Keshav Bathla's Blog
Python Basics & Installation

Python Basics & Installation

Day13

Keshav Bathla's photo
Keshav Bathla
·

5 min read

Table of contents

What is Python & why it is used in DevOps

Python is a versatile and popular high-level programming language, known for its simplicity and readability. It was created by Guido van Rossum in 1991 and has since become widely adopted in various fields, including DevOps.

DevOps is a software development methodology that emphasizes collaboration between development (Dev) and operations (Ops) teams, aiming to automate tasks and continuously integrate and deliver software. Python plays a crucial role in DevOps for several reasons:

  1. Scripting and Automation: Python is perfect for writing scripts to automate repetitive tasks such as deployment, configuration management, and infrastructure provisioning. It's user-friendly syntax and rich libraries, like Fabric, Ansible, and Puppet, make it an ideal choice for streamlining these processes.

  2. Versatility: Python can handle a wide range of tasks, from web development and data analysis to system administration and networking. DevOps engineers can use the same language across different aspects of the pipeline, making it easier to work on various parts of the project.

  3. Rich Ecosystem: Python boasts a vast ecosystem with numerous libraries and frameworks. DevOps teams benefit from popular libraries like Requests for HTTP requests, Paramiko for SSH communication, and Boto3 for interactions with cloud services like AWS.

  4. Integration with Configuration Management Tools: Python integrates seamlessly with configuration management tools like Ansible, Chef, and Puppet, allowing for more flexible and dynamic configuration management.

  5. Monitoring and Metrics: Python can be used to create monitoring scripts for collecting and analyzing system metrics, log data, and application performance, vital for maintaining a reliable system.

  6. Continuous Integration/Delivery (CI/CD) Pipelines: Python can be used within CI/CD pipelines to automate the build, test, and deployment processes. Popular tools like Jenkins, Travis CI, and GitLab CI/CD make it easy to integrate Python scripts into the pipeline.

  7. Container Orchestration: Python is instrumental in container orchestration platforms like Kubernetes, offering client libraries and automation tools for more manageable container and application management.

  8. Infrastructure as Code (IaC): Python enables writing Infrastructure as Code scripts, using frameworks like Terraform. This allows teams to define and provision infrastructure in a version-controlled and repeatable manner.

To sum up, Python's ease of use, powerful libraries, and extensive ecosystem make it an invaluable tool for DevOps engineers. It empowers them to automate tasks, manage infrastructure, and ensure the seamless functioning of the DevOps pipeline.

Python Essential Concepts

Sure! Here's an explanation of some Python basics, including Python variables, data types, lists, dictionaries, and other essential concepts:

  1. Python Variables: In Python, a variable is a name that refers to a value. You can assign values of different data types to variables. The variable's data type is dynamically determined based on the assigned value.

    Syntax:

     variable_name = value

    Example:

     name = "John"
 age = 30
 height = 6.2

  2. Data Types: Python supports various data types, including:

    • Integers (int): Whole numbers, e.g., 1, 100, -45.

    • Floating-Point Numbers (float): Decimal numbers, e.g., 3.14, -0.5, 2.0.

    • Strings (str): Sequence of characters, e.g., "Hello", 'Python'.

    • Boolean (bool): Represents True or False.

    • Lists (list): Ordered collection of elements, mutable.

    • Tuples (tuple): Ordered collection of elements, immutable.

    • Dictionaries (dict): Collection of key-value pairs, mutable and unordered.

    • Sets (set): Collection of unique elements.

  3. Lists: A list is an ordered collection of elements, enclosed in square brackets ([]), and elements can be of different data types. Lists are mutable, which means you can change their contents after creation.

    Syntax:

     my_list = [element1, element2, element3, ...]

    Example:

     numbers = [1, 2, 3, 4, 5]
 names = ["Alice", "Bob", "Charlie"]
 mixed_list = [1, "hello", 3.14, True]

  4. Dictionaries: A dictionary is a collection of key-value pairs, enclosed in curly braces ({}), where keys are unique, and each key is associated with a value. Dictionaries are mutable.

    Syntax:

     my_dict = {key1: value1, key2: value2, key3: value3, ...}

    Example:

     person = {"name": "John", "age": 30, "city": "New York"}
 grades = {"Math": 95, "Science": 87, "History": 78}

  5. Basic Operations:

    • Arithmetic Operations: +, -, *, /, % (modulo), ** (exponentiation).

    • Comparison Operators: == (equal), != (not equal), >, <, >=, <=.

    • Logical Operators: and, or, not.

Example:

    a = 10
    b = 5
    result1 = a + b  # 15
    result2 = a > b   # True
    result3 = not(result1 == 15 and result2)  # False

  1. Control Flow:

    • if-elif-else: Used for conditional branching.

    • for loop: Used for iterating over sequences (e.g., lists, strings).

    • while loop: Used for executing a block of code while a condition is true.

Example:

    # if-elif-else
    num = 42
    if num > 50:
        print("Number is greater than 50")
    elif num < 50:
        print("Number is less than 50")
    else:
        print("Number is 50")

    # for loop
    fruits = ["apple", "banana", "orange"]
    for fruit in fruits:
        print(fruit)

    # while loop
    count = 0
    while count < 5:
        print("Count:", count)
        count += 1

These are some of the fundamental concepts in Python. With this knowledge, you can start writing simple Python programs and explore more advanced topics as you progress.

Python Installation

  1. Windows Installation:

  • You can download Python directly from here .

  • Click on Download and an installer will be downloaded.

  • Double-click on it and it will show an install window.

  • Check the add to PATH option to add the PATH to Environment Variables

  • just follow it and hit next and select the folder to install it and hit install.

  • After installation, open a cmd and type python and hit enter

  • If you see the following screen, that means Python is installed now.

  1. Python Installation in Ubuntu:
  • Python is usually pre-installed on most Ubuntu versions. To check if Python is installed, open the terminal and type:
python3 --version
  • If Python is not installed, you can install it using the following command in the terminal:
sudo apt-get update
sudo apt-get install python3
Reading package lists... Done
Building dependency tree... Done
Reading state information... Done
python3 is already the newest version (3.10.6-1~22.04).
python3 set to manually installed.
0 upgraded, 0 newly installed, 0 to remove and 88 not upgraded.

  • Now if you see the below screen after typing python3 then it means python is working:

    So this was all from today's blog, Meet you in the next blog.

#90daysofdevopsPython