skills-Copy1.ipynb

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   "source": [
    "import os\n",
    "import re\n",
    "import sys\n",
    "import csv\n",
    "import random\n",
    "import dateutil\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import datetime, timedelta\n",
    "from collections import defaultdict, OrderedDict\n",
    "from itertools import combinations\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import rc\n",
    "rc('font',**{'family': 'Arial',\n",
    "        'weight': 'normal',\n",
    "        'size': 14})\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def get_team_sum(some_df, names):\n",
    "    result = np.zeros(len(project_skills))\n",
    "    for name in names:\n",
    "        for i in xrange(len(skill_names)):\n",
    "            result[i] += some_df[name][i]\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
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   "outputs": [],
   "source": [
    "def get_value(some_skills, some_project_skills):\n",
    "    result = 0\n",
    "    for i in xrange(some_project_skills.size):\n",
    "        if some_project_skills[i] != 0:\n",
    "           result += min(some_skills[i], some_project_skills[i])\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def levels_reachable(level, money):\n",
    "    ups = 0\n",
    "    for i in xrange(100):\n",
    "        cost = level + ups + 1\n",
    "        money -= cost\n",
    "        if money > 0:\n",
    "            ups +=1 \n",
    "    return ups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "__high_level_noob_cache = {}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
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   "source": [
    "import requests\n",
    "from cStringIO import StringIO\n",
    "\n",
    "\n",
    "def get_people_from_google():\n",
    "    headers = {\n",
    "        'accept-encoding': 'utf-8, deflate, sdch, br',\n",
    "        'accept-language': 'ru-RU,ru;q=0.8,en-US;q=0.6,en;q=0.4',\n",
    "        'x-chrome-uma-enabled': '1',\n",
    "        'cookie': 'WRITELY_SID=OwQ81DvVAjQaVQPvr8bcE11FE0yfgku4J5Na4E2gqeiR6m4H0iDgZQsnivWmpBXLcmfoUw.; SID=qwQ81Ml__3niSHk7ffcqg-IM3I6T3u9a6r1cG6_xPRsUhZZkVr0J65SuxKvlQffMBlBxxA.; HSID=At3mbruFYASwl53Gt; SSID=AjwhRtUSN4B-8Dyg2; APISID=qRcfUHe_8u2E5P5E/ASyl4GUqKzzuyO6RG; SAPISID=HHaDQdFUWDfltgsA/AxapAwFQBFKqTcDfg; S=explorer=KlmuqRS6PP4Lw2rtwhiPRLdiqrxNVO7L; NID=105=woipxjdGqeC26rkuoBb6QBP894ezHOZpl-Foo58_l0-vaJyQTwVeggjmpQW7q1uzdm_-wyt0ENZUqccEDefHMhRw6_tzeBn9T4Q9y4H3zQq_ZsO_dERzb7L6pc4cJ-wS2Ss-qKO2SISGpTj5_V2b_DZBn0AU_64M-f62mPNmLLQu8SxDTJmUzUjl1zFF6w8nBMn-X41Jo0SSBHNF63PBNWBYrABsJzPvoE1Id1Xxym_JEctszLV-tFhMvCKH6UaQo6W9eTDysL4VSSSaG-hSr4dlrsCfUeKmYiGqzeG2mmA5fxRtNxx5rnJCEh9OwypebgM',\n",
    "        'x-client-data': 'CJW2yQEIo7bJAQjEtskBCPqcygEIqZ3KAQjKnsoB',\n",
    "        'x-chrome-connected': 'id=109899821021679414341,mode=0,enable_account_consistency=false',\n",
    "        'pragma': 'no-cache',\n",
    "        'upgrade-insecure-requests': '1',\n",
    "        'x-compress': 'null',\n",
    "        'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36',\n",
    "        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',\n",
    "        'cache-control': 'no-cache',\n",
    "        'authority': 'docs.google.com',\n",
    "        'referer': 'https://docs.google.com/spreadsheets/d/1LXCX4PlBbnWWCGJVkQ-sOs3je__LiTgjLLDidHFzMJY/edit',\n",
    "    }\n",
    "\n",
    "    params = (\n",
    "        ('format', 'csv'),\n",
    "        ('id', '1LXCX4PlBbnWWCGJVkQ-sOs3je__LiTgjLLDidHFzMJY'),\n",
    "        ('gid', '418401891'),\n",
    "    )\n",
    "\n",
    "    print 'Получаем данные о людях...'\n",
    "    r = requests.get('https://docs.google.com/spreadsheets/export', headers=headers, params=params)\n",
    "    r.encoding = 'utf-8'\n",
    "    return StringIO(r.text.encode('utf-8'))    \n",
    "\n",
    "\n",
    "def get_project_from_google():\n",
    "    headers = {\n",
    "        'accept-encoding': 'gzip, deflate, sdch, br',\n",
    "        'accept-language': 'ru-RU,ru;q=0.8,en-US;q=0.6,en;q=0.4',\n",
    "        'x-chrome-uma-enabled': '1',\n",
    "        'cookie': 'WRITELY_SID=OwQ81DvVAjQaVQPvr8bcE11FE0yfgku4J5Na4E2gqeiR6m4H0iDgZQsnivWmpBXLcmfoUw.; SID=qwQ81Ml__3niSHk7ffcqg-IM3I6T3u9a6r1cG6_xPRsUhZZkVr0J65SuxKvlQffMBlBxxA.; HSID=At3mbruFYASwl53Gt; SSID=AjwhRtUSN4B-8Dyg2; APISID=qRcfUHe_8u2E5P5E/ASyl4GUqKzzuyO6RG; SAPISID=HHaDQdFUWDfltgsA/AxapAwFQBFKqTcDfg; S=explorer=KlmuqRS6PP4Lw2rtwhiPRLdiqrxNVO7L; NID=105=woipxjdGqeC26rkuoBb6QBP894ezHOZpl-Foo58_l0-vaJyQTwVeggjmpQW7q1uzdm_-wyt0ENZUqccEDefHMhRw6_tzeBn9T4Q9y4H3zQq_ZsO_dERzb7L6pc4cJ-wS2Ss-qKO2SISGpTj5_V2b_DZBn0AU_64M-f62mPNmLLQu8SxDTJmUzUjl1zFF6w8nBMn-X41Jo0SSBHNF63PBNWBYrABsJzPvoE1Id1Xxym_JEctszLV-tFhMvCKH6UaQo6W9eTDysL4VSSSaG-hSr4dlrsCfUeKmYiGqzeG2mmA5fxRtNxx5rnJCEh9OwypebgM',\n",
    "        'x-client-data': 'CJW2yQEIo7bJAQjEtskBCPqcygEIqZ3KAQjKnsoB',\n",
    "        'x-chrome-connected': 'id=109899821021679414341,mode=0,enable_account_consistency=false',\n",
    "        'pragma': 'no-cache',\n",
    "        'upgrade-insecure-requests': '1',\n",
    "        'x-compress': 'null',\n",
    "        'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36',\n",
    "        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',\n",
    "        'cache-control': 'no-cache',\n",
    "        'authority': 'docs.google.com',\n",
    "        'referer': 'https://docs.google.com/spreadsheets/d/1LXCX4PlBbnWWCGJVkQ-sOs3je__LiTgjLLDidHFzMJY/edit',\n",
    "    }\n",
    "\n",
    "    params = (\n",
    "        ('format', 'csv'),\n",
    "        ('id', '1LXCX4PlBbnWWCGJVkQ-sOs3je__LiTgjLLDidHFzMJY'),\n",
    "        ('gid', '1377104609'),\n",
    "    )\n",
    "    print 'Получаем данные о проекте...'\n",
    "    r = requests.get('https://docs.google.com/spreadsheets/export', headers=headers, params=params)\n",
    "    r.encoding = 'utf-8'\n",
    "    return StringIO(r.text.encode('utf-8'))\n",
    "\n",
    "def get_people_csv_reader(from_file=False):\n",
    "    if from_file:\n",
    "        f = open('/Users/apertsev/Downloads/Skills - БД.csv', 'rb')\n",
    "    else:\n",
    "        f = get_people_from_google()\n",
    "    \n",
    "    return csv.reader(f, delimiter=',', quotechar='|')\n",
    "\n",
    "def get_project_csv_reader(from_file=False):\n",
    "    if from_file:\n",
    "        f = open('/Users/apertsev/Downloads/Skills - Проект.csv', 'rb')\n",
    "    else:\n",
    "        f = get_project_from_google()\n",
    "    return csv.reader(f, delimiter=',', quotechar='|')\n",
    "\n",
    "def get_project_skills(from_cache=False, from_file=False):\n",
    "    if from_cache:\n",
    "        return __high_level_noob_cache['project']\n",
    "    \n",
    "    r = get_project_csv_reader(from_file)\n",
    "    \n",
    "    skill_names = []\n",
    "    project_skills = []\n",
    "    \n",
    "    for x in r:\n",
    "        skill_names.append(x[0])\n",
    "        skill_value = x[1].strip()\n",
    "        project_skills.append(int(skill_value) if skill_value != '' else 0)\n",
    "        \n",
    "    project_skills = np.array(project_skills)\n",
    "    \n",
    "    __high_level_noob_cache['project'] = (skill_names, project_skills)\n",
    "    return skill_names, project_skills  \n",
    "\n",
    "def get_people_data(from_cache=False, from_file=False):\n",
    "    if from_cache:\n",
    "        return __high_level_noob_cache['people']\n",
    "    \n",
    "    r = get_people_csv_reader(from_file)\n",
    "    people_data = {}\n",
    "    \n",
    "    for i, name in enumerate(r.next()[1:]):\n",
    "        people_data[i] = {'skills': [], 'money': 0, 'name': name}\n",
    "\n",
    "    for i, money in enumerate(r.next()[1:]):\n",
    "        money = int(money) if money != '' else 0\n",
    "        people_data[i]['money'] = money\n",
    "\n",
    "    for i, is_a_friend in enumerate(r.next()[1:]):\n",
    "        is_a_friend = is_a_friend == '1'\n",
    "        people_data[i]['is_a_friend'] = is_a_friend\n",
    "\n",
    "    for x in r:\n",
    "        for i, skill_value in enumerate(x[1:]):\n",
    "            people_data[i]['skills'].append(int(skill_value) if skill_value != '' else 0)\n",
    "            \n",
    "    __high_level_noob_cache['people'] = people_data\n",
    "    return people_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "project skills:                [0 2 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 3 3 0 1 1 0 0 0 0]\n",
      "preselected: [Перцев, Екасов, Калашник]\n",
      "team skills: \n",
      "   Делегирование 0\n",
      "   Контроль 1\n",
      "   Лидерство 0\n",
      "   Мотивация 0\n",
      "   Постановка целей 0\n",
      "   Наставничество 0\n",
      "   Новаторство 0\n",
      "   Саморазвитие 0\n",
      "   Системное мышление 0\n",
      "   Управление рисками 2\n",
      "   Многозадачность 1\n",
      "   Оперативность 0\n",
      "   Ответственность 0\n",
      "   Предприимчивость 2\n",
      "   Результативность 0\n",
      "   Влиятельность 0\n",
      "   Коммуникабельность 1\n",
      "   Метапозиционность 0\n",
      "   Стрессоустойчивость 0\n",
      "   Эмпатия 0\n",
      "   Адаптивность 0\n",
      "   Командность 0\n",
      "   Концентрация 1\n",
      "   Оптимистичность 0\n",
      "   Пунктуальность 0\n",
      "   Энергичность 1\n",
      "project_skills (preselected):  [0 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 3 3 0 1 1 0 0 0 0]\n",
      "need to hire: 7\n",
      "usefull guys: 5\n",
      "no teams\n"
     ]
    }
   ],
   "source": [
    "skill_names, project_skills = get_project_skills(from_cache=True)\n",
    "\n",
    "print 'project skills:               ', project_skills\n",
    "\n",
    "people_data = get_people_data(from_cache=True)\n",
    "people_names = {\n",
    "    data['name']: index for index, data in people_data.iteritems()\n",
    "}\n",
    "\n",
    "LEVEL_UPS = 0\n",
    "\n",
    "for data in people_data.itervalues():\n",
    "    data['level_ups'] = LEVEL_UPS #levels_reachable(sum(data['skills']), data['money'])\n",
    "    data['skills'] = np.array(data['skills'])\n",
    "\n",
    "            \n",
    "preselected=['Перцев', 'Екасов', 'Калашник']\n",
    "ban_list = []\n",
    "SEARCH_FRIENDS = True\n",
    "\n",
    "\n",
    "print 'preselected: [{}]'.format(', '.join(preselected))\n",
    "team_size = 10\n",
    "\n",
    "skill_sum = np.zeros(len(skill_names), dtype=np.int)\n",
    "\n",
    "for name in preselected:\n",
    "    data = people_data[people_names[name]]\n",
    "    skill_sum += data['skills']\n",
    "    project_skills = project_skills - data['skills']\n",
    "    \n",
    "print 'team skills: '\n",
    "for i, name in enumerate(skill_names):\n",
    "    print '  ', name, skill_sum[i]\n",
    "    \n",
    "project_skills = project_skills.clip(min=0)\n",
    "print 'project_skills (preselected): ', project_skills\n",
    "\n",
    "usefull_guys = []\n",
    "\n",
    "for i, data in people_data.iteritems():\n",
    "    if data['name'] in preselected or data['name'] in ban_list:\n",
    "        continue\n",
    "    \n",
    "    if SEARCH_FRIENDS and not data['is_a_friend']:\n",
    "        continue\n",
    "\n",
    "    value = get_value(data['skills'], project_skills)\n",
    "    if value > 1:\n",
    "        usefull_guys.append(i)\n",
    "    \n",
    "need_to_hire_num = team_size-len(preselected)\n",
    "print 'need to hire: ' + str(need_to_hire_num)\n",
    "print 'usefull guys: ' + str(len(usefull_guys))\n",
    "\n",
    "dream_teams = defaultdict(list)\n",
    "\n",
    "for team in combinations(usefull_guys, need_to_hire_num):\n",
    "    team_project_skills = project_skills\n",
    "    for man in team:\n",
    "        team_project_skills = team_project_skills - people_data[man]['skills'] \n",
    "\n",
    "    team_sum = 0\n",
    "    for value in team_project_skills:\n",
    "        if value > 1:\n",
    "            team_sum += value\n",
    "\n",
    "    for man in team:\n",
    "        team_sum -= people_data[man]['level_ups']\n",
    "\n",
    "    if team_sum < 10:\n",
    "        dream_teams[team_sum].append(team)\n",
    "\n",
    "if not dream_teams:\n",
    "    print 'no teams'\n",
    "\n",
    "for score, teams in sorted(dream_teams.items())[:2]:\n",
    "    for team in teams[:10]:\n",
    "        print ', '.join([people_data[man]['name'] for man in team] + preselected), ' - не хватает', score, 'навыков'\n",
    "        for i, name in enumerate(skill_names):\n",
    "            if team_project_skills[i] > 0:\n",
    "                print '  - ', name, team_project_skills[i]\n"
   ]
  },
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