Python client for managing AWX automation platform
Project description
🤖 PyAWX
Python client for managing AWX automation platform.
📌 Table of Contents
✨ Features
- 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.
📚 Documentation
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.
📦 Installation
📥 Pip
Install the pyawx package using pip:
pip install pyawx
📥 UV
Install the pyawx package using uv:
uv add pyawx
📖 Usage
🔒 Authentication
To interact with the AWX API, you need to authenticate using either Basic Authentication or OAuth2. Here's how to set up both methods:
🔑 Basic Authentication
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")
🔑 OAuth2 Authentication
from pyawx import Client
# Initialize the client with OAuth2 Authentication
client = Client("https://api.example.com", token="your_oauth2_token")
🔄 Working with Resources
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.
📜 Job Templates
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")
📜 Workflow Job Templates
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")
🤝 Contributing
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.
🧪 Testing
Run unit tests using pytest:
uv run pytest tests
🛠️ Roadmap
- Add asynchronous calls support.
- Add support for more AWX resources.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pyawx-0.1.3.tar.gz.
File metadata
- Download URL: pyawx-0.1.3.tar.gz
- Upload date:
- Size: 36.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.6.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
182c8ea490532274b08483f186bfa5d9bf0954d8e6dedcce5b0bd3070b6526a2
|
|
| MD5 |
f0d97bceec251e3883fce1242fc89cfa
|
|
| BLAKE2b-256 |
1285ea8f29d86e39b35832d056c5ab666d249bfa27ade8d8bb12050c3aa3ceb3
|
File details
Details for the file pyawx-0.1.3-py3-none-any.whl.
File metadata
- Download URL: pyawx-0.1.3-py3-none-any.whl
- Upload date:
- Size: 27.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.6.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
72cc5747793e40409265b5544e5debd074b1208f66fea40c8c8e2b780e2f69e1
|
|
| MD5 |
61b16dcbce3aeaa8f09d287a210501a2
|
|
| BLAKE2b-256 |
bc0a8bb9f371415c69351c73b5b9af23dad9c4bcc4bee8db74a50d881e48aaa6
|