Python Libraries for DevOps

Let's explore most widely used libraries in Python

1. JSON (JavaScript Object Notation) :

   It is a popular data format used for exchanging data between a server and a client.

   Library Name: json

   Purpose: The json library in Python provides functions to encode Python objects as JSON strings and decode JSON strings into Python objects.

   Usage :

   1. Use json.loads() to load JSON from a string.

   2. Use json.load() to load JSON from a file.

   3. Use json.dumps() to convert Python objects to a JSON string.

   4. Use json.dump() to write JSON to a file.

Importing the JSON Module :

1. First, you need to import the json module :

2. Loading JSON Data :

You can load JSON data from a string or a file.

From a JSON string :

If you have a JSON string, you can convert it into a Python dictionary using json.loads()

From a JSON file :

If you have a JSON file, you can read and parse it using json.load()

3. Converting to JSON :

You can convert Python objects (like dictionaries) to JSON strings or write them to a file.

To a JSON string :

Use json.dumps() to convert a Python object into a JSON string.

Output :

To a JSON File :

Creating a Dictionary and write it to a JSON File

Output :

Output :

2. YAML (YAML Ain't Markup Language):

• Library Name: pyyaml (Python YAML)

  Purpose : The pyyaml library in Python allows reading and writing data in YAML format.

• YAML is a human-readable data serialization format that is often used for configuration files and data exchange between systems, especially in situations where readability by humans is important.

Usage

:

• yaml.safe_load(): To load YAML from a string or a file.

• yaml.load(): Deserialize YAML data to a Python object.

• yaml.dump(): To convert Python objects to a YAML string or write them to a file.

• yaml.load with yaml.FullLoader :when you need more features and are sure the input is trusted.

In Python, you can use the PyYAML library to work with YAML files

1. Install PyYAML

First, you need to install the PyYAML library. You can install it using pip :

2. Importing the PyYAML Module

Once installed, you can import the yaml module in your Python script .

3. Loading YAML Data

   You can load YAML data from a string or a file.

From a YAML string :

From a YAML file :

4. Converting to YAML

You can convert Python objects (like dictionaries) to YAML strings or write them to a file.

To a YAML string :

To a YAML file :

Before executing this, make sure you have the pyyaml library installed (pip install pyyaml)

Output :

To summarize

• JSON is more commonly used for machine-to-machine communication due to its simplicity and ubiquity.

• YAML is often preferred for human-readable data storage and configuration files.