import pytest import random import datetime from model_bakery import baker from django.utils import timezone as tz from datetime import timedelta import pytz from aircox.models import Diffusion, Episode #TODO fixture for rerun diffusion @pytest.fixture def diffusions_time_variation(episodes): random_episode = random.choice([episodes[1], episodes[0], episodes[2]]) now_date = datetime.date.today() now_datetime = tz.now() tomorrow_datetime = now_datetime + timedelta(hours=25) yesterday_datetime = now_datetime - timedelta(hours=25) now_diffusion = baker.make( Diffusion, episode=random_episode, start=now_datetime - timedelta(minutes=30), end=now_datetime + timedelta(minutes=30), ) after_diffusion = baker.make( Diffusion, episode=random_episode, start=now_datetime + timedelta(minutes=30), end=now_datetime + timedelta(minutes=60), ) tomorrow_diffusion = baker.make( Diffusion, episode=random_episode, start=tomorrow_datetime, end=tomorrow_datetime + timedelta(minutes=30), ) before_diffusion = baker.make( Diffusion, episode=random_episode, start=now_datetime - timedelta(minutes=60), end=now_datetime - timedelta(minutes=30), ) yesterday_diffusion = baker.make( Diffusion, episode=random_episode, start=yesterday_datetime, end=yesterday_datetime + timedelta(minutes=30), ) return ( now_date, now_datetime, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) @pytest.fixture def diffusions_episode_variation(episodes): key_episode = episodes[1] another_episode = episodes[2] diffusions_with_the_key_episode = baker.make( Diffusion, _quantity=3, episode=key_episode ) diffusions_without_the_key_episode = baker.make( Diffusion, _quantity=3, episode=another_episode ) return ( key_episode, another_episode, diffusions_with_the_key_episode, diffusions_without_the_key_episode, ) class TestDiffusionQuerySet: @pytest.mark.django_db def test_episode_by_obj(self, diffusions_episode_variation): ( key_episode, _, diffusions_with_the_key_episode, diffusions_without_the_key_episode, ) = diffusions_episode_variation result = Diffusion.objects.episode(episode=key_episode) for diffusion in diffusions_with_the_key_episode: assert diffusion in result for diffusion in diffusions_without_the_key_episode: assert diffusion not in result @pytest.mark.django_db def test_episode_by_id(self, diffusions_episode_variation): ( key_episode, _, diffusions_with_the_key_episode, diffusions_without_the_key_episode, ) = diffusions_episode_variation result = Diffusion.objects.episode(id=key_episode.id) for diffusion in diffusions_with_the_key_episode: assert diffusion in result for diffusion in diffusions_without_the_key_episode: assert diffusion not in result @pytest.mark.django_db def test_on_air(self, episodes): for episode in episodes: random_type = random.choice( [Diffusion.TYPE_ON_AIR, Diffusion.TYPE_UNCONFIRMED] ) baker.make(Diffusion, episode=episode, type=random_type) result = Diffusion.objects.on_air() for diffusion in result: assert diffusion.type == Diffusion.TYPE_ON_AIR assert diffusion.type != Diffusion.TYPE_UNCONFIRMED # la méthode "now" filtre les diffusions en cours d'un moment précis. # elle prend en compte un objet datetime (date + heure) # les diffusions en cours sont définie en fonction de l'argument "now" ou de l'heure actuelle si now=None. # la méthode distinct élimine les doublons de diffusions (si ils ont des valeurs identiques pour tous les champs de la db) # TODO test si il y a doublon qu'un seul objet soit récupéré. @pytest.mark.django_db def test_now_test(self, diffusions_time_variation): now = tz.now() ( _, _, _, _, now_diffusion, _, _, ) = diffusions_time_variation result = Diffusion.objects.now(now=now, order=True) assert len(result) == 1 assert result[0] == now_diffusion assert result[0].start <= now <= result[0].end # méthode date filtre les diffusions en cours d'une date précise. # elle ne prend pas en compte un objet datetime mais un "objet date" uniquement # elle crée deux objets datetime (start and end) à partir de l'argument "date" (if none = today) # elle utilise la méthode "combine" de la classe "datetime" pour créer ces deux objets à partir de la date # elle filtre ensuite les diffusions qui ont lieu entre "start" et "end". @pytest.mark.django_db def test_date_without_date_arg(self, diffusions_time_variation): ( _, _, _, before_diffusion, now_diffusion, after_diffusion, _, ) = diffusions_time_variation result = Diffusion.objects.date() assert len(result) == 3 assert result[0] == before_diffusion assert result[1] == now_diffusion assert result[2] == after_diffusion @pytest.mark.django_db def test_date_with_date_arg(self, diffusions_time_variation): today_date = datetime.date.today() tomorrow_date = today_date + timedelta(days=1) ( _, _, _, _, _, _, tomorrow_diffusion, ) = diffusions_time_variation result = Diffusion.objects.date(date=tomorrow_date) assert len(result) == 1 assert result[0] == tomorrow_diffusion # la méthode at récupère les diffusions à une date donnée. # elle utilise la méthode now si la date est un objet datetime # elle utilise la méthode date si la date est un objet date @pytest.mark.django_db def test_at_datetimeobj(self, diffusions_time_variation): ( _, now_datetime, _, _, now_diffusion, _, _, ) = diffusions_time_variation result = Diffusion.objects.at(date=now_datetime) assert len(result) == 1 assert now_diffusion in result @pytest.mark.django_db def test_at_dateobj(self, diffusions_time_variation): ( now_date, _, _, before_diffusion, now_diffusion, after_diffusion, _, ) = diffusions_time_variation result = Diffusion.objects.at(date=now_date) assert len(result) == 3 assert result[0] == before_diffusion assert result[1] == now_diffusion assert result[2] == after_diffusion @pytest.mark.django_db def test_after_without_arg(self, diffusions_time_variation): ( _, _, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation from_now_diffusions = Diffusion.objects.after() assert tomorrow_diffusion in from_now_diffusions assert after_diffusion in from_now_diffusions assert now_diffusion in from_now_diffusions assert before_diffusion not in from_now_diffusions assert yesterday_diffusion not in from_now_diffusions @pytest.mark.django_db def test_after_with_datetime_arg(self, diffusions_time_variation): ( _, now_datetime, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation from_now_diffusions = Diffusion.objects.after(date=now_datetime) assert tomorrow_diffusion in from_now_diffusions assert after_diffusion in from_now_diffusions assert now_diffusion in from_now_diffusions assert before_diffusion not in from_now_diffusions assert yesterday_diffusion not in from_now_diffusions @pytest.mark.django_db def test_after_with_date_arg(self, diffusions_time_variation): ( now_date, _, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation from_today_diffusions = Diffusion.objects.after(date=now_date) assert tomorrow_diffusion in from_today_diffusions assert after_diffusion in from_today_diffusions assert now_diffusion in from_today_diffusions assert before_diffusion in from_today_diffusions assert yesterday_diffusion not in from_today_diffusions @pytest.mark.django_db def test_before_without_arg(self, diffusions_time_variation): ( _, _, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation before_now_diffusions = Diffusion.objects.before() assert tomorrow_diffusion not in before_now_diffusions assert after_diffusion not in before_now_diffusions assert now_diffusion in before_now_diffusions assert before_diffusion in before_now_diffusions assert yesterday_diffusion in before_now_diffusions @pytest.mark.django_db def test_before_with_datetime_arg(self, diffusions_time_variation): ( _, now_datetime, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation before_now_diffusions = Diffusion.objects.before(date=now_datetime) assert tomorrow_diffusion not in before_now_diffusions assert after_diffusion not in before_now_diffusions assert now_diffusion in before_now_diffusions assert before_diffusion in before_now_diffusions assert yesterday_diffusion in before_now_diffusions @pytest.mark.django_db def test_before_with_date_arg(self, diffusions_time_variation): ( now_date, _, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation before_today_diffusions = Diffusion.objects.before(date=now_date) assert tomorrow_diffusion not in before_today_diffusions assert after_diffusion not in before_today_diffusions assert now_diffusion not in before_today_diffusions assert before_diffusion not in before_today_diffusions assert yesterday_diffusion in before_today_diffusions @pytest.mark.django_db def test_range(self, episodes, diffusions_time_variation): ( _, _, yesterday_diffusion, before_diffusion, now_diffusion, after_diffusion, tomorrow_diffusion, ) = diffusions_time_variation start = before_diffusion.start end = after_diffusion.end overlaping_start_diffusion = baker.make( Diffusion, episode=episodes[0], start=start - timedelta(minutes=30), end=end, ) overlaping_end_diffusion = baker.make( Diffusion, episode=episodes[0], start=start, end=end + timedelta(minutes=30), ) range_diffusion = Diffusion.objects.range(start=start, end=end) assert before_diffusion in range_diffusion assert after_diffusion in range_diffusion assert now_diffusion in range_diffusion assert overlaping_start_diffusion not in range_diffusion assert overlaping_end_diffusion not in range_diffusion assert tomorrow_diffusion not in range_diffusion assert yesterday_diffusion not in range_diffusion class TestDiffusion: @pytest.mark.django_db def test__str__initial_diffusion(self, programs): episode = baker.make( Episode, program=programs[0], title="Episode title" ) diffusion = baker.make( Diffusion, episode=episode, start=datetime.datetime(2023, 5, 12, 13, 0, tzinfo=pytz.UTC), ) expected_str = "Episode title - 2023/05/12 13:00+0000" returned_str = diffusion.__str__() assert expected_str == returned_str @pytest.mark.django_db def test__str__rerun_diffusion(self, programs): episode = baker.make( Episode, program=programs[0], title="Episode title" ) initial_diffusion = baker.make(Diffusion, episode=episode) rerun_diffusion = baker.make( Diffusion, episode=episode, start=datetime.datetime(2023, 5, 12, 13, 0, tzinfo=pytz.UTC), initial=initial_diffusion, ) expected_str = "Episode title - 2023/05/12 13:00+0000 (rerun)" returned_str = rerun_diffusion.__str__() assert expected_str == returned_str # dans la méthode self._initial[valeur] est un dictionnaire qui stocke les valeurs initiales des champs de l'objet au moment de sa création # save # si diffusion est initial et si son épisode a été modifié depuis la création initiale # la méthode save update l'épisode et le programme sur paramètre initial (rerun_set) de la rediffusion (qui représente l'objet diffusion initial). """ je ne comprends pas rerun_set.update, que la méthode l'update ou pas, on accède quand même à l'épisode mis à jour sur la diffusion initiale""" @pytest.mark.django_db def test_save_rerun_diffusion(self, episodes, programs): initial_diffusion = baker.make( Diffusion, program=programs[0], episode=episodes[0] ) rerun_diffusion = baker.make( Diffusion, program=programs[0], episode=episodes[0], initial=initial_diffusion, ) initial_diffusion.episode = episodes[1] initial_diffusion.program = programs[1] initial_diffusion.save() assert rerun_diffusion.initial.episode == episodes[1] assert rerun_diffusion.initial.program == programs[1]