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117 lines
5.1 KiB
117 lines
5.1 KiB
# coding=utf-8
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import datetime
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import operator
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import itertools
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from dateutil import rrule
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from flask_restx import Resource, Namespace, reqparse, fields
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from functools import reduce
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from app.database import TableHistory, TableHistoryMovie
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from ..utils import authenticate
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api_ns_history_stats = Namespace('History Statistics', description='Get history statistics')
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@api_ns_history_stats.route('history/stats')
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class HistoryStats(Resource):
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get_request_parser = reqparse.RequestParser()
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get_request_parser.add_argument('timeFrame', type=str, default='month',
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help='Timeframe to get stats for. Must be in ["week", "month", "trimester", '
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'"year"]')
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get_request_parser.add_argument('action', type=str, default='All', help='Action type to filter for.')
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get_request_parser.add_argument('provider', type=str, default='All', help='Provider name to filter for.')
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get_request_parser.add_argument('language', type=str, default='All', help='Language name to filter for')
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series_data_model = api_ns_history_stats.model('history_series_stats_data_model', {
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'date': fields.String(),
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'count': fields.Integer(),
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})
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movies_data_model = api_ns_history_stats.model('history_movies_stats_data_model', {
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'date': fields.String(),
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'count': fields.Integer(),
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})
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get_response_model = api_ns_history_stats.model('HistoryStatsGetResponse', {
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'series': fields.Nested(series_data_model),
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'movies': fields.Nested(movies_data_model),
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})
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@authenticate
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@api_ns_history_stats.marshal_with(get_response_model, code=200)
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@api_ns_history_stats.response(401, 'Not Authenticated')
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@api_ns_history_stats.doc(parser=get_request_parser)
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def get(self):
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"""Get history statistics"""
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args = self.get_request_parser.parse_args()
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timeframe = args.get('timeFrame')
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action = args.get('action')
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provider = args.get('provider')
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language = args.get('language')
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# timeframe must be in ['week', 'month', 'trimester', 'year']
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if timeframe == 'year':
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delay = 364 * 24 * 60 * 60
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elif timeframe == 'trimester':
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delay = 90 * 24 * 60 * 60
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elif timeframe == 'month':
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delay = 30 * 24 * 60 * 60
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elif timeframe == 'week':
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delay = 6 * 24 * 60 * 60
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now = datetime.datetime.now()
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past = now - datetime.timedelta(seconds=delay)
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history_where_clauses = [(TableHistory.timestamp.between(past, now))]
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history_where_clauses_movie = [(TableHistoryMovie.timestamp.between(past, now))]
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if action != 'All':
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history_where_clauses.append((TableHistory.action == action))
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history_where_clauses_movie.append((TableHistoryMovie.action == action))
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else:
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history_where_clauses.append((TableHistory.action.in_([1, 2, 3])))
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history_where_clauses_movie.append((TableHistoryMovie.action.in_([1, 2, 3])))
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if provider != 'All':
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history_where_clauses.append((TableHistory.provider == provider))
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history_where_clauses_movie.append((TableHistoryMovie.provider == provider))
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if language != 'All':
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history_where_clauses.append((TableHistory.language == language))
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history_where_clauses_movie.append((TableHistoryMovie.language == language))
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history_where_clause = reduce(operator.and_, history_where_clauses)
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history_where_clause_movie = reduce(operator.and_, history_where_clauses_movie)
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data_series = TableHistory.select(TableHistory.timestamp, TableHistory.id)\
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.where(history_where_clause) \
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.dicts()
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data_series = [{'date': date[0], 'count': sum(1 for item in date[1])} for date in
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itertools.groupby(list(data_series),
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key=lambda x: x['timestamp'].strftime(
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'%Y-%m-%d'))]
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data_movies = TableHistoryMovie.select(TableHistoryMovie.timestamp, TableHistoryMovie.id) \
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.where(history_where_clause_movie) \
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.dicts()
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data_movies = [{'date': date[0], 'count': sum(1 for item in date[1])} for date in
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itertools.groupby(list(data_movies),
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key=lambda x: x['timestamp'].strftime(
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'%Y-%m-%d'))]
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for dt in rrule.rrule(rrule.DAILY,
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dtstart=datetime.datetime.now() - datetime.timedelta(seconds=delay),
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until=datetime.datetime.now()):
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if not any(d['date'] == dt.strftime('%Y-%m-%d') for d in data_series):
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data_series.append({'date': dt.strftime('%Y-%m-%d'), 'count': 0})
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if not any(d['date'] == dt.strftime('%Y-%m-%d') for d in data_movies):
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data_movies.append({'date': dt.strftime('%Y-%m-%d'), 'count': 0})
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sorted_data_series = sorted(data_series, key=lambda i: i['date'])
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sorted_data_movies = sorted(data_movies, key=lambda i: i['date'])
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return {'series': sorted_data_series, 'movies': sorted_data_movies}
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