# Importing the necessary module "setuptools" from the package "setuptools"
from setuptools import setup, find_packages

# Setting up the setup function with the necessary parameters
setup(
    # Defining the name of the package
    name='my_awesome_library',
    # Defining the version of the package
    version='1.0',
    # Finding all the packages within the root directory of the library
    packages=find_packages()
)

# Adding a comment to explain the purpose of the script
# This script is used to create a setup.py file for a Python library, which is necessary for managing dependencies and installing the library.

# Importing the necessary module "pip" from the package "setuptools"
from setuptools import setup, find_packages

# Setting up the setup function with the necessary parameters
setup(
    # Defining the name of the package
    name='my_awesome_library',
    # Defining the version of the package
    version='1.0',
    # Finding all the packages within the root directory of the library
    packages=find_packages()
)

# Adding a comment to explain the purpose of the script
# This script is used to create a setup.py file for a Python library, which is necessary for managing dependencies and installing the library.

# Adding a comment to explain the purpose of the pip package installer
# Pip is a package installer for Python that helps manage dependencies for a project.

# Adding a comment to explain how to use pip
# To use pip, you can add "pip install <package>" to your command line or create a requirements.txt file with all of your project's dependencies and then run "pip install -r requirements.txt".

# Adding a comment to explain how to add dependencies to a requirements.txt file
# To add dependencies to a requirements.txt file, you can list them one per line, using the format "<package>==<version>" if you want to specify a specific version of the package.

# Importing the pandas library and assigning it to the variable "pd"
import pandas as pd

# Setting the version of pandas to 1.0.5
pd.__version__ = "1.0.5"

# flake8 is a linter and code formatter for Python
# It is used to catch common coding mistakes before they become bigger problems
# To use it, we can add "flake8" to our command line or create a .flake8 file with configuration options

# Example: Setting a maximum line length of 100 characters in our code
# We can add this to our .flake8 file

# Importing the pandas library and assigning it to the variable "pd"
import pandas as pd

# Setting the version of pandas to 1.0.5
pd.__version__ = "1.0.5"

# flake8 is a linter and code formatter for Python
# It is used to catch common coding mistakes before they become bigger problems
# To use it, we can add "flake8" to our command line or create a .flake8 file with configuration options

# Example: Setting a maximum line length of 100 characters in our code
# We can add this to our .flake8 file by specifying the maximum line length as 100 characters.

# This script is used to demonstrate how to use the coverage tool for measuring test coverage in Python.

# Import the coverage module
import coverage

# Create a coverage object
cov = coverage.Coverage()

# Start measuring coverage
cov.start()

# Define a function to calculate the area of a rectangle
def calculate_area(length, width):
    """
    Calculates the area of a rectangle given its length and width.
    :param length: the length of the rectangle
    :param width: the width of the rectangle
    :return: the area of the rectangle
    """
    return length * width

# Define a function to calculate the perimeter of a rectangle
def calculate_perimeter(length, width):
    """
    Calculates the perimeter of a rectangle given its length and width.
    :param length: the length of the rectangle
    :param width: the width of the rectangle
    :return: the perimeter of the rectangle
    """
    return 2 * (length + width)

# Stop measuring coverage
cov.stop()

# Save the coverage data to a file
cov.save()

# Generate a report of the coverage data
cov.report()

# Exclude certain files from being covered by the tool (like test fixtures)
cov.exclude("test_fixtures/*")

# Generate an HTML report of the coverage data
cov.html_report()

# Print a message indicating the completion of the script
print("Coverage measurement and reporting completed.")

# Importing the pytest library for testing
import pytest

# Defining a function to test
def add(x, y):
    return x + y

# Creating a test case using the pytest syntax
def test_add():
    # Asserting that the add function returns the correct result
    assert add(2, 3) == 5

# Adding a configuration option to run tests in parallel
# This will speed up the testing process
# Note: This code segment is not necessary for the script to function, but it is a helpful configuration option for running tests
[pytest]
addopts = -n auto

# Running the test case using the pytest command line
# Note: This code segment is not necessary for the script to function, but it is a helpful way to run tests
# You can also run tests using other tools like coverage
# Example: pytest --cov=my_module tests/
# This will provide more detailed reporting on test coverage
# Note: The "tests/" at the end specifies the directory where the tests are located
# If your tests are in a different directory, you will need to specify the correct path
# Example: pytest --cov=my_module my_tests/
# This will run tests in the "my_tests" directory
pytest tests/