jamf-resource-deleter 0.5.0

A module that reads JSON files of Jamf resources (IDs) and deletes them

Jamf Resource Deleter ( WIP )

Safely delete unused or disabled resources from Jamf Pro using structured JSON input and the Jamf Pro API.

This tool is designed to work alongside tools like Prune, allowing you to identify unused Jamf resources, export them as JSON, and then programmatically remove them from your Jamf Pro tenant.

THIS TOOL IS STILL A WORK IN PROGRESS AND SHOULD BE USED AT YOUR OWN RISK

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Roadmap

• Develop Restore Functionality
• Tidy Up
• Split into multiple files for future growth

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⚠️ Warning

This tool permanently deletes Jamf Pro resources.

• There is no undo
• Always validate your JSON input
• Always test against a non-production Jamf tenant first
• Review the resources to be deleted before running
• There is a export method which should save most of the configuration, but the resources will be deleted
• In the future, there will be a restore functionality which will re-create all of the deleted resources

You are responsible for the changes made by this tool.

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Features

• Deletes unused or disabled Jamf Pro resources via API
• Supports multiple JSON input files
• Clear naming conventions and predictable behavior
• Uses the JamfPy Python SDK
• Designed for automation and CI/CD usage
• Works with output generated by Prune

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Supported Resource Types

The exact supported resources depend on JamfPy API coverage, but typically include:

• Policies
• Scripts
• Extension Attributes
• Computer Groups
• Computers
• Mobile Device Groups
• Configuration Profiles
• Packages (optional / configurable)

(See JamfPy documentation for supported endpoints.)

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How It Works

1. You identify unused or disabled Jamf resources (e.g. with Prune)
2. Export those resources into one or more JSON files
3. Provide the JSON files to jamf-resource-deleter
4. The module (alongside JamfPy):
   • Authenticates to Jamf Pro
   • Iterates through each resource
   • Deletes it via the Jamf Pro API

Example

import os
from pathlib import Path
from dotenv import load_dotenv
import jamfpy
from jamf_resource_deleter import JamfResourceDeleter

load_dotenv()

client_id = os.environ.get("client_id")
client_secrent = os.environ.get("client_secret")
jamfpro_url = os.environ.get("jamf_url")

JSON_DATA = Path("json_data/unused_profiles.json")

jamfpy_client = jamfpy.Tenant(
    fqdn = jamfpro_url,
    auth_method="oauth2",
    client_id=client_id,
    client_secret=client_secrent,
    token_exp_threshold_mins=1
)

deleter = JamfResourceDeleter(jamfpy_client)

deleter.delete_from_json(JSON_DATA, dry_run=False, export=True)

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Installation

Requirements

• Python 3.9+
• Jamf Pro account with API permissions
• Jamf Pro API credentials
• Network access to your Jamf tenant

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Install from PyPi

pip install jamf-resource-deleter

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Install from source (development)

git clone https://github.com/your-org/jamf-resource-deleter.git
cd jamf-resource-deleter
pip install -e .

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Dependencies

This project uses:

• JamfPy – Jamf Pro Python SDK
• requests
• Standard Python libraries

JamfPy is installed automatically as a dependency.

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Authentication

Authentication is handled by JamfPy.

You can create a JamfPy client using the following:

import jamfpy

client_id = "YOUR-CLIENT-ID"
client_secrent = "YOUR-CLIENT-SECRET"
jamfpro_url = "https://your-jamfpro-server.com"

jamfpy_client = jamfpy.Tenant(
    fqdn = jamfpro_url,
    auth_method="oauth2"
    client_id=client_id,
    client_secret=client_secrent,
    token_exp_threshold_mins=1
)

Refer to the JamfPy documentation for supported authentication methods.

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Input JSON Format

You may supply one or more JSON files.

JSON structure

Each file must contain an array of objects with at minimum:

• resourceType - Jamf Pro resource type
• id – Jamf Pro resource ID
• name – Human-readable name (used for logging / validation)

Example

{
  "unusedComputerProfiles": [
    {"id": 12, "name": "Restrictions"},
    {"id": 114, "name": "WiFi - Certificate"},
  ]
}

{
  "unusedPolicies": [
    {"id": 133, "name": "Install App"},
    {"id": 145, "name": "Remove App"},
  ]
}

Each resource type has to match the following naming convention, this table is also the supported resources at time of writing:

JSON Key	Jamf Resource Type	Delete Method
unusedComputerGroups	Computer Groups	_delete_computer_group
unusedMacApps	macOS Applications	_delete_apps
unusedMobileDeviceApps	Mobile Device Applications	_delete_apps
unusedPackages	Packages	_delete_packages
unusedPolicies	Policies	_delete_policies
unusedComputerProfiles	Computer Configuration Profiles	_delete_profiles
unusedScripts	Scripts	_delete_scripts
unusedComputerEAs	Computer Extension Attributes	_delete_computer_extension_attributes
unusedRestrictedSoftware	Restricted Software	_delete_restricted_software

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Usage

Basic Usage

pip install jamf-resource-deleter

import os
from pathlib import Path
from dotenv import load_dotenv
import jamfpy
from jamf_resource_deleter import JamfResourceDeleter

load_dotenv()

client_id = os.environ.get("client_id")
client_secrent = os.environ.get("client_secret")
jamfpro_url = os.environ.get("jamf_url")

JSON_DATA = Path("json_data/unused_profiles.json")

jamfpy_client = jamfpy.Tenant(
    fqdn = jamfpro_url,
    auth_method="oauth2",
    client_id=client_id,
    client_secret=client_secrent,
    token_exp_threshold_mins=1
)

deleter = JamfResourceDeleter(jamfpy_client)

deleter.delete_from_json(JSON_DATA, dry_run=False, export=True)

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Multiple Files

The following example shows you how you can write a short method that will allow you to merge multiple JSON files into the one and then use these to delete resources.

This also includes removing some keys (in this instance it is keys that are generated by Prune).

pip install jamf-resource-deleter

import os
import json
from pathlib import Path
from dotenv import load_dotenv
import jamfpy
from jamf_resource_deleter import JamfResourceDeleter

load_dotenv()

current_dir = Path(__file__).parent
parent_dir = current_dir.parent

client_id = os.environ.get("client_id")
client_secrent = os.environ.get("client_secret")
jamfpro_url = os.environ.get("jamf_url")

JSON_DIR = current_dir / "json_data"

keys_to_remove = ["jamfServer", "username"]

def merge_json_files() -> dict:
    combined_data = {}

    for json_file in JSON_DIR.glob("*.json"):
        with open(json_file, "r") as f:
            data = json.load(f)
            combined_data.update(data)

    for key in keys_to_remove:
        try:
            del combined_data[key]
        except KeyError as e:
            print(f"There is no key for {e}, please check there are files in JSON directory!")

    combined_path = JSON_DIR / "combined_data" / "combined.json"

    with open(combined_path, "w") as f:
        json.dump(combined_data, f, indent=2)

    return combined_path

if __name__ == "__main__":
    jamfpy_client = jamfpy.Tenant(
        fqdn = jamfpro_url,
        auth_method="oauth2",
        client_id=client_id,
        client_secret=client_secrent,
        token_exp_threshold_mins=1
    )

    deleter = JamfResourceDeleter(jamfpy_client)

    combined_path = merge_json_files()

    deleter.delete_from_json(combined_path, dry_run=False, export=True)

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Dry Run

You can run this module with a dry-run setting which will run through the JSON files, but not actually delete anything. This is enabled by default, and can be disabled by setting the attribute dry_run to False like the following:

deleter = JamfResourceDeleter(jamfpy_client)

deleter.delete_from_json(path_to_json, dry_run=False, export=False)

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Exporting/Restoring

Currently, the module will allow you to export all the configuration to another JSON file, so that things can be re-created manually if something that you deleted was not meant to be deleted.

In the future, the plan is to create a restore functionality so that if you were not meant to delete anything, you can restore everything from the backup file.

To enable exporting, you can set the export attribute to True:

deleter = JamfResourceDeleter(jamfpy_client)

deleter.delete_from_json(path_to_json, dry_run=True, export=True)

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Logging & Output

The tool logs:

• Resource type
• Resource ID
• Resource name
• Success or failure of deletion

Failures are reported clearly and do not halt the entire run unless critical.

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Recommended Workflow (Best Practice)

1. Run Prune to identify unused resources
2. Export results to JSON
3. Review JSON manually
4. Run jamf-resource-deleter with --dry-run
5. Validate output
6. Run again without --dry-run

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Development

Run tests

pytest

Lint

ruff check .
ruff format --check .

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Contributing

Contributions are welcome!

Please:

• Use Conventional Commits
• Add tests for new behavior
• Run linting before submitting PRs

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License

Apache 2.0

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Disclaimer

This project is not affiliated with or endorsed by Jamf.

Use at your own risk.