Import packages

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

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

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

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"])

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)

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.

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.

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

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

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.

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.

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.

Common mistakes

Import errors

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

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

Name conflicts

# 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"

What’s next?

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

Working with APIs

Connect to online services

Functions

External tools

Practical Python

Error handling

Classes

Using packages

Understanding the terminology

Import patterns explained

Built-in modules

Common built-in modules

Import methods

Installing packages

Creating requirements.txt

Installing from requirements.txt

Using external packages

Finding packages

Common mistakes

What’s next?

Working with APIs

​Using packages

​Understanding the terminology

​Import patterns explained

​Built-in modules

​Common built-in modules

​Import methods

​Installing packages

​Sharing your project: requirements.txt

​Creating requirements.txt

​Installing from requirements.txt

​Using external packages

​Finding packages

​Common mistakes

​What’s next?

Working with APIs

Using packages

Understanding the terminology

Import patterns explained

Built-in modules

Common built-in modules

Import methods

Installing packages

Sharing your project: requirements.txt

Creating requirements.txt

Installing from requirements.txt

Using external packages

Finding packages

Common mistakes

What’s next?