Python client for managing AWX automation platform.
📌 Table of Contents
- Authentication support: Built-in support for Basic Auth and OAuth2.
- Data validation: Pydantic models ensure that payloads conform to the AWX API's expected structure.
- Extensibility: Easily extendable to support new AWX resources or custom workflows.
Each module is documented in detail and can be explored using pdoc. Below is an overview of the key modules:
pyawx.auth: Authentication classes for Basic Auth and OAuth2.pyawx.http: HTTP client abstraction for handling API requests.pyawx.models: Pydantic models for data validation and serialization.pyawx.resources: Resource classes for interacting with AWX resources.pyawx.client: Client interface for interacting with the AWX API.
Install the pyawx package using pip:
pip install pyawxInstall the pyawx package using uv:
uv add pyawxTo interact with the AWX API, you need to authenticate using either Basic Authentication or OAuth2. Here's how to set up both methods:
from pyawx import Client
# Initialize the client with Basic Authentication
client = Client(
"https://api.example.com",
username="your_username",
password="your_password",
)
# Check if the client is authenticated
if not client.is_authenticated():
raise ValueError("Authentication failed: Invalid credentials")from pyawx import Client
# Initialize the client with OAuth2 Authentication
client = Client("https://api.example.com", token="your_oauth2_token")The library provides resource-specific classes to interact with different AWX API endpoints. Below are examples of how to work with job templates and workflow job templates.
Note
The library uses Pydantic models to ensure that the data conforms to the AWX API's expected structure. This helps in reducing runtime errors by validating the data before sending it to the API.
from pyawx.models import JobTemplateModel
# Fetch a job template by name
client.job_template.fetch("My Job Template")
# Create a new job template
new_job_template = JobTemplateModel(
name="My New Job",
inventory="inventory_1",
project="project_1",
playbook="deploy.yml"
)
client.job_template.create(new_job_template)
# Update an existing job template
updated_job_template = JobTemplateModel(
name="Updated Job Template",
inventory="inventory_1",
project="project_1",
playbook="deploy.yml"
)
client.job_template.update("My Job Template", updated_job_template)
# Delete a job template
client.job_template.delete("My Job Template")from pyawx.models import WorkflowJobTemplateModel
# Fetch a workflow job template by name
client.workflow_job_template.fetch("My Workflow Job Template")
# Create a new workflow job template
new_workflow = WorkflowJobTemplateModel(
name="Release Deployment Workflow",
inventory="prod_inventory",
extra_vars='{"version": "1.2.3"}'
)
client.workflow_job_template.create(new_workflow)
# Update an existing workflow job template
updated_workflow = WorkflowJobTemplateModel(
name="Updated Workflow",
inventory="prod_inventory",
extra_vars='{"version": "1.2.4"}'
)
client.workflow_job_template.update("Release Deployment Workflow", updated_workflow)
# Delete a workflow job template
client.workflow_job_template.delete("Release Deployment Workflow")We welcome contributions! Please follow these steps:
- Open an issue to discuss your proposed changes.
- Fork the repository.
- Clone the fork.
- Create a new branch (
git checkout -b feature/my-feat-branch). - Make your changes.
- Commit your changes (
git commit -m "feat: Add mew feature"). - Push to the branch (
git push origin feature/my-feat-branch). - Open a pull request.
Run unit tests using pytest:
uv run pytest tests- Add asynchronous calls support.
- Add support for more AWX resources.