Ch5. Python — Standard Library & Package Management

datetime: Date and Time

from datetime import datetime, timedelta, date

# Current date/time
now = datetime.now()
print(now)  # 2026-05-26 14:30:15.123456

# Format output
print(now.strftime("%B %d, %Y"))  # May 26, 2026
print(now.strftime("%Y-%m-%d"))   # 2026-05-26

# Date arithmetic
tomorrow = now + timedelta(days=1)
next_week = now + timedelta(weeks=1)

# Difference between dates
date1 = date(2024, 1, 1)
date2 = date(2026, 5, 26)
diff = date2 - date1
print(f"{diff.days} days apart")  # 876 days apart

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os: Operating System Interface

import os

# Current working directory
print(os.getcwd())

# List directory contents
files = os.listdir(".")

# Create directories
os.makedirs("data/outputs", exist_ok=True)

# Environment variables
api_key = os.environ.get("API_KEY", "default_value")

# Path operations
path = os.path.join("data", "results.csv")
print(os.path.exists(path))      # File exists?
print(os.path.basename(path))    # results.csv
print(os.path.dirname(path))     # data

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random: Random Number Generation

import random

print(random.randint(1, 100))    # Random integer 1-100
print(random.random())           # Random float 0.0-1.0

items = ["apple", "banana", "cherry", "mango"]
print(random.choice(items))      # Random single item
print(random.sample(items, 2))   # 2 unique random items

random.shuffle(items)             # Shuffle in place
print(items)

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collections: Advanced Data Structures

from collections import Counter, defaultdict, deque

# Counter: count element frequencies
text = "hello world python programming"
word_count = Counter(text.split())
print(word_count.most_common(3))

# defaultdict: auto-create missing keys
grades = defaultdict(list)
grades["Alice"].append(90)
grades["Alice"].append(85)

# deque: double-ended queue
queue = deque([1, 2, 3])
queue.appendleft(0)   # Add to left
queue.append(4)       # Add to right
queue.popleft()       # Remove from left

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pip: Package Management

# Install packages
pip install requests
pip install pandas numpy matplotlib

# Install specific version
pip install requests==2.31.0

# List installed packages
pip list

# Save requirements
pip freeze > requirements.txt

# Install from requirements
pip install -r requirements.txt

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Virtual Environments

# Create virtual environment
python -m venv myenv

# Activate (Windows)
myenv\Scripts\activate

# Activate (Mac/Linux)
source myenv/bin/activate

# Deactivate
deactivate

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Next: Data Analysis Basics — pandas and NumPy for data manipulation, matplotlib for visualization.