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Using packages

Python packages add new functionality to your programs. There are two types:
  • Built-in: Come with Python (no installation needed)
  • External: Need to install first with pip

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Understanding the terminology

Let’s clarify what these terms mean:
  • Module: A single Python file (like math.py)
  • Package: A folder containing multiple modules
  • Function: A reusable block of code (like print() or sqrt())
  • Class: A blueprint for creating objects (we’ll cover this later)
Think of it like this:
  • A module is like a toolbox
  • A package is like a garage with multiple toolboxes
  • A function is like a specific tool (hammer, screwdriver)
  • A class is like a blueprint for building tools

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Import patterns explained

# Pattern 1: Import the whole module
import math
# Now use: math.sqrt(16)

# Pattern 2: Import specific items from a module
from math import sqrt, pi
# Now use: sqrt(16)
What’s happening:
  • import math - brings in the entire math toolbox
  • from math import sqrt - takes just the sqrt tool from the math toolbox

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Built-in modules

Python includes many useful modules: 
# Import entire module
import random

# Use module functions
number = random.randint(1, 10)
choice = random.choice(["apple", "banana", "orange"])

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Common built-in modules

# Date and time
import datetime
today = datetime.date.today()
print(today)  # 2024-01-15

# Operating system
import os
current_dir = os.getcwd()
print(current_dir)

# JSON data
import json
data = {"name": "Alice", "age": 30}
json_string = json.dumps(data)

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Import methods

Different ways to import: 
# Import entire module
import math
result = math.sqrt(16)

# Import specific functions
from math import sqrt, pi
result = sqrt(16)
circle_area = pi * radius ** 2

# Import with alias
import pandas as pd
df = pd.DataFrame(data)

# Import everything (avoid this!)
from math import *
Avoid from module import * as it can cause naming conflicts and makes code harder to understand.

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Installing packages

External packages need installation: 
# Install a package
pip install requests

# Install specific version
pip install requests==2.28.0

# Install multiple packages
pip install pandas numpy matplotlib
Always ensure your virtual environment is activated before installing! This is the #1 source of import errors. If you get “ModuleNotFoundError” after installing, you probably installed to the wrong environment. Learn more about virtual environments.

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Sharing your project: requirements.txt

When you share your Python project, others need to know which packages to install. The standard way is using a requirements.txt file:

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Creating requirements.txt

List all your project’s packages: 
pip freeze > requirements.txt
This creates a file like: 
certifi==2024.2.2
charset-normalizer==3.3.2
idna==3.6
requests==2.31.0
urllib3==2.2.0

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Installing from requirements.txt

When someone gets your project, they run: 
pip install -r requirements.txt
This installs all the packages at once!
Later in the course, we’ll learn about uv - a modern, faster alternative to pip that makes package management even easier.

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Using external packages

After installation, import and use: 
# Web requests
import requests

response = requests.get("https://api.example.com/data")
data = response.json()

# Data analysis
import pandas as pd

# Create a simple DataFrame
data = {
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 30, 35],
    'city': ['NYC', 'LA', 'Chicago']
}
df = pd.DataFrame(data)
print(df)
Always use virtual environments for projects. They prevent package conflicts between different projects.

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Finding packages

Where to find packages:
  • PyPI - Official Python package index
  • Awesome Python - Curated list
  • ChatGPT - Ask “What Python package should I use for [task]?” - Great for recommendations and comparisons
  • Google “Python package for [task]”
ChatGPT is excellent for finding packages. Try asking: “What’s the best Python package for reading Excel files?” or “Compare pandas vs polars for data analysis.” It can explain which package to use and why.

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Common mistakes

# Wrong - package not installed or venv not activated
import pandas  # ModuleNotFoundError

# Right - install first
# Run: pip install pandas
import pandas

# Wrong - overwrites built-in
import datetime
datetime = "2024-01-01"  # Now module is gone!

# Right - use different names
import datetime
date_string = "2024-01-01"

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What’s next?

Learn to connect to APIs and fetch data from the internet!

Working with APIs

Connect to online services