Python DevOps

Overview

Python-Devops is a collection of Python stack templates designed for DevOps purposes. These templates can be used as a foundation for implementing various projects. The focus of Python-Devops is on utilizing Docker for containerization.

Features

• Basic Python: Provides basic Python templates and tools such as AutoPEP8 for code formatting and graph function dependencies for visualizing function dependencies.
• Basic Backend: Includes Flask templates with various databases (MongoDB, Redis, MySQL, PostgreSQL, Elasticsearch) and functionality such as REST APIs and PubSub.
• Scaling-up Backend: Offers templates for scaling up Flask applications with features like SocketIO, load balancing with Nginx, and integrating RabbitMQ with Celery.
• Big data piping: Provides templates for handling big data pipelines, including streaming data from Tweepy to Elasticsearch and using Luigi for scheduled crawling.
• Apache big data: Includes templates for integrating Flask with Apache big data tools like Hadoop, Kafka, Hive, PySpark, Flink, and Storm.
• Unit test: Offers templates using Pytest for unit testing Python code.
• Stress test: Provides templates using Locust for stress testing applications.
• Miscellaneous: Includes templates for Elasticsearch and Kibana, Jupyter notebook (with and without Jupyterhub), Hadoop cluster with Luigi and Jupyter Notebook, Kafka cluster, and Apache Storm.

Summary

Python-Devops is a collection of Python stack templates tailored for DevOps purposes. With a focus on Docker, it offers a wide range of templates for basic Python development, backend development with Flask and various databases, scaling up backend applications, handling big data pipelines, integrating with Apache big data tools, unit testing, stress testing, and more. By using Docker-Compose, users can easily set up and manage their development environments.