Lecture 8 – Modules and Packages in Python (import, pip, libraries, virtual environments)

How Python modules and packages work in Lecture 8. Understand import statements, pip installations, built-in modules, external libraries, and virtual environments with examples, MCQs, and practice problems.

What You Will Learn Today

By the end of this lecture, you will understand:

What modules and packages are
How to import modules
Built-in Python modules
Installing external packages using pip
Understanding virtual environments
How to create your own modules
How to use Python packages in Data Science
MCQs + practice tasks

1) What Are Modules?

A module is simply a Python file containing:

• Functions
• Variables
• Classes

Examples of modules:
math, datetime, random, os, json

Using modules allows you to reuse code instead of writing everything from scratch.

2) Importing Modules

Basic import:

import math
print(math.sqrt(25))

Import specific function:

from math import sqrt
print(sqrt(25))

Import with alias:

import math as m
print(m.pi)

Lecture 7 – Lambda, Map, Filter, Reduce

3) Built-in Python Modules (With Examples)

datetime – Working with date/time

import datetime
today = datetime.date.today()
print(today)

random Generate random values

import random
print(random.randint(1, 100))

statistics – Data analysis

import statistics
nums = [10, 20, 30]
print(statistics.mean(nums))

os – Access system commands

import os
print(os.getcwd())

json – Convert Python ↔ JSON

import json
student = {"name": "Ali", "age": 20}
print(json.dumps(student))

4) What Are Packages?

A package is a collection of multiple modules stored inside a folder with an __init__.py file.

Examples of famous Python packages:

• NumPy → mathematical operations
• Pandas → data analysis
• Matplotlib → visualizations
• Requests → APIs
• TensorFlow / PyTorch → deep learning

5) Installing Packages Using pip

pip = Python package installer.

Install:

pip install numpy

Upgrade:

pip install --upgrade numpy

Uninstall:

pip uninstall numpy

Check version:

pip show numpy

6) Importing Packages

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

7) Real Data Science Examples

Example 1 – Using NumPy

import numpy as np

arr = np.array([1, 2, 3, 4])
print(arr * 2)

Example 2 – Using Pandas

import pandas as pd

data = {"name": ["Ali", "Sara"], "score": [90, 85]}
df = pd.DataFrame(data)
print(df)

Example 3 – Using Matplotlib

import matplotlib.pyplot as plt

plt.plot([1,2,3], [2,4,6])
plt.show()

Example 4 – Using Requests to call API

import requests

response = requests.get("https://api.github.com")
print(response.status_code)

Example 5 – Using OS to automate files

import os

files = os.listdir()
print(files)

The Python Tutorial Documentation

8) Creating Your Own Module

Step 1: Create a Python file

mymath.py

def add(a, b):
    return a + b

Step 2: Import it

import mymath
print(mymath.add(3, 4))

9) Understanding Virtual Environments (Important!)

A virtual environment keeps project packages separate.

Create:

python -m venv myenv

Activate (Windows):

myenv\Scripts\activate

Activate (Mac/Linux):

source myenv/bin/activate

Install packages inside it:

pip install numpy

Deactivate:

deactivate

A module in Python is:

a) A file
b) A package
c) A class
d) A folder

Answer: a) A file

Which command installs a package?

a) install package numpy
b) python install numpy
c) pip install numpy
d) import numpy

Answer: c) pip install numpy

What will this print?

import math
print(math.pi)

Answer: 3.141592653589793

What is required for a folder to be considered a package?

a) readme.txt
b) init.py
c) requirements.txt
d) activate.bat

Answer: b) init.py

Next Lecture 9 – Object-Oriented Programming

import random
print(random.randint(1, 10))

def hello():
    print("Welcome to ElecturesAI")

pip install pandas
import pandas as pd

import json
print(json.dumps({"name": "Ali", "age": 20}))

import os
print(os.listdir())