia Foundation,53\n",
        "jayvdb,Unknown,45\n",
        "Sam Reed,Wikimedia Foundation,43\n",
        "Matthew Flaschen,Wikimedia Foundation,42\n",
        "Niklas Laxstr\u00f6m,Wikimedia Foundation,42\n",
        "Phuedx,Unknown,39\n",
        "ssastry,Unknown,38\n",
        "Bryan Davis,Wikimedia Foundation,35\n",
        "Krinkle,Wikimedia Foundation,35\n",
        "zfilipin,Unknown,34\n",
        "Umherirrender,Unknown,33\n",
        "thiemowmde,Wikimedia Deutschland,33\n",
        "Santhosh Thottingal,Wikimedia Foundation,33\n",
        "bmansurov,Unknown,31\n",
        "MaxSem,Wikimedia Foundation,29\n",
        "mlitn,Wikimedia Foundation,28\n",
        "Arlolra,Wikimedia Foundation,27\n",
        "krenair,Unknown,26\n",
        "siebrand,Unknown,25\n",
        "Anomie,Wikimedia Foundation,25\n",
        "ebernhardson,Unknown,25\n",
        "jsahleen,Unknown,24\n",
        "Fabian Neundorf,Unknown,23\n",
        "Jon Robson,Wikimedia Foundation,22\n",
        "Chad,Wikimedia Foundation,21\n",
        "Gilles Dubuc,Wikimedia Foundation,21\n",
        "Adam Roses Wight,Wikimedia Foundation,19\n",
        "ori,Unknown,19\n",
        "isarra,Unknown,19\n",
        "amire80,Wikimedia Foundation,18\n",
        "florianschmidtwelzow,Unknown,18\n",
        "rmoen,Unknown,17\n",
        "hashar,Unknown,17\n",
        "jeroendedauw,Wikimedia Deutschland,17\n",
        "MarkTraceur,Wikimedia Foundation,15\n",
        "Aaron Schulz,Wikimedia Foundation,14\n",
        "dbrant,Unknown,14\n",
        "JanZerebecki,Unknown,13\n",
        "xqt,Independent,13\n",
        "bsitzmann,Unknown,13\n",
        "mhurd,Unknown,13\n",
        "aude,Unknown,13\n",
        "Henning Snater,Unknown,13\n",
        "dr0ptp4kt,Unknown,13\n",
        "kaldari,Wikimedia Foundation,11\n",
        "addshore,Independent,11\n",
        "daniel,Unknown,11\n",
        "jhernandez,Unknown,9\n",
        "TTO,Unknown,9\n",
        "marcoil,Unknown,9\n",
        "KartikMistry,Unknown,8\n",
        "Ejegg,Unknown,8\n",
        "Chris McMahon,Wikimedia Foundation,8\n",
        "Andrew Garrett,Wikimedia Foundation,8\n",
        "Mooeypoo,Unknown,7\n",
        "Brion Vibber,Wikimedia Foundation,7\n",
        "Robert Vogel,Unknown,7\n",
        "Gabriel Wicke,Wikimedia Foundation,6\n",
        "Gergo Tisza,Unknown,6\n",
        "Andrew Green,Wikimedia Foundation,5\n",
        "yurik,Unknown,5\n",
        "Jack Phoenix,Unknown,5\n",
        "Merlijn van Deen,Independent,5\n",
        "Tim Starling,Wikimedia Foundation,4\n",
        "Dan Duvall,Unknown,4\n",
        "Mpaa,Unknown,4\n",
        "milimetric,Unknown,4\n",
        "ryasmeen,Unknown,4\n",
        "yuvipanda,Unknown,4\n",
        "gnosygnu,Unknown,3\n",
        "hartman,Unknown,3\n",
        "Moritz Schubotz,Unknown,3\n",
        "Alexandros Kosiaris,Wikimedia Foundation,3\n",
        "tpt,Independent,3\n",
        "Jackmcbarn,Unknown,3\n",
        "Andrew,Unknown,2\n",
        "Deskana,Unknown,2\n",
        "ladsgroup,Unknown,2\n",
        "wirth,Unknown,2\n",
        "csteipp,Unknown,2\n",
        "Tyler Anthony Romeo,Independent,2\n",
        "tamaraslosarek,Unknown,2\n",
        "Mukunda Modell,Unknown,2\n",
        "nuria,Unknown,2\n",
        "wctaiwan,Unknown,2\n",
        "tonythomas01,Unknown,2\n",
        "Yaron Koren,WikiWorks,2\n",
        "Raimond Spekking,Independent,2\n",
        "Katie Horn,Wikimedia Foundation,2\n",
        "dzahn,Unknown,2\n",
        "jonas.keutel,Unknown,1\n",
        "mark,Unknown,1\n",
        "Malvineous,Unknown,1\n",
        "Foxtrott,Unknown,1\n",
        "MZMcBride,Unknown,1\n",
        "PleaseStand,Unknown,1\n",
        "cicalese,Unknown,1\n",
        "otto,Unknown,1\n",
        "Pigpen,Unknown,1\n",
        "mwjames,Unknown,1\n",
        "prtksxna,Unknown,1\n",
        "Manybubbles,Wikimedia Foundation,1\n",
        "Marcel Ruiz Forns,Unknown,1\n",
        "tosfos,Unknown,1\n",
        "ricordisamoa,Unknown,1\n",
        "pginer,Unknown,1\n",
        "soeren.oldag,Unknown,1\n",
        "Mobrovac,Unknown,1\n",
        "JoelKP,Unknown,1\n",
        "cscott,Unknown,1\n",
        "Hypergrove,Unknown,1\n",
        "rush,Unknown,1\n",
        "Felipe Schenone,Unknown,1\n",
        "russblau,Unknown,1\n",
        "mah,Unknown,1\n",
        "pcoombe,Unknown,1\n",
        "o0lilu0o1980,Unknown,1\n",
        "Marielle Volz,Unknown,1\n",
        "Tweichart,Unknown,1\n",
        "filippo,Unknown,1\n",
        "Giuseppe Lavagetto,Unknown,1\n"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}