recopytex/tests/model/fakes.py

94 lines
2.4 KiB
Python

from random import choice, randint
from faker import Faker
from faker.providers import DynamicProvider
from backend.model.assessment import Assessment, Domain, Exercise, Question, Skill
from backend.model.student import Student
from backend.model.tribe import Tribe
from backend.repository.abstract_repository import AbstractRepository
level_provider = DynamicProvider(
provider_name="level",
elements=["2nd", "1ST", "SNT", "1G", "TG", "EnsSci"],
)
faker = Faker("fr_FR")
faker.add_provider(level_provider)
def build_tribes(quantity: int = 1) -> list[Tribe]:
return [Tribe(name=faker.word(), level=faker.level()) for _ in range(quantity)]
def build_assessments(
tribes: list[Tribe], assessment_per_tribe: int = 1
) -> list[Assessment]:
assessments = []
for t in tribes:
assessments += [
Assessment("faker.word()", t, randint(1, 3))
for _ in range(assessment_per_tribe)
]
return assessments
def build_exercises(
assessments: list[Assessment], exercise_per_assessment=1
) -> list[Exercise]:
exercises = []
for assessment in assessments:
exercises += [
Exercise("faker.word()", assessment, "today")
for _ in range(exercise_per_assessment)
]
return exercises
def build_skills(quantity=1) -> list[Skill]:
return [Skill(faker.word(), faker.text()) for _ in range(quantity)]
def build_domains(quantity=1) -> list[Domain]:
return [Domain(faker.word(), faker.text()) for _ in range(quantity)]
def build_questions(
exercises: list[Exercise],
question_per_exercise=1,
) -> list[Question]:
skills = build_skills()
domains = build_domains()
questions = []
for exercise in exercises:
questions += [
Question(
faker.word(),
exercise,
description="desc",
skill=choice(skills),
domain=choice(domains),
is_leveled=choice([True, False]),
scale=randint(1, 20),
)
for _ in range(question_per_exercise)
]
return questions
def build_student(
tribes: list[Tribe],
students_per_tribe=1,
) -> list[Student]:
students = []
for tribe in tribes:
students += [
Student(name=faker.name(), tribe=tribe) for _ in range(students_per_tribe)
]
return students