Python's built-in libraries

Compute a factorial, find today's date, shuffle a list, read JSON — none of this needs anything installed. It already ships with Python out of the box: dozens of ready-made modules available right after an import, with no pip install. This is the standard (built-in) library.

What are built-in libraries?

The main built-in libraries

Let's go through several of the most useful built-in libraries in Python.

math: mathematical functions

The math module provides access to mathematical functions defined in the C language standard:

Python 3.13
1234
import math

# Constants
print(f"Number π: {math.pi}")
Number π: 3.141592653589793
5
print(f"Number e: {math.e}")
Number e: 2.718281828459045
678
# Trigonometric functions
angle = math.pi / 4  # 45 degrees in radians
print(f"Sine of 45°: {math.sin(angle):.4f}")
Sine of 45°: 0.7071
9
print(f"Cosine of 45°: {math.cos(angle):.4f}")
Cosine of 45°: 0.7071
1011
# Other functions
print(f"Factorial of 5: {math.factorial(5)}")
Factorial of 5: 120
12
print(f"Greatest common divisor of 12 and 18: {math.gcd(12, 18)}")
Greatest common divisor of 12 and 18: 6

random: generating random numbers

The random module provides functions for generating random numbers and picking random elements:

Python 3.13
1234
import random

# Generating a random integer in a range
print(f"Random number between 1 and 10: {random.randint(1, 10)}")
Random number between 1 and 10: 7
56
# Random float between 0 and 1
print(f"Random number between 0 and 1: {random.random():.4f}")
Random number between 0 and 1: 0.3528
789
# Picking a random element from a sequence
fruits = ["apple", "banana", "orange", "pear"]
print(f"Random fruit: {random.choice(fruits)}")
Random fruit: orange
10111213
# Shuffling a sequence
numbers = [1, 2, 3, 4, 5]
random.shuffle(numbers)
print(f"Shuffled numbers: {numbers}")
Shuffled numbers: [3, 1, 5, 2, 4]

datetime: dates and times

The datetime module can parse dates from strings, add intervals to them, and format them back. That set is enough for typical date operations:

Python 3.13
12345678910
from datetime import datetime, timedelta

# parse a string into a date using the "day.month.year" pattern
d = datetime.strptime("31.12.2022", "%d.%m.%Y")

# add an interval
new_d = d + timedelta(days=5)

# format the date back into a string
print(new_d.strftime("%d.%m.%Y"))
05.01.2023

This is just the tip of the iceberg — datetime can do a lot more, and it has its own chapter, "Working with dates and times", later in the module.

Two more big standard-library topics have chapters of their own, so here we'll just name the modules:

But collections didn't get its own chapter, so let's look at it right now.

collections: specialised data types

The collections module provides several convenient data structures on top of the built-in ones. One of the most useful is Counter for counting elements:

Python 3.13
1234567
from collections import Counter

orders = ["apple", "banana", "apple", "cherry", "apple", "banana"]
counts = Counter(orders)

# most_common() sorts by count, highest first
print(counts.most_common())
[('apple', 3), ('banana', 2), ('cherry', 1)]

The module also has defaultdict, namedtuple, deque and others, advanced tools that will come in handy later.

Understanding check

Which library is best suited for working with dates in Python?

In the next lesson we'll look at third-party libraries, the ones installed via pip install that extend Python beyond the standard distribution.