# Simple Mathematical Operators
# Division
Python does integer division when both operands are integers. The behavior of Python's division operators have changed from Python 2.x and 3.x (see also Integer Division (opens new window) ).
a, b, c, d, e = 3, 2, 2.0, -3, 10
In Python 2 the result of the ' / ' operator depends on the type of the numerator and denominator.
a / b # = 1
a / c # = 1.5
d / b # = -2
b / a # = 0
d / e # = -1
Note that because both a and b are ints, the result is an int.
The result is always rounded down (floored).
Because c is a float, the result of a / c is a float.
You can also use the operator module:
import operator # the operator module provides 2-argument arithmetic functions
operator.div(a, b) # = 1
operator.__div__(a, b) # = 1
What if you want float division:
Recommended:
from __future__ import division # applies Python 3 style division to the entire module
a / b # = 1.5
a // b # = 1
Okay (if you don't want to apply to the whole module):
a / (b * 1.0) # = 1.5
1.0 * a / b # = 1.5
a / b * 1.0 # = 1.0 (careful with order of operations)
from operator import truediv
truediv(a, b) # = 1.5
Not recommended (may raise TypeError, eg if argument is complex):
float(a) / b # = 1.5
a / float(b) # = 1.5
The ' // ' operator in Python 2 forces floored division regardless of type.
a // b # = 1
a // c # = 1.0
In Python 3 the / operator performs 'true' division regardless of types. The // operator performs floor division and maintains type.
a / b # = 1.5
e / b # = 5.0
a // b # = 1
a // c # = 1.0
import operator # the operator module provides 2-argument arithmetic functions
operator.truediv(a, b) # = 1.5
operator.floordiv(a, b) # = 1
operator.floordiv(a, c) # = 1.0
Possible combinations (builtin types):
intandint(gives anintin Python 2 and afloatin Python 3)intandfloat(gives afloat)intandcomplex(gives acomplex)floatandfloat(gives afloat)floatandcomplex(gives acomplex)complexandcomplex(gives acomplex)
See PEP 238 (opens new window) for more information.
# Addition
a, b = 1, 2
# Using the "+" operator:
a + b # = 3
# Using the "in-place" "+=" operator to add and assign:
a += b # a = 3 (equivalent to a = a + b)
import operator # contains 2 argument arithmetic functions for the examples
operator.add(a, b) # = 5 since a is set to 3 right before this line
# The "+=" operator is equivalent to:
a = operator.iadd(a, b) # a = 5 since a is set to 3 right before this line
Possible combinations (builtin types):
intandint(gives anint)intandfloat(gives afloat)intandcomplex(gives acomplex)floatandfloat(gives afloat)floatandcomplex(gives acomplex)complexandcomplex(gives acomplex)
Note: the + operator is also used for concatenating strings, lists and tuples:
"first string " + "second string" # = 'first string second string'
[1, 2, 3] + [4, 5, 6] # = [1, 2, 3, 4, 5, 6]
# Exponentation
a, b = 2, 3
(a ** b) # = 8
pow(a, b) # = 8
import math
math.pow(a, b) # = 8.0 (always float; does not allow complex results)
import operator
operator.pow(a, b) # = 8
Another difference between the built-in pow and math.pow is that the built-in pow can accept three arguments:
a, b, c = 2, 3, 2
pow(2, 3, 2) # 0, calculates (2 ** 3) % 2, but as per Python docs,
# does so more efficiently
# Special functions
The function math.sqrt(x) calculates the square root of x.
import math
import cmath
c = 4
math.sqrt(c) # = 2.0 (always float; does not allow complex results)
cmath.sqrt(c) # = (2+0j) (always complex)
To compute other roots, such as a cube root, raise the number to the reciprocal of the degree of the root. This could be done with any of the exponential functions or operator.
import math
x = 8
math.pow(x, 1/3) # evaluates to 2.0
x**(1/3) # evaluates to 2.0
The function math.exp(x) computes e ** x.
math.exp(0) # 1.0
math.exp(1) # 2.718281828459045 (e)
The function math.expm1(x) computes e ** x - 1. When x is small, this gives significantly better precision than math.exp(x) - 1.
math.expm1(0) # 0.0
math.exp(1e-6) - 1 # 1.0000004999621837e-06
math.expm1(1e-6) # 1.0000005000001665e-06
# exact result # 1.000000500000166666708333341666...
# Trigonometric Functions
a, b = 1, 2
import math
math.sin(a) # returns the sine of 'a' in radians
# Out: 0.8414709848078965
math.cosh(b) # returns the inverse hyperbolic cosine of 'b' in radians
# Out: 3.7621956910836314
math.atan(math.pi) # returns the arc tangent of 'pi' in radians
# Out: 1.2626272556789115
math.hypot(a, b) # returns the Euclidean norm, same as math.sqrt(a*a + b*b)
# Out: 2.23606797749979
Note that math.hypot(x, y) is also the length of the vector (or Euclidean distance) from the origin (0, 0) to the point (x, y).
To compute the Euclidean distance between two points (x1, y1) & (x2, y2) you can use
math.hypot as follows
math.hypot(x2-x1, y2-y1)
To convert from radians -> degrees and degrees -> radians respectively use math.degrees and math.radians
math.degrees(a)
# Out: 57.29577951308232
math.radians(57.29577951308232)
# Out: 1.0
# Inplace Operations
It is common within applications to need to have code like this :
a = a + 1
or
a = a * 2
There is an effective shortcut for these in place operations :
a += 1
# and
a *= 2
Any mathematic operator can be used before the '=' character to make an inplace operation :
-=decrement the variable in place+=increment the variable in place*=multiply the variable in place/=divide the variable in place//=floor divide the variable in place # Python 3%=return the modulus of the variable in place**=raise to a power in place
Other in place operators exist for the bitwise operators (^, | etc)
# Subtraction
a, b = 1, 2
# Using the "-" operator:
b - a # = 1
import operator # contains 2 argument arithmetic functions
operator.sub(b, a) # = 1
Possible combinations (builtin types):
intandint(gives anint)intandfloat(gives afloat)intandcomplex(gives acomplex)floatandfloat(gives afloat)floatandcomplex(gives acomplex)complexandcomplex(gives acomplex)
# Multiplication
a, b = 2, 3
a * b # = 6
import operator
operator.mul(a, b) # = 6
Possible combinations (builtin types):
intandint(gives anint)intandfloat(gives afloat)intandcomplex(gives acomplex)floatandfloat(gives afloat)floatandcomplex(gives acomplex)complexandcomplex(gives acomplex)
Note: The * operator is also used for repeated concatenation of strings, lists, and tuples:
3 * 'ab' # = 'ababab'
3 * ('a', 'b') # = ('a', 'b', 'a', 'b', 'a', 'b')
# Logarithms
By default, the math.log function calculates the logarithm of a number, base e. You can optionally specify a base as the second argument.
import math
import cmath
math.log(5) # = 1.6094379124341003
# optional base argument. Default is math.e
math.log(5, math.e) # = 1.6094379124341003
cmath.log(5) # = (1.6094379124341003+0j)
math.log(1000, 10) # 3.0 (always returns float)
cmath.log(1000, 10) # (3+0j)
Special variations of the math.log function exist for different bases.
# Logarithm base e - 1 (higher precision for low values)
math.log1p(5) # = 1.791759469228055
# Logarithm base 2
math.log2(8) # = 3.0
# Logarithm base 10
math.log10(100) # = 2.0
cmath.log10(100) # = (2+0j)
# Modulus
Like in many other languages, Python uses the % operator for calculating modulus.
3 % 4 # 3
10 % 2 # 0
6 % 4 # 2
Or by using the operator module:
import operator
operator.mod(3 , 4) # 3
operator.mod(10 , 2) # 0
operator.mod(6 , 4) # 2
You can also use negative numbers.
-9 % 7 # 5
9 % -7 # -5
-9 % -7 # -2
If you need to find the result of integer division and modulus, you can use the divmod function as a shortcut:
quotient, remainder = divmod(9, 4)
# quotient = 2, remainder = 1 as 4 * 2 + 1 == 9
# Remarks
# Numerical types and their metaclasses
The numbers module contains the abstract metaclasses for the numerical types:
← Set Bitwise Operators →