Python Math: Essential Functions and Operations for Beginners

Python’s standard math module provides functions and constants for floating-point mathematics, including square roots, logarithms, trigonometry, rounding helpers, and combinatorics.

Import the Module

import math

Square Roots and Powers

print(math.sqrt(16))  # 4.0
print(math.pow(2, 3)) # 8.0
print(2 ** 3)         # 8

For ordinary exponentiation, the ** operator is usually simpler. math.pow() converts its arguments to floating point and returns a float.

Rounding Helpers

print(math.ceil(4.2))   # 5
print(math.floor(4.8))  # 4
print(math.trunc(4.8))  # 4

Python’s built-in round() serves a different purpose and follows round-to-even behavior for halfway cases:

print(round(2.5))  # 2
print(round(3.5))  # 4

Absolute Values

For most numeric types, use the built-in abs():

print(abs(-7))  # 7

math.fabs() always returns a float:

print(math.fabs(-7))  # 7.0

Useful Constants

print(math.pi)
print(math.e)
print(math.tau)
print(math.inf)

Trigonometry

The trigonometric functions use radians:

angle = math.radians(30)

print(math.sin(angle))
print(math.cos(angle))
print(math.tan(angle))

Convert back to degrees with:

print(math.degrees(math.pi / 2))  # 90.0

Logarithms and Exponentials

print(math.log(math.e))   # 1.0
print(math.log10(1000))   # 3.0
print(math.log2(8))       # 3.0
print(math.exp(1))        # e

math.log(x, base) also supports a custom base, though specialized log2() and log10() functions can provide clearer intent.

Factorials and Combinatorics

print(math.factorial(5))  # 120
print(math.comb(5, 2))    # 10
print(math.perm(5, 2))    # 20

These operate on non-negative integers under their documented constraints.

GCD and LCM

print(math.gcd(24, 36))  # 12
print(math.lcm(6, 8))    # 24

Accurate Floating-Point Summation

For many floating-point values, math.fsum() can be more numerically accurate than the built-in sum():

values = [0.1] * 10
print(math.fsum(values))

Distance and Hypotenuse

print(math.hypot(3, 4))  # 5.0
print(math.dist((0, 0), (3, 4)))  # 5.0

math Is for Real-Valued Mathematics

Most math functions expect real numbers. For complex-number operations, use cmath:

import cmath

print(cmath.sqrt(-1))  # 1j

For vectorized numerical work over arrays, NumPy is usually a better fit than repeatedly calling math functions in Python loops.

Conclusion

The math module covers common real-number mathematics without external dependencies. Use built-in operators such as ** and abs() when they express the operation directly, and reach for math when you need specialized functions, constants, combinatorics, or improved numerical routines.