def test_if_booking_on_physical_good_type_but_has_url_return_0(self):
# Given
create_user(id=1)
create_deposit(amount=500)
create_offerer(id=10)
create_product(id=1, product_type="ThingType.MUSIQUE")
create_venue(id=15, offerer_id=10)
create_offer(
id=30,
venue_id=15,
product_type="ThingType.MUSIQUE",
url="u.rl",
product_id=1,
)
create_stock(id=20, offer_id=30)
create_booking(user_id=1, amount=10, quantity=1, stock_id=20)
# When
query = _get_theoric_amount_spent_in_physical_goods_query()
# Then
with ENGINE.connect() as connection:
theoric_amount_spent_in_physical = pandas.read_sql(
query, connection, index_col="user_id")
pandas.testing.assert_frame_equal(
theoric_amount_spent_in_physical,
pandas.DataFrame(
[0.0],
columns=["Dépenses physiques"],
index=Int64Index([1], name="user_id"),
),
)
def test_if_booking_is_not_used_return_zero(self):
# Given
create_user(id=45)
create_offerer(id=1)
create_venue(offerer_id=1)
create_product(id=1)
create_offer(venue_id=1, product_id=1, id=1)
create_stock(offer_id=1, id=1)
create_deposit(user_id=45)
create_booking(
user_id=45,
stock_id=1,
quantity=1,
amount=10,
is_cancelled=False,
is_used=False,
)
# When
query = _get_actual_amount_spent_query()
# Then
with ENGINE.connect() as connection:
amount_spent = pandas.read_sql(query,
connection,
index_col="user_id")
pandas.testing.assert_frame_equal(
amount_spent,
pandas.DataFrame(
[0.0],
columns=["Montant réél dépensé"],
index=Int64Index([45], name="user_id"),
),
)
def test_if_booking_amount_10_and_quantity_2_return_20(self):
# Given
create_user(id=45)
create_offerer(id=1)
create_venue(offerer_id=1)
create_product(id=1)
create_offer(venue_id=1, product_id=1, id=1)
create_stock(offer_id=1, id=1)
create_deposit(user_id=45)
create_booking(
user_id=45,
stock_id=1,
quantity=2,
amount=10,
is_cancelled=False,
is_used=True,
)
# When
query = _get_theoric_amount_spent_query()
# Then
with ENGINE.connect() as connection:
theoric_amount_spent = pandas.read_sql(query,
connection,
index_col="user_id")
pandas.testing.assert_frame_equal(
theoric_amount_spent,
pandas.DataFrame(
[20.0],
columns=["Montant théorique dépensé"],
index=Int64Index([45], name="user_id"),
),
)
def test_if_booking_on_outings_return_amount(self):
# Given
create_user(id=1)
create_deposit(amount=500)
create_offerer(id=10)
create_product(id=1,
product_type="ThingType.MUSEES_PATRIMOINE_ABO")
create_venue(id=15, offerer_id=10)
create_offer(
id=30,
venue_id=15,
product_type="ThingType.MUSEES_PATRIMOINE_ABO",
product_id=1,
)
create_stock(id=20, offer_id=30)
create_booking(user_id=1, amount=10, quantity=2, stock_id=20)
# When
query = _get_theoric_amount_spent_in_outings_query()
# Then
with ENGINE.connect() as connection:
theoric_amount_spent_in_outings = pandas.read_sql(
query, connection, index_col="user_id")
pandas.testing.assert_frame_equal(
theoric_amount_spent_in_outings,
pandas.DataFrame(
[20.0],
columns=["Dépenses sorties"],
index=Int64Index([1], name="user_id"),
),
)
def test_should_return_how_many_time_first_booking(self):
# Given
create_user(id=1)
create_deposit(amount=500)
create_offerer(id=10)
create_product(id=1,
product_type="ThingType.MUSEES_PATRIMOINE_ABO")
create_venue(id=15, offerer_id=10)
create_offer(
id=30,
venue_id=15,
product_type="ThingType.MUSEES_PATRIMOINE_ABO",
product_id=1,
)
create_stock(id=20, offer_id=30)
create_booking(id=1,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
is_used=True)
create_booking(
id=2,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
token="ABC321",
is_used=True,
)
create_booking(
id=3,
user_id=1,
amount=10,
quantity=3,
stock_id=20,
token="FAM321",
is_cancelled=True,
)
expected_first_booking_number = pandas.Series(
index=pandas.Index(data=[30], name="offer_id"),
data=[1],
name="Nombre de premières réservations",
)
# When
query = _get_count_first_booking_query()
# Then
with ENGINE.connect() as connection:
count_first_booking = pandas.read_sql(query,
connection,
index_col="offer_id")
pandas.testing.assert_series_equal(
count_first_booking["Nombre de premières réservations"],
expected_first_booking_number,
)
def test_should_return_exact_booking_amount(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,
)
expected_amount_per_booking = pandas.Series(
data=[0.0, 10.0, 15.0],
name="Montant de la réservation",
index=Int64Index([1, 2, 3], name="booking_id"),
)
# When
query = get_booking_amount()
# Then
with ENGINE.connect() as connection:
booking_amount = pandas.read_sql(query,
connection,
index_col="booking_id")
pandas.testing.assert_series_equal(
booking_amount["Montant de la réservation"],
expected_amount_per_booking)
def test_should_return_real_revenue_per_venue(self, app):
# Given
create_user(id=1)
create_deposit(id=1, 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",
date_created="2020-05-13",
)
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",
date_created="2020-05-10",
)
create_offer(
venue_id=1,
product_id=2,
id=3,
product_type="ThingType.MUSIQUE",
date_created="2020-05-11",
)
create_stock(offer_id=2, id=2, price=10)
create_stock(offer_id=3, id=3, price=20)
create_booking(id=1,
user_id=1,
quantity=1,
stock_id=2,
amount=10,
is_used=True)
create_booking(
id=2,
user_id=1,
quantity=1,
stock_id=2,
amount=10,
token="ABC321",
is_used=True,
)
create_booking(
id=3,
user_id=1,
quantity=1,
stock_id=2,
amount=10,
token="FAM321",
is_cancelled=True,
)
create_booking(
id=4,
user_id=1,
quantity=1,
stock_id=1,
token="CON321",
is_cancelled=False,
)
create_booking(
id=5,
user_id=1,
quantity=2,
stock_id=3,
amount=20,
token="LAB123",
is_cancelled=False,
)
expected_real_revenue_per_venue = pandas.Series(
data=[20.0],
name="real_revenue",
index=Int64Index([1], name="venue_id"))
# When
query = _get_real_revenue_per_venue()
# Then
with ENGINE.connect() as connection:
real_revenue_per_venue = pandas.read_sql(query,
connection,
index_col="venue_id")
pandas.testing.assert_series_equal(
expected_real_revenue_per_venue,
real_revenue_per_venue["real_revenue"])
def test_should_return_current_year_revenue(self):
# Given
create_user(id=1)
create_deposit(amount=500)
create_offerer(id=10)
create_product(id=1,
product_type="ThingType.MUSEES_PATRIMOINE_ABO")
create_venue(id=15, offerer_id=10)
create_offer(
id=30,
venue_id=15,
product_type="ThingType.MUSEES_PATRIMOINE_ABO",
product_id=1,
)
create_stock(id=20, offer_id=30)
create_booking(
id=1,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
is_used=True,
)
create_booking(id=2,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
token="ABC321",
is_used=True,
date_created=f'{datetime.now().year}-01-05')
create_booking(
id=3,
user_id=1,
amount=10,
quantity=3,
stock_id=20,
token="FAM321",
is_cancelled=True,
)
expected_current_year_revenue = pandas.Series(
index=pandas.Index(data=[10], name="offerer_id"),
data=[10.0],
name="Chiffre d'affaire réel année civile en cours",
)
# When
query = _get_current_year_revenue()
# Then
with ENGINE.connect() as connection:
current_year_revenue = pandas.read_sql(query,
connection,
index_col="offerer_id")
pandas.testing.assert_series_equal(
current_year_revenue[
"Chiffre d'affaire réel année civile en cours"],
expected_current_year_revenue,
)
def test_should_return_booking_cancelled_booking_and_used_booking_number_columns(
self, ):
# Given
create_user(id=1)
create_deposit(amount=500)
create_offerer(id=10)
create_product(id=1,
product_type="ThingType.MUSEES_PATRIMOINE_ABO")
create_venue(id=15, offerer_id=10)
create_offer(
id=30,
venue_id=15,
product_type="ThingType.MUSEES_PATRIMOINE_ABO",
product_id=1,
)
create_stock(id=20, offer_id=30)
create_booking(id=1,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
is_used=True)
create_booking(
id=2,
user_id=1,
amount=10,
quantity=1,
stock_id=20,
token="ABC321",
is_used=True,
)
create_booking(
id=3,
user_id=1,
amount=10,
quantity=3,
stock_id=20,
token="FAM321",
is_cancelled=True,
)
expected_booking_number = pandas.Series(
index=pandas.Index(data=[30], name="offer_id"),
data=[5],
name="Nombre de réservations",
)
expected_cancelled_booking_number = pandas.Series(
index=pandas.Index(data=[30], name="offer_id"),
data=[3],
name="Nombre de réservations annulées",
)
expected_used_booking_number = pandas.Series(
index=pandas.Index(data=[30], name="offer_id"),
data=[2],
name="Nombre de réservations validées",
)
# When
query = _get_offer_booking_information_query()
# Then
with ENGINE.connect() as connection:
offer_booking_information = pandas.read_sql(
query, connection, index_col="offer_id")
pandas.testing.assert_series_equal(
offer_booking_information["Nombre de réservations"],
expected_booking_number,
)
pandas.testing.assert_series_equal(
offer_booking_information["Nombre de réservations annulées"],
expected_cancelled_booking_number,
)
pandas.testing.assert_series_equal(
offer_booking_information["Nombre de réservations validées"],
expected_used_booking_number,
)
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,
)
