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yi-jiayu/autoquizzarium.ipynb

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Automatically guessing Quizzarium answers from DuckDuckGo search results based on hints.
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autoquizzarium.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"from bs4 import BeautifulSoup\n",
"\n",
"ddg_query_base = 'https://duckduckgo.com/html/?q='\n",
"\n",
"resp = requests.get(ddg_query_base + 'Who originally sang vocals for ACDC?')\n",
"text = resp.text"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [],
"source": [
"import re\n",
"\n",
"whitespace_regexp = re.compile('\\s+')\n",
"\n",
"def get_search_result(question):\n",
" resp = requests.get(ddg_query_base + question)\n",
" soup = BeautifulSoup(resp.text)\n",
" pageText = soup.findAll(text=True)\n",
" non_empty_texts = [t for t in pageText if whitespace_regexp.fullmatch(t) is None]\n",
" stripped_texts = [t.strip() for t in non_empty_texts]\n",
" return stripped_texts"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"re.compile(r'(?:^|[^\\w])(\\w\\w\\w\\w \\w\\wa\\ws)(?:$|[^\\w])', re.UNICODE)"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def build_hint_regexp(hint):\n",
" hint = ' '.join([h.replace(' ', '').replace('_', '\\w') for h in hint.split(' ')])\n",
" hint = '(?:^|[^\\w])(' + hint + ')(?:$|[^\\w])'\n",
" return re.compile(hint)\n",
"build_hint_regexp('_ _ _ _ _ _ a _ s')"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['html class']\n",
"['html class']\n",
"['html class']\n",
"['Dirt Cheap']\n",
"['Dirt Cheap']\n",
"['Dirt Cheap']\n",
"['that music']\n",
"['sold three']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['This video']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['like Brian']\n",
"['coal miner']\n",
"['Dirt Cheap']\n",
"['Dirt Cheap']\n",
"['Dave Evans', 'band needs']\n",
"['Long sheet']\n",
"['with scene']\n",
"['from their']\n",
"['know which']\n",
"['that seems', 'that brian']\n",
"['Hell after']\n",
"['Dave Evans']\n",
"['Mark Evans']\n",
"['wave group']\n"
]
}
],
"source": [
"hint_regexp = build_hint_regexp('_ _ _ _ _ _ _ _ _')\n",
"for t in stripped_texts:\n",
" m = hint_regexp.findall(t)\n",
" if m:\n",
" print(m)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['html class']\n",
"['html class']\n",
"['html class']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Mark Evans']\n"
]
}
],
"source": [
"hint_regexp = build_hint_regexp('_ _ _ _ _ _ a _ s')\n",
"for t in stripped_texts:\n",
" m = hint_regexp.findall(t)\n",
" if m:\n",
" print(m)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Dave Evans']\n",
"['Mark Evans']\n"
]
}
],
"source": [
"hint_regexp = build_hint_regexp(' _ _ _ _ _ v a n s')\n",
"for t in stripped_texts:\n",
" m = hint_regexp.findall(t)\n",
" if m:\n",
" print(m)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"def find_answer(search_result, hint):\n",
" hint_regexp = build_hint_regexp(hint)\n",
" for t in search_result:\n",
" m = hint_regexp.findall(t)\n",
" if m:\n",
" print(m)"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['David Copperfield']\n",
"['Joyce Frankenberg']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n",
"['David Copperfield']\n"
]
}
],
"source": [
"search_result = get_search_result('What eponymous Dickens character born with a caul over head')\n",
"find_answer(search_result, '_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _')"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['html class']\n",
"['html class']\n",
"['html class']\n",
"['John Books']\n",
"['1975 novel']\n",
"['that would']\n",
"['Five Movie']\n",
"['many 1980s', 'Sure Thing']\n",
"['2018 Oscar']\n",
"['Know About']\n",
"['tall today']\n",
"['Were Never', 'Same After']\n",
"['from these']\n",
"['Feud shows']\n",
"['Know About']\n"
]
}
],
"source": [
"search_result = get_search_result('John Books was the final role of which actor')\n",
"find_answer(search_result, '_ _ _ _ _ _ _ _ _')"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Bluestones', 'Trilithons', 'DuckDuckGo']\n",
"['Historical']\n",
"['Historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['historical', 'bluestones', 'trilithons']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['guaranteed']\n",
"['bluestones', 'trilithons']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['conditions']\n",
"['Bluestones']\n",
"['guaranteed']\n",
"['bluestones', 'trilithons']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['abprivivry']\n",
"['collegiate']\n",
"['coursehero']\n",
"['translator']\n",
"['Dictionary']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['deviantART']\n",
"['scientific']\n",
"['containing']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['Trilithons']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['Trilithons']\n",
"['stonehenge']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['biljoissac']\n",
"['Wallpapers']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['biljoissac']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['triviaquiz']\n",
"['Historical']\n",
"['Bluestones']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['seatmerazu']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['cufamosist']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['historical']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge', 'monographs']\n",
"['Stonehenge']\n",
"['Bluestones']\n",
"['everywhere']\n",
"['monographs']\n",
"['Bluestones']\n",
"['appearance']\n",
"['Bluestones']\n",
"['appearance']\n",
"['Fibreglass']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n",
"['Bluestones']\n",
"['Trilithons']\n",
"['Stonehenge']\n"
]
}
],
"source": [
"search_result = get_search_result('Where would you find Saracens Bluestones and Trilithons')\n",
"find_answer(search_result, '_ _ _ _ _ _ _ _ _ _')"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n",
"['Stonehenge']\n"
]
}
],
"source": [
"search_result = get_search_result('Where would you find Saracens Bluestones and Trilithons')\n",
"find_answer(search_result, '_ _ _ _ _ _ e n _ _')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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