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1 changed files with 108 additions and 220 deletions
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@ -1,6 +1,6 @@
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'''
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'''
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Recommendation Engine ver 1
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Recommendation Engine Example
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30 Nov 2018, 0x2620
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1 Nov 2017, 0x2620
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'''
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'''
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from collections import defaultdict
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from collections import defaultdict
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@ -33,10 +33,6 @@ class Engine:
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if os.path.exists(filename):
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if os.path.exists(filename):
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with open(filename) as f:
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with open(filename) as f:
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self.playlists = json.load(f)
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self.playlists = json.load(f)
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# ## the following is for testing purpose.
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# for playlist in self.playlists:
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# for clip in playlist["clips"]:
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# clip["pass"] = bool(random.getrandbits(1))
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else:
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else:
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self.playlists = []
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self.playlists = []
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@ -47,25 +43,18 @@ class Engine:
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else:
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else:
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self.state = {
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self.state = {
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'channels': {
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'channels': {
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'globalKeywords': {'locked': False, 'value': 8},
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'globalKeywords': {'locked': False, 'value': 7},
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'userKeywords': {'locked': False, 'value': 8}
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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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},
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'globalKeywords': {},
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'globalKeywords': {},
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}
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}
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if 'gridChange' not in self.state:
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if 'gridChange' not in self.state:
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self.state['gridChange'] = {
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self.state['gridChange'] = {
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'nextClip': {'locked': False, 'value': 5},
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'nextClip': {'locked': True, 'value': 4},
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'nextPlaylist': {'locked': False, 'value': 8},
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'nextPlaylist': {'locked': False, 'value': 4},
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'staySame': {'locked': True, 'value': 3}
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'staySame': {'locked': False, 'value': 8}
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}
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}
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if 'userKeywordsWeights' not in self.state:
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self.state['userKeywordsWeights'] = {
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'themeTags': {'locked': False, 'value': 0.3},
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'characterTags': {'locked': False, 'value': 0.7},
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'random': {'locked': False, 'value': False}
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}
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if 'random' not in self.state['userKeywordsWeights']:
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self.state['userKeywordsWeights']['random'] = {'locked': False, 'value': False}
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self.update_keywords()
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self.update_keywords()
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@property
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@property
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@ -98,80 +87,46 @@ class Engine:
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def get_videos(self, user):
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def get_videos(self, user):
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## Output is a dictionary of: user keyword scores, list of videos for each grid index (0-15),
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if user.get('events', [{}])[0].get("event")=="login":
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## and parameters to be displayed on debug view.
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return self.get_recommendations(user)
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## It implements "next clip" "next playlist" "stay same" grid allocation for the output video, depending on the user log history.
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# Update self_playlists to reflect user log history
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playlists = self.update_user_playlists(user)
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# Get the user keyword scores for debug view
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user_keywords = copy.deepcopy(user.get('keywords', {}))
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theme_tags = {k.lower():v for k,v in user_keywords.items() if not k.isupper()}
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character_tags = {k:v for k,v in user_keywords.items() if k.isupper()}
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top_user_keywords = sorted([(k,v) for (k,v) in theme_tags.items()], key=lambda kv: kv[1])[-10:]
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top_user_characters = sorted([(k,v) for (k,v) in character_tags.items()], key=lambda kv: kv[1])[-10:]
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debug_index_output = defaultdict(list)
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# If the most recent event is "login," initialize grid videos.
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if user.get('events', [{}])[0].get("event")=="login":
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rec = self.get_recommendations(playlists, user)
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return {
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'user': {
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'keywords': user.get('keywords', {})
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},
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'videos': rec["videos"],
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"_debug": {
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"top_user_keywords": top_user_keywords,
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"top_user_characters": top_user_characters,
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"top_user_playlists": rec["top_user_playlists"],
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"top_global_playlists": rec["top_global_playlists"]
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}
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}
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channels = {k: v.get('value', 0) for k, v in self.state['channels'].items()}
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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()}
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sliders = {k: v.get('value', 0) for k, v in self.state['globalKeywords'].items()}
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grid_change = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
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grid_change = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
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# check if there were grid events for all indexes.
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grid_events = {}
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grid_events = {}
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(nc, np, ns) = (grid_change.get("nextClip"), grid_change.get("nextPlaylist"), grid_change.get("staySame"))
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(nc, np, ns) = (grid_change.get("nextClip"), grid_change.get("nextPlaylist"), grid_change.get("staySame"))
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video_num = nc + np + ns
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video_num = nc + np + ns
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# collect the most recent grid event for each grid index and the grid index of the most recent play event.
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# for event in user.get('events', []):
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# the following requires "index" in play event data (previously unavailable)
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# if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
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# grid_events[event.get('data').get('index')] = event.get('data')
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# if len(grid_events) == video_num:
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# break
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# # The version where the loop also extract play_index (requires "index" in play event data):
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play_index = None
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play_index = None
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for event in user.get('events', []):
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for event in user.get('events', []):
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if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
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if event.get('event') == "grid" and event.get('data').get('index') not in grid_events:
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grid_events[event.get('data').get('index')] = event.get('data')
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grid_events[event.get('data').get('index')] = event.get('data')
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if event.get('event') == "play" and event["data"].get("type") == "video" and not play_index:
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if event.get('event') == "play" and event["data"].get("type") == "video" and not play_index:
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play_index = event.get('data').get('index')
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play_index = event.get('data').get('index')
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if len(grid_events) == video_num and play_index:
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if len(grid_events) == video_num and play_index:
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break
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break
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prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
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prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
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# if there were no grid events for all, initialize all grids.
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# if there were no grid events for all, initialize all grids.
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if len(prev_grid_list) < video_num:
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if len(prev_grid_list) < video_num:
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rec = self.get_recommendations(playlists, user)
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return self.get_recommendations(user)
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return {
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'user': {
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'keywords': user.get('keywords', {})
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},
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'videos': rec["videos"],
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"_debug": {
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"top_user_keywords": top_user_keywords,
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"top_user_characters": top_user_characters,
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"top_user_playlists": rec["top_user_playlists"],
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"top_global_playlists": rec["top_global_playlists"]
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}
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}
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else:
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else:
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if play_index is None:
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if play_index is None:
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video_indx = list(range(video_num))
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video_indx = list(range(video_num))
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random.shuffle(video_indx)
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random.shuffle(video_indx)
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else:
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else:
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# play index is excluded from the random shuffle and deterministically added to staySame pool.
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# played index is excluded from the random shuffle and deterministically added to staySame pool.
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video_indx = [*range(play_index)]+[*range(play_index+1,video_num)]
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video_indx = [*range(play_index)]+[*range(play_index+1,video_num)]
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random.shuffle(video_indx)
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random.shuffle(video_indx)
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video_indx.append(play_index)
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video_indx.append(play_index)
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@ -181,132 +136,76 @@ class Engine:
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stay_same_index = video_indx[nc+np:]
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stay_same_index = video_indx[nc+np:]
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rec_list = []
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rec_list = []
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# select next clip for nextClip pool except when the playlist has only one clip.
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# nextClip pool: select next clip except when the playlist has only one clip. skip the clip with "pass":True when selecting the next clip.
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for i in next_clip_index:
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for i in next_clip_index:
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# add this to deal with the absence of "playlist" data in old grid event or the case where the playlist has been eliminated due to update_user_playlists().
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if prev_grid_list[i].get('playlist') is None:
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if prev_grid_list[i].get("playlist") not in [playlist["name"] for playlist in playlists]:
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# add this to deal with the absence of "playlist" data in old grid event.
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next_playlist_index.append(i)
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# If there's no playlist data recorded, add the nextClip pool to nextPlaylist pool.
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next_playlist_index.append(next_clip_index)
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break
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else:
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else:
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for playlist in playlists:
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# if "playlist" and "playlistPostion" (if not, default to 0) exists in grid event
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for playlist in self.playlists:
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if playlist.get('name')== prev_grid_list[i].get('playlist'):
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if playlist.get('name')== prev_grid_list[i].get('playlist'):
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unwatched_clips_indx = [j for j in range(len(playlist["clips"])) if not playlist["clips"][j].get("pass")]
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if len(playlist["clips"]) == 1:
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if len(playlist["clips"]) == 1:
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next_playlist_index.append(i)
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next_playlist_index.append(i)
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break
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# Discuss how this behavour should be: should it switch to a new playlist if it is the end of the playlist clip sequence already?
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elif prev_grid_list[i].get('playlistPosition', 0) + 1 == len(playlist['clips']):
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playlist_pos = 0
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else:
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else:
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next_unwatched_indx = [j for j in unwatched_clips_indx if j > prev_grid_list[i]['playlistPosition']]
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playlist_pos = prev_grid_list[i].get('playlistPosition', 0) + 1
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if len(next_unwatched_indx) == 0:
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if unwatched_clips_indx[0] != prev_grid_list[i]['playlistPosition']:
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rec_list.append((i, {
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playlist_pos = unwatched_clips_indx[0]
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'clips': playlist['clips'],
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else:
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# 'position': random.randrange(len(playlist['clips'])),
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next_playlist_index.append(i)
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'position': playlist_pos,
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break
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'name': playlist['name'],
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else:
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'tags': playlist['tags'],
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playlist_pos = next_unwatched_indx[0]
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}))
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rec_list.append((i, {
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# randomly select playlists (excluding the playlists from the current grid once "playlist" is recorded for grid events)
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'clips': playlist['clips'],
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# for nextPlaylist pool.
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'position': playlist_pos,
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'name': playlist['name'],
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'tags': playlist['tags']
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}))
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debug_index_output["next_clip"].append((i,playlist['name']))
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#staySame pool
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for i in stay_same_index:
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# add this to deal with the absence of "playlist" data in old grid event or the case where the playlist has been eliminated due to update_user_playlists().
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if prev_grid_list[i].get("playlist") not in [playlist["name"] for playlist in playlists]:
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next_playlist_index.append(i)
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else:
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rec_list.append((i,{}))
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debug_index_output["stay_same"].append(i)
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# nextPlaylist pool: randomly select playlists (excluding the playlists from the current grid).
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vids_exclude = [e.get("playlist") for e in prev_grid_list]
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vids_exclude = [e.get("playlist") for e in prev_grid_list]
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while None in vids_exclude:
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while None in vids_exclude:
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vids_exclude.remove(None)
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vids_exclude.remove(None)
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rec = self.get_recommendations(playlists, user, vids_exclude)
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video = self.get_recommendations(user, vids_exclude)
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rec_list += [(i, rec['videos'][i]) for i in next_playlist_index]
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rec_list += [(i, video[i]) for i in next_playlist_index]
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debug_index_output["new_playlist"] = [(i, rec['videos'][i]["name"]) for i in next_playlist_index]
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#staySame pool
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rec_list += [(i,{}) for i in stay_same_index]
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rec_list = sorted(rec_list, key=lambda k:k[0])
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rec_list = sorted(rec_list, key=lambda k:k[0])
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videos_ = [e[1] for e in rec_list]
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return [e[1] for e in rec_list]
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return {
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'user': {
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'keywords': user.get('keywords', {})
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},
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'videos': videos_,
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"_debug": {
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"top_user_keywords": top_user_keywords, # list of (keyword, score)
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"top_user_characters": top_user_characters, # list of (keyword, score)
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"top_user_playlists": rec["top_user_playlists"], # list of (playlist name, score)
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"top_global_playlists": rec["top_global_playlists"], # list of (playlist name, score)
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"stay_same_index": debug_index_output["stay_same"], # list of integers
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"next_clip_index": debug_index_output["next_clip"], # list of (integer, playlist name)
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"new_playlist_index": debug_index_output["new_playlist"] # list of (integer, playlist name)
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}
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}
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def get_recommendations(self, playlists, user, vids_exclude = []):
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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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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()}
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sliders = {k: v.get('value', 0) for k, v in self.state['globalKeywords'].items()}
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gridChange = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
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gridChange = {k: v.get('value', 0) for k, v in self.state['gridChange'].items()}
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userKeywordsWeights = {k: v.get('value', 1) for k, v in self.state['userKeywordsWeights'].items()}
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# Exclude playlists from the most recent grid
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# Exclude playlists from the most recent grid
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playlists = copy.deepcopy(self.playlists)
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if len(vids_exclude) > 0:
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if len(vids_exclude) > 0:
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for playlist in playlists:
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for playlist in playlists:
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if playlist["name"] in vids_exclude:
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if playlist["name"] in vids_exclude:
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playlists.remove(playlist)
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playlists.remove(playlist)
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# Generate random weights if random option is chosen in the dashboard:
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# For each playlist, compute user keyword score
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if userKeywordsWeights.get('random'):
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user_keywords = user.get('keywords', {})
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themeWeights = random.random()
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charWeights = 1-themeWeights
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else:
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themeWeights = userKeywordsWeights['themeTags']
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charWeights = userKeywordsWeights['characterTags']
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# For each playlist, compute user keyword score by theme and character tags
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user_keywords = copy.deepcopy(user.get('keywords', {}))
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theme_tags = {k.lower():v for k,v in user_keywords.items() if not k.isupper()}
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character_tags = {k:v for k,v in user_keywords.items() if k.isupper()}
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# manually modify some of the user keywords to match the playlist tags
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theme_tags["god"] = theme_tags.get("god - gods",0)
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theme_tags["visionary"] = theme_tags.get("visionary - enlightenment",0)
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theme_tags["enlightenment"] = theme_tags.get("visionary - enlightenment",0)
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character_tags["FEDOR MIKHAILOVICH SOFRONOV"] = character_tags.get("FYODOR MIKHAILOVICH SOFRONOV",0)
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character_tags["SHKABARNYA OLGA SERGEEVNA"] = character_tags.get("OLGA SERGEEVNA SHKABARNYA",0)
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character_tags["VICTORIA OLEGOVNA SKITSKAYA"] = character_tags.get("VIKTORIA OLEGOVNA SKITSKAYA",0)
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score = {}
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score = {}
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for playlist in playlists:
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for playlist in playlists:
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score[playlist['name']] = random.random() * 0.1
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score[playlist['name']] = random.random()
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for tag in playlist['tags']:
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for tag in [tag for tag in playlist['tags'] if tag in user_keywords]:
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if tag in theme_tags:
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score[playlist['name']] += user_keywords[tag]
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score[playlist['name']] += theme_tags[tag] * themeWeights
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elif tag in character_tags:
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score[playlist['name']] += character_tags[tag] * charWeights
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# Select highest scoring playlists
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# Select highest scoring playlists
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playlists = sorted(
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playlists = sorted(
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playlists,
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playlists,
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key=lambda playlist: -score[playlist['name']]
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key=lambda playlist: -score[playlist['name']]
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)
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)
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# Record the following for debug view input
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top_user_playlists = [(playlist['name'], score[playlist['name']]) for playlist in playlists[:channels['userKeywords']]]
|
|
||||||
# top_user_playlists = [{
|
|
||||||
# 'name': playlist['name'],
|
|
||||||
# 'tags': playlist['tags'],
|
|
||||||
# 'score': score[playlist['name']],
|
|
||||||
# } for playlist in playlists[:channels['userKeywords']]]
|
|
||||||
|
|
||||||
videos = playlists[:channels['userKeywords']]
|
videos = playlists[:channels['userKeywords']]
|
||||||
playlists = playlists[channels['userKeywords']:]
|
playlists = playlists[channels['userKeywords']:]
|
||||||
# For each playlist, compute global keyword score
|
# For each playlist, compute global keyword score
|
||||||
score = {}
|
score = {}
|
||||||
for playlist in playlists:
|
for playlist in playlists:
|
||||||
score[playlist['name']] = random.random()
|
score[playlist['name']] = random.random()
|
||||||
|
@ -317,43 +216,46 @@ class Engine:
|
||||||
playlists,
|
playlists,
|
||||||
key=lambda playlist: -score[playlist['name']]
|
key=lambda playlist: -score[playlist['name']]
|
||||||
)
|
)
|
||||||
# Record the following for debug view input
|
videos += playlists[:channels['globalKeywords']]
|
||||||
top_global_playlists = [(playlist['name'], score[playlist['name']]) for playlist in playlists[:channels['globalKeywords']]]
|
playlists = playlists[channels['globalKeywords']:]
|
||||||
# top_global_playlists = [{
|
# Count products the user has seen
|
||||||
# 'name': playlist['name'],
|
count = defaultdict(lambda: 0)
|
||||||
# 'tags': playlist['tags'],
|
for event in user.get('events', []):
|
||||||
# 'score': score[playlist['name']],
|
if event.get('data', {}).get('product'):
|
||||||
# } for playlist in playlists[:channels['globalKeywords']]]
|
count[event['data']['product']] += 1
|
||||||
|
# For each product in playlist tags, increment score by count
|
||||||
videos += playlists[:16 - channels['userKeywords']]
|
for playlist in playlists:
|
||||||
|
score[playlist['name']] = random.random()
|
||||||
|
for tag in set(playlist['tags']) & set(count):
|
||||||
|
score[playlist['name']] += count[tag]
|
||||||
|
# Select highest scoring playlists
|
||||||
|
videos += sorted(
|
||||||
|
playlists,
|
||||||
|
key=lambda playlist: -score[playlist['name']]
|
||||||
|
)[:16 - channels['userKeywords'] - channels['globalKeywords']]
|
||||||
# Shuffle playlists (randomize layout) and shift clips (randomize start)
|
# Shuffle playlists (randomize layout) and shift clips (randomize start)
|
||||||
random.shuffle(videos)
|
random.shuffle(videos)
|
||||||
return {
|
return [{
|
||||||
'videos': [{
|
'clips': video['clips'],
|
||||||
'clips': video['clips'],
|
'position': random.randrange(len(video['clips'])),
|
||||||
'position': random.choice([i for i in range(len(video["clips"])) if not video["clips"][i].get("pass")]),
|
'name': video['name'],
|
||||||
'name': video['name'],
|
'tags': video['tags'],
|
||||||
'tags': video['tags'],
|
} for video in videos]
|
||||||
} for video in videos],
|
|
||||||
"top_user_playlists":top_user_playlists,
|
|
||||||
"top_global_playlists": top_global_playlists
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
def update_user_playlists(self, user, watch_cutoff = 0.9):
|
def update_user_playlists(playlists, user, watch_cutoff = 0.9):
|
||||||
# Output: playlists with updated in/out time of clips that have been watched as well as "pass" indicators for the clips that has been watched for more than watch_cutoff.
|
# Output: playlists with updated in/out time of clips that have been watched.
|
||||||
# Watched is defined as a video being played in full screen.
|
# Watched is defined as a video being played in full screen.
|
||||||
# "watch_cutoff" parameter: the portion of the clip duration to be determined as watched the whole clip. should be [0,1]
|
# "watch_cutoff" parameter: the portion of the clip duration to be determined as watched the whole clip. should be [0,1]
|
||||||
# + check (play, pause) pairs and eliminate unusual cases most likely due to a bug.
|
# + check (play, pause) pairs and eliminate unusual cases most likely due to a bug.
|
||||||
# + If (play, pause) pairs exceed XX(80-90?) percent of the clip length, add "pass": True to the clip.
|
# + If (play, pause) pairs exceed XX(80-90?) percent of the clip length, eliminate the clip from the playlist.
|
||||||
# + Otherwise, find the last pause position of a clip and record it as "in" position of the clip.
|
# + Otherwise, find the last pause position of a clip and record it as "in" position of the clip.
|
||||||
# + If clips are all marked as "pass" in a playlist, elliminate the playlist from the user playlists.
|
# + If the clips are all eliminated from a playlist, eliminate the playlist.
|
||||||
playlists = copy.deepcopy(self.playlists)
|
|
||||||
play = {}
|
play = {}
|
||||||
|
watched = []
|
||||||
clip_max_dur = 10800 # = 3 hours; arbitrary max duration allowed for (pause time - play time) to detect outlier/bugs
|
clip_max_dur = 10800 # = 3 hours; arbitrary max duration allowed for (pause time - play time) to detect outlier/bugs
|
||||||
# The current max time of a clip duration is 10379.383333377269 from "DDLaunch: Erik Verlinde, Gravity as an emergent force (1956)"
|
# The current max time of a clip duration is 10379.383333377269 from "DDLaunch: Erik Verlinde, Gravity as an emergent force (1956)"
|
||||||
# A user could potentially spend more than 3 hours if they keep watching after the clip enters into the subsequent "scene"
|
for event in user["events"][::-1]:
|
||||||
for event in user.get('events', [])[::-1]:
|
|
||||||
if event["event"] == "play" and event["data"].get("type") == "video":
|
if event["event"] == "play" and event["data"].get("type") == "video":
|
||||||
play = event
|
play = event
|
||||||
elif event["event"] == "pause" and play!={} and event["data"].get("type") == "video":
|
elif event["event"] == "pause" and play!={} and event["data"].get("type") == "video":
|
||||||
|
@ -368,37 +270,28 @@ class Engine:
|
||||||
if play["data"]["position"] >= max(playlist["clips"][i]["in"] - 15, 0) and event["data"]["position"] <= playlist["clips"][i]["out"] + 15:
|
if play["data"]["position"] >= max(playlist["clips"][i]["in"] - 15, 0) and event["data"]["position"] <= playlist["clips"][i]["out"] + 15:
|
||||||
# This assumes the (play, pause) fits inside the clip's (in, out) segment with +/- 15secs buffer. There were newer edits of clip positions with 12 seconds difference.
|
# This assumes the (play, pause) fits inside the clip's (in, out) segment with +/- 15secs buffer. There were newer edits of clip positions with 12 seconds difference.
|
||||||
# instances where this might not be the case: clip in/out may be largely edited (before after edit inconsistency); skip may trigger jump to a wrong clip (bug)
|
# instances where this might not be the case: clip in/out may be largely edited (before after edit inconsistency); skip may trigger jump to a wrong clip (bug)
|
||||||
if "orig_in" not in playlist["clips"][i]:
|
if event["data"]["position"] >= ((playlist["clips"][i]["out"]-playlist["clips"][i]["in"])*watch_cutoff + playlist["clips"][i]["in"]):
|
||||||
cutoff_pos = (playlist["clips"][i]["out"]-playlist["clips"][i]["in"])*watch_cutoff + playlist["clips"][i]["in"]
|
watched.append((playlist["name"],i))
|
||||||
else:
|
else:
|
||||||
cutoff_pos = (playlist["clips"][i]["out"]-playlist["clips"][i]["orig_in"])*watch_cutoff + playlist["clips"][i]["orig_in"]
|
|
||||||
|
|
||||||
if event["data"]["position"] >= cutoff_pos:
|
|
||||||
playlist["clips"][i]["pass"] = True
|
|
||||||
|
|
||||||
else:
|
|
||||||
if "orig_in" not in playlist["clips"][i]:
|
|
||||||
# record the original "in" position to calculate cutoff position in the future
|
|
||||||
playlist["clips"][i]["orig_in"] = playlist["clips"][i]["in"]
|
|
||||||
# update "in" position of the clip in the playlist
|
|
||||||
playlist["clips"][i]["in"] = event["data"]["position"]
|
playlist["clips"][i]["in"] = event["data"]["position"]
|
||||||
break
|
break
|
||||||
play = {}
|
play = {}
|
||||||
|
|
||||||
for playlist in playlists.copy():
|
d_watched = defaultdict(set)
|
||||||
unwatched = [clip for clip in playlist["clips"] if not clip.get("pass")]
|
for k, v in watched:
|
||||||
if not unwatched:
|
d_watched[k].add(v)
|
||||||
playlists.remove(playlist)
|
for k, v in d_watched.items():
|
||||||
# If the number of playlists is reduced to 30, reset it to the original.
|
for playlist in playlists:
|
||||||
if len(playlists) < 30:
|
if playlist["name"] == k:
|
||||||
playlists = copy.deepcopy(self.playlists)
|
if len(v) == len(playlist["clips"]):
|
||||||
|
playlists.remove(playlist)
|
||||||
|
else:
|
||||||
|
playlist["clips"] = [playlist["clips"][i] for i in range(len(playlist["clips"])) if i not in v]
|
||||||
|
break
|
||||||
return(playlists)
|
return(playlists)
|
||||||
|
|
||||||
|
|
||||||
def get_next(self, user, position):
|
def get_next(self, user, position):
|
||||||
# Update self_playlists to reflect user log history
|
|
||||||
playlists = self.update_user_playlists(user)
|
|
||||||
|
|
||||||
grid_events = {}
|
grid_events = {}
|
||||||
video_num = 16
|
video_num = 16
|
||||||
|
|
||||||
|
@ -409,8 +302,8 @@ class Engine:
|
||||||
break
|
break
|
||||||
prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
|
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]
|
vids_exclude = [e.get("playlist") for e in prev_grid_list]
|
||||||
rec = self.get_recommendations(playlists, user, vids_exclude)
|
video = self.get_recommendations(user, vids_exclude)[position]
|
||||||
return rec["videos"][position]
|
return video
|
||||||
|
|
||||||
def update_state(self, data):
|
def update_state(self, data):
|
||||||
for key in data:
|
for key in data:
|
||||||
|
@ -472,15 +365,10 @@ class Engine:
|
||||||
f.write(json.dumps(videos, indent=4, sort_keys=True))
|
f.write(json.dumps(videos, indent=4, sort_keys=True))
|
||||||
# Get video order
|
# Get video order
|
||||||
order = {video['id']: int(video['order']) for video in videos}
|
order = {video['id']: int(video['order']) for video in videos}
|
||||||
code = {video['id']: video['code'] for video in videos}
|
|
||||||
# Sort clips
|
# Sort clips
|
||||||
clips = sorted(
|
clips = sorted(
|
||||||
clips,
|
clips,
|
||||||
key=lambda clip: (
|
key=lambda clip: (order[clip['id'].split('/')[0]], clip['in'])
|
||||||
order[clip['id'].split('/')[0]],
|
|
||||||
ox.sort_string(code[clip['id'].split('/')[0]]),
|
|
||||||
clip['in']
|
|
||||||
)
|
|
||||||
)
|
)
|
||||||
# Get and cache playlists
|
# Get and cache playlists
|
||||||
self.playlists = [playlist for playlist in [{
|
self.playlists = [playlist for playlist in [{
|
||||||
|
@ -489,13 +377,13 @@ class Engine:
|
||||||
'tags': storyline['tags'],
|
'tags': storyline['tags'],
|
||||||
'clips': [{
|
'clips': [{
|
||||||
'item': clip['id'].split('/')[0],
|
'item': clip['id'].split('/')[0],
|
||||||
'id': '%s_%0.3f-%0.3f' % (clip['id'].split('/')[0], clip['in'], clip['out']),
|
'id': clip['id'],
|
||||||
'in': clip['in'],
|
'in': clip['in'],
|
||||||
'out': clip['out']
|
'out': clip['out']
|
||||||
} for clip in clips if clip['value'] == storyline['name']]
|
} for clip in clips if clip['value'] == storyline['name']]
|
||||||
} for storyline in storylines] if playlist['clips']]
|
} for storyline in storylines] if playlist['clips']]
|
||||||
with open(os.path.join(self.path, 'playlists.json'), 'w') as f:
|
with open(os.path.join(self.path, 'playlists.json'), 'w') as f:
|
||||||
f.write(json.dumps(self.playlists, indent=4, sort_keys=True, ensure_ascii=False))
|
f.write(json.dumps(self.playlists, indent=4, sort_keys=True))
|
||||||
self.update_keywords()
|
self.update_keywords()
|
||||||
|
|
||||||
def update_keywords(self):
|
def update_keywords(self):
|
||||||
|
|
Loading…
Reference in a new issue