Keeping Up with Python: the 2.2 Release

Python 2.2 resolves some well known deficiencies of the language and introduces some new powerful constructs that are key strengths of other object-oriented languages.
Floor Division

A new divisor operator ( // ) has been created that always truncates the fraction and rounds it to the next smallest whole number toward the left on the number line, regardless of the operands' numeric types. This operator works starting in 2.2 and does not require the __future__ directive above.

>>> 1 // 2          # floors result, returns integer
0
>>> 1.0 // 2.0      # floors result, returns float
0.0
>>> -1 // 2         # move left on number line
-1

Without getting into the arguments of this change, the feeling is that perhaps Python's division operator has been flawed since the beginning, especially because Python is a strong choice as a first programming language for people who aren't used to floor division. One of the examples Guido uses in his “What's New in Python 2.2” ZPUG talk is:

def velocity(distance, totalTime):
    rate = distance / totalTime
This is bad because this function is not numeric-type-independent. Your results with a pair of floats certainly differs from that of sending in a pair of integers. To bridge the dichotomy, you must resolve the following intransitivity in your head:
>>> 1 == 1.0
1
>>> 2 == 2.0
1
>>> 1 / 2 == 1.0 / 2.0            # classic division
0
If you use Python's new model of division, the universe is at peace once again:
>>> from __future__ import division
>>> 1 / 2 == 1.0 / 2.0            # true division
1
>>> 1 // 2 == 1.0 // 2.0          # floor division
1
While this seems like the proper and right thing to do, one cannot help but be concerned with the code breakage it may lead to. Fortunately, the Python developers have kept this in mind, as this change will not be permanent until Python 3.0, which is still years away. Those who desire the new division can import it or start Python with the -Qnew command-line option. There are a few options to turn on warnings to prepare for the upcoming new division.

You can get more information from PEP 238, but dig through the comp.lang.python archives for the heated debates. Table 2 summarizes the division operators in the various releases of Python and the differences in operation when you import division (from __future__).

Table 2. Division Operator Summary

Merging Types and Classes

Merging Python types and classes has been on the want list for quite a while. Programmers are dismayed to discover that they cannot subclass existing data types, such as a list, to customize for their applications.

To learn more, it can't hurt to look through both the PEPs involved and a tutorial Guido wrote specifically for those who want to get up to speed quickly on the new style classes without having to wade through all the intricate details found in the PEPs (see Resources). We will also give you a teaser class that extends a Python list with enhanced stack features.

This example, stack2.py, is motivated by one of the iterator examples above (see also Example 6.2 at the Core Python Programming web site).

#!/bin/env python
'stack2.py -- subclasses and extends a list'
class Stack(list):
  def __init__(self, *args):
      list.__init__(self, args)   # call base class
                                  # constructor
  def push(self, *args):
      for eachItem in args:       # can push multiple
          self.append(eachItem)   # items
  def pop(self, n=1):
      if n == 1:                  # pop single item
          return list.pop(self)
      else:                       # pop multiple items
          return [ list.pop(self) for i in range(n) ]

Below is the output we get from flexing our newfound capabilities:

>>> from stack2 import Stack
>>> m = Stack(123, 'xyz')
>>> m
[123, 'xyz']
>>> m.push(4.5)
>>> m
[123, 'xyz', 4.5]
>>> m.push(1+2j, 'abc')
>>> m
[123, 'xyz', 4.5, (1+2j), 'abc']
>>> m.pop()
'abc'
>>> m.pop(3)
[(1+2j), 4.5, 'xyz']
>>> m
[123]
In addition to being able to subclass built-in types, other highlights of the new style classes include:
  • “Cast” functions being factories.

  • New __class__, __dict__, and __bases__ attributes.

  • __getattribute__() Special Method (smarter than __getattr__()).

  • Class descriptors.

  • Class properties.

  • Static methods.

  • Class methods.

  • Superclass method calls.

  • Cooperative methods.

  • New diamond diagram name resolution.

  • Fixed set of allowed class attributes with Slots.

For more information on the new style classes and the unification of types and classes, see both PEPs 252 and 253 as well as the aforementioned tutorial by Guido.

______________________

White Paper
Linux Management with Red Hat Satellite: Measuring Business Impact and ROI

Linux has become a key foundation for supporting today's rapidly growing IT environments. Linux is being used to deploy business applications and databases, trading on its reputation as a low-cost operating environment. For many IT organizations, Linux is a mainstay for deploying Web servers and has evolved from handling basic file, print, and utility workloads to running mission-critical applications and databases, physically, virtually, and in the cloud. As Linux grows in importance in terms of value to the business, managing Linux environments to high standards of service quality — availability, security, and performance — becomes an essential requirement for business success.

Learn More

Sponsored by Red Hat

White Paper
Private PaaS for the Agile Enterprise

If you already use virtualized infrastructure, you are well on your way to leveraging the power of the cloud. Virtualization offers the promise of limitless resources, but how do you manage that scalability when your DevOps team doesn’t scale? In today’s hypercompetitive markets, fast results can make a difference between leading the pack vs. obsolescence. Organizations need more benefits from cloud computing than just raw resources. They need agility, flexibility, convenience, ROI, and control.

Stackato private Platform-as-a-Service technology from ActiveState extends your private cloud infrastructure by creating a private PaaS to provide on-demand availability, flexibility, control, and ultimately, faster time-to-market for your enterprise.

Learn More

Sponsored by ActiveState