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286 lines
9.5 KiB
286 lines
9.5 KiB
# imports {{{ #
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import math
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import random
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import requests
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import urllib
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import secrets
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import string
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import csv
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from django.shortcuts import render, redirect
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from django.http import JsonResponse
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from django.db.models import Count, Q, Max
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from django.core.files import File
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from .utils import *
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from .models import *
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from login.models import User
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from login.utils import get_user_context
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from dateutil.parser import parse
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from pprint import pprint
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from login.models import HistoryUpload
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# }}} imports #
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# constants {{{ #
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USER_TRACKS_LIMIT = 50
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TRACKS_LIMIT = 50
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HISTORY_LIMIT = 50
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ARTIST_LIMIT = 50
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FEATURES_LIMIT = 100
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# ARTIST_LIMIT = 25
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# FEATURES_LIMIT = 25
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# TRACKS_TO_QUERY = 100
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TRACKS_TO_QUERY = 500
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TRACKS_ENDPOINT = 'https://api.spotify.com/v1/tracks'
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CONSOLE_LOGGING = True
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# CONSOLE_LOGGING = False
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# }}} constants #
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# parse_library {{{ #
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def parse_library(request, user_secret):
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"""Scans user's library for num_tracks and store the information in a
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database.
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:user_secret: secret for User object who's library is being scanned.
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:returns: None
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"""
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offset = 0
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payload = {'limit': str(USER_TRACKS_LIMIT)}
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artist_genre_queue = []
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features_queue = []
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user_obj = User.objects.get(secret=user_secret)
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user_headers = get_user_header(user_obj)
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# create this obj so loop runs at least once
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saved_tracks_response = [0]
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# scan until reach num_tracks or no tracks left if scanning entire library
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while ((TRACKS_TO_QUERY == 0 or offset < TRACKS_TO_QUERY) and
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len(saved_tracks_response) > 0):
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payload['offset'] = str(offset)
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saved_tracks_response = requests.get('https://api.spotify.com/v1/me/tracks',
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headers=user_headers,
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params=payload).json()['items']
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tracks_processed = 0
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for track_dict in saved_tracks_response:
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track_artists = save_track_artists(track_dict['track'], artist_genre_queue,
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user_headers)
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track_obj, track_created = save_track_obj(track_dict['track'],
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track_artists, user_obj)
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# add audio features {{{ #
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# if a new track is not created, the associated audio feature does
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# not need to be created again
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if track_created:
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features_queue.append(track_obj)
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if len(features_queue) == FEATURES_LIMIT:
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get_audio_features(user_headers, features_queue)
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features_queue = []
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# }}} add audio features #
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if CONSOLE_LOGGING:
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tracks_processed += 1
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print("Added track #{}: {} - {}".format(
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offset + tracks_processed,
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track_obj.artists.first(),
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track_obj.name,
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))
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# calculates num_songs with offset + songs retrieved
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offset += USER_TRACKS_LIMIT
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# clean-up {{{ #
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# update remaining artists without genres and songs without features if
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# there are any
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if len(artist_genre_queue) > 0:
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add_artist_genres(user_headers, artist_genre_queue)
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if len(features_queue) > 0:
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get_audio_features(user_headers, features_queue)
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# }}} clean-up #
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update_track_genres(user_obj)
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return render(request, 'graphs/logged_in.html', get_user_context(user_obj))
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# }}} parse_library #
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# parse_history_request {{{ #
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def parse_history_request(request, user_secret):
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"""Request function to call parse_history. Scans user's listening history
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and stores the information in a database.
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:user_secret: secret for User object who's library is being scanned.
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:returns: redirects user to logged in page
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"""
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parse_history(user_secret)
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return render(request, 'graphs/logged_in.html',
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get_user_context(User.objects.get(secret=user_secret)))
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# }}} get_history #
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# get_artist_data {{{ #
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def get_artist_data(request, user_secret):
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"""Returns artist data as a JSON serialized list of dictionaries
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The (key, value) pairs are (artist name, song count for said artist)
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:param request: the HTTP request
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:param user_secret: the user secret used for identification
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:return: a JsonResponse
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"""
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user = User.objects.get(secret=user_secret)
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artist_counts = Artist.objects.annotate(num_songs=Count('track',
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filter=Q(track__users=user)))
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processed_artist_counts = [{'name': artist.name, 'num_songs': artist.num_songs}
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for artist in artist_counts if artist.num_songs > 2]
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if CONSOLE_LOGGING:
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pprint(processed_artist_counts)
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return JsonResponse(data=processed_artist_counts, safe=False)
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# }}} get_artist_data #
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# get_audio_feature_data {{{ #
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def get_audio_feature_data(request, audio_feature, user_secret):
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"""Returns all data points for a given audio feature
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Args:
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request: the HTTP request
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audio_feature: The audio feature to be queried
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user_secret: client secret, used to identify the user
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"""
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user = User.objects.get(secret=user_secret)
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user_tracks = Track.objects.filter(users=user)
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response_payload = {
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'data_points': [],
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}
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for track in user_tracks:
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try:
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audio_feature_obj = AudioFeatures.objects.get(track=track)
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response_payload['data_points'].append(getattr(audio_feature_obj, audio_feature))
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except AudioFeatures.DoesNotExist:
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continue
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return JsonResponse(response_payload)
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# }}} get_audio_feature_data #
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# get_genre_data {{{ #
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def get_genre_data(request, user_secret):
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"""Return genre data needed to create the graph
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TODO
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"""
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user = User.objects.get(secret=user_secret)
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genre_counts = (Track.objects.filter(users__exact=user)
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.values('genre')
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.order_by('genre')
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# annotates each genre and not each Track, due to the earlier values() call
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.annotate(num_songs=Count('genre'))
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)
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genre_counts = [genre_dict for genre_dict in genre_counts if
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genre_dict['num_songs'] > 3]
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# genre_counts is a QuerySet with the format
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'''
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Now genre_counts has the format [ {'genre': 'classical', 'num_songs': 100,
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'artists': { 'Helene Grimaud': 40.5, 'Beethoven': 31.2, ... }},... ]
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'''
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for genre_dict in genre_counts:
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genre_dict['artists'] = get_artists_in_genre(user, genre_dict['genre'])
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if CONSOLE_LOGGING:
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print("*** Genre Breakdown ***")
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pprint(list(genre_counts))
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return JsonResponse(data=list(genre_counts), safe=False)
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# }}} get_genre_data #
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# import_history {{{ #
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def import_history(request, upload_id):
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"""Import history for the user from the file they uploaded.
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:upload_id: ID (PK) of the HistoryUpload entry
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:returns: None
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"""
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# setup {{{ #
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headers = ['timestamp', 'track_id']
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upload_obj = HistoryUpload.objects.get(id=upload_id)
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user_headers = get_user_header(upload_obj.user)
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with upload_obj.document.open('r') as f:
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csv_reader = csv.reader(f, delimiter=',')
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rows_read = 0
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history_obj_info_lst = []
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artist_genre_queue = []
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# skip header row
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last_row, history_obj_info = get_next_history_row(csv_reader, headers,
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{})
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while not last_row:
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last_row, history_obj_info = get_next_history_row(csv_reader,
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headers, history_obj_info)
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# }}} setup #
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history_obj_info_lst.append(history_obj_info)
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# PU: refactor saving History object right away if Track obj already
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# exists
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# PU: refactor below?
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rows_read += 1
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if (rows_read % TRACKS_LIMIT == 0) or last_row:
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# get tracks_response {{{ #
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track_ids_lst = [info['track_id'] for info in history_obj_info_lst]
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# print(len(track_ids_lst))
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track_ids = ','.join(track_ids_lst)
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payload = {'ids': track_ids}
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tracks_response = requests.get(TRACKS_ENDPOINT,
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headers=user_headers,
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params=payload).json()['tracks']
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responses_processed = 0
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# }}} get tracks_response #
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for track_dict in tracks_response:
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# don't associate history track with User, not necessarily in their
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# library
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track_artists = save_track_artists(track_dict, artist_genre_queue,
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user_headers)
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track_obj, track_created = save_track_obj(track_dict,
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track_artists, None)
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timestamp = \
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parse(history_obj_info_lst[responses_processed]['timestamp'])
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history_obj = save_history_obj(upload_obj.user, timestamp,
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track_obj)
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if CONSOLE_LOGGING:
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print("Processed row #{}: {}".format(
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(rows_read - TRACKS_LIMIT) + responses_processed, history_obj,))
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responses_processed += 1
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history_obj_info_lst = []
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if len(artist_genre_queue) > 0:
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add_artist_genres(user_headers, artist_genre_queue)
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# TODO: update track genres from History relation
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# update_track_genres(user_obj)
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return redirect('graphs:display_history_table')
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# }}} get_history #
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