Python 2.3 Final Released

An anonymous reader writes "Nineteen months in the making, Python 2.3 has just been released. With a plethora of changes since version 2.2, this release is definately worth the upgrade. Be sure to read the Release Notes and the Highlights file for more information."

Comments

Re:Reviewing a book 101

[Sir Haxalot]

Ask any Python aficionado and you'll hear that Python programmers have it all: an elegant language that offers object-oriented programming support, a readable, maintainable syntax, integration with C components, and an enormous collection of precoded standard library and extension modules. Moreover, Python is easy to learn but powerful enough to take on the most ambitious programming challenges. But what Python programmers have lacked is one concise and clear reference resource, with the appropriate measure of guidance in how best to use Python's great power. Now Python in a Nutshell fills this need.

In the tradition of O'Reilly's "In a Nutshell" series, this book offers Python programmers one place to look when they need help remembering or deciphering the syntax of this open source language and its many modules. This comprehensive reference guide makes it easy to look up all the most frequently needed information--not just about the Python language itself, but also the most frequently used parts of the standard library and the most important third-party extensions.

Python in a Nutshell focuses on Python 2.2 (and all its point releases), currently the most stable and widespread Python release. This book includes:

A fast-paced tutorial on the syntax of the Python language itself

An explanation of object-oriented programming in Python, covering both the classic and new-style object models

Coverage of other core topics, including exceptions, modules, strings, and regular expressions

A quick reference for Python's built-in types and functions, as well as the key modules in the Python standard library, including sys, os, time, thread, math, and socket, among many others

Reference material on important third-party extensions, such as Numeric and Tkinter

Information about extending Python and embedding it into other applications

Python in a Nutshell provides a solid, no-nonsense quick reference to information that programmers rely on the most. This latest addition to the best-selling "In a Nutshell" series will immediately earn its place in any Python programmer's library.

Synopsis
In the tradition of O'Reilly's "In a Nutshell" series, this book offers Python programmers help remembering or deciphering the syntax of this open source language and its many modules. This comprehensive reference guide should make it easy to look up all the most frequently needed information - not just about the Python language itself, but also the most frequently used parts of the standard library and the most important third-party extensions. The book includes: a fast-paced tutorial on the syntax of the Python language itself; an explanation of object-oriented programming in Python, covering both the classic and new-style object models; coverage of other core topics, including exceptions, modules, strings, and regular expressions; a quick reference for Python's built-in types and functions, as well as the key modules in the Python standard library, including sys, os, time, thread, math, and socket, among many others; reference material on important third-party extensions, such as Numeric and Tkinter; and information about extending Python and embedding it into other applications.

Happy? :)

Better than Learning Python.

[Big Sean O]

Learning Python is getting quite dated (it covers Python 1.5). I recommend Python: A Visual Quickstart Guide by Chris Fehily. It's a better book than Learning Python, at least.

I've been learning Python Language for a while, but since I don't work with other programmers, it's taken me quite a while. I learned python the usual way (a mix between the on-line tutorial and Learning Python) and my fluency is improving.

I picked up this book recently while I was at a convention in Baltimore. I liked its organization: the book features a whole chapter on each datatype (strings, numbers, tuples, lists, and dictionaries). There are also chapters on Control Flow Statements, Functions, Modules, Files, Classes, and Exceptions.

Because of its organization, it's as useful as a reference as it is a tutorial. Each chapter contains progressively advanced examples that end up demonstrating the finer points of each topic.

For example, one hint was to use the vars() function creates a dictionary of the local namespace. This makes it useful when string formatting:

>>> quality = 'color'
>>> thing = 'orange'
>>> print "What %s is an %s?" % (quality, thing) # useful for simple formatting.
What color is an orange?
>>> print "What %(quality)s is an %(thing)s?" % vars() # more legible and useful.
What color is an orange?

The book does not cover advanced topics like Tkinter, Jython, or extending Python with C. Nor does it cover the Library modules (the Python online documentation is actually quite good).

"Python" is newer, cheaper (22 USD vs. 30 USD), and longer (410pp vs. 368pp) than "Learning Python"

I would recommend this book to anyone who would like to learn Python. If you're an intermediate Pythoneer, I agree with the parent: you will want to get "Python In A Nutshell".

Re:Its 20-30% faster !!

[elflord]

If the speed of execution of python scripts can be made comparable to compiled C/C++ code, then it would be awesome.

Out by an order of magnitude, and not getting closer any time soon. Last I checked, it's out by a factor of 100 or so for small operations (loops, etc) But this isn't a problem in practice -- one can code the speed-critical stuff (whether that be objects, or functions) in C or C++, then wrap them in python, and enjoy all the benefits of python.

Also, it often happens that 1% of the speed of C and C++ is actually good enough. Sounds slow, but only compared to C and C++ which may be well over 100x faster than what's required.

Python programs can never be as fast as compiled code, but if the difference in the speed is not significant, it will be a big win for Python

It is much slower, and unavoidably so. It's a very dynamic language, and this has consequences as far as performance is concerned.

Re:ATTENTION!

[larry bagina]

Upgrading to Python 2.3 will _not_ increase your skill levels, and will NOT make your AOL downloads faster!

Actually, it could. The PHP crowd blew every horn they could find when yahoo switched over to PHP, but AOL has been using python behind the scenes for a long time with little fanfare (or problems). So if it's AOL doing the upgrading, it might help your AOL downloads be faster.