{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Generate random movie plot elements\n",
"\n",
"Data from [IMDB](http://www.imdb.com/interfaces), held at [ftp://ftp.fu-berlin.de/pub/misc/movies/database/](ftp://ftp.fu-berlin.de/pub/misc/movies/database/), in the `keywords.list.gz` file.\n",
"\n",
"[Abulafia generator](http://www.random-generator.com/index.php?title=Plot_Keyword_Oracle) and [Story-games thread](http://story-games.com/forums/discussion/3502/new-toy-imdb-plot-keywords), and [an earlier version of the list](http://www.logrus.com/~moose/page1/files/cleanplots.txt)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Get the file\n",
"!wget ftp://ftp.fu-berlin.de/pub/misc/movies/database/keywords.list.gz\n",
"\n",
"!gunzip keywords.list.gz"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"generate-random-plots.ipynb keywords.list\r\n"
]
}
],
"source": [
"!ls"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import collections\n",
"import re\n",
"import random\n",
"import itertools"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def read_keywords_from_list(line):\n",
" if not line:\n",
" return []\n",
" accumulator = []\n",
" for kn in re.split('\\t+', line):\n",
" k, n = kn.split()\n",
" n = int(n[1:-1])\n",
" accumulator += [k] * n\n",
" return accumulator"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['blue-pantyhose', 'blue-party', 'blue-party', 'blue-pearl']"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"read_keywords_from_list('blue-pantyhose (1)\t\tblue-party (2)\tblue-pearl (1)')"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def read_keywords_from_title(line):\n",
" if line:\n",
" return [re.split('\\t+', line)[1]]\n",
" else:\n",
" return []"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"['beer-drinking']"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"read_keywords_from_title('Been Down So Long It Looks Like Up to Me (1971)\t\tbeer-drinking')"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"skipping underlines ========\n",
"ending list 5: Submission Rules\n",
"skipping underlines =============\n",
"skipping underlines ==================\n",
"skipping underlines ===============\n",
"starting list keywords in use:\n",
"ending list 5: Submission Rules\n",
"skipping underlines ===================\n",
"skipping underlines ==============\n",
"skipping underlines ======================\n",
"skipping underlines =================================================\n",
"pre-title 8: THE KEYWORDS LIST\n",
"starting title ====================\n"
]
}
],
"source": [
"keywords_from_list = collections.Counter()\n",
"keywords_from_title = collections.Counter()\n",
"reading_state = None\n",
"for line in open('keywords.list', encoding='latin-1').readlines():\n",
" \n",
" if line.strip().startswith('keywords in use'):\n",
" reading_state = 'keywords_from_list'\n",
" print('starting list', line.strip())\n",
" continue\n",
" if line.strip().startswith('5: Submission Rules'):\n",
" readings_state = None\n",
" print('ending list', line.strip())\n",
" continue\n",
" if reading_state == 'pre_from_title':\n",
" if line.strip().startswith('==='):\n",
" reading_state = 'keywords_from_title'\n",
" print('starting title', line.strip())\n",
" else:\n",
" reading_state = None\n",
" print('not start of titles', line.strip())\n",
" continue\n",
" if line.strip().startswith('8: THE KEYWORDS LIST'):\n",
" reading_state = 'pre_from_title'\n",
" print('pre-title', line.strip())\n",
" continue\n",
" if line.strip().startswith('==='):\n",
" reading_state = None\n",
" print('skipping underlines', line.strip())\n",
" continue\n",
" \n",
" if reading_state == 'keywords_from_list':\n",
" keywords_from_list.update(read_keywords_from_list(line.strip()))\n",
" elif reading_state == 'keywords_from_title':\n",
" keywords_from_title.update(read_keywords_from_title(line.strip()))\n",
"\n",
"sum_keywords = sum(keywords_from_list.values())"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[('sex', 83531),\n",
" ('hardcore', 69247),\n",
" ('character-name-in-title', 44747),\n",
" ('independent-film', 37932)]"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"keywords_from_list.most_common(4)"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"[('sex', 83531),\n",
" ('hardcore', 69247),\n",
" ('character-name-in-title', 44747),\n",
" ('independent-film', 37932)]"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"keywords_from_title.most_common(4)"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def pick_random(items, count):\n",
" i = random.randint(0, count)\n",
" return list(itertools.islice(items.elements(), i, i+1))[0]"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"mother-daughter-relationship\n",
"oral-sex\n",
"cyberpunk\n",
"main-character-shot\n",
"medical-gloves\n",
"tv-show\n",
"female-nudity\n",
"conundrum\n",
"los-angeles-california\n",
"elevator\n",
"yorkshireman\n",
"paper-money\n",
"unfaithful-husband\n",
"brain-teaser\n",
"birthday\n",
"ranch\n",
"festival\n",
"world-war-two\n",
"reference-to-wikipedia\n",
"sundance\n"
]
}
],
"source": [
"for _ in range(20):\n",
" print(pick_random(keywords_from_list, sum_keywords))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"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": "3.4.3+"
}
},
"nbformat": 4,
"nbformat_minor": 0
}