nautobot.apps.factory
¶
Nautobot classes and utilities for factory boy.
nautobot.apps.factory.BaseModelFactory
¶
Bases: DjangoModelFactory
Base class for all Nautobot model factories.
nautobot.apps.factory.NautobotBoolIterator
¶
Bases: Iterator
Factory iterator that returns a semi-random sampling of boolean values
Iterator that returns a random sampling of True and False values while limiting the number of repeated values in a given number of iterations. Used in factories when a data set must contain both True and False values.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
cycle |
boolean
|
If True, iterator will restart at the beginning when all values are
exhausted. Otherwise raise a |
True
|
chance_of_getting_true |
int
|
Percentage (0-100) of the values in the returned iterable set to True. Defaults to 50. |
NAUTOBOT_BOOL_ITERATOR_DEFAULT_PROBABILITY
|
length |
int
|
Length of the returned iterable. Defaults to 8. |
NAUTOBOT_BOOL_ITERATOR_DEFAULT_LENGTH
|
nautobot.apps.factory.NautobotFakerProvider
¶
Bases: BaseProvider
Faker provider to generate fake data specific to Nautobot or network automation use cases.
ipv6_network()
¶
Produce a random IPv6 network with a valid CIDR greater than 0
nautobot.apps.factory.OrganizationalModelFactory
¶
Bases: BaseModelFactory
Factory base class for OrganizationalModel subclasses.
nautobot.apps.factory.PrimaryModelFactory
¶
nautobot.apps.factory.UniqueFaker
¶
Bases: Faker
https://github.com/FactoryBoy/factory_boy/pull/820#issuecomment-1004802669
nautobot.apps.factory.get_random_instances(model_or_queryset_or_lambda, minimum=0, maximum=None)
¶
Factory helper - retrieve a random number of instances of the given model.
This is different from random_instance() in that it's not itself a lazy function generator, but should instead be called only from within a @lazy_attribute or @post_generation function.
This is not an evenly weighted distribution (all counts equally likely), because in most of our code, the relevant code paths distinguish between 0, 1, or >1 instances - there's not a functional difference between "2 instances" and "10 instances" in most cases. Therefore, this implementation provides: - 1/3 chance of no instances - 1/3 chance of 1 instance - 1/3 chance of (2 to n) instances, where each possibility is equally likely within this range
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_or_queryset_or_lambda |
Union[BaseModel, QuerySet, func]
|
Either a model class, a model queryset, or a lambda that returns one of those |
required |
minimum |
int
|
Minimum number of objects to return |
0
|
maximum |
int
|
Maximum number of objects to return, or None for no limit |
None
|
nautobot.apps.factory.random_instance(model_or_queryset_or_lambda, allow_null=True)
¶
Factory helper - construct a LazyFunction that gets a random instance of the given model or queryset when evaluated.
TODO: once we have factories for all mandatory foreign keys, change allow_null default to False
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
model_or_queryset_or_lambda |
Union[BaseModel, QuerySet, func]
|
Either a model class, a model queryset, or a lambda that returns one of those |
required |
allow_null |
bool
|
If False, and the given queryset contains no objects, raise a RuntimeError. |
True
|
Example
class ObjectFactory(DjangoModelFactory): class Meta: model = Object exclude = ("has_group,")
# Required foreign key
user = random_instance(User, allow_null=False)
# Optional foreign key
has_group = NautobotBoolIterator()
group = factory.Maybe("has_group", random_instance(Group), None)
# Foreign key selected from a filtered queryset
tenant = random_instance(Tenant.objects.filter(group__isnull=False))
# Foreign key selected from a queryset generated by a lambda
# This needs to be done this way because .get_for_model() evaluates a ContentType queryset,
# and we need to defer evaluation of that queryset as well.
status = random_instance(lambda: Status.objects.get_for_model(Object), allow_null=False)