DevOps Bootcamp - Python Basics

Source: My personal notes from DevOps course by TechWorld with Nana

Overview

Programming basics
- Data types
- Lists
- Variables and functions
- Accept user input
- Input validation, conditionals
- Error handling
- Loops
- Modules using and creating
  - Date time
  - Packages
- Project
- Object oriented programming, classes
- API requests to GitLab
Automation
Why learn programming?
As of 2023, Python is the most popular language. For web development, data science, machine learning, and automation.

Introduction to Python

Python is a programming language. Its advantages are:

Simple syntax
Easy to set up
Large ecosystem: many libraries and users
Flexible: not limited to language specifics, can be used many purposes

What is Python used for?

Use cases:

Web development
Data science
Machine learning
Artificial intelligence (AI)
- e.g. voice, face recognitions
Web scraping
Automation
- Modules for CI/CD, cloud, monitoring
- Automate general tasks
  - Working with Excel sheets
Mobile, game and desktop development (though less common)

Why Python as a DevOps engineer?

It is common requirements for DevOps jobs
DevOps works with many tools and combine them
- Examples:
  - Update Jira ticket after Jenkins build
  - Trigger Jenkins jobs on events
  - Send notifications to people on events
  - Monitoring
  - Scheduled tasks
  - Data visualizations
  - Custom Ansible modules
  - Backups
  - Clean up old docker images
- Any repetitive tasks - more automations and less manual
- Automation scripts and programs for your teams

Installation and Local Setup

Example install
- Download from https://www.python.org/downloads/ for your operating system
- Add python to your path
- Make sure you use Python version 3+

PyCharm

Install PyCharm IDE: https://www.jetbrains.com/pycharm/download/
Start Pycharm
Create new project
- Select appropriate location or use default
- Note use of python interpreter - it knows the python code and translates to computer instructions
- One main.py

Our first Python Program

Print commands

Python IDE vs Simple File Editor

Integrated Development Environment (IDE) helps with writing code and output
- Write and run right away
  - Syntax highlights
  - Autocompletion
- Common interface: Navigation, write code, execution context
Simple file editor
- Edit code in file in editor
- Run code like python main.py

Strings and Number Data Types

Strings can be surrounded by single or double quotes. They are the same
Numbers can be integers (numbers with decimal places) and floats
- Numbers can be used in calculations
Strings can be combined (called concatenation) and using for output

#"string2"
#'string3'
print("string1")

# Numbers as:
## Float
3.5
## Integers
2
print(2)

# Print number of minutes in 20 days
print(20 * 24 * 60)

# String concatenation, adding strings together using +
## Convert a float number to string using str()
print("20 days are " + str(28800) + " minutes")

# f strings (Python 3 only, does not work in python 2)
## Better string formatting is using f strings and { }
## Brackets show where to insert the value
## Note the f before the string
print (f"20 days are {28800} minutes")
## Do calculation with string
print (f"20 days are {20 * 24 * 60} minutes")

Variables

Variables are containers to store values
Python is dynamically typed vs statically typed where variables’ type is defined and fixed
Python naming convention is to use lowercase and underscore to separate words like my_variable
- Variables must avoid reserved words in Python
- Use descriptive names, like type of value, what it is used for

# Using example from above, let's use
# variables to store values and
# easily change the values throughout a program

# Number of units in a day
## Integer variable
calculation_to_units = 24 * 60 * 60
## String variable
name_of_unit = "seconds"

print (f"35 days are {35 * calculation_to_units} {name_of_unit}")

Functions

Functions are blocks of code that can be reused
- Look at duplicated variable usage and statements
- Avoid repeating the same logic
- Only runs when called
- Functions can take in parameters
  - Parameters are variables inside the function
  - If a parameter is not given, but one a function needs one, the python interpreter will tell us a argument (parameter) is missing
  - There can be as many parameters as needed 0 to more
- Function body is the code inside the function
  - Variables created in the function body are local scoped and can be used in the function
Define function with def keyword like def days_to_units():
Variables can be scoped - where is the variable defined and can be used
- Global scope = variables available from anywhere like in main program and functions
- Local scope = variables only available in a function

##############################################################
# String/number data types, variables, functions, parameters #
##############################################################

# Number of units in a day
# Integer variable, global scope variable
calculation_to_units = 24 * 60 * 60
# String variable
name_of_unit = "seconds"


def days_to_units_20():
    print(f"20 days are {20 * calculation_to_units} {name_of_unit}")


# Define a new function called days_to_units
# function parameter is num_of_days, a local scope variable
def days_to_units(num_of_days: object, custom_message: object) -> object:
    print(f"{num_of_days} days are {num_of_days * calculation_to_units} {name_of_unit}")
    print(custom_message)


def scope_check(number_of_days):
    my_local_variable = "variable inside function"
    print(my_local_variable)
    print(calculation_to_units)
    print(number_of_days)

# Call functions to see number of seconds in days
days_to_units_20()
days_to_units(20, "Awesome!")
days_to_units(110, "Nice!")

scope_check(54)

Accepting User Input

Have a program accept user input and use it
Ask user for input using input() built in function
An expression is a combination of values, variables, operators, and calls to functions that evaluates to a value
Casting: convert one data type to another
- int() converts to integer
- float() converts to float
- str() converts to string

#########
# Input #
#########


# Return number of units in days as string
def days_to_units_text(num_of_days):
    return f"{num_of_days} days are {num_of_days * calculation_to_units} {name_of_unit}"

# Ask users for input and store user's input in a variable
# The input function always returns a string variable
user_input = input("Input a number of days and I will convert it to seconds\n")
print(user_input)

# To use the user_input as a number
# use casting, call the int function to convert the string to an integer
user_input_number = int(user_input)

calculated_value = days_to_units_text(user_input_number)
print(calculated_value)

Conditionals (if / else) and Boolean Data Type

When users input values, programs must validate input is valid and will not crash or cause problems in the program
Validate user input for:
- It makes sense
- Will not cause errors or crash program
- It is secure
Conditionals evaluate to true or false on statements
- They use comparison operators in Python:
  - != not equal
  - == equal
  - =< less than or equal
  - => greater than or equal
  - < less than
  - > greater than
Conditionals evaluate to a boolean that is True or False
- Use if , else =, =elif keywords
Use type() function to check the data type of a variable
Functions can be nested meaning a function can call another function

###################################################
# Conditionals (if / else) and Boolean Data Type  #
# Input validation                                #
###################################################


# Return number of units in days as string
# Validate input is a positive number
def days_to_units_text_checked(num_of_days):
    # Check if parameter is a positive number
    condition_check = num_of_days > 0
    # Print the data type of the condition_check variable
    print(type(condition_check))
    # Conditional to check if parameter is a positive number and evaluates to a boolean
    # true: parameter is a positive number
    # false: parameter is not a positive number
    if num_of_days > 0:
        return f"{num_of_days} days are {num_of_days * calculation_to_units} {name_of_unit}"
    else:
        return "Enter a positive number, other values or data types are not allowed"


checked_calculated_value = days_to_units_text_checked(user_input_number)
print(checked_calculated_value)


# Additional checking
# Return number of units in days as string
# Validate input is a positive number
def days_to_units_text_checked(num_of_days):
    # Check if parameter is a positive number
    # assumes num_of_days is an integer data type
    condition_check = num_of_days > 0

    # Print the data type of the condition_check variable
    print(type(condition_check))
    # Conditional to check if parameter is a positive number and evaluates to a boolean
    # true: parameter is a positive number
    # false: parameter is not a positive number
    if num_of_days > 0:
        return f"{num_of_days} days are {num_of_days * calculation_to_units} {name_of_unit}"
    elif num_of_days == 0:
        return "You entered a 0. Enter a positive number"
    else:
        return "You entered a negative or other data type. Enter a positive number."


# Validate input is an integer
# isdigit() method returns True if all characters in a string are digits
if user_input.isdigit():
    user_input_number = int(user_input)
    checked_calculated_value = days_to_units_text_checked(user_input_number)
    print(checked_calculated_value)
else:
    print("Your input is not a valid number. Enter a positive number.")

##################
# Cleaned up Code


def validate_and_execute():
    if user_input.isdigit():
        user_input_number = int(user_input)
        if user_input_number > 0:
            checked_calculated_value = days_to_units_text_validated(user_input_number)
            print(checked_calculated_value)
        elif user_input_number == 0:
            return "You entered a 0. Enter a positive number"
    else:
        print("Your input is not a valid number. Enter a positive number.")


# Return number of units in days as string
# Parameter num_of_days must be a postive integer
def days_to_units_text_validated(num_of_days):
    return f"{num_of_days} days are {num_of_days * calculation_to_units} {name_of_unit}"


validate_and_execute()

Error Handling with Try-Except

Error handling prevents programs from crashing
Try-Except catches any failures, capture the error and handle it in the program
Allows program to catch all possible errors
Use try and except keywords in a block. Other languages use try-catch block
Error type can be specified for all types (type is not specified)

##################################
# Error Handling with Try-Except #
##################################

def validate_and_execute_try_except():
try:
    user_input_number = int(user_input)
    if user_input_number > 0:
        calculated_value = days_to_units_text_validated(user_input_number)
        print(calculated_value)
    elif user_input_number == 0:
        print("You entered a 0. Enter a positive number")
    else:
        print("You entered a negative number. Enter a positive number.")
except ValueError:
    print("Error: Your input is not a valid number.")


validate_and_execute_try_except()

While Loops

Loops do the same thing (programming logic) multiple times
Python has 2 loop commands: while and for
- Loops use conditions which evaluate to True or False. Note Python capitalizes the booleans.
- Loops check the condition to determine whether to do the logic

###############
# While Loops #
###############

# Prepare user's input variable
# for while loop evaluation
user_input = ""
# Run continously until user inputs exit
while user_input != "exit":
    user_input = input("Enter number of days that this program will convert to hours or type exit to stop\n")
    validate_and_execute_try_except()

Lists and For Loops

Lists are a collection of things like values. Lists store multiple items in a single variable.

Lists are a Python data type and can store different data types like:

Strings
Integers
Float
Boolean (True or False)

Lists can contain duplicate values in order

Example list of integers: list_of_random_integers = [1, 3, 4, 5, 6]

# Basic list operations:
# Create
list_of_months = ["January", "February", "March"]

# List: access specific value in list, in this case first element
list_of_months[0]

# Access items of list, Get first item (January)
# with index 0
# when accesing index out of range, you will get an
# index out of range error
print(list_of_months[0])

# Add items
list_of_months.append("April")

# Remove items
list_of_months.remove("January")

# Change items
list_of_months[0] = "New January"

print(list_of_months)

For loop is used to go over a number of items
- It can be each to go over each item in a list

#############
# For Loops #
#############

# Allow user to provide a list of values
# Validate all values and return calculation
for num_of_days_elements in user_input.split(", ")
  validate_and_execute

Comments

Comments give yourself and people looking at it notes about the code:

Help explain code
Comment out code that is not needed or should not be executed and may have been used for testing, debugging, and exploring options

Single line comments in Python start with #

Multiple line comments in Python start and end with """

Good practice is to minimize comments and write code that can explain itself.

Sets

It is a list of elements but does not allow duplicate values. Used when you need unique values only.

The set does not allow access of individual elements by an index like lists, though elements can be accessed like in a for loop or the set’s functions.

########
# Sets #
########

# Set: Apply set to a given list
list_of_months = ["January", "February", "March", "January"]
# Set will only contain first 3 months, duplicate January is removed
set(list_of_months)

# Set: Create set
my_months_set = {"January", "February", "March"}

# Set: Add element
my_months_set.add("April")

# Set: Remove element
my_months_set.remove("April")

print(my_months_set)

Built-In Functions

These are functions included in Python.

#################################
# Functions, Built-in Functions #
#################################

# Print a calculation
# Define a new function called days_to_units
# function parameter is num_of_days, a local scope variable
def days_to_units_20():
    print(f"20 days are {20 * calculation_to_units} {name_of_unit}")

# Get user input
# Ask users for input and store user's input in a variable
# The input function always returns a string variable
user_input = input("Input a number of days and I will convert it to seconds\n")
print(user_input)

# Create a set from a list
set(my_list)

# Convert to integer
int("20")

# Call built-in function on data type
## String split function
"2, 3".split()
## List count
[1, 2, 3].count()

Dictionary Data Type

The final project file can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/days-to-units

Modules

The project files used in this lecture can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/modules

Project: Countdown App

The project files for this lecture can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/countdown-project

Packages, PyPI and pip

Project: Automation with Python (Spreadsheet)

The project files used in this lecture can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/automation-inventory-project

OOP: Classes and Objects

The project files can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/classes-and-objects

Project: API Request to GitLab

The files used in this project can be found here: https://gitlab.com/twn-devops-bootcamp/latest/13-programming-with-python/gitlab-api-request