The Nautobot Python Shell¶
Nautobot includes a Python management shell within which objects can be directly queried, created, modified, and deleted. To enter the shell, run the following command:
# Shell Plus Model Imports from constance.backends.database.models import Constance from django.contrib.admin.models import LogEntry from django.contrib.auth.models import Group, Permission from django.contrib.contenttypes.models import ContentType from django.contrib.sessions.models import Session from django_celery_beat.models import ClockedSchedule, CrontabSchedule, IntervalSchedule, PeriodicTask, PeriodicTasks, SolarSchedule from django_celery_results.models import ChordCounter, GroupResult, TaskResult from example_plugin.models import AnotherExampleModel, ExampleModel from nautobot.circuits.models import Circuit, CircuitTermination, CircuitType, Provider, ProviderNetwork from nautobot.dcim.models.cables import Cable, CablePath from nautobot.dcim.models.device_component_templates import ConsolePortTemplate, ConsoleServerPortTemplate, DeviceBayTemplate, FrontPortTemplate, InterfaceTemplate, PowerOutletTemplate, PowerPortTemplate, RearPortTemplate from nautobot.dcim.models.device_components import ConsolePort, ConsoleServerPort, DeviceBay, FrontPort, Interface, InventoryItem, PowerOutlet, PowerPort, RearPort from nautobot.dcim.models.devices import Device, DeviceRedundancyGroup, DeviceType, Manufacturer, Platform, VirtualChassis from nautobot.dcim.models.locations import Location, LocationType from nautobot.dcim.models.power import PowerFeed, PowerPanel from nautobot.dcim.models.racks import Rack, RackGroup, RackReservation from nautobot.extras.models.change_logging import ObjectChange from nautobot.extras.models.customfields import ComputedField, CustomField, CustomFieldChoice from nautobot.extras.models.datasources import GitRepository from nautobot.extras.models.groups import DynamicGroup, DynamicGroupMembership from nautobot.extras.models.jobs import Job, JobHook, JobLogEntry, JobResult, ScheduledJob, ScheduledJobs from nautobot.extras.models.models import ConfigContext, ConfigContextSchema, CustomLink, ExportTemplate, FileAttachment, FileProxy, GraphQLQuery, HealthCheckTestModel, ImageAttachment, Note, Webhook from nautobot.extras.models.relationships import Relationship, RelationshipAssociation from nautobot.extras.models.roles import Role from nautobot.extras.models.secrets import Secret, SecretsGroup, SecretsGroupAssociation from nautobot.extras.models.statuses import Status from nautobot.extras.models.tags import Tag, TaggedItem from nautobot.ipam.models import IPAddress, Prefix, RIR, RouteTarget, Service, VLAN, VLANGroup, VRF from nautobot.tenancy.models import Tenant, TenantGroup from nautobot.users.models import AdminGroup, ObjectPermission, Token, User from nautobot.virtualization.models import Cluster, ClusterGroup, ClusterType, VMInterface, VirtualMachine from social_django.models import Association, Code, Nonce, Partial, UserSocialAuth # Shell Plus Django Imports from django.core.cache import cache from django.conf import settings from django.contrib.auth import get_user_model from django.db import transaction from django.db.models import Avg, Case, Count, F, Max, Min, Prefetch, Q, Sum, When from django.utils import timezone from django.urls import reverse from django.db.models import Exists, OuterRef, Subquery # Django version 3.2.18 # Nautobot version 2.0.0a2 # Example Nautobot App version 1.0.0 Python 3.8.16 (default, Mar 23 2023, 04:48:11) [GCC 10.2.1 20210110] on linux Type "help", "copyright", "credits" or "license" for more information. (InteractiveConsole) >>>
As you can see from the above output, the Nautobot shell automatically loads all relevant database models, including those built-in to Django, those provided by Nautobot itself, and those provided by any installed Nautobot apps. It also loads a number of useful Django utilities as well.
The Nautobot shell affords direct access to Nautobot data and function with very little validation in place. As such, it is crucial to ensure that only authorized, knowledgeable users are ever granted access to it. Never perform any action in the management shell without having a full backup in place.
Objects are retrieved from the database using a Django queryset. The base queryset for an object takes the form
<model>.objects.all(), which will return a (truncated) list of all objects of that type.
for loop to cycle through all objects in the list:
>>> for device in Device.objects.all(): ... print(device.name, device.device_type) ... ('TestDevice1', <DeviceType: PacketThingy 9000>) ('TestDevice2', <DeviceType: PacketThingy 9000>) ('TestDevice3', <DeviceType: PacketThingy 9000>) ('TestDevice4', <DeviceType: PacketThingy 9000>) ('TestDevice5', <DeviceType: PacketThingy 9000>) ...
To count all objects matching the query, replace
To retrieve a particular object (typically by its primary key or other unique field), use
In most cases, you will want to retrieve only a specific subset of objects. To filter a queryset, replace
filter() and pass one or more keyword arguments. For example:
Querysets support slicing to return a specific range of objects.
count() method can be appended to the queryset to return a count of objects rather than the full list.
Relationships with other models can be traversed by concatenating attribute names with a double-underscore. For example, the following will return all devices assigned to the tenant named "Pied Piper."
This approach can span multiple levels of relations. For example, the following will return all IP addresses assigned to a device in North America:
While the above query is functional, it's not very efficient. There are ways to optimize such requests, however they are out of scope for this document. For more information, see the Django queryset method reference documentation.
Reverse relationships can be traversed as well. For example, the following will find all devices with an interface named "em0":
Character fields can be filtered against partial matches using the
icontains field lookup (the later of which is case-insensitive).
Similarly, numeric fields can be filtered by values less than, greater than, and/or equal to a given value.
Multiple filters can be combined to further refine a queryset.
To return the inverse of a filtered queryset, use
exclude() instead of
The examples above are intended only to provide a cursory introduction to queryset filtering. For an exhaustive list of the available filters, please consult the Django queryset API documentation.
Creating and Updating Objects¶
New objects can be created by instantiating the desired model, defining values for all required attributes, and calling
validated_save() on the instance. For example, we can create a new VLAN by specifying its numeric ID, name, and assigned location:
Alternatively, the above can be performed as a single operation. (Note, however, that
validated_save() does not return the new instance for reuse.)
To modify an existing object, we retrieve it, update the desired field(s), and call
It is recommended to make use of the
validated_save() convenience method which exists on all core models. While the Django
save() method still exists, the
validated_save() method saves the instance data but first enforces model validation logic. Simply calling
save() on the model instance does not enforce validation automatically and may lead to bad data. See the development best practices.
The Django ORM provides methods to create/edit many objects at once, namely
update(). These are best avoided in most cases as they bypass a model's built-in validation and can easily lead to database corruption if not used carefully.
To delete an object, simply call
delete() on its instance. This will return a dictionary of all objects (including related objects) which have been deleted as a result of this operation.
To delete multiple objects at once, call
delete() on a filtered queryset. It's a good idea to always sanity-check the count of selected objects before deleting them.
Deletions are immediate and irreversible. Always consider the impact of deleting objects carefully before calling
delete() on an instance or queryset.
Change Logging and Webhooks¶
Note that Nautobot's change logging and webhook processing features operate under the context of an HTTP request. As such, these functions do not work automatically when using the ORM directly, either through the Nautobot shell or otherwise. A special context manager is provided to allow these features to operate under an emulated HTTP request context. This context manager must be explicitly invoked for change log entries and webhooks to be created when interacting with objects through the ORM. Here is an example using the
web_request_context context manager within the Nautobot shell:
>>> from nautobot.extras.context_managers import web_request_context >>> user = User.objects.get(username="admin") >>> with web_request_context(user): ... location_type = LocationType.objects.get(name="Airport") ... status = Status.objects.get_for_model(Location).first() ... lax = Location(name="LAX", location_type=location_type, status=status) ... lax.validated_save()
User object must be provided. A
WSGIRequest may optionally be passed and one will automatically be created if not provided.