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