def test_should_not_count_bookings_appearing_on_payment_if_payment_s_current_status_is_banned(
self, ):
# Given
create_user(id=1)
create_user(id=2, email="*****@*****.**")
create_product(id=1)
create_product(id=2)
create_offerer(id=3)
create_venue(
offerer_id=3,
id=1,
siret=None,
postal_code=None,
city=None,
departement_code=None,
is_virtual=True,
)
create_offer(venue_id=1, product_id=1, id=3)
create_stock(offer_id=3, id=1)
create_offer(venue_id=1, product_id=2, id=2)
create_stock(offer_id=2, id=2)
create_booking(user_id=1, stock_id=1, id=4, quantity=2)
create_payment(booking_id=4, id=1)
create_payment_status(payment_id=1,
id=1,
date="2019-01-01",
status="PENDING")
create_payment_status(payment_id=1,
id=2,
date="2019-01-02",
status="BANNED")
expected_stocks_booking_information = pandas.Series(
index=pandas.Index(data=[1, 2], name="stock_id"),
data=[0, 0],
name="Nombre de réservations ayant un paiement",
)
# When
query = _get_stocks_booking_information_query()
# Then
with ENGINE.connect() as connection:
stocks_booking_information = pandas.read_sql(
query, connection, index_col="stock_id")
pandas.testing.assert_series_equal(
stocks_booking_information[
"Nombre de réservations ayant un paiement"],
expected_stocks_booking_information,
)
# Then
pandas.testing.assert_series_equal(
stocks_booking_information[
"Nombre de réservations ayant un paiement"],
expected_stocks_booking_information,
)
def test_should_return_column_with_number_of_bookings_appearing_on_payment(
self, ):
# Given
create_user(id=1)
create_user(id=2, email="*****@*****.**")
create_product(id=1)
create_product(id=2)
create_offerer(id=3)
create_venue(
offerer_id=3,
id=1,
siret=None,
postal_code=None,
city=None,
departement_code=None,
is_virtual=True,
)
create_offer(venue_id=1, product_id=1, id=3)
create_stock(offer_id=3, id=1)
create_offer(venue_id=1, product_id=2, id=2)
create_stock(offer_id=2, id=2)
create_booking(user_id=1, stock_id=1, id=4, quantity=2)
create_booking(user_id=2,
stock_id=2,
id=5,
quantity=1,
token="IS02JE")
create_payment(booking_id=4, id=1)
create_payment_status(payment_id=1)
expected_stocks_booking_information = pandas.Series(
index=pandas.Index(data=[1, 2], name="stock_id"),
data=[2, 0],
name="Nombre de réservations ayant un paiement",
)
# When
query = _get_stocks_booking_information_query()
# Then
with ENGINE.connect() as connection:
stocks_booking_information = pandas.read_sql(
query, connection, index_col="stock_id")
pandas.testing.assert_series_equal(
stocks_booking_information[
"Nombre de réservations ayant un paiement"],
expected_stocks_booking_information,
)
def test_should_return_all_values(self):
# Given
create_user(id=1)
create_user(id=2, email="*****@*****.**")
create_product(id=1, product_type="EventType.CINEMA")
create_product(id=2, product_type="ThingType.LIVRE_EDITION")
create_offerer(id=3)
create_venue(
offerer_id=3,
id=1,
siret=None,
postal_code=None,
city=None,
departement_code=None,
is_virtual=True,
)
create_offer(
venue_id=1,
product_id=1,
id=3,
product_type="EventType.CINEMA",
name="Test",
)
create_stock(
offer_id=3,
id=1,
date_created="2019-11-01",
quantity=10,
booking_limit_datetime="2019-11-23",
beginning_datetime="2019-11-24",
)
create_offer(
venue_id=1,
product_id=2,
id=2,
product_type="ThingType.LIVRE_EDITION",
name="Test bis",
)
create_stock(offer_id=2,
id=2,
date_created="2019-10-01",
quantity=12)
create_booking(user_id=1, stock_id=1, id=4, quantity=2)
create_payment(booking_id=4, id=1)
create_payment_status(payment_id=1,
id=1,
date="2019-01-01",
status="PENDING")
create_stocks_booking_view(ENGINE)
create_available_stocks_view(ENGINE)
expected_stocks_details = pandas.DataFrame(
index=pandas.Index(data=[1, 2], name="stock_id"),
data={
"Identifiant de l'offre": [3, 2],
"Nom de l'offre": ["Test", "Test bis"],
"offerer_id": [3, 3],
"Type d'offre":
["EventType.CINEMA", "ThingType.LIVRE_EDITION"],
"Département": [None, None],
"Date de création du stock": [
datetime(2019, 11, 1),
datetime(2019, 10, 1),
],
"Date limite de réservation":
[datetime(2019, 11, 23), pandas.NaT],
"Date de début de l'évènement": [
datetime(2019, 11, 24),
pandas.NaT,
],
"Stock disponible réel": [8, 12],
"Stock disponible brut de réservations": [10, 12],
"Nombre total de réservations": [2, 0],
"Nombre de réservations annulées": [0, 0],
"Nombre de réservations ayant un paiement": [2, 0],
},
)
# When
create_materialized_enriched_stock_view(ENGINE)
# Then
with ENGINE.connect() as connection:
stocks_details = pandas.read_sql_table("enriched_stock_data",
connection,
index_col="stock_id")
pandas.testing.assert_frame_equal(stocks_details,
expected_stocks_details)
def test_should_create_enriched_offer_data_view_without_duplicates(
self):
# Given
create_user(id=1)
create_user(id=2, email="*****@*****.**")
create_user(id=3, email="*****@*****.**")
create_product(id=1, product_type="EventType.CINEMA")
create_product(id=2, product_type="ThingType.LIVRE_EDITION")
create_offerer(id=3)
create_offerer(id=4, siren="234567890")
create_venue(offerer_id=3, id=1, siret="12345678900026")
create_venue(offerer_id=4, id=2, siret="23456789000067")
create_offer(
venue_id=1,
product_id=1,
id=3,
product_type="EventType.CINEMA",
name="Test",
)
create_offer(
venue_id=2,
product_id=2,
id=4,
product_type="ThingType.LIVRE_EDITION",
name="RIP Dylan Rieder",
)
create_stock(
offer_id=3,
id=1,
date_created="2019-11-01",
quantity=10,
booking_limit_datetime="2019-11-23",
beginning_datetime="2019-11-24",
)
create_stock(offer_id=4,
id=2,
date_created="2019-10-01",
quantity=12)
create_booking(user_id=1, stock_id=1, id=4, quantity=2)
create_payment(booking_id=4, id=1)
create_payment_status(payment_id=1,
id=1,
date="2019-01-01",
status="PENDING")
create_favorite(id=1, offer_id=3, user_id=1)
create_favorite(id=2, offer_id=4, user_id=2)
create_favorite(id=3, offer_id=3, user_id=3)
expected_enriched_offer = pandas.DataFrame(
index=pandas.Index(data=[3, 4], name="offer_id"),
data={
"Identifiant de la structure": [3, 4],
"Nom de la structure": ["Test Offerer", "Test Offerer"],
"Identifiant du lieu": [1, 2],
"Nom du lieu": ["Test Venue", "Test Venue"],
"Département du lieu": ["93", "93"],
"Nom de l'offre": ["Test", "RIP Dylan Rieder"],
"Catégorie de l'offre": [
"EventType.CINEMA",
"ThingType.LIVRE_EDITION",
],
"Date de création de l'offre": [
datetime(2019, 11, 20),
datetime(2019, 11, 20),
],
"isDuo": [False, False],
"Offre numérique": [False, False],
"Bien physique": [False, True],
"Sortie": [True, False],
"Nombre de réservations": [2.0, 0.0],
"Nombre de réservations annulées": [0.0, 0.0],
"Nombre de réservations validées": [0.0, 0.0],
"Nombre de fois où l'offre a été mise en favoris":
[2.0, 1.0],
"Stock": [10.0, 12.0],
"offer_humanized_id": ["AM", "AQ"],
"Lien portail pro": [
"https://pro.passculture.beta.gouv.fr/offres/AM",
"https://pro.passculture.beta.gouv.fr/offres/AQ"
],
"Lien WEBAPP": [
"https://app.passculture.beta.gouv.fr/offre/details/AM",
"https://app.passculture.beta.gouv.fr/offre/details/AQ"
],
"Lien vers FlaskAdmin": [
"https://backend.passculture.beta.gouv.fr/pc/back-office/offersqlentity/edit/?id=3",
"https://backend.passculture.beta.gouv.fr/pc/back-office/offersqlentity/edit/?id=4"
],
"Nombre de premières réservations": [1.0, np.nan]
},
)
# When
create_enriched_offer_data(ENGINE)
# Then
with ENGINE.connect() as connection:
offer_details = pandas.read_sql_table("enriched_offer_data",
connection,
index_col="offer_id")
pandas.testing.assert_frame_equal(offer_details,
expected_enriched_offer)
def test_should_return_booking_payment_status(self, app):
# Given
create_user(id=1)
create_deposit(user_id=1)
create_offerer(id=1)
create_venue(offerer_id=1, id=1)
create_product(id=1, product_type="ThingType.ACTIVATION")
create_offer(venue_id=1,
product_id=1,
id=1,
product_type="ThingType.ACTIVATION")
create_stock(offer_id=1, id=1)
create_product(id=2, product_type="ThingType.MUSIQUE")
create_offer(venue_id=1,
product_id=2,
id=2,
product_type="ThingType.MUSIQUE")
create_stock(offer_id=2, id=2)
create_booking(id=1,
user_id=1,
quantity=1,
stock_id=2,
is_used=True)
create_booking(
id=2,
user_id=1,
quantity=1,
amount=10,
stock_id=2,
token="ABC321",
is_used=True,
)
create_booking(
id=3,
user_id=1,
quantity=3,
amount=5,
stock_id=2,
token="FAM321",
is_cancelled=True,
)
create_payment(id=1, booking_id=2, amount=10)
create_payment_status(id=1, payment_id=1, status="SENT")
create_payment(id=2, booking_id=3, amount=15)
create_payment_status(id=2, payment_id=2, status="PENDING")
expected_booking_payment_status = pandas.Series(
data=["Remboursé"],
name="Remboursé",
index=Int64Index([2], name="booking_id"),
)
# When
query = get_booking_payment_status()
# Then
with ENGINE.connect() as connection:
booking_payment = pandas.read_sql(query,
connection,
index_col="booking_id")
pandas.testing.assert_series_equal(
booking_payment["Remboursé"],
expected_booking_payment_status)
def test_should_return_booking_ranking(app):
# Given
create_user(id=1)
create_user(id=2, email="*****@*****.**")
create_deposit(id=1, user_id=1)
create_deposit(id=2, user_id=2)
create_offerer(id=1)
create_venue(offerer_id=1, id=1)
create_product(id=1, product_type="ThingType.ACTIVATION")
create_offer(venue_id=1,
product_id=1,
id=1,
product_type="ThingType.ACTIVATION")
create_stock(offer_id=1, id=1)
create_product(id=2, product_type="ThingType.MUSIQUE")
create_offer(venue_id=1,
product_id=2,
id=2,
product_type="ThingType.MUSIQUE")
create_stock(offer_id=2, id=2)
create_product(id=3, product_type="ThingType.AUDIOVISUEL")
create_offer(venue_id=1,
product_id=3,
id=3,
product_type="ThingType.AUDIOVISUEL")
create_stock(offer_id=3, id=3)
create_booking(id=1,
user_id=1,
quantity=1,
stock_id=2,
is_used=True)
create_booking(
id=2,
user_id=1,
quantity=1,
amount=10,
stock_id=3,
token="ABC321",
is_used=True,
date_created="2020-05-11",
)
create_booking(
id=3,
user_id=1,
quantity=3,
amount=5,
stock_id=2,
token="FAM321",
is_cancelled=True,
date_created="2020-06-21",
)
create_booking(
id=4,
user_id=2,
quantity=1,
amount=5,
stock_id=3,
token="OLD321",
is_used=True,
date_created="2020-06-21",
)
create_booking(
id=5,
user_id=2,
quantity=1,
amount=5,
stock_id=2,
token="YOO321",
is_used=True,
date_created="2020-10-25",
)
create_payment(id=1, booking_id=2, amount=10)
create_payment_status(id=1, payment_id=1, status="SENT")
create_payment(id=2, booking_id=3, amount=15)
create_payment_status(id=2, payment_id=2, status="PENDING")
expected_booking_ranking = pandas.Series(
data=[1, 1, 2, 1, 1],
name="Classement de la réservation dans la même catégorie",
index=Int64Index([1, 2, 3, 4, 5], name="booking_id"),
)
# When
query = get_booking_ranking_in_category()
# Then
with ENGINE.connect() as connection:
booking_ranking = pandas.read_sql(query,
connection,
index_col="booking_id")
pandas.testing.assert_series_equal(
booking_ranking[
"Classement de la réservation dans la même catégorie"],
expected_booking_ranking,
)