urban-meal-delivery/tests/db/fake_data/factories.py
Alexander Hess 4b6d92958d
Add functionality for drawing folium.Maps
- this code is not unit-tested due to the complexity involving
  interactive `folium.Map`s => visual checks give high confidence
2021-01-26 17:07:50 +01:00

378 lines
14 KiB
Python

"""Factories to create instances for the SQLAlchemy models."""
import datetime as dt
import random
import string
import factory
import faker
from factory import alchemy
from geopy import distance
from tests import config as test_config
from urban_meal_delivery import db
def _random_timespan( # noqa:WPS211
*,
min_hours=0,
min_minutes=0,
min_seconds=0,
max_hours=0,
max_minutes=0,
max_seconds=0,
):
"""A randomized `timedelta` object between the specified arguments."""
total_min_seconds = min_hours * 3600 + min_minutes * 60 + min_seconds
total_max_seconds = max_hours * 3600 + max_minutes * 60 + max_seconds
return dt.timedelta(seconds=random.randint(total_min_seconds, total_max_seconds))
def _early_in_the_morning():
"""A randomized `datetime` object early in the morning."""
early = dt.datetime(test_config.YEAR, test_config.MONTH, test_config.DAY, 3, 0)
return early + _random_timespan(max_hours=2)
class AddressFactory(alchemy.SQLAlchemyModelFactory):
"""Create instances of the `db.Address` model."""
class Meta:
model = db.Address
sqlalchemy_get_or_create = ('id',)
id = factory.Sequence(lambda num: num) # noqa:WPS125
created_at = factory.LazyFunction(_early_in_the_morning)
# When testing, all addresses are considered primary ones.
# As non-primary addresses have no different behavior and
# the property is only kept from the original dataset for
# completeness sake, that is ok to do.
primary_id = factory.LazyAttribute(lambda obj: obj.id)
# Mimic a Google Maps Place ID with just random characters.
place_id = factory.LazyFunction(
lambda: ''.join(random.choice(string.ascii_lowercase) for _ in range(20)),
)
# Place the addresses somewhere in downtown Paris.
latitude = factory.Faker('coordinate', center=48.855, radius=0.01)
longitude = factory.Faker('coordinate', center=2.34, radius=0.03)
# city -> set by the `make_address` fixture as there is only one `city`
city_name = 'Paris'
zip_code = factory.LazyFunction(lambda: random.randint(75001, 75020))
street = factory.Faker('street_address', locale='fr_FR')
class CourierFactory(alchemy.SQLAlchemyModelFactory):
"""Create instances of the `db.Courier` model."""
class Meta:
model = db.Courier
sqlalchemy_get_or_create = ('id',)
id = factory.Sequence(lambda num: num) # noqa:WPS125
created_at = factory.LazyFunction(_early_in_the_morning)
vehicle = 'bicycle'
historic_speed = 7.89
capacity = 100
pay_per_hour = 750
pay_per_order = 200
class CustomerFactory(alchemy.SQLAlchemyModelFactory):
"""Create instances of the `db.Customer` model."""
class Meta:
model = db.Customer
sqlalchemy_get_or_create = ('id',)
id = factory.Sequence(lambda num: num) # noqa:WPS125
_restaurant_names = faker.Faker()
class RestaurantFactory(alchemy.SQLAlchemyModelFactory):
"""Create instances of the `db.Restaurant` model."""
class Meta:
model = db.Restaurant
sqlalchemy_get_or_create = ('id',)
id = factory.Sequence(lambda num: num) # noqa:WPS125
created_at = factory.LazyFunction(_early_in_the_morning)
name = factory.LazyFunction(
lambda: f"{_restaurant_names.first_name()}'s Restaurant",
)
# address -> set by the `make_restaurant` fixture as there is only one `city`
estimated_prep_duration = 1000
class AdHocOrderFactory(alchemy.SQLAlchemyModelFactory):
"""Create instances of the `db.Order` model.
This factory creates ad-hoc `Order`s while the `ScheduledOrderFactory`
below creates pre-orders. They are split into two classes mainly
because the logic regarding how the timestamps are calculated from
each other differs.
See the docstring in the contained `Params` class for
flags to adapt how the `Order` is created.
"""
class Meta:
model = db.Order
sqlalchemy_get_or_create = ('id',)
class Params:
"""Define flags that overwrite some attributes.
The `factory.Trait` objects in this class are executed after all
the normal attributes in the `OrderFactory` classes were evaluated.
Flags:
cancel_before_pickup
cancel_after_pickup
"""
# Timestamps after `cancelled_at` are discarded
# by the `post_generation` hook at the end of the `OrderFactory`.
cancel_ = factory.Trait( # noqa:WPS120 -> leading underscore does not work
cancelled=True, cancelled_at_corrected=False,
)
cancel_before_pickup = factory.Trait(
cancel_=True,
cancelled_at=factory.LazyAttribute(
lambda obj: obj.dispatch_at
+ _random_timespan(
max_seconds=(obj.pickup_at - obj.dispatch_at).total_seconds(),
),
),
)
cancel_after_pickup = factory.Trait(
cancel_=True,
cancelled_at=factory.LazyAttribute(
lambda obj: obj.pickup_at
+ _random_timespan(
max_seconds=(obj.delivery_at - obj.pickup_at).total_seconds(),
),
),
)
# Generic attributes
id = factory.Sequence(lambda num: num) # noqa:WPS125
# customer -> set by the `make_order` fixture for better control
# Attributes regarding the specialization of an `Order`: ad-hoc or scheduled.
# Ad-hoc `Order`s are placed between 11.45 and 14.15.
placed_at = factory.LazyFunction(
lambda: dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 11, 45,
)
+ _random_timespan(max_hours=2, max_minutes=30),
)
ad_hoc = True
scheduled_delivery_at = None
scheduled_delivery_at_corrected = None
# Without statistical info, we assume an ad-hoc `Order` delivered after 45 minutes.
first_estimated_delivery_at = factory.LazyAttribute(
lambda obj: obj.placed_at + dt.timedelta(minutes=45),
)
# Attributes regarding the cancellation of an `Order`.
# May be overwritten with the `cancel_before_pickup` or `cancel_after_pickup` flags.
cancelled = False
cancelled_at = None
cancelled_at_corrected = None
# Price-related attributes -> sample realistic prices
sub_total = factory.LazyFunction(lambda: 100 * random.randint(15, 25))
delivery_fee = 250
total = factory.LazyAttribute(lambda obj: obj.sub_total + obj.delivery_fee)
# Restaurant-related attributes
# restaurant -> set by the `make_order` fixture for better control
restaurant_notified_at = factory.LazyAttribute(
lambda obj: obj.placed_at + _random_timespan(min_seconds=30, max_seconds=90),
)
restaurant_notified_at_corrected = False
restaurant_confirmed_at = factory.LazyAttribute(
lambda obj: obj.restaurant_notified_at
+ _random_timespan(min_seconds=30, max_seconds=150),
)
restaurant_confirmed_at_corrected = False
# Use the database defaults of the historic data.
estimated_prep_duration = 900
estimated_prep_duration_corrected = False
estimated_prep_buffer = 480
# Dispatch-related columns
# courier -> set by the `make_order` fixture for better control
dispatch_at = factory.LazyAttribute(
lambda obj: obj.placed_at + _random_timespan(min_seconds=600, max_seconds=1080),
)
dispatch_at_corrected = False
courier_notified_at = factory.LazyAttribute(
lambda obj: obj.dispatch_at
+ _random_timespan(min_seconds=100, max_seconds=140),
)
courier_notified_at_corrected = False
courier_accepted_at = factory.LazyAttribute(
lambda obj: obj.courier_notified_at
+ _random_timespan(min_seconds=15, max_seconds=45),
)
courier_accepted_at_corrected = False
# Sample a realistic utilization.
utilization = factory.LazyFunction(lambda: random.choice([50, 60, 70, 80, 90, 100]))
# Pickup-related attributes
# pickup_address -> aligned with `restaurant.address` by the `make_order` fixture
reached_pickup_at = factory.LazyAttribute(
lambda obj: obj.courier_accepted_at
+ _random_timespan(min_seconds=300, max_seconds=600),
)
pickup_at = factory.LazyAttribute(
lambda obj: obj.reached_pickup_at
+ _random_timespan(min_seconds=120, max_seconds=600),
)
pickup_at_corrected = False
pickup_not_confirmed = False
left_pickup_at = factory.LazyAttribute(
lambda obj: obj.pickup_at + _random_timespan(min_seconds=60, max_seconds=180),
)
left_pickup_at_corrected = False
# Delivery-related attributes
# delivery_address -> set by the `make_order` fixture as there is only one `city`
reached_delivery_at = factory.LazyAttribute(
lambda obj: obj.left_pickup_at
+ _random_timespan(min_seconds=240, max_seconds=480),
)
delivery_at = factory.LazyAttribute(
lambda obj: obj.reached_delivery_at
+ _random_timespan(min_seconds=240, max_seconds=660),
)
delivery_at_corrected = False
delivery_not_confirmed = False
_courier_waited_at_delivery = factory.LazyAttribute(
lambda obj: False if obj.delivery_at else None,
)
# Statistical attributes -> calculate realistic stats
logged_delivery_distance = factory.LazyAttribute(
lambda obj: distance.great_circle( # noqa:WPS317
(obj.pickup_address.latitude, obj.pickup_address.longitude),
(obj.delivery_address.latitude, obj.delivery_address.longitude),
).meters,
)
logged_avg_speed = factory.LazyAttribute( # noqa:ECE001
lambda obj: round(
(
obj.logged_avg_speed_distance
/ (obj.delivery_at - obj.pickup_at).total_seconds()
),
2,
),
)
logged_avg_speed_distance = factory.LazyAttribute(
lambda obj: 0.95 * obj.logged_delivery_distance,
)
@factory.post_generation
def post( # noqa:C901,WPS231
obj, create, extracted, **kwargs, # noqa:B902,N805
):
"""Discard timestamps that occur after cancellation."""
if obj.cancelled:
if obj.cancelled_at <= obj.restaurant_notified_at:
obj.restaurant_notified_at = None
obj.restaurant_notified_at_corrected = None
if obj.cancelled_at <= obj.restaurant_confirmed_at:
obj.restaurant_confirmed_at = None
obj.restaurant_confirmed_at_corrected = None
if obj.cancelled_at <= obj.dispatch_at:
obj.dispatch_at = None
obj.dispatch_at_corrected = None
if obj.cancelled_at <= obj.courier_notified_at:
obj.courier_notified_at = None
obj.courier_notified_at_corrected = None
if obj.cancelled_at <= obj.courier_accepted_at:
obj.courier_accepted_at = None
obj.courier_accepted_at_corrected = None
if obj.cancelled_at <= obj.reached_pickup_at:
obj.reached_pickup_at = None
if obj.cancelled_at <= obj.pickup_at:
obj.pickup_at = None
obj.pickup_at_corrected = None
obj.pickup_not_confirmed = None
if obj.cancelled_at <= obj.left_pickup_at:
obj.left_pickup_at = None
obj.left_pickup_at_corrected = None
if obj.cancelled_at <= obj.reached_delivery_at:
obj.reached_delivery_at = None
if obj.cancelled_at <= obj.delivery_at:
obj.delivery_at = None
obj.delivery_at_corrected = None
obj.delivery_not_confirmed = None
obj._courier_waited_at_delivery = None
class ScheduledOrderFactory(AdHocOrderFactory):
"""Create instances of the `db.Order` model.
This class takes care of the various timestamps for pre-orders.
Pre-orders are placed long before the test day's lunch time starts.
All timestamps are relative to either `.dispatch_at` or `.restaurant_notified_at`
and calculated backwards from `.scheduled_delivery_at`.
"""
# Attributes regarding the specialization of an `Order`: ad-hoc or scheduled.
placed_at = factory.LazyFunction(_early_in_the_morning)
ad_hoc = False
# Discrete `datetime` objects in the "core" lunch time are enough.
scheduled_delivery_at = factory.LazyFunction(
lambda: random.choice(
[
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 12, 0,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 12, 15,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 12, 30,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 12, 45,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 13, 0,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 13, 15,
),
dt.datetime(
test_config.YEAR, test_config.MONTH, test_config.DAY, 13, 30,
),
],
),
)
scheduled_delivery_at_corrected = False
# Assume the `Order` is on time.
first_estimated_delivery_at = factory.LazyAttribute(
lambda obj: obj.scheduled_delivery_at,
)
# Restaurant-related attributes
restaurant_notified_at = factory.LazyAttribute(
lambda obj: obj.scheduled_delivery_at
- _random_timespan(min_minutes=45, max_minutes=50),
)
# Dispatch-related attributes
dispatch_at = factory.LazyAttribute(
lambda obj: obj.scheduled_delivery_at
- _random_timespan(min_minutes=40, max_minutes=45),
)