Learning Python - Mark Lutz [78]
Coding other numeric types
As we’ll see later in this chapter, there are additional, more advanced number types not included in Table 5-1. Some of these are created by calling functions in imported modules (e.g., decimals and fractions), and others have literal syntax all their own (e.g., sets).
Built-in Numeric Tools
Besides the built-in number literals shown in Table 5-1, Python provides a set of tools for processing number objects:
Expression operators
+, -, *, /, >>, **, &, etc.
Built-in mathematical functions
pow, abs, round, int, hex, bin, etc.
Utility modules
random, math, etc.
We’ll meet all of these as we go along.
Although numbers are primarily processed with expressions, built-ins, and modules, they also have a handful of type-specific methods today, which we’ll meet in this chapter as well. Floating-point numbers, for example, have an as_integer_ratio method that is useful for the fraction number type, and an is_integer method to test if the number is an integer. Integers have various attributes, including a new bit_length method in the upcoming Python 3.1 release that gives the number of bits necessary to represent the object’s value. Moreover, as part collection and part number, sets also support both methods and expressions.
Since expressions are the most essential tool for most number types, though, let’s turn to them next.
Python Expression Operators
Perhaps the most fundamental tool that processes numbers is the expression: a combination of numbers (or other objects) and operators that computes a value when executed by Python. In Python, expressions are written using the usual mathematical notation and operator symbols. For instance, to add two numbers X and Y you would say X + Y, which tells Python to apply the + operator to the values named by X and Y. The result of the expression is the sum of X and Y, another number object.
Table 5-2 lists all the operator expressions available in Python. Many are self-explanatory; for instance, the usual mathematical operators (+, −, *, /, and so on) are supported. A few will be familiar if you’ve used other languages in the past: % computes a division remainder, << performs a bitwise left-shift, & computes a bitwise AND result, and so on. Others are more Python-specific, and not all are numeric in nature: for example, the is operator tests object identity (i.e., address in memory, a strict form of equality), and lambda creates unnamed functions.
Table 5-2. Python expression operators and precedence
Operators
Description
yield x
Generator function send protocol
lambda args: expression
Anonymous function generation
x if y else z
Ternary selection (x is evaluated only if y is true)
x or y
Logical OR (y is evaluated only if x is false)
x and y
Logical AND (y is evaluated only if x is true)
not x
Logical negation
x in y, x not in y
Membership (iterables, sets)
x is y, x is not y
Object identity tests
x < y, x <= y, x > y, x >= y
x == y, x != y
Magnitude comparison, set subset and superset;
Value equality operators
x | y
Bitwise OR, set union
x ^ y
Bitwise XOR, set symmetric difference
x & y
Bitwise AND, set intersection
x << y, x >> y
Shift x left or right by y bits
x + y
x – y
Addition, concatenation;
Subtraction, set difference
x * y
x % y
x / y, x // y
Multiplication, repetition;
Remainder, format;
Division: true and floor
−x, +x
Negation, identity
˜x
Bitwise NOT (inversion)
x ** y
Power (exponentiation)
x[i]
Indexing (sequence, mapping, others)
x[i:j:k]
Slicing
x(...)
Call (function, method, class, other callable)
x.attr
Attribute reference
(...)
Tuple, expression, generator expression
[...]
List, list comprehension
{...}
Dictionary, set, set and dictionary