Day 15: Python Libraries for DevOps

What is YAML?

YAML was previously known as "Yet another markup language." But now it is called "YAML ain't markup language."

It is not a programming language. It is basically a data format used to exchange data. It is similar to XML and JSON data types. YAML is a human-readable language that can be used to represent data.

#YAML Example
person:
  name: John Doe
  age: 30
  gender: Male
  address:
    city: New York
    street: 123 Main Street
  hobbies:
    - Reading
    - Photography

What is JSON?

JSON (JavaScript Object Notation) is a lightweight data interchange format that is easy for humans to read and write and easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language, and it is often used to transmit data between a server and a web application, as an alternative to XML.

#JSON Example
{
  "name": "John Doe",
  "age": 30,
  "email": "johndoe@example.com",
  "is_active": true,
  "address": {
    "street": "123 Main Street",
    "city": "Anytown",
    "country": "USA"
  },
  "hobbies": ["Reading", "Hiking", "Cooking"]
}

Functions of YAML

YAML (YAML Ain't Markup Language) is a human-readable data serialization format.
It is often used for configuration files, data exchange between languages, and other structured data representations.
YAML uses indentation and colons to represent hierarchical data structures.
It supports various data types, including strings, numbers, booleans, null, arrays (lists), and objects (mappings).
YAML allows for multiline strings, making it easy to represent long blocks of text.
YAML comments start with the # symbol and can be used to provide additional information or explanations.

Functions of JSON

JSON is a data interchange format used to represent structured data as a string.
In Python, JSON is supported through the json module in the standard library.
The json module provides functions to work with JSON data in Python.
json.dumps(): This function is used to convert a Python object (e.g., dictionary, list) into a JSON-formatted string.
json.loads(): This function is used to parse a JSON-formatted string and convert it into a Python object (e.g., dictionary, list).
JSON keys must be strings, and the values can be strings, numbers, booleans, None, lists, or other JSON objects (dictionaries).

Task 1: Create a Dictionary in Python and write it to a JSON File.

import json

# Create a dictionary
my_dict = {
    "name": "John Doe",
    "age": 30,
    "is_student": True,
    "hobbies": ["Reading", "Hiking"]
}

# Define the file path for the JSON file
json_file_path = "data.json"

# Write the dictionary to a JSON file
with open(json_file_path, "w") as json_file:
    json.dump(my_dict, json_file, indent=4)

print("Data written to 'data.json'.")

After running this code, you will find the JSON data written to a file named data.json in the current working directory. The content of the JSON file will be:

{
    "name": "John Doe",
    "age": 30,
    "is_student": true,
    "hobbies": [
        "Reading",
        "Hiking"
    ]
}

Task 2: Read the JSON file `services.json` kept in this folder and print the service names of every cloud service provider.

import json

# Define the file path for the JSON file
json_file_path = "services.json"

# Read the JSON data from the file
with open(json_file_path, "r") as json_file:
    data = json.load(json_file)

# Extract and print the service names of every cloud service provider
for provider, services in data.items():
    print(f"Cloud Service Provider: {provider}")
    for service in services:
        print(f"- {service['name']}")
    print()  # Add a newline for better readability between providers

Task 3: Read the YAML file using Python, file services.yaml and read the contents to convert yaml to json.

import yaml
import json

# Define the file path for the YAML file
yaml_file_path = "services.yaml"

# Read the YAML data from the file
with open(yaml_file_path, "r") as yaml_file:
    data = yaml.safe_load(yaml_file)

# Convert the YAML data to JSON format
json_data = json.dumps(data, indent=4)

# Print the JSON data
print(json_data)

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