- 2.1 Program Output, the print Statement, and Hello World!
- 2.2 Program Input and the raw_input()Built-in Function
- 2.3 Comments
- 2.4 Operators
- 2.5 Variables and Assignment
- 2.6 Numbers
- 2.7 Strings
- 2.8 Lists and Tuples
- 2.9 Dictionaries
- 2.10 Code Blocks Use Indentation
- 2.11 if Statement
- 2.12 while Loop
- 2.13 for Loop and the range() Built-in Function
- 2.14 List Comprehensions
- 2.15 Files and the open() and file() Built-in Functions
- 2.16 Errors and Exceptions
- 2.17 Functions
- 2.18 Classes
- 2.19 Modules
- 2.20 Useful Functions
- 2.21 Exercises
Python supports five basic numerical types, three of which are integer types.
- int (signed integers)
- long (long integers)
- bool (Boolean values)
- float (floating point real numbers)
- complex (complex numbers)
Here are some examples:
int 0101 84 -237 0x80 017 -680 -0X92 long 29979062458L -84140l 0xDECADEDEADBEEFBADFEEDDEAL bool True False float 3.14159 4.2E-10 -90. 6.022e23 -1.609E-19 complex 6.23+1.5j -1.23-875J 0+1j 9.80665-8.31441J -.0224+0j
Numeric types of interest are the Python long and complex types. Python long integers should not be confused with C longs. Python longs have a capacity that surpasses any C long. You are limited only by the amount of (virtual) memory in your system as far as range is concerned. If you are familiar with Java, a Python long is similar to numbers of the BigInteger class type.
Moving forward, ints and longs are in the process of becoming unified into a single integer type. Beginning in version 2.3, overflow errors are no longer reported—the result is automagically converted to a long. In a future version of Python, the distinction will be seamless because the trailing “L” will no longer be used or required.
Boolean values are a special case of integer. Although represented by the constants True and False, if put in a numeric context such as addition with other numbers, True is treated as the integer with value 1, and False has a value of 0.
Complex numbers (numbers that involve the square root of -1, so-called “imaginary” numbers) are not supported in many languages and perhaps are implemented only as classes in others.
There is also a sixth numeric type, decimal, for decimal floating numbers, but it is not a built-in type. You must import the decimal module to use these types of numbers. They were added to Python (version 2.4) because of a need for more accuracy. For example, the number 1.1 cannot be accurately representing with binary floating point numbers (floats) because it has a repeating fraction in binary. Because of this, numbers like 1.1 look like this as a float:
>>> 1.1 1.1000000000000001 >>> print decimal.Decimal('1.1') 1.1
All numeric types are covered in Chapter 5.