fillmydb
Fill your database with mocked instances.
Wrap you ORM model into a ModelWrapper, specify how your fields should look
like and then generate how many instances you want of each model.
Installation
-
pip install fillmydb[peewee]if you plan to use it with peewee models -
pip install fillmydb[django]if you plan to use it with djanog models (not implemented yet) -
pip install fillmydb[sqlalchemy]if you plan to use it with sqlalchemy models (not implemented yet)
Usage with fake-factory
Generating instances for a single model:
import faker
factory = faker.Factory.create()
wrapper = ModelWrapper(TestModel)
wrapper[TestModel].client_name = FieldSpec(factory.name)
wrapper[TestModel].description = FieldSpec(factory.text)
wrapper[TestModel].password_hash = FieldSpec(factory.binary, length=25)
wrapper[TestModel].email = FieldSpec(factory.email)
wrapper[TestModel].visits = FieldSpec(factory.pyint)
item = wrapper.generate(100)
Generating instances for multipe models:
from tests.models import User, Post, Like
import faker
factory = faker.Factory.create()
wrapper = ModelWrapper(User, Like, Post)
wrapper[User].name = FieldSpec(factory.name)
wrapper[User].username = FieldSpec(factory.user_name)
wrapper[User].description = FieldSpec(factory.text)
wrapper[User].password_hash = FieldSpec(factory.binary, length=25)
wrapper[User].email = FieldSpec(factory.email)
wrapper[User].visits = FieldSpec(factory.pyint)
wrapper[Post].title = FieldSpec(lambda _: "test", 1)
wrapper[Post].text = FieldSpec(factory.text)
# generating 10 users, 100 likes and 20 posts
wrapper.generate(10, 100, 20)
General workflow
Pseudo-code:
initial_to_order_queue()
while models_to_process():
model = get_next_model()
if model.has_unresolved_dependency():
push_back_to_queue(model)
# process model
for _ in range(number_of_instances):
for field in model.fields():
# resolve_field(field)
if field == ForeignKey:
field = get_random_ref_model_instance()
else:
field = resolve_normal()
mark_as_processed(model)
