Working with Libraries & Next Steps

Popular Third-Party Libraries

Data Science & Analysis

import numpy as np           # Numerical computing
import pandas as pd          # Data manipulation and analysis
import matplotlib.pyplot as plt  # Plotting and visualization
import scipy                 # Scientific computing

Web Development

import requests              # HTTP client — make API calls
# import flask               # Web framework (micro)
# import django              # Web framework (full-featured)
# import fastapi             # async API framework

Common Patterns

import requests

response = requests.get("https://api.github.com")
if response.status_code == 200:
    data = response.json()
    print(f"Found {len(data)} items")

Project Structure

A well-organized Python project:

my_project/
  README.md
  requirements.txt
  pyproject.toml
  src/
    my_package/
      __init__.py
      module_a.py
      module_b.py
  tests/
    test_module_a.py
    test_module_b.py

if name == “main”

# my_script.py
def main():
    print("Running as a script")

if __name__ == "__main__":
    main()

This block runs only when the file is executed directly (not imported).

Writing Idiomatic Python

Use enumerate instead of range(len())

# Bad
for i in range(len(fruits)):
    print(fruits[i])

# Good
for i, fruit in enumerate(fruits):
    print(f"{i}: {fruit}")

Use zip to iterate in parallel

names = ["Alice", "Bob", "Charlie"]
scores = [85, 92, 78]
for name, score in zip(names, scores):
    print(f"{name}: {score}")

Use in for membership testing

# Bad
if fruit.find("apple") != -1:

# Good
if "apple" in fruit:

Use context managers

# Bad
f = open("file.txt")
data = f.read()
f.close()

# Good
with open("file.txt") as f:
    data = f.read()

Use pathlib over os.path

# Bad
import os
path = os.path.join("data", "config.json")

# Good
from pathlib import Path
path = Path("data") / "config.json"

Resources for Continued Learning

Resource	Description
Python Docs	Official documentation and tutorials
Real Python	In-depth tutorials and articles
PyPI	Python Package Index — find any library
Python Crash Course	Book by Eric Matthes
Exercism Python Track	Practice with mentor feedback

Final Advice

• Write code every day — even 15 minutes of practice compounds.
• Read other people’s code — GitHub is your library.
• Build projects — the fastest way to learn is to build something real.
• Embrace errors — every traceback is a learning opportunity.
• Python’s community is welcoming — ask questions on Stack Overflow, Reddit r/learnpython, or Python Discord.

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