# Custom Scripts

Custom scripting was introduced to provide a way for users to execute custom logic from within the NetBox UI. Custom scripts enable the user to directly and conveniently manipulate NetBox data in a prescribed fashion. They can be used to accomplish myriad tasks, such as:

* Automatically populate new devices and cables in preparation for a new site deployment
* Create a range of new reserved prefixes or IP addresses
* Fetch data from an external source and import it to NetBox
* Update objects with invalid or incomplete data

They can also be used as a mechanism for validating the integrity of data within NetBox. Script authors can define test to check object against specific rules and conditions. For example, you can write script to check that:

* All top-of-rack switches have a console connection
* Every router has a loopback interface with an IP address assigned
* Each interface description conforms to a standard format
* Every site has a minimum set of VLANs defined
* All IP addresses have a parent prefix

Custom scripts are Python code which exists outside the NetBox code base, so they can be updated and changed without interfering with the core NetBox installation. And because they're completely custom, there is no inherent limitation on what a script can accomplish.

## Writing Custom Scripts

All custom scripts must inherit from the `extras.scripts.Script` base class. This class provides the functionality necessary to generate forms and log activity.

```python
from extras.scripts import Script

class MyScript(Script):
    ...
```

Scripts comprise two core components: a set of variables and a `run()` method. Variables allow your script to accept user input via the NetBox UI, but they are optional: If your script does not require any user input, there is no need to define any variables.

The `run()` method is where your script's execution logic lives. (Note that your script can have as many methods as needed: this is merely the point of invocation for NetBox.)

```python
class MyScript(Script):
    var1 = StringVar(...)
    var2 = IntegerVar(...)
    var3 = ObjectVar(...)

    def run(self, data, commit):
        ...
```

The `run()` method should accept two arguments:

* `data` - A dictionary containing all the variable data passed via the web form.
* `commit` - A boolean indicating whether database changes will be committed.

Defining script variables is optional: You may create a script with only a `run()` method if no user input is needed.

Any output generated by the script during its execution will be displayed under the "output" tab in the UI.

By default, scripts within a module are ordered alphabetically in the scripts list page. To return scripts in a specific order, you can define the `script_order` variable at the end of your module. The `script_order` variable is a tuple which contains each Script class in the desired order. Any scripts that are omitted from this list will be listed last.

```python
from extras.scripts import Script

class MyCustomScript(Script):
    ...

class AnotherCustomScript(Script):
    ...

script_order = (MyCustomScript, AnotherCustomScript)
```

## Module Attributes

### `name`

You can define `name` within a script module (the Python file which contains one or more scripts) to set the module name. If `name` is not defined, the module's file name will be used.

## Script Attributes

Script attributes are defined under a class named `Meta` within the script. These are optional, but encouraged.

### `name`

This is the human-friendly names of your script. If omitted, the class name will be used.

### `description`

A human-friendly description of what your script does.

### `field_order`

By default, script variables will be ordered in the form as they are defined in the script. `field_order` may be defined as an iterable of field names to determine the order in which variables are rendered within a default "Script Data" group. Any fields not included in this iterable be listed last. If `fieldsets` is defined, `field_order` will be ignored.  A fieldset group for "Script Execution Parameters" will be added to the end of the form by default for the user.

### `fieldsets`

`fieldsets` may be defined as an iterable of field groups and their field names to determine the order in which variables are group and rendered. Any fields not included in this iterable will not be displayed in the form. If `fieldsets` is defined, `field_order` will be ignored.  A fieldset group for "Script Execution Parameters" will be added to the end of the fieldsets by default for the user.

An example fieldset definition is provided below:

```python
class MyScript(Script):
    class Meta:
        fieldsets = (
            ('First group', ('field1', 'field2', 'field3')),
            ('Second group', ('field4', 'field5')),
        )
```

### `commit_default`

The checkbox to commit database changes when executing a script is checked by default. Set `commit_default` to False under the script's Meta class to leave this option unchecked by default.

```python
commit_default = False
```

### `scheduling_enabled`

By default, a script can be scheduled for execution at a later time. Setting `scheduling_enabled` to False disables this ability: Only immediate execution will be possible. (This also disables the ability to set a recurring execution interval.)

### `job_timeout`

Set the maximum allowed runtime for the script. If not set, `RQ_DEFAULT_TIMEOUT` will be used.

## Accessing Request Data

Details of the current HTTP request (the one being made to execute the script) are available as the instance attribute `self.request`. This can be used to infer, for example, the user executing the script and the client IP address:

```python
username = self.request.user.username
ip_address = self.request.META.get('HTTP_X_FORWARDED_FOR') or \
    self.request.META.get('REMOTE_ADDR')
self.log_info(f"Running as user {username} (IP: {ip_address})...")
```

For a complete list of available request parameters, please see the [Django documentation](https://docs.djangoproject.com/en/stable/ref/request-response/).

## Reading Data from Files

The Script class provides two convenience methods for reading data from files:

* `load_yaml`
* `load_json`

These two methods will load data in YAML or JSON format, respectively, from files within the local path (i.e. `SCRIPTS_ROOT`).

## Logging

The Script object provides a set of convenient functions for recording messages at different severity levels:

* `log_debug(message, object=None)`
* `log_success(message, object=None)`
* `log_info(message, object=None)`
* `log_warning(message, object=None)`
* `log_failure(message, object=None)`

Log messages are returned to the user upon execution of the script. Markdown rendering is supported for log messages. A message may optionally be associated with a particular object by passing it as the second argument to the logging method.

## Test Methods

A script can define one or more test methods to report on certain conditions. All test methods must have a name beginning with `test_` and accept no arguments beyond `self`.

These methods are detected and run automatically when the script is executed, unless its `run()` method has been overridden. (When overriding `run()`, `run_tests()` can be called to run all test methods present in the script.)

!!! info
    This functionality was ported from [legacy reports](./reports.md) in NetBox v4.0.

### Example

```
from dcim.choices import DeviceStatusChoices
from dcim.models import ConsolePort, Device, PowerPort
from extras.scripts import Script


class DeviceConnectionsReport(Script):
    description = "Validate the minimum physical connections for each device"

    def test_console_connection(self):

        # Check that every console port for every active device has a connection defined.
        active = DeviceStatusChoices.STATUS_ACTIVE
        for console_port in ConsolePort.objects.prefetch_related('device').filter(device__status=active):
            if not console_port.connected_endpoints:
                self.log_failure(
                    f"No console connection defined for {console_port.name}",
                    console_port.device,
                )
            elif not console_port.connection_status:
                self.log_warning(
                    f"Console connection for {console_port.name} marked as planned",
                    console_port.device,
                )
            else:
                self.log_success("Passed", console_port.device)

    def test_power_connections(self):

        # Check that every active device has at least two connected power supplies.
        for device in Device.objects.filter(status=DeviceStatusChoices.STATUS_ACTIVE):
            connected_ports = 0
            for power_port in PowerPort.objects.filter(device=device):
                if power_port.connected_endpoints:
                    connected_ports += 1
                    if not power_port.path.is_active:
                        self.log_warning(
                            f"Power connection for {power_port.name} marked as planned",
                            device,
                        )
            if connected_ports < 2:
                self.log_failure(
                    f"{connected_ports} connected power supplies found (2 needed)",
                    device,
                )
            else:
                self.log_success("Passed", device)
```

## Change Logging

To generate the correct change log data when editing an existing object, a snapshot of the object must be taken before making any changes to the object.

```python
if obj.pk and hasattr(obj, 'snapshot'):
    obj.snapshot()

obj.property = "New Value"
obj.full_clean()
obj.save()
```

## Error handling

Sometimes things go wrong and a script will run into an `Exception`. If that happens and an uncaught exception is raised by the custom script, the execution is aborted and a full stack trace is reported.

Although this is helpful for debugging, in some situations it might be required to cleanly abort the execution of a custom script (e.g. because of invalid input data) and thereby make sure no changes are performed on the database. In this case the script can throw an `AbortScript` exception, which will prevent the stack trace from being reported, but still terminating the script's execution and reporting a given error message.

```python
from utilities.exceptions import AbortScript

if some_error:
    raise AbortScript("Some meaningful error message")
```

## Variable Reference

### Default Options

All custom script variables support the following default options:

* `default` - The field's default value
* `description` - A brief user-friendly description of the field
* `label` - The field name to be displayed in the rendered form
* `required` - Indicates whether the field is mandatory (all fields are required by default)
* `widget` - The class of form widget to use (see the [Django documentation](https://docs.djangoproject.com/en/stable/ref/forms/widgets/))

### StringVar

Stores a string of characters (i.e. text). Options include:

* `min_length` - Minimum number of characters
* `max_length` - Maximum number of characters
* `regex` - A regular expression against which the provided value must match

Note that `min_length` and `max_length` can be set to the same number to effect a fixed-length field.

### TextVar

Arbitrary text of any length. Renders as a multi-line text input field.

### IntegerVar

Stores a numeric integer. Options include:

* `min_value` - Minimum value
* `max_value` - Maximum value

### BooleanVar

A true/false flag. This field has no options beyond the defaults listed above.

### ChoiceVar

A set of choices from which the user can select one.

* `choices` - A list of `(value, label)` tuples representing the available choices. For example:

```python
CHOICES = (
    ('n', 'North'),
    ('s', 'South'),
    ('e', 'East'),
    ('w', 'West')
)

direction = ChoiceVar(choices=CHOICES)
```

In the example above, selecting the choice labeled "North" will submit the value `n`.

### MultiChoiceVar

Similar to `ChoiceVar`, but allows for the selection of multiple choices.

### ObjectVar

A particular object within NetBox. Each ObjectVar must specify a particular model, and allows the user to select one of the available instances. ObjectVar accepts several arguments, listed below.

* `model` - The model class
* `query_params` - A dictionary of query parameters to use when retrieving available options (optional)
* `context` - A custom dictionary mapping template context variables to fields, used when rendering `<option>` elements within the dropdown menu (optional; see below)
* `null_option` - A label representing a "null" or empty choice (optional)

To limit the selections available within the list, additional query parameters can be passed as the `query_params` dictionary. For example, to show only devices with an "active" status:

```python
device = ObjectVar(
    model=Device,
    query_params={
        'status': 'active'
    }
)
```

Multiple values can be specified by assigning a list to the dictionary key. It is also possible to reference the value of other fields in the form by prepending a dollar sign (`$`) to the variable's name.

```python
region = ObjectVar(
    model=Region
)
site = ObjectVar(
    model=Site,
    query_params={
        'region_id': '$region'
    }
)
```

#### Context Variables

Custom context variables can be passed to override the default attribute names or to display additional information, such as a parent object.

| Name          | Default         | Description                                                                  |
|---------------|-----------------|------------------------------------------------------------------------------|
| `value`       | `"id"`          | The attribute which contains the option's value                              |
| `label`       | `"display"`     | The attribute used as the option's human-friendly label                      |
| `description` | `"description"` | The attribute to use as a description                                        |
| `depth`[^1]   | `"_depth"`      | The attribute which indicates an object's depth within a recursive hierarchy |
| `disabled`    | --              | The attribute which, if true, signifies that the option should be disabled   |
| `parent`      | --              | The attribute which represents the object's parent object                    |
| `count`[^1]   | --              | The attribute which contains a numeric count of related objects              |

[^1]: The value of this attribute must be a positive integer

### MultiObjectVar

Similar to `ObjectVar`, but allows for the selection of multiple objects.

### FileVar

An uploaded file. Note that uploaded files are present in memory only for the duration of the script's execution: They will not be automatically saved for future use. The script is responsible for writing file contents to disk where necessary.

### IPAddressVar

An IPv4 or IPv6 address, without a mask. Returns a `netaddr.IPAddress` object.

### IPAddressWithMaskVar

An IPv4 or IPv6 address with a mask. Returns a `netaddr.IPNetwork` object which includes the mask.

### IPNetworkVar

An IPv4 or IPv6 network with a mask. Returns a `netaddr.IPNetwork` object. Two attributes are available to validate the provided mask:

* `min_prefix_length` - Minimum length of the mask
* `max_prefix_length` - Maximum length of the mask

## Running Custom Scripts

!!! note
    To run a custom script, a user must be assigned permissions for `Extras > Script`, `Extras > Script Module`, and `Core > Managed File` objects. They must also be assigned the `extras.run_script` permission. This is achieved by assigning the user (or group) a permission on the Script object and specifying the `run` action in "Permissions" as shown below.

    ![Adding the run action to a permission](../media/run_permission.png)

### Via the Web UI

Custom scripts can be run via the web UI by navigating to the script, completing any required form data, and clicking the "run script" button. It is possible to schedule a script to be executed at specified time in the future. A scheduled script can be canceled by deleting the associated job result object.

### Via the API

To run a script via the REST API, issue a POST request to the script's endpoint specifying the form data and commitment. For example, to run a script named `example.MyReport`, we would make a request such as the following:

```no-highlight
curl -X POST \
-H "Authorization: Token $TOKEN" \
-H "Content-Type: application/json" \
-H "Accept: application/json; indent=4" \
http://netbox/api/extras/scripts/example.MyReport/ \
--data '{"data": {"foo": "somevalue", "bar": 123}, "commit": true}'
```

Optionally `schedule_at` can be passed in the form data with a datetime string to schedule a script at the specified date and time.

### Via the CLI

Scripts can be run on the CLI by invoking the management command:

```
python3 manage.py runscript [--commit] [--loglevel {debug,info,warning,error,critical}] [--data "<data>"] <module>.<script>
```

The required ``<module>.<script>`` argument is the script to run where ``<module>`` is the name of the python file in the ``scripts`` directory without the ``.py`` extension and ``<script>`` is the name of the script class in the ``<module>`` to run.

The optional ``--data "<data>"`` argument is the data to send to the script

The optional ``--loglevel`` argument is the desired logging level to output to the console.

The optional ``--commit`` argument will commit any changes in the script to the database.

## Example

Below is an example script that creates new objects for a planned site. The user is prompted for three variables:

* The name of the new site
* The device model (a filtered list of defined device types)
* The number of access switches to create

These variables are presented as a web form to be completed by the user. Once submitted, the script's `run()` method is called to create the appropriate objects.

```python
from django.utils.text import slugify

from dcim.choices import DeviceStatusChoices, SiteStatusChoices
from dcim.models import Device, DeviceRole, DeviceType, Manufacturer, Site
from extras.scripts import *


class NewBranchScript(Script):

    class Meta:
        name = "New Branch"
        description = "Provision a new branch site"
        field_order = ['site_name', 'switch_count', 'switch_model']

    site_name = StringVar(
        description="Name of the new site"
    )
    switch_count = IntegerVar(
        description="Number of access switches to create"
    )
    manufacturer = ObjectVar(
        model=Manufacturer,
        required=False
    )
    switch_model = ObjectVar(
        description="Access switch model",
        model=DeviceType,
        query_params={
            'manufacturer_id': '$manufacturer'
        }
    )

    def run(self, data, commit):

        # Create the new site
        site = Site(
            name=data['site_name'],
            slug=slugify(data['site_name']),
            status=SiteStatusChoices.STATUS_PLANNED
        )
        site.full_clean()
        site.save()
        self.log_success(f"Created new site: {site}")

        # Create access switches
        switch_role = DeviceRole.objects.get(name='Access Switch')
        for i in range(1, data['switch_count'] + 1):
            switch = Device(
                device_type=data['switch_model'],
                name=f'{site.slug}-switch{i}',
                site=site,
                status=DeviceStatusChoices.STATUS_PLANNED,
                role=switch_role
            )
            switch.full_clean()
            switch.save()
            self.log_success(f"Created new switch: {switch}")

        # Generate a CSV table of new devices
        output = [
            'name,make,model'
        ]
        for switch in Device.objects.filter(site=site):
            attrs = [
                switch.name,
                switch.device_type.manufacturer.name,
                switch.device_type.model
            ]
            output.append(','.join(attrs))

        return '\n'.join(output)
```
