Use numbers and numeric operators. See the add, multiply, subtract and divide constructs.

Numbers. It is 2 PM. It is 50 degrees F. There is a beauty in numbers. Human beings use them to describe our world. Programs too are built of numbers.

Operators. Tiny functions called operators act upon numbers. With operators and operands (the values operated upon), we make expressions and statements.

Division. We have two division operators. With one slash, we divide two numbers. And with two slashes "//" we divide and round down the result.

Operator 1: The "/" operator leaves the fractional part of the result intact. It does not matter if the two operands are fractional or not.

Operator 2: The "//" operator divides in the same way. But it also rounds the result down to the nearest integer.

Python program that divides numbers
a = 100
b = 7
# Divide 100 by 7.
print(a / b)
# Discard fractional part of result.
print(a // b)
Output
14.285714285714286
14

Integral division. This operator does not round up if the value is closer to the higher value. This means 5 // 3 will give 1, even though 5 / 3 gives 1.6, which is closer to 2 than to 1.

Python common line division
>>> 5//3
1
>>> 5/3
1.6666666666666667

Float converts data to floating-point numbers. It acts on string values (like "10.0") or integers (like 10). On strings, it handles signs (positive or negative) and infinity values ("inf").

Conversion: Float is similar to other built-ins like int or str. Python simplifies common conversions.

Python program that uses float# Float converts a string into a float number.
value = "3.14"
number = float(value)
print(number)
print(number == 3.14)
print(value == "3.14")
print()
# Float also converts an integer into a float number.
integer = 100
floating = float(integer)
print(floating)
print(integer)
Output
3.14
True
True
100.0
100

Int. Like float, int() converts from strings and other number types. It returns an integer (a number with nothing past the decimal—no fractional part).Int

Note: Int will cause an error if we try to convert a floating-point number within a string (like "123.4").

Python program that uses int# Convert a string to int.
input = "123"
result = int(input)
print(result)
# Use int to convert from floating to integral.
input = 456.9
result = int(input)
print(result)
Output
123
456

Hex converts an integer into a hexadecimal number. This form of number can be useful in interoperating with other programs and systems. We see the hex representations of 10 and 100.

Python program that uses hex# Convert this value to a hex.
value = 10
result = hex(value)
print(result)
# Convert another value.
value = 100
result = hex(value)
print(result)
Output
0xa
0x64

Octal numbers use not a base 10 like we are used to, but a base 8. So they only contain the digits 0 through 7. With oct() we convert a base 10 number into its octal representation.

Python program that uses oct# Convert 74 into octal which is 112.
number = 74
octal = oct(number)
print(octal)
Output
0o112

Bits. In computers, numbers are presented with bits, as binary. With the bin() built-in, we get a string representation of an integer. Zeros on the left of the representation are discarded.

Negative: The sign bit is represented by the 0 before the lowercase "b." A -1 has a leading minus sign.

Python program that uses bin
number = 100
# Convert this number to a binary string.
result = bin(number)
print(result)
Output
0b1100100
More bin examples
bin(-1) -0b1
bin(0) 0b0

Complex. Complexity is not just in our computer programs. We also encounter complex numbers. These numbers have two components—real and imaginary.

Imaginary unit: Complex numbers include an "imaginary unit" that is separate from the real parts. These numbers never become bored.

Info: In Python we have the complex() built-in function. These numbers can be added, subtracted, and manipulated in other ways.

Python program that uses complex numbers# Create two complex numbers.
complexA = complex(3, 10)
complexB = complex(5, 15)
# Add the two together.
# ... The result is also complex.
complexC = complexA + complexB
print(complexC)
Output
(8+25j)

Benchmark, division. Division is a slow operation on processors. In Python we have both the "/" and "//" operators. Is there some optimization in the latter one? My benchmark tests this.

Version 1: This version of the code uses the single-slash operator to perform a division.

Version 2: Here we use the double-slash operator to perform division and get an integer-only result.

Result: We find that the "//" operator is slower than the "/" operator. It adds steps beyond the regular operator.

Python program that times division
import time
a = 1000
b = 223
c = 0
print (time.time())
# Version 1: normal division
i = 0
while i < 10000000:
c = a / b
i += 1
print (time.time())
# Version 2: integer result division
i = 0
while i < 10000000:
c = a // b
i += 1
print (time.time())
Output
1345843075.764
1345843077.922 (/ = 2.158 s)
1345843080.448 (// = 2.526 s)

Divmod, modulo. The divmod function is built into the Python language. It computes two kinds of division at once: it does an integral division and a modulo division. It returns a tuple.Divmod

Random numbers can be generated in Python with the randint method. But for a random selection in a list or other collection, random.choice is an ideal option.Random

Pow. The pow built-in, or two asterisks, means exponentiation. We can raise a number to a certain power with clear syntax. The two syntax forms are equivalent.pow

Bool converts an expression into True or False. It is similar to the if-statement, which also evaluates expressions. Bool is a value—often languages store False as 0 and True as 1.bool

Is a number prime? We implement a prime-testing method with a def and a for-loop. Some arithmetic optimizations are applied to this method—we test the number's square.Prime Number

Numeric operations are everywhere. All memory accesses in programs use numeric computations. An access to an element of a list, at an index, requires multiplications to locate memory.

Compilers handle these. A simple program is an illusion. All programs involve complex numeric computation. All levels of programming, from the metal to object models, are numeric.