smt-boolean.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from z3 import *\n",
    "from time import time\n",
    "from tqdm import tqdm\n",
    "\n",
    "floors = set(range(4, 22))\n",
    "\n",
    "male_floors = set([8, 10, 16, 19])\n",
    "female_floors = set([7, 14, 18, 20])\n",
    "mixed_floors = floors.difference(male_floors).difference(female_floors)\n",
    "\n",
    "rf_floors = set(range(5, 22, 4))\n",
    "laundry_floors = set([9, 17])\n",
    "\n",
    "freshmen_floors = set([6, 8, 11, 14, 16, 17, 20])\n",
    "senior_floors = floors.difference(freshmen_floors)\n",
    "\n",
    "corridor_nonaircon_pos = set(map(str, range(101, 107) + range(115, 120)))\n",
    "corridor_aircon_pos = set(map(str, range(109, 115)))\n",
    "suite_room_letters = map(lambda x: chr(ord('A') + x), range(6))\n",
    "suite_nonaircon_pos = set([str(suite_num) + letter for suite_num in [100, 107] for letter in suite_room_letters])\n",
    "suite_aircon_pos = set([str(suite_num) + letter for suite_num in [108] for letter in suite_room_letters])\n",
    "aircon_pos = corridor_aircon_pos.union(suite_aircon_pos)\n",
    "nonaircon_pos = corridor_nonaircon_pos.union(suite_nonaircon_pos)\n",
    "corridor_pos = corridor_nonaircon_pos.union(corridor_aircon_pos)\n",
    "suite_room_pos = suite_nonaircon_pos.union(suite_aircon_pos)\n",
    "absent_laundry_pos = set(map(str, range(103, 107)))\n",
    "room_pos = corridor_pos.union(suite_room_pos)\n",
    "\n",
    "def get_valid_floors(is_male, pref_mixed, is_freshmen):\n",
    "    gender_floors = male_floors if is_male else female_floors\n",
    "    gender_floors = gender_floors.union(mixed_floors) if pref_mixed else gender_floors\n",
    "    seniority_floors = freshmen_floors if is_freshmen else senior_floors\n",
    "    return gender_floors.intersection(seniority_floors)\n",
    "\n",
    "def get_valid_pos(floor_num, is_suite, is_aircon):\n",
    "    pos = room_pos\n",
    "    pos = pos.difference(corridor_pos) if is_suite else pos.difference(suite_room_pos)\n",
    "    pos = pos.difference(nonaircon_pos) if is_aircon else pos.difference(aircon_pos)\n",
    "        \n",
    "    if floor_num not in floors:\n",
    "        pos = pos.difference(room_pos)\n",
    "        \n",
    "    if floor_num in rf_floors:\n",
    "        pos = pos.difference(suite_aircon_pos)\n",
    "    \n",
    "    if floor_num in laundry_floors:\n",
    "        pos = pos.difference(absent_laundry_pos)\n",
    "\n",
    "    return pos\n",
    "\n",
    "def get_valid_rooms(is_male=True, pref_mixed=False, is_freshmen=False, is_suite=True, is_aircon=False):\n",
    "    valid_floors = get_valid_floors(is_male, pref_mixed, is_freshmen)\n",
    "    valid_rooms = [str(floor_num) + '-' + pos for floor_num in valid_floors for pos in get_valid_pos(floor_num, is_suite, is_aircon)]    \n",
    "    return set(valid_rooms)\n",
    "\n",
    "def get_all_rooms():\n",
    "    rooms = []\n",
    "    for floor_num in floors:\n",
    "        if floor_num in laundry_floors:\n",
    "            rooms.extend([str(floor_num) + '-' + pos for pos in room_pos.difference(absent_laundry_pos)])\n",
    "        elif floor_num in rf_floors:\n",
    "            rooms.extend([str(floor_num) + '-' + pos for pos in room_pos.difference(suite_aircon_pos)])\n",
    "        else:\n",
    "            rooms.extend([str(floor_num) + '-' + pos for pos in room_pos])\n",
    "    return rooms\n",
    "    \n",
    "class Person():\n",
    "    def __init__(self, name, gender, pref_mixed, usp_status, is_suite, is_aircon, floor_pref, room_pref):\n",
    "        self.name = name\n",
    "        self.gender = gender\n",
    "        self.pref_mixed = pref_mixed\n",
    "        self.usp_status = usp_status\n",
    "        self.is_suite = is_suite\n",
    "        self.is_aircon = is_aircon\n",
    "        self.floor_pref = floor_pref\n",
    "        self.room_pref = room_pref\n",
    "    \n",
    "    def __str__(self):\n",
    "        return self.name\n",
    "    \n",
    "    def valid_pos(self):\n",
    "        return get_valid_pos(16,\n",
    "                             self.is_suite == \"suite\",\n",
    "                             self.is_aircon == \"aircon\"\n",
    "                            )\n",
    "        \n",
    "    def valid_floors(self):\n",
    "        return get_valid_floors(self.gender == \"male\",\n",
    "                               self.pref_mixed == \"yes\",\n",
    "                               self.usp_status == \"freshmen\"\n",
    "                               )\n",
    "    \n",
    "    def valid_rooms(self):\n",
    "        return get_valid_rooms(self.gender == \"male\",\n",
    "                               self.pref_mixed == \"yes\",\n",
    "                               self.usp_status == \"freshmen\",\n",
    "                               self.is_suite == \"suite\",\n",
    "                               self.is_aircon == \"aircon\"\n",
    "                              )\n",
    "    \n",
    "    __repr__ = __str__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_people_constraints(people):\n",
    "    rooms = set()\n",
    "    opc = []\n",
    "    pc = []\n",
    "    for person in tqdm(people):\n",
    "        if person.floor_pref and person.room_pref:\n",
    "            sym = Bool(person.name + \"-\" + person.floor_pref + '-' + person.room_pref)\n",
    "            opc.append(sym)\n",
    "        elif person.floor_pref:\n",
    "            syms = Or([Bool(person.name + \"-\" + person.floor_pref + '-' + room) for room in person.valid_pos()])\n",
    "            opc.append(syms)\n",
    "        elif person.room_pref:\n",
    "            syms = []\n",
    "            for floor_pref in person.valid_floors():\n",
    "                if person.room_pref in suite_aircon_pos and floor_pref in rf_floors:\n",
    "                    continue\n",
    "                \n",
    "                if person.room_pref in absent_laundry_pos and floor_pref in laundry_floors:\n",
    "                    continue\n",
    "                \n",
    "                sym = Bool(person.name + \"-\" + str(floor_pref) + '-' + person.room_pref)\n",
    "                syms.append(sym)\n",
    "\n",
    "            opc.append(Or(syms))\n",
    "            \n",
    "        p_valid_rooms = person.valid_rooms()\n",
    "        rooms = rooms.union(p_valid_rooms)\n",
    "        \n",
    "        rs = [Bool(person.name + \"-\" + room) for room in p_valid_rooms]\n",
    "        choices = []\n",
    "        for i in range(len(rs)):\n",
    "            select_i_room = map(Not, rs)\n",
    "            select_i_room[i] = rs[i]\n",
    "            choices.append(And(select_i_room))\n",
    "\n",
    "        pc.append(Or(choices))\n",
    "    \n",
    "    return pc, opc, rooms\n",
    "\n",
    "def get_room_constraints(people, rooms):\n",
    "    rc = []\n",
    "    for room in tqdm(rooms):\n",
    "        ps = [Bool(person.name + \"-\" + room) for person in people]\n",
    "        choices = [And(map(Not, ps))]\n",
    "        for i in range(len(ps)):\n",
    "            select_i_person = map(Not, ps)\n",
    "            select_i_person[i] = ps[i]\n",
    "            choices.append(And(select_i_person))\n",
    "\n",
    "        rc.append(Or(choices))\n",
    "    \n",
    "    return rc\n",
    "    \n",
    "def write_assignments(input_file, assignments):\n",
    "    d = dict()\n",
    "    for a in assignments:\n",
    "        name, floor, room = obj_to_string(a).split('-')\n",
    "        d[name] = [floor, room]\n",
    "    \n",
    "    input_file_values = input_file.iloc[:].values\n",
    "    output_file_array = []\n",
    "    for row in input_file_values:\n",
    "        row_name = str(row[0])\n",
    "        row_floor, row_room = d[row_name]\n",
    "        out_row = list(row)\n",
    "        out_row[-2] = row_floor\n",
    "        out_row[-1] = row_room\n",
    "        output_file_array.append(out_row)\n",
    "\n",
    "    out_df = pd.DataFrame(output_file_array)\n",
    "    out_df.columns = input_file.columns\n",
    "    out_df.to_csv('output.csv', index=False)\n",
    "    \n",
    "    return out_df\n",
    "\n",
    "def view_times(times):\n",
    "    if len(times) < 1:\n",
    "        return\n",
    "    last_t = times[0][1]\n",
    "    new_times = []\n",
    "    for t in times:\n",
    "        new_times.append([t[0], t[1] - last_t])\n",
    "        last_t = t[1]\n",
    "\n",
    "    return pd.DataFrame(new_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def solve(nrows=None):\n",
    "    times = []\n",
    "    times.append([\"start time\", time()])\n",
    "    input_file = pd.read_csv('simple.csv', nrows=nrows, dtype=object).fillna('')\n",
    "    times.append([\"read file\", time()])\n",
    "    print times[-1][0], times[-1][1] - times[-2][1]\n",
    "\n",
    "    people = []\n",
    "    for row in input_file.iloc[:].values:\n",
    "        person = Person(*row)\n",
    "        people.append(person)\n",
    "\n",
    "    prs = [Bool(person.name + \"-\" + room) for person in people for room in person.valid_rooms()]\n",
    "    pc, opc, rooms = get_people_constraints(people)\n",
    "    times.append([\"get people constraints\", time()])\n",
    "    print times[-1][0], times[-1][1] - times[-2][1]\n",
    "    \n",
    "    rc = get_room_constraints(people, rooms)\n",
    "    times.append([\"get room constraints\", time()])\n",
    "    print times[-1][0], times[-1][1] - times[-2][1]\n",
    "\n",
    "    constraints = [And(pc), And(rc)]\n",
    "    claim = And(constraints)\n",
    "\n",
    "    opt = Optimize()\n",
    "    opt.add(claim)\n",
    "    for op in opc:\n",
    "        opt.add_soft(op)\n",
    "    times.append([\"add constraints to optimizer\", time()])\n",
    "    print times[-1][0], times[-1][1] - times[-2][1]\n",
    "\n",
    "    sat_result = opt.check()\n",
    "    times.append([\"do sat check\", time()])\n",
    "    print times[-1][0], times[-1][1] - times[-2][1]\n",
    "    \n",
    "    if sat_result == sat:\n",
    "        model = opt.model()\n",
    "        assignments = filter(lambda x: is_true(model.eval(x)), prs)\n",
    "        w = write_assignments(input_file, assignments)\n",
    "        times.append([\"write assignments\", time()])\n",
    "        print times[-1][0], times[-1][1] - times[-2][1]\n",
    "        return w, times\n",
    "    else:\n",
    "        return \"No solution found\", times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "IOError",
     "evalue": "File simple.csv does not exist",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIOError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-59e055cd41f0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mout_df\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mview_times\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-4-d0829157e75a>\u001b[0m in \u001b[0;36msolve\u001b[0;34m(nrows)\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0mtimes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mtimes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"start time\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0minput_file\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'simple.csv'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mobject\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0mtimes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"read file\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0;32mprint\u001b[0m \u001b[0mtimes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mtimes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sushinoya/Projects/usp/usp-roomalloc/.direnv/python-2.7.10/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    707\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    711\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sushinoya/Projects/usp/usp-roomalloc/.direnv/python-2.7.10/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    448\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    451\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sushinoya/Projects/usp/usp-roomalloc/.direnv/python-2.7.10/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    816\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sushinoya/Projects/usp/usp-roomalloc/.direnv/python-2.7.10/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1047\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1048\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1049\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1050\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1051\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/sushinoya/Projects/usp/usp-roomalloc/.direnv/python-2.7.10/lib/python2.7/site-packages/pandas/io/parsers.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1693\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1694\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1695\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1697\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mIOError\u001b[0m: File simple.csv does not exist"
     ]
    }
   ],
   "source": [
    "out_df, times = solve(10)\n",
    "view_times(times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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