Python is a dynamically typed language. The interpreter infers the data type of a value based on pre-determined rules. In the previous chapter, string values were coded using single quotes around a sequence of characters. Similarly, there are rules by which you can declare different numeric data types.
Integer numbers are made up of digits
9 and can be prefixed with unary operators like
-. There is no restriction to the size of numbers that can be used, only limited by the memory available on your system. Here's some examples:
>>> 42 42 >>> 0 0 >>> +100 100 >>> -5 -5
For readability purposes, you can use underscores in between the digits.
>>> 1_000_000_000 1000000000
Underscore cannot be used as the first or last character, and cannot be used consecutively.
Here's some examples for floating-point numbers.
>>> 3.14 3.14 >>> -1.12 -1.12
Python also supports the exponential notation. See wikipedia: E scientific notation for details about this form of expressing numbers.
>>> 543.15e20 5.4315e+22 >>> 1.5e-5 1.5e-05
Unlike integers, floating-point numbers have a limited precision. Python will automatically convert very small or very large floating-point numbers to the exponential notation.
>>> 0.0000000001234567890123456789 1.2345678901234568e-10 >>> 31415926535897935809629384623048923.649234324234 3.1415926535897936e+34
You might also get seemingly strange results as shown below. See docs.python: Floating Point Arithmetic Issues and Limitations and stackoverflow: Is floating point math broken? for details and workarounds.
>>> 3.14 + 2 5.140000000000001
All arithmetic operators you'd typically expect are available. If any operand is a floating-point number, result will be of
float data type. Use
+ for addition,
- for subtraction,
* for multiplication and
** for exponentiation. As mentioned before, REPL is quite useful for learning purposes. It makes for a good calculator for number crunching as well. You can also use
_ to refer to the result of the previous expression (this is applicable only in the REPL, not in Python scripts).
>>> 25 + 17 42 >>> 10 - 8 2 >>> 25 * 3.3 82.5 >>> 32 ** 42 1645504557321206042154969182557350504982735865633579863348609024 >>> 5 + 2 7 >>> _ * 3 21
There are two operators for division. Use
/ if you want a floating-point result. Using
// between two integers will give only the integer portion of the result (no rounding).
>>> 4.5 / 1.5 3.0 >>> 5 / 3 1.6666666666666667 >>> 5 // 3 1
Use modulo operator
% to get the remainder. Sign of the result is same as the sign of the second operand.
>>> 5 % 3 2 >>> -5 % 3 1 >>> 5 % -3 -1 >>> 6.5 % -3 -2.5
See docs.python: Binary arithmetic operations and stackoverflow: modulo operation on negative numbers for more details.
Arithmetic operator precedence follows the familiar PEMDAS or BODMAS abbreviations. Precedence, higher to lower is listed below:
- Expression inside parentheses
- multiplication, division, modulo
- addition, subtraction
Expression is evaluated left-to-right when operators have the same precedence. Unary operator precedence is between exponentiation and multiplication/division operators. See docs.python: Operator precedence for complete details.
The integer examples so far have been coded using base 10, i.e. decimal format. Python has provision for representing binary, octal and hexadecimal formats as well. To distinguish between these different formats, a prefix is used.
All four formats fall under the
int data type. Underscores can be used for readability for any of these formats.
>>> 0b1000_1111 143 >>> 0o10 8 >>> 0x10 16 >>> 5 + 0xa 15
As a consequence, decimal format numbers cannot be prefixed by
0, other than
>>> 00000 0 >>> 09 File "<stdin>", line 1 09 ^ SyntaxError: leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers
If code execution hits a snag, you'll get an error message along with the code snippet that the interpreter thinks caused the issue. In Python parlance, an exception has occurred. The exception has a name (
SyntaxError in the above example) followed by the error message.
Other numeric types
Python's standard data type also includes complex type (imaginary part is suffixed with the character
j). Others like
fractions are provided as modules.
Some of the numeric types can have alphabets like
j, etc in their values. As Python is a dynamically typed language, you cannot use variable names beginning with a number. Otherwise, it would be impossible to evaluate an expression like
result = initial_value + 0x12 - 2j.
There are many third-party libraries that are useful for number crunching in mathematical context, engineering applications, etc. See my list py_resources: Scientific computing for curated resources.
Top comments (0)