dd-re/recommendation_engine.py

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'''
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Recommendation Engine Example
1 Nov 2017, 0x2620
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'''
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from collections import defaultdict
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import json
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import logging
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import os
import random
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import time
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import ox
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from utils import run_async
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logger = logging.getLogger(__name__)
verbose = True
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class Engine:
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_pandora = None
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def __init__(self, path, **kwargs):
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self.path = path
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self.pandora_args = dict(
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url=kwargs.get('pandora', 'http://pandora.dmp/api/'),
username=kwargs.get('username', 'dd.re'),
password=kwargs.get('password', 'dd.re')
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)
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filename = os.path.join(self.path, 'playlists.json')
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if os.path.exists(filename):
with open(filename) as f:
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self.playlists = json.load(f)
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else:
self.playlists = []
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filename = os.path.join(self.path, 'state.json')
if os.path.exists(filename):
with open(filename) as f:
self.state = json.load(f)
else:
self.state = {
'channels': {
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'globalKeywords': {'locked': False, 'value': 7},
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'userKeywords': {'locked': False, 'value': 7},
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'screenings': {'locked': True, 'value': 2}
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},
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'globalKeywords': {},
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}
if 'gridChange' not in self.state:
self.state['gridChange'] = {
'nextClip': {'locked': False, 'value': 4},
'nextPlaylist': {'locked': False, 'value': 4},
'staySame': {'locked': False, 'value': 8}
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}
self.update_keywords()
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@property
def pandora(self):
while not self._pandora:
try:
self._pandora = Pandora(**self.pandora_args)
except:
logger.error('failed to connect to pandora, retry in 10 seconds')
time.sleep(10)
return self._pandora
def _patch_clips(self, clips):
inpoints = {}
for index, clip in enumerate(clips):
video_id = clip['id'].split('/')[0]
inpoints[video_id] = inpoints.get(video_id, []) + [{
'index': index,
'position': clip['in']
}]
for video_id in inpoints:
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for i, inpoint in enumerate(sorted(
inpoints[video_id], key=lambda inpoint: inpoint['position']
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)):
if i < len(inpoints[video_id]) - 1:
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clips[inpoint['index']]['out'] = inpoints[video_id][i + 1]['position']
else:
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clips[inpoint['index']]['out'] = self.pandora.get(video_id, ['duration'])['duration']
return clips
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def get_videos(self, user):
channels = {k: v.get('value', 0) for k, v in self.state['channels'].items()}
sliders = {k: v.get('value', 0) for k, v in self.state['globalKeywords'].items()}
grid_change = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
# check if there were grid events for all indexes.
grid_events = {}
(nc, np, ns) = (grid_change.get("nextClip"), grid_change.get("nextPlaylist"), grid_change.get("staySame"))
# this assumes np + nc + ns = total number of videos in the grid view (16).
# Make sure sanity check exists in front-end (error if it does not add up to 16).
video_num = nc + np + ns
# for event in user.get('events', []):
# if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
# grid_events[event.get('data').get('index')] = event.get('data')
# if len(grid_events) == video_num:
# break
# # The version where the loop also extract play_index (requires "index" in play event data):
play_index = None
for event in user.get('events', []):
if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
grid_events[event.get('data').get('index')] = event.get('data')
if event.get('event') == "play" and not play_index:
play_index = event.get('data').get('index')
if len(grid_events) == video_num and play_index:
break
prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
# if there were no grid events for all, initialize all grids.
if len(prev_grid_list) < video_num:
return self.get_recommendations(user)
else:
# played index is excluded from the random shuffle and deterministically added to staySame pool.
video_indx = [*range(play_index)]+[*range(play_index+1,video_num)]
# video_indx = list(range(video_num))
random.shuffle(video_indx)
video_indx.append(play_index)
next_clip_index = video_indx[:nc]
next_playlist_index = video_indx[nc:nc+np]
stay_same_index = video_indx[nc+np:]
rec_list = []
# select next clip for nextClip pool except when the playlist has only one clip.
for i in next_clip_index:
for playlist in self.playlists:
if playlist.get('name')== prev_grid_list[i].get('playlist'):
if len(playlist["clips"]) == 1:
next_playlist_index.append(i)
break
# Discuss how this behavour should be: should it switch to a new playlist if it is the end of the playlist clip sequence already?
elif prev_grid_list[i].get('playlistPosition') + 1 == len(playlist['clips']):
playlist_pos = 0
else:
playlist_pos = prev_grid_list[i].get('playlistPosition') + 1
rec_list.append((i, {
'clips': playlist['clips'],
# 'position': random.randrange(len(playlist['clips'])),
'position': playlist_pos,
'name': playlist['name'],
'tags': playlist['tags'],
}))
# randomly select playlists (excluding the playlists from the current grid once "playlist" is recorded for grid events)
# for nextPlaylist pool.
vids_exclude = [e.get("playlist") for e in prev_grid_list]
video = self.get_recommendations(user, vids_exclude)
rec_list += [(i, video[i]) for i in next_playlist_index]
#staySame pool
rec_list += [(i,{}) for i in stay_same_index]
rec_list = sorted(rec_list, key=lambda k:k[0])
return [e[1] for e in rec_list]
# NOTE for future improvement: vids_exclude element unit could be clip or in/out time pairs, rather than playlist.
# The same playlist could be played in the grid view as long as these are differenct clips or separate times.
def get_recommendations(self, user, vids_exclude = []):
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channels = {k: v.get('value', 0) for k, v in self.state['channels'].items()}
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sliders = {k: v.get('value', 0) for k, v in self.state['globalKeywords'].items()}
gridChange = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
# Exclude playlists from the most recent grid
playlists = self.playlists
if len(vids_exclude) > 0:
for playlist in playlists:
if playlist["name"] in vids_exclude:
playlists.remove(playlist)
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# For each playlist, compute user keyword score
user_keywords = user.get('keywords', {})
score = {}
for playlist in playlists:
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score[playlist['name']] = random.random()
for tag in [tag for tag in playlist['tags'] if tag in user_keywords]:
score[playlist['name']] += user_keywords[tag]
# Select highest scoring playlists
playlists = sorted(
playlists,
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key=lambda playlist: -score[playlist['name']]
)
videos = playlists[:channels['userKeywords']]
playlists = playlists[channels['userKeywords']:]
# For each playlist, compute global keyword score
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score = {}
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for playlist in playlists:
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score[playlist['name']] = random.random()
for tag in [tag for tag in playlist['tags'] if tag in sliders]:
score[playlist['name']] += sliders[tag]
# Select highest scoring playlists
playlists = sorted(
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playlists,
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key=lambda playlist: -score[playlist['name']]
)
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videos += playlists[:channels['globalKeywords']]
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playlists = playlists[channels['globalKeywords']:]
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# Count products the user has seen
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count = defaultdict(lambda: 0)
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for event in user.get('events', []):
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if event.get('data', {}).get('product'):
count[event['data']['product']] += 1
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# For each product in playlist tags, increment score by count
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for playlist in playlists:
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score[playlist['name']] = random.random()
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for tag in set(playlist['tags']) & set(count):
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score[playlist['name']] += count[tag]
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# Select highest scoring playlists
videos += sorted(
playlists,
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key=lambda playlist: -score[playlist['name']]
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)[:16 - channels['userKeywords'] - channels['globalKeywords']]
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# Shuffle playlists (randomize layout) and shift clips (randomize start)
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random.shuffle(videos)
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return [{
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'clips': video['clips'],
'position': random.randrange(len(video['clips'])),
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'name': video['name'],
'tags': video['tags'],
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} for video in videos]
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def get_next(self, user, position):
grid_events = {}
video_num = 16
for event in user.get('events', []):
if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
grid_events[event.get('data').get('index')] = event.get('data')
if len(grid_events) == video_num:
break
prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
vids_exclude = [e.get("playlist") for e in prev_grid_list]
video = self.get_recommendations(user, vids_exclude)[position]
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return video
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def update_state(self, data):
for key in data:
if key in self.state:
self.state[key].update(data[key])
else:
self.state[key] = data[key]
self.save_state()
return self.state
def save_state(self):
filename = os.path.join(self.path, 'state.json')
with open(filename, 'w') as f:
json.dump(self.state, f, indent=4, ensure_ascii=False, sort_keys=True)
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def update(self):
# Get all storylines with tags
storylines = [{
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'id': entity['id'],
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'name': entity['name'],
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'nodename': entity['nodename'],
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'tags': [t.strip() for t in entity['tags']]
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} for entity in self.pandora.find_entities({
'conditions': [
{'key': 'type', 'operator': '==', 'value': 'storylines'},
],
'operator': '&'
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}, ['id', 'name', 'tags', 'nodename']) if entity.get('tags', []) and entity.get('nodename')]
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# Get list of storyline names
names = list(set([storyline['name'] for storyline in storylines]))
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# Get list of items to use in DD
items = [item['id'] for item in self.pandora.find({
'conditions': [
{'key': 'list', 'operator': '==', 'value': 'dau:DD'}
]
}, ['id'])]
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# Get all clips annotated with storyline references
clips = [clip for clip in self.pandora.find_annotations({
'conditions': [
{'key': 'layer', 'operator': '==', 'value': 'storylines'}
],
'operator': '&'
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}, ['id', 'in', 'out', 'value']) if clip['value'] in names and clip['id'].split('/')[0] in items]
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# Get list of ids for videos with clips
ids = list(set([clip['id'].split('/')[0] for clip in clips]))
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# Get and cache video data
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filename = os.path.join(self.path, 'videos.json')
if os.path.exists(filename):
with open(filename) as f:
videos_ = json.loads(f.read())
ids_ = [video['id'] for video in videos_]
else:
videos_, ids_ = [], []
videos = sorted(videos_ + [
self.pandora.get(id, ['code', 'id', 'order', 'title'])
for id in ids if not id in ids_
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], key=lambda video: int(video['order']))
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with open(filename, 'w') as f:
f.write(json.dumps(videos, indent=4, sort_keys=True))
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# Get video order
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order = {video['id']: int(video['order']) for video in videos}
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# Sort clips
clips = sorted(
clips,
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key=lambda clip: (order[clip['id'].split('/')[0]], clip['in'])
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)
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# Get and cache playlists
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self.playlists = [playlist for playlist in [{
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'id': storyline['id'],
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'name': storyline['nodename'].strip(),
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'tags': storyline['tags'],
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'clips': [{
'item': clip['id'].split('/')[0],
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'id': clip['id'],
'in': clip['in'],
'out': clip['out']
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} for clip in clips if clip['value'] == storyline['name']]
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} for storyline in storylines] if playlist['clips']]
with open(os.path.join(self.path, 'playlists.json'), 'w') as f:
f.write(json.dumps(self.playlists, indent=4, sort_keys=True))
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self.update_keywords()
def update_keywords(self):
changed = False
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if 'globalKeywords' not in self.state:
self.state['globalKeywords'] = {}
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changed = True
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existing_tags = set()
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for playlist in self.playlists:
for tag in playlist.get('tags', []):
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if not tag.isupper() and tag:
existing_tags.add(tag)
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if not tag.isupper() and tag not in self.state['globalKeywords']:
self.state['globalKeywords'][tag] = {'value': 0}
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changed = True
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for tag in set(self.state['globalKeywords']) - existing_tags:
del self.state['globalKeywords'][tag]
changed = True
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if changed:
self.save_state()
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@run_async
def update_async(self):
self.update()
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class Pandora:
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# pan.do/ra API wrapper
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def __init__(self, url, username, password):
self.api = ox.API(url)
self.api.signin(username=username, password=password)
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def find(self, query, keys):
# print('FIND', query, keys)
return self.api.find({
'keys': keys,
'query': query,
'range': [0, 1000000]
})['data']['items']
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def find_annotations(self, query, keys):
# print('FIND ANNOTATIONS', query, keys)
return self.api.findAnnotations({
'keys': keys,
'query': query,
'range': [0, 1000000]
})['data']['items']
def find_entities(self, query, keys):
# print('FIND ENTITIES', query, keys)
return self.api.findEntities({
'keys': keys,
'query': query,
'range': [0, 1000000]
})['data']['items']
def get(self, id, keys):
# print('GET', id, keys)
return self.api.get({
'id': id,
'keys': keys
})['data']
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if __name__ == '__main__':
engine = Engine('json')
engine.update()