Python Scripting Fundamentals

1. Getting Started: Your First Python Script

Before we dive in, ensure you have Python installed. If not, you can download it from python.org. As a DevOps engineer, you're likely familiar with installing software, but the "How to Install Python 3" guide in the resource A Practical Python Tutorial for Beginners is a good reference if you need it.

Let's create our first script. Open a text editor, create a file named hello.py, and add the following line:

print("Hello, DevOps World!")

Save the file. Now, open your terminal, navigate to the directory where you saved the file, and run it with the command:

python3 hello.py

You should see Hello, DevOps World! printed to your console. The print() function is the primary way to display output in Python, similar to echo in Bash.

2. Storing Information: Variables and Data Types

Just like in Bash, we use variables to store information that we can use and reuse in our scripts. Think of a variable as a labeled container for a value.

Unlike Bash, where almost everything is treated as a string, Python has distinct data types. This allows you to work with numbers, text, and other kinds of information more intuitively.

The following video provides an excellent introduction to variables and the four most common basic data types.

Key Concepts from the Video

Let's summarize the essential data types you just saw:

• String (str): A sequence of text, enclosed in single (') or double (") quotes. Used for names, file paths, messages, etc.
  • hostname = "server-01"
• Integer (int): A whole number, without a decimal point. Used for counts, IDs, status codes, etc.
  • cpu_cores = 8
• Float (float): A number with a decimal point. Used for measurements like temperature or financial data.
  • load_average = 1.25
• Boolean (bool): Can only be one of two values: True or False (note the capital letters). Essential for checks and conditions.
  • is_service_running = True

This diagram provides a nice visual overview of how these data types are categorized in Python.

Python is dynamically typed, which means you don't have to declare the type of a variable. Python infers the type from the value you assign to it.

# Python knows 'port' is an integer
port = 8080

# Python knows 'status' is a string
status = "running"

3. Making Decisions: Control Flow Structures

Writing a script isn't just about executing commands one after another. Control flow statements allow you to control the order of execution, making your scripts dynamic and intelligent. They let you execute code conditionally (decision) or repeatedly (repetition).

Conditional Statements (if, elif, else)

Conditional statements allow your script to make decisions. The if statement checks if a condition is true and executes a block of code only if it is. You can provide alternative paths with elif (else if) and else.

This is the Python equivalent of the if/then/else/fi structure you mastered in Bash.

A key takeaway is Python's use of indentation (whitespace at the beginning of a line) to define code blocks. Where Bash uses then and fi, Python uses a colon (:) followed by an indented block.

# A simple DevOps example
cpu_usage = 85

if cpu_usage > 90:
    print("ALERT: High CPU usage!")
elif cpu_usage > 75:
    print("WARNING: CPU usage is getting high.")
else:
    print("OK: CPU usage is normal.")

# This will print: WARNING: CPU usage is getting high.

Repetition / Loops (for and while)

Loops are used to execute a block of code multiple times. This is incredibly useful for repetitive tasks, like processing a list of servers or reading lines from a log file.

Python has two main types of loops:

• for loop: Executes a code block for each item in a sequence (like a list of servers or a range of numbers).
• while loop: Executes a code block as long as a specified condition remains true.

Here's a quick summary:

• Use a for loop when you know how many times you want to iterate. For example, to ping 5 servers.

  # The range(5) function generates numbers from 0 to 4
  for i in range(5):
      print(f"Pinging server #{i+1}...") 
  

• Use a while loop when you want to loop until a condition changes. For example, to wait for a service to start.

  # A simple countdown
  seconds_left = 5
  while seconds_left > 0:
      print(f"{seconds_left}...")
      seconds_left = seconds_left - 1 # Decrement the counter
  print("Go!")
  

4. Practical Application: Your First Python Scripts

Now, let's combine these concepts to solve a few simple problems. Try to write the code for these exercises yourself before looking at the solution.

def multiplication_or_sum(num1, num2):
    # Calculate the product of the two numbers
    product = num1 * num2
    
    # Check if the product is less than or equal to 1000
    if product <= 1000:
        return product
    else:
        # If the product is greater than 1000, return the sum
        return num1 + num2

# First condition
result = multiplication_or_sum(20, 30)
print("The result is", result)

# Second condition
result = multiplication_or_sum(40, 30)
print("The result is", result)

10
20
55

num_list = [10, 20, 33, 46, 55]
print("Given list is:", num_list)
print('Divisible by 5:')

for num in num_list:
    if num % 5 == 0:
        print(num)

Conclusion

Great work today! You've taken your first and most important step into using Python for automation. You've moved from the command-centric world of Bash to the data-centric world of a general-purpose programming language.

Key Takeaways:

• Python scripts are run using the python3 interpreter.
• Variables store data, and Python uses data types like str, int, float, and bool to understand what kind of data it's working with.
• Control flow statements direct the logic of your script:
  • if/elif/else statements make decisions based on conditions.
  • for loops repeat actions for a known number of items.
  • while loops repeat actions until a condition is no longer true.
• Indentation is a critical part of Python's syntax for defining code blocks.

Next Up

You now have the fundamental building blocks. In our next lesson, we will explore some of Python's more powerful data structures: lists and dictionaries. These are essential for managing collections of data, such as a list of servers or the JSON response from an API. We will also learn how to create reusable blocks of code with functions.