https://github.com/glueops/python-glueops-helpers-library
The GlueOps Helpers Library is a collection of utility functions and classes for simplifying common tasks in Python projects. It includes helpers for logging, AWS interactions, Kubernetes configuration, Vault integration, and GetOutline API management. Easily installable via pip.
https://github.com/glueops/python-glueops-helpers-library
api api-client aws-interactions getoutline getoutline-api glueops-platform kubernetes kubernetes-configuration logging python python-getoutline python-kubernetes python-logging python-outline utilities vault vault-integration
Last synced: 3 months ago
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The GlueOps Helpers Library is a collection of utility functions and classes for simplifying common tasks in Python projects. It includes helpers for logging, AWS interactions, Kubernetes configuration, Vault integration, and GetOutline API management. Easily installable via pip.
- Host: GitHub
- URL: https://github.com/glueops/python-glueops-helpers-library
- Owner: GlueOps
- Created: 2023-10-08T01:33:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-21T19:47:21.000Z (7 months ago)
- Last Synced: 2025-03-28T11:44:05.475Z (3 months ago)
- Topics: api, api-client, aws-interactions, getoutline, getoutline-api, glueops-platform, kubernetes, kubernetes-configuration, logging, python, python-getoutline, python-kubernetes, python-logging, python-outline, utilities, vault, vault-integration
- Language: Python
- Homepage:
- Size: 77.1 KB
- Stars: 1
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# GlueOps Helpers Library
The GlueOps Helpers Library is a collection of utility functions and classes designed to simplify common tasks in Python projects. This library includes helpers for logging, AWS interactions, Kubernetes configuration, and more.
## Installation
To install the GlueOps Helpers Library, you can use pip with the following command:
```bash
pip install https://github.com/GlueOps/python-glueops-helpers-library/archive/refs/tags/v0.6.0.zip
```
# Usage
## Logging
The library provides a logging configuration utility that sets up a JSON formatter for structured logging.
```python
import os
from glueops import setup_logging
LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO")
logger = setup_logging.configure(level=LOG_LEVEL)
logger.info("This is an info message")
logger.error("This is an error message")
```
## AWS
The library includes helpers for creating AWS clients and retrieving resources based on tags.
```python
from glueops.aws import create_aws_client, get_resource_arns_using_tags
# Create an AWS client
s3_client = create_aws_client('s3')
# Get resource ARNs using tags
tags = [{'Key': 'Environment', 'Value': 'Production'}]
resource_arns = get_resource_arns_using_tags(tags, ['s3'])
print(resource_arns)
```
## Kubernetes
```python
import os
from glueops.setup_kubernetes import load_kubernetes_config
logger = setup_logging.configure(level="INFO")
v1, custom_api = load_kubernetes_config(logger)
# Example: List all pods in the default namespace
pods = v1.list_namespaced_pod(namespace='default')
for pod in pods.items:
print(pod.metadata.name)
```
## Vault
The library includes a client for interacting with HashiCorp Vault, supporting both Kubernetes and Pomerium authentication.
```python
from glueops.vault_client import VaultClient
vault_url = "https://vault.example.com"
kubernetes_role = "my-role"
vault_client = VaultClient(vault_url, kubernetes_role)
# Get data from Vault
secret_path = "secret/data/my-secret"
data = vault_client.get_data_from_vault(secret_path)
print(data)
# Write data to Vault
data_to_write = {"key": "value"}
vault_client.write_data_to_vault(secret_path, data_to_write)
```
## GetOutline
The library provides a client for interacting with the GetOutline API for managing documents.
```python
from glueops.getoutline import GetOutlineClient
api_url = "https://api.getoutline.com"
document_id = "your_document_id"
api_token = "your_api_token"
outline_client = GetOutlineClient(api_url, document_id, api_token)
# Create a new document
parent_document_id = "parent_document_id"
title = "New Document"
text = "This is the content of the new document."
outline_client.create_document(parent_document_id, title, text)
```