541 lines
25 KiB
Python
541 lines
25 KiB
Python
'''
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Recommendation Engine ver 1
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30 Nov 2018, 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
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import random
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import time
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import copy
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import ox
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from utils import run_async
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logger = logging.getLogger(__name__)
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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/'),
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username=kwargs.get('username', 'dd.re'),
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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):
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with open(filename) as 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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self.playlists = []
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filename = os.path.join(self.path, 'state.json')
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if os.path.exists(filename):
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with open(filename) as f:
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self.state = json.load(f)
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else:
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self.state = {
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'channels': {
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'globalKeywords': {'locked': False, 'value': 8},
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'userKeywords': {'locked': False, 'value': 8}
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},
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'globalKeywords': {},
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}
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if 'gridChange' not in self.state:
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self.state['gridChange'] = {
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'nextClip': {'locked': True, 'value': 4},
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'nextPlaylist': {'locked': False, 'value': 4},
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'staySame': {'locked': False, 'value': 8}
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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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}
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self.update_keywords()
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@property
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def pandora(self):
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while not self._pandora:
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try:
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self._pandora = Pandora(**self.pandora_args)
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except:
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logger.error('failed to connect to pandora, retry in 10 seconds')
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time.sleep(10)
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return self._pandora
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def _patch_clips(self, clips):
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inpoints = {}
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for index, clip in enumerate(clips):
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video_id = clip['id'].split('/')[0]
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inpoints[video_id] = inpoints.get(video_id, []) + [{
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'index': index,
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'position': clip['in']
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}]
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for video_id in inpoints:
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for i, inpoint in enumerate(sorted(
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inpoints[video_id], key=lambda inpoint: inpoint['position']
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)):
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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']
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else:
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clips[inpoint['index']]['out'] = self.pandora.get(video_id, ['duration'])['duration']
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return clips
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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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## and parameters to be displayed on debug view.
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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])[-5:]
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top_user_characters = sorted([(k,v) for (k,v) in character_tags.items()], key=lambda kv: kv[1])[-5:]
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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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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_events = {}
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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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# collect the most recent grid event for each grid index and the grid index of the most recent play event.
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# the following requires "index" in play event data (previously unavailable)
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play_index = None
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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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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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play_index = event.get('data').get('index')
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if len(grid_events) == video_num and play_index:
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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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# 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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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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else:
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if play_index is None:
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video_indx = list(range(video_num))
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random.shuffle(video_indx)
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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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video_indx = [*range(play_index)]+[*range(play_index+1,video_num)]
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random.shuffle(video_indx)
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video_indx.append(play_index)
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next_clip_index = video_indx[:nc]
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next_playlist_index = video_indx[nc:nc+np]
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stay_same_index = video_indx[nc+np:]
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rec_list = []
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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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# 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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for playlist in playlists:
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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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next_playlist_index.append(i)
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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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if len(next_unwatched_indx) == 0:
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if unwatched_clips_indx[0] != prev_grid_list[i]['playlistPosition']:
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playlist_pos = unwatched_clips_indx[0]
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else:
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next_playlist_index.append(i)
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break
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else:
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playlist_pos = next_unwatched_indx[0]
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rec_list.append((i, {
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'clips': playlist['clips'],
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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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#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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# 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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while None in vids_exclude:
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vids_exclude.remove(None)
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rec = self.get_recommendations(playlists, 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 = 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 {
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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,
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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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def get_recommendations(self, playlists, 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()}
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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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if len(vids_exclude) > 0:
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for playlist in playlists:
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if playlist["name"] in vids_exclude:
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playlists.remove(playlist)
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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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for playlist in playlists:
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score[playlist['name']] = random.random() * 0.001
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for tag in playlist['tags']:
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if tag in theme_tags:
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score[playlist['name']] += theme_tags[tag] * userKeywordsWeights["themeTags"]
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elif tag in character_tags:
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score[playlist['name']] += character_tags[tag] * userKeywordsWeights["characterTags"]
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# Select highest scoring playlists
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playlists = sorted(
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playlists,
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key=lambda playlist: -score[playlist['name']]
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)
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# Record the following for debug view input
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top_user_playlists = [{
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'name': playlist['name'],
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'tags': playlist['tags']
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'score': score[playlist['name']]
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} for playlist in playlists[:channels['userKeywords']]]
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videos = playlists[:channels['userKeywords']]
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playlists = playlists[channels['userKeywords']:]
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# 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()
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for tag in [tag for tag in playlist['tags'] if tag in sliders]:
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score[playlist['name']] += sliders[tag]
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# Select highest scoring playlists
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playlists = sorted(
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playlists,
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key=lambda playlist: -score[playlist['name']]
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)
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# Record the following for debug view input
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top_global_playlists = [{
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'name': playlist['name'],
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'tags': playlist['tags']
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'score': score[playlist['name']]
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} for playlist in playlists[:channels['globalKeywords']]]
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videos += playlists[:16 - channels['userKeywords']]
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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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'videos': [{
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'clips': video['clips'],
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'position': random.choice([i for i in range(len(video["clips"])) if not video["clips"][i].get("pass")]),
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'name': video['name'],
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'tags': video['tags'],
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} for video in videos],
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"top_user_playlists":top_user_playlists,
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"top_global_playlists": top_global_playlists
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}
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def update_user_playlists(self, user, watch_cutoff = 0.9):
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# 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.
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# Watched is defined as a video being played in full screen.
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# "watch_cutoff" parameter: the portion of the clip duration to be determined as watched the whole clip. should be [0,1]
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# + check (play, pause) pairs and eliminate unusual cases most likely due to a bug.
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# + If (play, pause) pairs exceed XX(80-90?) percent of the clip length, add "pass": True to the clip.
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# + Otherwise, find the last pause position of a clip and record it as "in" position of the clip.
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# + If clips are all marked as "pass" in a playlist, elliminate the playlist from the user playlists.
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playlists = copy.deepcopy(self.playlists)
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play = {}
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clip_max_dur = 10800 # = 3 hours; arbitrary max duration allowed for (pause time - play time) to detect outlier/bugs
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# The current max time of a clip duration is 10379.383333377269 from "DDLaunch: Erik Verlinde, Gravity as an emergent force (1956)"
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# A user could potentially spend more than 3 hours if they keep watching after the clip enters into the subsequent "scene"
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for event in user.get('events', [])[::-1]:
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if event["event"] == "play" and event["data"].get("type") == "video":
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play = event
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elif event["event"] == "pause" and play!={} and event["data"].get("type") == "video":
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if "position" not in play["data"]:
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play = {}
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break
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if play["data"].get("playlist") == event["data"].get("playlist"):
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if event["data"]["position"] - play["data"]["position"] > 0 and event["data"]["position"] - play["data"]["position"] < clip_max_dur and event["data"].get("playlistPosition") == play["data"].get("playlistPosition") and event["data"].get("playlistPosition") is not None:
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i = event["data"]["playlistPosition"]
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for playlist in playlists:
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if playlist["name"] == event["data"]["playlist"] and i < len(playlist["clips"]):
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if play["data"]["position"] >= max(playlist["clips"][i]["in"] - 15, 0) and event["data"]["position"] <= playlist["clips"][i]["out"] + 15:
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# 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.
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# 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)
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if "orig_in" not in playlist["clips"][i]:
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cutoff_pos = (playlist["clips"][i]["out"]-playlist["clips"][i]["in"])*watch_cutoff + playlist["clips"][i]["in"]
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else:
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cutoff_pos = (playlist["clips"][i]["out"]-playlist["clips"][i]["orig_in"])*watch_cutoff + playlist["clips"][i]["orig_in"]
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if event["data"]["position"] >= cutoff_pos:
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playlist["clips"][i]["pass"] = True
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else:
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if "orig_in" not in playlist["clips"][i]:
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# record the original "in" position to calculate cutoff position in the future
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playlist["clips"][i]["orig_in"] = playlist["clips"][i]["in"]
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# update "in" position of the clip in the playlist
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playlist["clips"][i]["in"] = event["data"]["position"]
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break
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play = {}
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for playlist in playlists.copy():
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unwatched = [clip for clip in playlist["clips"] if not clip.get("pass")]
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if not unwatched:
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playlists.remove(playlist)
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# If the number of playlists is reduced to 30, reset it to the original.
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if len(playlists) < 30:
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playlists = copy.deepcopy(self.playlists)
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return(playlists)
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def get_next(self, user, position):
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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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grid_events = {}
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video_num = 16
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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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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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prev_grid_list = sorted([v for v in grid_events.values()], key=lambda k:k['index'])
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vids_exclude = [e.get("playlist") for e in prev_grid_list]
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rec = self.get_recommendations(playlists, user, vids_exclude)
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return rec["videos"][position]
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def update_state(self, data):
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for key in data:
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if key in self.state:
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self.state[key].update(data[key])
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else:
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self.state[key] = data[key]
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self.save_state()
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return self.state
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def save_state(self):
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filename = os.path.join(self.path, 'state.json')
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with open(filename, 'w') as f:
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json.dump(self.state, f, indent=4, ensure_ascii=False, sort_keys=True)
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def update(self):
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# Get all storylines with tags
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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({
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'conditions': [
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{'key': 'type', 'operator': '==', 'value': 'storylines'},
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],
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'operator': '&'
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|
}, ['id', 'name', 'tags', 'nodename']) if entity.get('tags', []) and entity.get('nodename')]
|
|
# Get list of storyline names
|
|
names = list(set([storyline['name'] for storyline in storylines]))
|
|
# 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'])]
|
|
# Get all clips annotated with storyline references
|
|
clips = [clip for clip in self.pandora.find_annotations({
|
|
'conditions': [
|
|
{'key': 'layer', 'operator': '==', 'value': 'storylines'}
|
|
],
|
|
'operator': '&'
|
|
}, ['id', 'in', 'out', 'value']) if clip['value'] in names and clip['id'].split('/')[0] in items]
|
|
# Get list of ids for videos with clips
|
|
ids = list(set([clip['id'].split('/')[0] for clip in clips]))
|
|
# Get and cache video data
|
|
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_
|
|
], key=lambda video: int(video['order']))
|
|
with open(filename, 'w') as f:
|
|
f.write(json.dumps(videos, indent=4, sort_keys=True))
|
|
# Get video order
|
|
order = {video['id']: int(video['order']) for video in videos}
|
|
# Sort clips
|
|
clips = sorted(
|
|
clips,
|
|
key=lambda clip: (order[clip['id'].split('/')[0]], clip['in'])
|
|
)
|
|
# Get and cache playlists
|
|
self.playlists = [playlist for playlist in [{
|
|
'id': storyline['id'],
|
|
'name': storyline['nodename'].strip(),
|
|
'tags': storyline['tags'],
|
|
'clips': [{
|
|
'item': clip['id'].split('/')[0],
|
|
'id': clip['id'],
|
|
'in': clip['in'],
|
|
'out': clip['out']
|
|
} for clip in clips if clip['value'] == storyline['name']]
|
|
} 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))
|
|
self.update_keywords()
|
|
|
|
def update_keywords(self):
|
|
changed = False
|
|
if 'globalKeywords' not in self.state:
|
|
self.state['globalKeywords'] = {}
|
|
changed = True
|
|
existing_tags = set()
|
|
for playlist in self.playlists:
|
|
for tag in playlist.get('tags', []):
|
|
if not tag.isupper() and tag:
|
|
existing_tags.add(tag)
|
|
if not tag.isupper() and tag not in self.state['globalKeywords']:
|
|
self.state['globalKeywords'][tag] = {'value': 0}
|
|
changed = True
|
|
for tag in set(self.state['globalKeywords']) - existing_tags:
|
|
del self.state['globalKeywords'][tag]
|
|
changed = True
|
|
if changed:
|
|
self.save_state()
|
|
|
|
@run_async
|
|
def update_async(self):
|
|
self.update()
|
|
|
|
|
|
class Pandora:
|
|
|
|
# pan.do/ra API wrapper
|
|
|
|
def __init__(self, url, username, password):
|
|
self.api = ox.API(url)
|
|
self.api.signin(username=username, password=password)
|
|
|
|
def find(self, query, keys):
|
|
# print('FIND', query, keys)
|
|
return self.api.find({
|
|
'keys': keys,
|
|
'query': query,
|
|
'range': [0, 1000000]
|
|
})['data']['items']
|
|
|
|
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']
|
|
|
|
|
|
if __name__ == '__main__':
|
|
engine = Engine('json')
|
|
engine.update()
|