
🚀 Welcome to Day 13 of #90DaysOfDevOps! 🎉
Today, let's dive into a crucial aspect of being a DevOps Engineer - reading JSON and YAML in Python. 🐍📚
📝 Reading JSON and YAML in Python As DevOps Engineers, parsing files is a fundamental skill. Python offers powerful libraries that simplify handling various file formats like txt, json, and yaml.
Libraries for DevOps in Python Python boasts a wealth of libraries like os, sys, json, and yaml, which prove indispensable in our day-to-day tasks.
Task 1: Create a Dictionary and Write to JSON Let's start by creating a Python dictionary and writing it to a JSON file. JSON provides an organized and human-readable structure for data exchange.
import json # Create a Python dictionary data = { "name": "John Doe", "age": 30, "occupation": "DevOps Engineer" } # Write dictionary to JSON file with open("data.json", "w") as json_file: json.dump(data, json_file, indent=4)
Task 2: Read JSON and Extract Cloud Service Names Now, we'll read a JSON file, "services.json," and extract the service names of each cloud service provider. The content of "services.json" is shown below:
{ "services": { "debug": "on", "aws": { "name": "EC2", "type": "pay per hour", "instances": 500, "count": 500 }, "azure": { "name": "VM", "type": "pay per hour", "instances": 500, "count": 500 }, "gcp": { "name": "Compute Engine", "type": "pay per hour", "instances": 500, "count": 500 } } }# Read JSON and extract cloud service names with open("services.json", "r") as json_file: data = json.load(json_file) cloud_providers = data["services"].keys() print("Cloud Service Providers:") for provider in cloud_providers: if provider != "debug": print("- ", provider)
Task 3: Read YAML and Convert to JSON YAML is another popular data serialization format. Let's read "services.yaml" and convert its contents to JSON. The content of "services.yaml" is shown below:
--- services: debug: 'on' aws: name: EC2 type: pay per hour instances: 500 count: 500 azure: name: VM type: pay per hour instances: 500 count: 500 gcp: name: Compute Engine type: pay per hour instances: 500 count: 500import yaml # Read YAML and convert to JSON with open("services.yaml", "r") as yaml_file: data = yaml.safe_load(yaml_file) with open("services_converted.json", "w") as json_file: json.dump(data, json_file, indent=4)

🏁 Conclusion: Reading JSON and YAML files in Python is a fundamental skill for DevOps Engineers. With Python's powerful libraries, we can efficiently handle data and extract valuable information. Make sure to practice these tasks to enhance your DevOps toolkit! 💼🔧
Feel free to connect with me on LinkedIn 🤝 Check out my GitHub for more resources 📚
Happy learning, and stay tuned for more exciting DevOps content! 🚀🎉
About the author
👩💻 As a seasoned software engineer with 7+ years of experience, my expertise includes:
- 🌐 Developing web applications using Javascript (frontend and backend)
- 💼 Working across diverse industries like construction, finance, marketing, and entrepreneurship
- 🎓 Holding a postgraduate degree in Master of Computer Applications from the University of Pune
🔧 My technical prowess lies in:
- ⚛️ Leading Javascript frameworks: React, Node.js, and Express.js
- 🚀 Delivering robust and scalable web applications with the best software engineering practices
🌱 Excitingly, I've started my DevOps learning journey with #90DaysOfDevOps to enhance my skills in this area.
🧠 Beyond technical skills, I offer:
- 💡 Exceptional problem-solving abilities and a strong aptitude for learning new technologies
- 🤝 A collaborative mindset, making me a valuable team player in diverse environments
🚀 My passion is in delivering high-quality software solutions that solve real-world problems. If you're seeking a skilled and experienced software engineer for top-notch web applications, let's connect and explore potential opportunities together! 🤝
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