Day 15 Task: Python Libraries for DevOps

In the world of Python programming, handling data efficiently is crucial. JSON (JavaScript Object Notation) and YAML (YAML Ain't Markup Language) are two popular formats for storing and exchanging data. Let's explore how Python makes working with JSON and YAML a breeze!

JSON in Python:

• JSON is a syntax for storing and exchanging data.

• JSON is text, written with JavaScript object notation.

• Python has a built-in package called json, which can be used to work with JSON data.

• If you have a JSON string, you can parse it by using the json.loads()method.

• If you have a Python object, you can convert it into a JSON string by using the json.dumps() method.

    import json
    #Convert from JSON to Python
    json_data = '{ "name":"vaishnavi","country":"india"}'
    python_obj = json.loads(json_data)  # convert into python
    print(python_obj)     #{'name': 'vaishnavi', 'country': 'india'}
  
    #Convert from Python to JSON
    python_obj = {"name": "Vaishnavi","city": "India"}
    json_data = json.dumps(python_obj) # convert into JSON
    print(json_data)  #{"name": "Vaishnavi", "city": "India"}
  

YAML in Python:

• YAML is an abbreviation of Yet Another Markup Language.

• It stores the configuration file data in a serialized manner and is often used in data storage or transmission.

• The YAML files are saved with the .yaml or .yml extension.

• PyYAML is a Python module that provides a range of methods to perform several operations on the YAML file.

• The yaml.load() method is used to read the YAML file. This method parses and converts the YAML object to a Python dictionary so that we can read the content easily. This process is called the Deserialization of YAML files into Python.

• To convert a Python object to a YAML string, you can use the yaml.dump() function.

    import yaml
  
    # YAML to Python object
    yaml_data = '''
      name: John
      age: 30 
     '''
    python_obj = yaml.load(yaml_data)
    print(python_obj) #{'name': 'John', 'age': 30}
  
    # Python object to YAML
    python_obj = {'name': 'John', 'age': 30}
    yaml_data = yaml.dump(python_obj)
    print(yaml_data)   # Output: "age: 30 name: John"
  

Tasks

1. Create a Dictionary in Python and write it to a json File.

   

   

2. Read a json file services.json kept in this folder and print the service names of every cloud service provider.

   

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

Conclusion:

Whether you're parsing data from APIs, configuring applications, or exchanging data between systems, Python's support for JSON and YAML empowers you to handle data with ease and efficiency. With straightforward integration and powerful parsing capabilities, Python simplifies the process of working with JSON and YAML, unlocking the magic of data manipulation in your projects.

Embrace JSON and YAML in Python today and elevate your data handling capabilities to new heights!