Basics of Python for DevOps Engineers

What is Python?

• Python is an open-source, general-purpose, high-level, and object-oriented programming language.

• It was created by Guido van Rossum.

• Python consists of vast libraries and various frameworks like Django, TensorFlow, Flask, Pandas, Keras, etc.

How to Install Python?

You can install Python on your system, whether it is Ubuntu.

• Ubuntu: apt-get install python3.6

  Task 1:

  1. Install Python on your respective OS, and check the version.

  2. Read about different data types in Python.

Task 2: Read About Different Data Types in Python

Understanding data types is crucial for programming in Python. Here are some basic data types in Python:

• Integers: Whole numbers (e.g., 1, 2, 3)

• Floats: Decimal numbers (e.g., 1.1, 2.5, 3.14)

• Strings: Sequence of characters (e.g., "hello", "world")

• Lists: Ordered collection of items (e.g., [1, 2, 3], ["a", "b", "c"])

• Dictionaries: Key-value pairs (e.g., {"name": "Alice", "age": 25})

• Tuples: Immutable ordered collection of items (e.g., (1, 2, 3))

• Sets: Unordered collection of unique items (e.g., {1, 2, 3})

Datatypes

Integer :

# Integer
a = 5
print("The value of a is:", a)
print("The type of a is:", type(a))

2. Floats

# Float
b = 3.14
print("The value of b is:", b)
print("The type of b is:", type(b))

3. Strings

# String
c = "Hello, DevOps!"
print("The value of c is:", c)
print("The type of c is:", type(c))

4. Lists

# List
d = [1, 2, 3, "a", "b", "c"]
print("The value of d is:", d)
print("The type of d is:", type(d))

5. Dictionaries

# Dictionary
e = {"name": "Alice", "age": 25}
print("The value of e is:", e)
print("The type of e is:", type(e))

6. Tuples

# Tuple
f = (1, 2, 3)
print("The value of f is:", f)
print("The type of f is:", type(f))

7. Sets

# Set
g = {1, 2, 3}
print("The value of g is:", g)
print("The type of g is:", type(g))

Conclusion

Learning Python is a fundamental step for any DevOps engineer. With Python's simplicity and extensive libraries, you can automate tasks, manage infrastructure, and build robust applications. Start with the basics, practice regularly, and explore the vast ecosystem of Python libraries and frameworks. By integrating Python into your DevOps toolkit, you'll enhance your ability to streamline operations and deliver efficient solutions.