Slashdot Mirror

The Python Software Foundation has settled on a new governance model for the programming language Python. The decision to come up with a new model was made after Python creator and chief Guido van Rossum stepped down as the "Benevolent Dictator For Life" (BDFL). SDTimes: The new governance model will rely on a five-person steering council to establish standard practices for introducing new features to the Python programming language. Based on tested methods, the proposal was designed to be "boring," comprehensive, flexible and lightweight, the steering council model document explained. "We're not experts in governance, and we don't think Python is a good place to experiment with new and untried governance models," software developers Nathaniel Smith and Donald Stufft explained in the Python documentation.

"So this proposal sticks to mature, well-known, previously tested processes as much as possible. The high-level approach of a mostly-hands-off council is arguably the most common across large successful F/OSS projects, and low-level details are derived directly from Django's governance." The steering council will serve as the "court of final appeal" for changes to the language and will have broad authority over the decision-making process, including the ability to accept or reject PEPs (Python Enhancement Proposals) (such as the one used to introduce this governance model), enforce and update the project's code of conduct, create subcommittees and manage project assets. But the intended goal of the council is to take a more hands-off and occasional approach to flexing its powers, Smith and Stufft explained.

After almost 30 years of overseeing the development of the world's most popular language, Python, its founder and "Benevolent Dictator For Life" (BDFL), Guido van Rossum, has decided to remove himself entirely from the decision process. From a report: Van Rossum isn't leaving Python entirely. He said, "I'll still be there for a while as an ordinary core dev, and I'll still be available to mentor people -- possibly more available." It's clear from van Rossum's note he's sick and tired of running the organization. He wrote, "I don't ever want to have to fight so hard for a PEP (Python Enhancement Proposals) [PEP 572 Assignment Expressions] and find that so many people despise my decisions." In addition, van Rossum hints he's not been well. "I'm not getting younger... (I'll spare you the list of medical issues.)" So, "I'm basically giving myself a permanent vacation from being BDFL, and you all will be on your own." From the email: I am not going to appoint a successor. So what are you all going to do? Create a democracy? Anarchy? A dictatorship? A federation? I'm not worried about the day to day decisions in the issue tracker or on GitHub. Very rarely I get asked for an opinion, and usually it's not actually important. So this can just be dealt with as it has always been. At Slashdot, we had the privilege of interviewing Guido van Rossum, a Computer History Museum honoree, in 2013.

An anonymous reader writes: A new feature proposal for the Python programming language wants to add "transparency" to the runtime and let security and auditing tools view when Python may be running potentially dangerous operations. In its current form, Python does not allow security tools to see what operations the runtime is performing. Unless one of those operations generates particular errors that may raise a sign of alarm, security and auditing tools are blind that an attacker may be using Python to carry out malicious operations on a system.

But in Python Enhancement Proposal 551 (PEP-551), Steve Dower, a core Python developer, has proposed the addition of two new APIs that will let security tools detect when Python is executing potentially dangerous operations. The first, the Audit Hook API, will raise warning messages about certain type of Python operations; while the second, the Verified Open Hook API, is a mechanism to let the Python runtime know what files it is permitted to execute or tamper with.

Initial plans were to have PEP-551 ship with Python 3.7, scheduled for release in mid-June 2018, but the proposal did not make the final cut, according to a list of new features added for next month's release. This doesn't mean PEP-551 won't ship with a future version of Python. This is the second major scripting engine to open its runtime to security tools, after PowerShell.

On Friday, more than a year after Python 3.5, core developers Elvis Pranskevichus and Yury Selivanov announced the release of version 3.6. An anonymous reader writes: InfoWorld describes the changes as async in more places, speed and memory usage improvements, and pluggable support for JITs, tracers, and debuggers. "Python 3.6 also provides support for DTrace and SystemTap, brings a secrets module to the standard library [to generate authentication tokens], introduces new string and number formats, and adds type annotations for variables. It also gives us easier methods to customize the creation of subclasses."
You can read Slashdot's interview with Python creator Guido van Rossum from 2013. I also remember an interview this July where Perl creator Larry Wall called Python "a pretty okay first language, with a tendency towards style enforcement, monoculture, and group-think...more interested in giving you one adequate way to do something than it is in giving you a workshop that you, the programmer, get to choose the best tool from." Anyone want to share their thoughts today about the future of Python?

On Friday, more than a year after Python 3.5, core developers Elvis Pranskevichus and Yury Selivanov announced the release of version 3.6. An anonymous reader writes: InfoWorld describes the changes as async in more places, speed and memory usage improvements, and pluggable support for JITs, tracers, and debuggers. "Python 3.6 also provides support for DTrace and SystemTap, brings a secrets module to the standard library [to generate authentication tokens], introduces new string and number formats, and adds type annotations for variables. It also gives us easier methods to customize the creation of subclasses."
You can read Slashdot's interview with Python creator Guido van Rossum from 2013. I also remember an interview this July where Perl creator Larry Wall called Python "a pretty okay first language, with a tendency towards style enforcement, monoculture, and group-think...more interested in giving you one adequate way to do something than it is in giving you a workshop that you, the programmer, get to choose the best tool from." Anyone want to share their thoughts today about the future of Python?

On Friday, more than a year after Python 3.5, core developers Elvis Pranskevichus and Yury Selivanov announced the release of version 3.6. An anonymous reader writes: InfoWorld describes the changes as async in more places, speed and memory usage improvements, and pluggable support for JITs, tracers, and debuggers. "Python 3.6 also provides support for DTrace and SystemTap, brings a secrets module to the standard library [to generate authentication tokens], introduces new string and number formats, and adds type annotations for variables. It also gives us easier methods to customize the creation of subclasses."
You can read Slashdot's interview with Python creator Guido van Rossum from 2013. I also remember an interview this July where Perl creator Larry Wall called Python "a pretty okay first language, with a tendency towards style enforcement, monoculture, and group-think...more interested in giving you one adequate way to do something than it is in giving you a workshop that you, the programmer, get to choose the best tool from." Anyone want to share their thoughts today about the future of Python?

On Friday, more than a year after Python 3.5, core developers Elvis Pranskevichus and Yury Selivanov announced the release of version 3.6. An anonymous reader writes: InfoWorld describes the changes as async in more places, speed and memory usage improvements, and pluggable support for JITs, tracers, and debuggers. "Python 3.6 also provides support for DTrace and SystemTap, brings a secrets module to the standard library [to generate authentication tokens], introduces new string and number formats, and adds type annotations for variables. It also gives us easier methods to customize the creation of subclasses."
You can read Slashdot's interview with Python creator Guido van Rossum from 2013. I also remember an interview this July where Perl creator Larry Wall called Python "a pretty okay first language, with a tendency towards style enforcement, monoculture, and group-think...more interested in giving you one adequate way to do something than it is in giving you a workshop that you, the programmer, get to choose the best tool from." Anyone want to share their thoughts today about the future of Python?

On Friday, more than a year after Python 3.5, core developers Elvis Pranskevichus and Yury Selivanov announced the release of version 3.6. An anonymous reader writes: InfoWorld describes the changes as async in more places, speed and memory usage improvements, and pluggable support for JITs, tracers, and debuggers. "Python 3.6 also provides support for DTrace and SystemTap, brings a secrets module to the standard library [to generate authentication tokens], introduces new string and number formats, and adds type annotations for variables. It also gives us easier methods to customize the creation of subclasses."
You can read Slashdot's interview with Python creator Guido van Rossum from 2013. I also remember an interview this July where Perl creator Larry Wall called Python "a pretty okay first language, with a tendency towards style enforcement, monoculture, and group-think...more interested in giving you one adequate way to do something than it is in giving you a workshop that you, the programmer, get to choose the best tool from." Anyone want to share their thoughts today about the future of Python?

Nerval's Lobster writes: Since Python is a general-purpose language, it finds its way into a whole lot of different uses and industries. That means the industry in which you work has a way of determining what you actually need to know in terms of the language, as developer Jeff Cogswell explains in a new Dice piece. For example, if you're hired to write apps that interact with operating systems and monitor devices, you might not need to know how to use the Python modules for scientific and numerical programming. In a similar fashion, if you're hired to write Python code that interacts with a MySQL database, then you won't need to master how it works with CouchDB. The question is, how much do you need to know about Python's basics? Cogswell suggests there are three basic levels to learning Python: Learn the core language itself, such as the syntax and basic types (and the difference between Python 2 and Python 3); learn the commonly used modules, and familiarize yourself with other modules; learn the bigger picture of software development with Python, such as including Python in a build process, using the pip package manager, and so on. But is that enough?

Nerval's Lobster writes: Since Python is a general-purpose language, it finds its way into a whole lot of different uses and industries. That means the industry in which you work has a way of determining what you actually need to know in terms of the language, as developer Jeff Cogswell explains in a new Dice piece. For example, if you're hired to write apps that interact with operating systems and monitor devices, you might not need to know how to use the Python modules for scientific and numerical programming. In a similar fashion, if you're hired to write Python code that interacts with a MySQL database, then you won't need to master how it works with CouchDB. The question is, how much do you need to know about Python's basics? Cogswell suggests there are three basic levels to learning Python: Learn the core language itself, such as the syntax and basic types (and the difference between Python 2 and Python 3); learn the commonly used modules, and familiarize yourself with other modules; learn the bigger picture of software development with Python, such as including Python in a build process, using the pip package manager, and so on. But is that enough?

Nerval's Lobster writes: Since Python is a general-purpose language, it finds its way into a whole lot of different uses and industries. That means the industry in which you work has a way of determining what you actually need to know in terms of the language, as developer Jeff Cogswell explains in a new Dice piece. For example, if you're hired to write apps that interact with operating systems and monitor devices, you might not need to know how to use the Python modules for scientific and numerical programming. In a similar fashion, if you're hired to write Python code that interacts with a MySQL database, then you won't need to master how it works with CouchDB. The question is, how much do you need to know about Python's basics? Cogswell suggests there are three basic levels to learning Python: Learn the core language itself, such as the syntax and basic types (and the difference between Python 2 and Python 3); learn the commonly used modules, and familiarize yourself with other modules; learn the bigger picture of software development with Python, such as including Python in a build process, using the pip package manager, and so on. But is that enough?

GNU Mailman, likely the most popular mailing list manager in use today, has finally announced the release of a beta for version 3. GNU Mailman 3.0 is a major rewrite, features include a central server with a REST API replacing the dozen or two programs that manipulated Mailman data directly, a shiny new web fron end (Postorius), and a new archiver (HyperKitty). Fedora is already using the new archiver and interface, which is quite a bit more modern looking than Mailman 2.x's interface (wayback machine link for posterity). Individual message thread views are greatly improved, and you can even reply from the web by logging in with your list credentials. If you'd like to try it out, see the announcement message.

GNU Mailman, likely the most popular mailing list manager in use today, has finally announced the release of a beta for version 3. GNU Mailman 3.0 is a major rewrite, features include a central server with a REST API replacing the dozen or two programs that manipulated Mailman data directly, a shiny new web fron end (Postorius), and a new archiver (HyperKitty). Fedora is already using the new archiver and interface, which is quite a bit more modern looking than Mailman 2.x's interface (wayback machine link for posterity). Individual message thread views are greatly improved, and you can even reply from the web by logging in with your list credentials. If you'd like to try it out, see the announcement message.

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

New submitter gadfium writes: "Python 3.4 has been released. It adds new library features, bug fixes, and security improvements. It includes: at standardized implementation of enumeration types, a statistics module, improvements to object finalization, a more secure and interchangeable hash algorithm for strings and binary data, asynchronous I/O support, and an installer for the pip package manager."

The Python developers have been busy this weekend, releasing three new versions at different points on the Python continuum: 2.7.4 (a 2.7 series bugfix release), 3.2.4 (what's new), and production releases 3.3.1. Here's what's new in 3.3.1.

The Python developers have been busy this weekend, releasing three new versions at different points on the Python continuum: 2.7.4 (a 2.7 series bugfix release), 3.2.4 (what's new), and production releases 3.3.1. Here's what's new in 3.3.1.

The Python developers have been busy this weekend, releasing three new versions at different points on the Python continuum: 2.7.4 (a 2.7 series bugfix release), 3.2.4 (what's new), and production releases 3.3.1. Here's what's new in 3.3.1.

The Python developers have been busy this weekend, releasing three new versions at different points on the Python continuum: 2.7.4 (a 2.7 series bugfix release), 3.2.4 (what's new), and production releases 3.3.1. Here's what's new in 3.3.1.

The Python developers have been busy this weekend, releasing three new versions at different points on the Python continuum: 2.7.4 (a 2.7 series bugfix release), 3.2.4 (what's new), and production releases 3.3.1. Here's what's new in 3.3.1.

An anonymous reader writes "After just over a month of release candidates, the final version of Python 3.3 launched today. This version includes new syntax, including the yield from expression for generator delegation; new library modules, including fault handler (for debugging crashes), ipaddress, and lzma (for data compression using the XZ/LZMA algorithm); a reworked OS and I/O exception hierarchy; the venv module for programmatic access to Python virtual environments; and a host of API changes. The full list of features and the change log are both available."

An anonymous reader writes "After just over a month of release candidates, the final version of Python 3.3 launched today. This version includes new syntax, including the yield from expression for generator delegation; new library modules, including fault handler (for debugging crashes), ipaddress, and lzma (for data compression using the XZ/LZMA algorithm); a reworked OS and I/O exception hierarchy; the venv module for programmatic access to Python virtual environments; and a host of API changes. The full list of features and the change log are both available."

An anonymous reader writes "After just over a month of release candidates, the final version of Python 3.3 launched today. This version includes new syntax, including the yield from expression for generator delegation; new library modules, including fault handler (for debugging crashes), ipaddress, and lzma (for data compression using the XZ/LZMA algorithm); a reworked OS and I/O exception hierarchy; the venv module for programmatic access to Python virtual environments; and a host of API changes. The full list of features and the change log are both available."

Here is a breakdown of R, Octave and Python, and how analysts can rely on open-source software and online learning resources to bring data-mining capabilities into their companies. The article breaks down which of the three is easiest to use, which do well with visualizations, which handle big data the best, etc. The lack of a budget shouldn't prevent you from experiencing all the benefits of a top-shelf data analysis package, and each of these options brings its own set of strengths while being much cheaper to implement than the typical proprietary solutions.

thatpythonguy writes "Addison-Wesley publishers has released The Python Standard Library By Example, another Python book that strategically fits in between programming cookbooks and library reference manuals. It brings the Python standard library that much closer to Python programmers and helps make them more proficient in their trade." Read below for Ahmed's first Slashdot review. The Python Standard Library by Example author Doug Hellmann pages 1344 publisher Addison-Wesley Professional rating 8 of 10 reviewer Ahmed Al-Saadi ISBN 978-0-321-76734-9 summary A unique guide to the Python standard library that is between a cookbook and a reference manual There has been an explosion in the availability of published titles for the Python programming language in the past few years. This has been driven by the rising popularity of this multi-paradigm language that has proven useful in domains spanning web, games, graphics, financial, science, automation and others. Many large and small corporations, universities and governmental organizations are using Python in their respective fields with seeming success.

One of the main reasons for the success of Python is the quality, breadth, and depth of its standard library. Unfortunately, this library is not documented sufficiently in titles that serve as introductory or reference material due to the nature of introductory texts that deal with the basics; on the other hand, reference texts are often too concise and lack sufficient examples. The title at hand is a library-centric tutorial/reference that can be a great tool when you need to learn how to solve certain problems using Python.

The book addresses itself to intermediate Python programmers and covers versions 2.7 and 3.x of the language. Although an experienced programmer coming from another language can learn a lot about Python by reading this book, I personally favor the traditional top-down, gradual method of learning a new language which involves an introductory, tutorial-style, and verbose introductory book. However, realizing that others might not like my cup of tea, I can envision, for example, someone familiar with socket programming picking up this book and writing a network application without prior Python experience. He or she might still need to look up language features on the way, but that should not be too hard as the language is easy to understand and there is a rich library of on-line (and printed) content for basic language constructs.

This title comes in a hefty 1300-plus-page, soft-cover book (or eBook) that is organized around thematic grouping of library modules. The groups are: text, data structures, algorithms, dates and times, mathematics, file system, data persistence and exchange, data compression and archiving, cryptography, processes and threads, networking, the Internet, email, application building blocks, internationalization and localization, developer tools, runtime features, language tools, modules and packages.

Each group contains the relevant modules from the standard library. For example, the text group contains the string, textwrap, re and difflib modules. Each of these modules is briefly described first and then its use is demonstrated in various ways under an appropriate heading. For example, the socket module (networking group) has sections covering addressing, TCP/IP client/Server, UDP clients/servers, UNIX domain sockets and multicast, among others. The code is written in such a way as to focus on the topic being discussed while not overlooking good practices such as wrapping a socket connection call with a try/finally block to ensure that the connection is closed in case of error.

A more advanced module, that is also described in the networking group, is SocketServer. This is a higher-level (on top of the socket layer) facility that enables the creation of network servers (e.g., HTTP or AMQP). It is nice to see that the book demonstrates the creation of an echo server using this module while incorporating more advanced topics such as threading and asynchronous I/O which are necessities in real-life, production code.

Although the content covers quite a bit of ground that surpasses many other sources in terms of coverage, the Python standard library is so vast that any one-volume book attempting to provide comprehensive coverage will necessarily fail! Nonetheless, you will find at the end of each section pointers to other material such as on-line resources, RFCs, and related books that can be used for a deeper study of the relevant topics.

I think that the text could use some typographical features to enhance the clarity of the content. These include highlighting the code using indents or an alternative font to set it apart from the text that surrounds it as I found it hard to visually distinguish the two. The code should also have the name of the file at the top of the listing so that when that name is used subsequently to invoke the code, it would be easy to reference the file contents. Also,I find the general typesetting not as pleasing nor as easy to read as titles from certain other publishers. This latter point is somewhat subjective and, in any case, does not detract from the utility of the content.

Despite the caveat above, I have to say that I like this class of documentation that is between a cookbook and a reference manual. I find it useful that the examples are not so terse nor overly verbose. I also appreciate the quality of the code and the references for further readings. I think that this book fills a void that will make many Python programmers more proficient.

Ahmed Al-Saadi is the Principal Software Consultant for Solea Research, a software consultancy and development company based in Montreal, Canada. He spends his free time writing, contemplating software architecture and playing his Flamenco guitar."

You can purchase The Python Standard Library by Example from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

digitalderbs writes "Python 3.2 was released on Feb 20th 2011 with many new improvements. New features include many useful updates to the unittest module, a stable ABI for extensions, pyc repository directories, improvements to the email and ssl modules and many others. This also marks the first release in the 3000-series that is no longer backported to the 2.0-series."

digitalderbs writes "Python 3.2 was released on Feb 20th 2011 with many new improvements. New features include many useful updates to the unittest module, a stable ABI for extensions, pyc repository directories, improvements to the email and ssl modules and many others. This also marks the first release in the 3000-series that is no longer backported to the 2.0-series."

johnmccollum writes "A wealth of tools are available to debug and test Django applications, but knowing when and how to use these resources can intimidate the new user. Django 1.1 Testing and Debugging, by Karen M. Tracey, aims to walk the user through the process of creating a web application from scratch, ensuring that the resulting code is bug-free and ready for production." Keep reading for the rest of John's review. Django 1.1 Testing and Debugging author Karen M. Tracey pages 409 publisher Packt Publishing rating 9/10 reviewer John McCollum ISBN 978-1-847197-56-6 summary Building rigorously tested and bug-free Django applications In a way, Django makes it deceptively easy to write a dynamic web application. With a few lines of code, you can have an fully functional application up and running in a short space of time, and complex applications take less time than ever to develop. Inevitably, though, bugs will creep in to the development process, and the professional developer will want to make sure that their application is as bug-free as possible before launching.

The book opens with a simple question: "How do you know when code you have written is working as intended?" The answer, of course, is that you test it. But if you're not a cowboy coder, you'll want to leverage the full power of Django's automated testing framework for best results. In the course of this book, the author develops a full web application, from start to finish, and describes how each section would be tested and debugged.

The author's intended audience for this book is perhaps one that is relatively new to Django. Ideally, the reader will have a functioning installation of Django, will have worked through at least the tutorial, and may well have written a couple of applications. This book would also be excellent for someone migrating to Python from another language, or moving into MVC frameworks for the first time. Crucially, the book doesn't just explain how to test, it also explains when and what to test too, so it serves as an ideal introduction into testing in general. There are many code examples and screenshots, and each line of code is fully explained.

The book kicks off with an examination of doctests and unit tests. Their relative pros and cons are explained in some depth, and the author does a great job in this section of discussing exactly what you should be testing, initially beginning with data models. She then moves on to more advanced unit testing strategies and applications, such as testing views and customizations of the admin area.

One of Python's greatest strengths is its ecosystem, and the following chapters cover some of the other tools you might want to integrate into your project. Django-coverage provides reporting on how much of your code is covered by tests, and Twill is a package that essentially replaces Django's test client to provide enhanced functionality — particularly for working with forms. Both packages have fully explained and in-depth examples to work through. (Code downloads are available at Packt Publishing's web site for the terminally lazy!)

With the testing section of the book complete, the author moves on to the debugging section of the book. Starting with the very basics (setting up Django in debug mode), the book then takes a detailed look at the Django debug page. This is something that I could see being useful for many new users — the debug page contains a wealth of information (and not all of it is always entirely relevant, if not outright misleading), so learning to understand this page is crucial to your success as a Djangonaut.

The book then takes a tour of the excellent django-debug-toolbar, before moving on to what was, for me, the most valuable chapter of the book: "When you don't know even know what to log: Using Debuggers." This chapter introduces the PDB (Python Debugger) library.

Like many others, I suppose, Django was my first introduction to Python. For that reason, my knowledge of the standard library is perhaps not as strong as it could be. For me, learning about the different ways of using the debugger was the highlight of the book, and something that will probably change the way I develop with Django.

The book concludes, of course, by taking the application into a production environment. And in line with the latest advice, that means setting up the site using Apache and mod_wsgi. In keeping with the theme of the book, the most common issues in deployment are identified and resolved.

This book weighs in at over four hundred pages, and its greatest strength is its wide scope. Although the basics of testing in Django are easy to understand, it's another thing entirely to see an entire application built from the ground up with testing at the forefront. As I mentioned before, the focus is as much on developing a testing and debugging strategy as it is on the technical aspects.

From a more technical point of view, the subject matter ranges from beginner to advanced. From writing the most basic doctests to debugging multi-process race conditions, the difficulty level increases incrementally, and no important details are skirted over. The prose is well-written and easy to read throughout.

If I had one gripe about the book, it would be that in places, it goes into a little too much detail. There's a section on using the Django web site (the bug tracker, the mailing list etc.) that I could have done without entirely. Although it might be useful for some users, the site is pretty self-explanatory and doesn't really warrant the attention it gets, in my opinion.

You shouldn't let that put you off though — this really is an excellent exploration of the topic. In addition, Packt Publishing will make a donation to the Django project for every book sold, so in purchasing this book, you'll be indirectly helping the project financially too.

This book is worth a place on any Django developer's bookshelf.

You can purchase Django 1.1 Testing and Debugging from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

stoolpigeon writes "It has been ten years since David Beazley wrote the first edition of Python Essential Reference. The book has proven itself as a valuable resource to Python developers and has been kept current over those ten years, with the fourth edition coming at an interesting time for Python. Python 3 was a major release that broke backwards compatibility. Python 3 has been around for a year now. That said, the current download page at the official Python site states, 'If you don't know which version to use, start with Python 2.6.4; more existing third party software is compatible with Python 2 than Python 3 right now.' Beazley, in keeping with the pragmatic roots of a reference that sticks to what is 'essential,' has removed the coverage on features from 2 that were removed from 3. At the same time, the primary focus for new features that came with 3 is limited to those that have been back-ported to 2. This approach, born out of a desire to keep the reference relevant, provides a blended approach that is above all else practical." Read on for the rest of JR's review. Python Essential Reference 4th Ed. author David M. Beazley pages 738 publisher Addison-Wesley rating 9/10 reviewer JR Peck ISBN 978-0-672-32978-4 summary A definitive guide to the core Python language and the essential parts of the Python library. The end result of that choice is a reference document consisting of those parts of Python that are shared between versions 2 and 3. This is a significant portion of the language and I think this approach is really what will give this reference more traction than many of the other guides that focus purely on 3. I think that those are valuable and over time the balance will shift but as of right now, for a little while to come, this book takes the most realistic approach. That feels very fuzzy, but I have no idea how long it will be until Python 3 truly is the dominant version and Python 2 is truly put to bed.

If I had to guess how Beazley's Python Essential Reference has held in there over the years, the key would be that there is a lot of what a developer needs and very little of what she doesn't need. There is a twenty-four page tutorial introduction, but this is not a guide on how to program or how to use Python for beginners. An experienced programmer could probably use this reference to shift to Python as a new language, but someone completely new to writing code would probably not want to start here. A quick look at the table of contents shows that an explanation of the language itself is covered in under 200 pages. Extending and embedding Python also get their own section, but close to 400 pages is given to the Python library.

An inevitable question is what one will gain with this reference over the online documentation. A good example to see how things vary is to look at chapter nineteen, Operating System Services and the online documentation for Generic Operating System Services. The online documentation is very thorough, and covers each piece of the library starting with os and io, building from there. While every facet is documented much of it is rather brief. For example section 16.2.3. Raw File I/O is a very straightforward listing of the very low level functionality available via io.FileIO. In contrast, looking at the 3.1.1 Docs for Raw IO shows that parameters for FileIO changed with that version. Looking to the documentation for 2.7a1 Raw File I/O shows that these changes are being back-ported to Python 2.

In Python Essential Reference none of this hunting down changes and checking to see if they are coming to 2 are necessary. Beazley shows them in his documentation. This is the strength of his choice on how to handle these types of situations. On top of that, Beazley provides more than the online documents by including four paragraphs of additional information on Raw I/O and when its use is appropriate. This added content is probably available googling around for it, but then I have to take the time to check dates on posts to see if things are still current and in general just hope that things are accurate. I have never read a technical book that was completely error free, and there are probably at the very least some typos in Python Essential Reference, though I haven't caught any of them on my read through or use of the book yet. But the important thing is that I don't expect the book to be perfect, rather I value it for being a known quantity. I am aware of just when the material was compiled, who put it together and I have it all in one place.errno symbols is not exhaustive and oddly enough is not ordered alphabetically. Beazley provides two lists for errno symbols. They are provided in alphabetical order, have a description and are grouped as POSIX error codes and Windows error codes. A quick glance at these tables in a skimming of the book might lead one to believe that this is just a simple quick grab from already available sources, but that isn't the case. There is real value added even here.

The index is solid. It would seem that one should be able to take this for granted with a technical reference but I've seen some sad exceptions. Between the thorough index and the detailed table of contents I've never had to spend more than a few seconds looking for what I need. This is the result of those tools as well as the fact that this is not an exhaustive reference. After initially reading through the book for this review, I've taken some time just to use it day to day, as I doubt many will be reading it from front to back. I don't use Python professionally. I'm purely a hobbyist when it comes to programming, but I've found that if I want to get the most out of the time I do have to play with personal projects, I want this book close. I'm not cranking out code that fast to begin with and so I need all the help I can get. I've found that Beazley seems to have hit that sweet spot where he gives enough information to get me where I need to be without bogging down in too many details or the things that I just don't need to know. I imagine this proper balance of information is due to Beazley's extensive experience with Python and that of Noah Gift the technical editor for the book.

I've mentioned repeatedly that I approve of how the shift between Python 2 and 3 has been handled. Beazley hasn't completely integrated everything and left some of the unique new features of 3 out in the cold. There is an appendix that deals specifically with Python 3. It is short but does have some value. New features, common pitfalls for those making the move from 2 to 3 and how to run both at the same time in a single environment are covered. This is helpful and keeps my desk a little neater, though I think if I were going to be spending extensive time working with Python 3 then I would probably want to have another reference on hand.

If you are a week-end hacker like me, or someone that is writing Python on the clock, I think that this compact reference is very useful. I don't have any trouble running across huge technical books that do come in handy for any project that requires something heavy. I also see a lot of little books that seem to be quickly produced summaries of what is already out there, spending most of their short content on fluff. Every so often though, someone hits that sweet spot of concise usefulness. Beazley did this with Python Essential Reference and this new edition continues that history in strong fashion.

You can purchase Python Essential Reference 4th Ed. from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

stoolpigeon writes "It has been ten years since David Beazley wrote the first edition of Python Essential Reference. The book has proven itself as a valuable resource to Python developers and has been kept current over those ten years, with the fourth edition coming at an interesting time for Python. Python 3 was a major release that broke backwards compatibility. Python 3 has been around for a year now. That said, the current download page at the official Python site states, 'If you don't know which version to use, start with Python 2.6.4; more existing third party software is compatible with Python 2 than Python 3 right now.' Beazley, in keeping with the pragmatic roots of a reference that sticks to what is 'essential,' has removed the coverage on features from 2 that were removed from 3. At the same time, the primary focus for new features that came with 3 is limited to those that have been back-ported to 2. This approach, born out of a desire to keep the reference relevant, provides a blended approach that is above all else practical." Read on for the rest of JR's review. Python Essential Reference 4th Ed. author David M. Beazley pages 738 publisher Addison-Wesley rating 9/10 reviewer JR Peck ISBN 978-0-672-32978-4 summary A definitive guide to the core Python language and the essential parts of the Python library. The end result of that choice is a reference document consisting of those parts of Python that are shared between versions 2 and 3. This is a significant portion of the language and I think this approach is really what will give this reference more traction than many of the other guides that focus purely on 3. I think that those are valuable and over time the balance will shift but as of right now, for a little while to come, this book takes the most realistic approach. That feels very fuzzy, but I have no idea how long it will be until Python 3 truly is the dominant version and Python 2 is truly put to bed.

If I had to guess how Beazley's Python Essential Reference has held in there over the years, the key would be that there is a lot of what a developer needs and very little of what she doesn't need. There is a twenty-four page tutorial introduction, but this is not a guide on how to program or how to use Python for beginners. An experienced programmer could probably use this reference to shift to Python as a new language, but someone completely new to writing code would probably not want to start here. A quick look at the table of contents shows that an explanation of the language itself is covered in under 200 pages. Extending and embedding Python also get their own section, but close to 400 pages is given to the Python library.

An inevitable question is what one will gain with this reference over the online documentation. A good example to see how things vary is to look at chapter nineteen, Operating System Services and the online documentation for Generic Operating System Services. The online documentation is very thorough, and covers each piece of the library starting with os and io, building from there. While every facet is documented much of it is rather brief. For example section 16.2.3. Raw File I/O is a very straightforward listing of the very low level functionality available via io.FileIO. In contrast, looking at the 3.1.1 Docs for Raw IO shows that parameters for FileIO changed with that version. Looking to the documentation for 2.7a1 Raw File I/O shows that these changes are being back-ported to Python 2.

In Python Essential Reference none of this hunting down changes and checking to see if they are coming to 2 are necessary. Beazley shows them in his documentation. This is the strength of his choice on how to handle these types of situations. On top of that, Beazley provides more than the online documents by including four paragraphs of additional information on Raw I/O and when its use is appropriate. This added content is probably available googling around for it, but then I have to take the time to check dates on posts to see if things are still current and in general just hope that things are accurate. I have never read a technical book that was completely error free, and there are probably at the very least some typos in Python Essential Reference, though I haven't caught any of them on my read through or use of the book yet. But the important thing is that I don't expect the book to be perfect, rather I value it for being a known quantity. I am aware of just when the material was compiled, who put it together and I have it all in one place.errno symbols is not exhaustive and oddly enough is not ordered alphabetically. Beazley provides two lists for errno symbols. They are provided in alphabetical order, have a description and are grouped as POSIX error codes and Windows error codes. A quick glance at these tables in a skimming of the book might lead one to believe that this is just a simple quick grab from already available sources, but that isn't the case. There is real value added even here.

The index is solid. It would seem that one should be able to take this for granted with a technical reference but I've seen some sad exceptions. Between the thorough index and the detailed table of contents I've never had to spend more than a few seconds looking for what I need. This is the result of those tools as well as the fact that this is not an exhaustive reference. After initially reading through the book for this review, I've taken some time just to use it day to day, as I doubt many will be reading it from front to back. I don't use Python professionally. I'm purely a hobbyist when it comes to programming, but I've found that if I want to get the most out of the time I do have to play with personal projects, I want this book close. I'm not cranking out code that fast to begin with and so I need all the help I can get. I've found that Beazley seems to have hit that sweet spot where he gives enough information to get me where I need to be without bogging down in too many details or the things that I just don't need to know. I imagine this proper balance of information is due to Beazley's extensive experience with Python and that of Noah Gift the technical editor for the book.

I've mentioned repeatedly that I approve of how the shift between Python 2 and 3 has been handled. Beazley hasn't completely integrated everything and left some of the unique new features of 3 out in the cold. There is an appendix that deals specifically with Python 3. It is short but does have some value. New features, common pitfalls for those making the move from 2 to 3 and how to run both at the same time in a single environment are covered. This is helpful and keeps my desk a little neater, though I think if I were going to be spending extensive time working with Python 3 then I would probably want to have another reference on hand.

If you are a week-end hacker like me, or someone that is writing Python on the clock, I think that this compact reference is very useful. I don't have any trouble running across huge technical books that do come in handy for any project that requires something heavy. I also see a lot of little books that seem to be quickly produced summaries of what is already out there, spending most of their short content on fluff. Every so often though, someone hits that sweet spot of concise usefulness. Beazley did this with Python Essential Reference and this new edition continues that history in strong fashion.

You can purchase Python Essential Reference 4th Ed. from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

stoolpigeon writes "It has been ten years since David Beazley wrote the first edition of Python Essential Reference. The book has proven itself as a valuable resource to Python developers and has been kept current over those ten years, with the fourth edition coming at an interesting time for Python. Python 3 was a major release that broke backwards compatibility. Python 3 has been around for a year now. That said, the current download page at the official Python site states, 'If you don't know which version to use, start with Python 2.6.4; more existing third party software is compatible with Python 2 than Python 3 right now.' Beazley, in keeping with the pragmatic roots of a reference that sticks to what is 'essential,' has removed the coverage on features from 2 that were removed from 3. At the same time, the primary focus for new features that came with 3 is limited to those that have been back-ported to 2. This approach, born out of a desire to keep the reference relevant, provides a blended approach that is above all else practical." Read on for the rest of JR's review. Python Essential Reference 4th Ed. author David M. Beazley pages 738 publisher Addison-Wesley rating 9/10 reviewer JR Peck ISBN 978-0-672-32978-4 summary A definitive guide to the core Python language and the essential parts of the Python library. The end result of that choice is a reference document consisting of those parts of Python that are shared between versions 2 and 3. This is a significant portion of the language and I think this approach is really what will give this reference more traction than many of the other guides that focus purely on 3. I think that those are valuable and over time the balance will shift but as of right now, for a little while to come, this book takes the most realistic approach. That feels very fuzzy, but I have no idea how long it will be until Python 3 truly is the dominant version and Python 2 is truly put to bed.

If I had to guess how Beazley's Python Essential Reference has held in there over the years, the key would be that there is a lot of what a developer needs and very little of what she doesn't need. There is a twenty-four page tutorial introduction, but this is not a guide on how to program or how to use Python for beginners. An experienced programmer could probably use this reference to shift to Python as a new language, but someone completely new to writing code would probably not want to start here. A quick look at the table of contents shows that an explanation of the language itself is covered in under 200 pages. Extending and embedding Python also get their own section, but close to 400 pages is given to the Python library.

An inevitable question is what one will gain with this reference over the online documentation. A good example to see how things vary is to look at chapter nineteen, Operating System Services and the online documentation for Generic Operating System Services. The online documentation is very thorough, and covers each piece of the library starting with os and io, building from there. While every facet is documented much of it is rather brief. For example section 16.2.3. Raw File I/O is a very straightforward listing of the very low level functionality available via io.FileIO. In contrast, looking at the 3.1.1 Docs for Raw IO shows that parameters for FileIO changed with that version. Looking to the documentation for 2.7a1 Raw File I/O shows that these changes are being back-ported to Python 2.

In Python Essential Reference none of this hunting down changes and checking to see if they are coming to 2 are necessary. Beazley shows them in his documentation. This is the strength of his choice on how to handle these types of situations. On top of that, Beazley provides more than the online documents by including four paragraphs of additional information on Raw I/O and when its use is appropriate. This added content is probably available googling around for it, but then I have to take the time to check dates on posts to see if things are still current and in general just hope that things are accurate. I have never read a technical book that was completely error free, and there are probably at the very least some typos in Python Essential Reference, though I haven't caught any of them on my read through or use of the book yet. But the important thing is that I don't expect the book to be perfect, rather I value it for being a known quantity. I am aware of just when the material was compiled, who put it together and I have it all in one place.errno symbols is not exhaustive and oddly enough is not ordered alphabetically. Beazley provides two lists for errno symbols. They are provided in alphabetical order, have a description and are grouped as POSIX error codes and Windows error codes. A quick glance at these tables in a skimming of the book might lead one to believe that this is just a simple quick grab from already available sources, but that isn't the case. There is real value added even here.

The index is solid. It would seem that one should be able to take this for granted with a technical reference but I've seen some sad exceptions. Between the thorough index and the detailed table of contents I've never had to spend more than a few seconds looking for what I need. This is the result of those tools as well as the fact that this is not an exhaustive reference. After initially reading through the book for this review, I've taken some time just to use it day to day, as I doubt many will be reading it from front to back. I don't use Python professionally. I'm purely a hobbyist when it comes to programming, but I've found that if I want to get the most out of the time I do have to play with personal projects, I want this book close. I'm not cranking out code that fast to begin with and so I need all the help I can get. I've found that Beazley seems to have hit that sweet spot where he gives enough information to get me where I need to be without bogging down in too many details or the things that I just don't need to know. I imagine this proper balance of information is due to Beazley's extensive experience with Python and that of Noah Gift the technical editor for the book.

I've mentioned repeatedly that I approve of how the shift between Python 2 and 3 has been handled. Beazley hasn't completely integrated everything and left some of the unique new features of 3 out in the cold. There is an appendix that deals specifically with Python 3. It is short but does have some value. New features, common pitfalls for those making the move from 2 to 3 and how to run both at the same time in a single environment are covered. This is helpful and keeps my desk a little neater, though I think if I were going to be spending extensive time working with Python 3 then I would probably want to have another reference on hand.

If you are a week-end hacker like me, or someone that is writing Python on the clock, I think that this compact reference is very useful. I don't have any trouble running across huge technical books that do come in handy for any project that requires something heavy. I also see a lot of little books that seem to be quickly produced summaries of what is already out there, spending most of their short content on fluff. Every so often though, someone hits that sweet spot of concise usefulness. Beazley did this with Python Essential Reference and this new edition continues that history in strong fashion.

You can purchase Python Essential Reference 4th Ed. from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

stoolpigeon writes "It has been ten years since David Beazley wrote the first edition of Python Essential Reference. The book has proven itself as a valuable resource to Python developers and has been kept current over those ten years, with the fourth edition coming at an interesting time for Python. Python 3 was a major release that broke backwards compatibility. Python 3 has been around for a year now. That said, the current download page at the official Python site states, 'If you don't know which version to use, start with Python 2.6.4; more existing third party software is compatible with Python 2 than Python 3 right now.' Beazley, in keeping with the pragmatic roots of a reference that sticks to what is 'essential,' has removed the coverage on features from 2 that were removed from 3. At the same time, the primary focus for new features that came with 3 is limited to those that have been back-ported to 2. This approach, born out of a desire to keep the reference relevant, provides a blended approach that is above all else practical." Read on for the rest of JR's review. Python Essential Reference 4th Ed. author David M. Beazley pages 738 publisher Addison-Wesley rating 9/10 reviewer JR Peck ISBN 978-0-672-32978-4 summary A definitive guide to the core Python language and the essential parts of the Python library. The end result of that choice is a reference document consisting of those parts of Python that are shared between versions 2 and 3. This is a significant portion of the language and I think this approach is really what will give this reference more traction than many of the other guides that focus purely on 3. I think that those are valuable and over time the balance will shift but as of right now, for a little while to come, this book takes the most realistic approach. That feels very fuzzy, but I have no idea how long it will be until Python 3 truly is the dominant version and Python 2 is truly put to bed.

If I had to guess how Beazley's Python Essential Reference has held in there over the years, the key would be that there is a lot of what a developer needs and very little of what she doesn't need. There is a twenty-four page tutorial introduction, but this is not a guide on how to program or how to use Python for beginners. An experienced programmer could probably use this reference to shift to Python as a new language, but someone completely new to writing code would probably not want to start here. A quick look at the table of contents shows that an explanation of the language itself is covered in under 200 pages. Extending and embedding Python also get their own section, but close to 400 pages is given to the Python library.

An inevitable question is what one will gain with this reference over the online documentation. A good example to see how things vary is to look at chapter nineteen, Operating System Services and the online documentation for Generic Operating System Services. The online documentation is very thorough, and covers each piece of the library starting with os and io, building from there. While every facet is documented much of it is rather brief. For example section 16.2.3. Raw File I/O is a very straightforward listing of the very low level functionality available via io.FileIO. In contrast, looking at the 3.1.1 Docs for Raw IO shows that parameters for FileIO changed with that version. Looking to the documentation for 2.7a1 Raw File I/O shows that these changes are being back-ported to Python 2.

In Python Essential Reference none of this hunting down changes and checking to see if they are coming to 2 are necessary. Beazley shows them in his documentation. This is the strength of his choice on how to handle these types of situations. On top of that, Beazley provides more than the online documents by including four paragraphs of additional information on Raw I/O and when its use is appropriate. This added content is probably available googling around for it, but then I have to take the time to check dates on posts to see if things are still current and in general just hope that things are accurate. I have never read a technical book that was completely error free, and there are probably at the very least some typos in Python Essential Reference, though I haven't caught any of them on my read through or use of the book yet. But the important thing is that I don't expect the book to be perfect, rather I value it for being a known quantity. I am aware of just when the material was compiled, who put it together and I have it all in one place.errno symbols is not exhaustive and oddly enough is not ordered alphabetically. Beazley provides two lists for errno symbols. They are provided in alphabetical order, have a description and are grouped as POSIX error codes and Windows error codes. A quick glance at these tables in a skimming of the book might lead one to believe that this is just a simple quick grab from already available sources, but that isn't the case. There is real value added even here.

The index is solid. It would seem that one should be able to take this for granted with a technical reference but I've seen some sad exceptions. Between the thorough index and the detailed table of contents I've never had to spend more than a few seconds looking for what I need. This is the result of those tools as well as the fact that this is not an exhaustive reference. After initially reading through the book for this review, I've taken some time just to use it day to day, as I doubt many will be reading it from front to back. I don't use Python professionally. I'm purely a hobbyist when it comes to programming, but I've found that if I want to get the most out of the time I do have to play with personal projects, I want this book close. I'm not cranking out code that fast to begin with and so I need all the help I can get. I've found that Beazley seems to have hit that sweet spot where he gives enough information to get me where I need to be without bogging down in too many details or the things that I just don't need to know. I imagine this proper balance of information is due to Beazley's extensive experience with Python and that of Noah Gift the technical editor for the book.

I've mentioned repeatedly that I approve of how the shift between Python 2 and 3 has been handled. Beazley hasn't completely integrated everything and left some of the unique new features of 3 out in the cold. There is an appendix that deals specifically with Python 3. It is short but does have some value. New features, common pitfalls for those making the move from 2 to 3 and how to run both at the same time in a single environment are covered. This is helpful and keeps my desk a little neater, though I think if I were going to be spending extensive time working with Python 3 then I would probably want to have another reference on hand.

If you are a week-end hacker like me, or someone that is writing Python on the clock, I think that this compact reference is very useful. I don't have any trouble running across huge technical books that do come in handy for any project that requires something heavy. I also see a lot of little books that seem to be quickly produced summaries of what is already out there, spending most of their short content on fluff. Every so often though, someone hits that sweet spot of concise usefulness. Beazley did this with Python Essential Reference and this new edition continues that history in strong fashion.

You can purchase Python Essential Reference 4th Ed. from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

stoolpigeon writes "It has been ten years since David Beazley wrote the first edition of Python Essential Reference. The book has proven itself as a valuable resource to Python developers and has been kept current over those ten years, with the fourth edition coming at an interesting time for Python. Python 3 was a major release that broke backwards compatibility. Python 3 has been around for a year now. That said, the current download page at the official Python site states, 'If you don't know which version to use, start with Python 2.6.4; more existing third party software is compatible with Python 2 than Python 3 right now.' Beazley, in keeping with the pragmatic roots of a reference that sticks to what is 'essential,' has removed the coverage on features from 2 that were removed from 3. At the same time, the primary focus for new features that came with 3 is limited to those that have been back-ported to 2. This approach, born out of a desire to keep the reference relevant, provides a blended approach that is above all else practical." Read on for the rest of JR's review. Python Essential Reference 4th Ed. author David M. Beazley pages 738 publisher Addison-Wesley rating 9/10 reviewer JR Peck ISBN 978-0-672-32978-4 summary A definitive guide to the core Python language and the essential parts of the Python library. The end result of that choice is a reference document consisting of those parts of Python that are shared between versions 2 and 3. This is a significant portion of the language and I think this approach is really what will give this reference more traction than many of the other guides that focus purely on 3. I think that those are valuable and over time the balance will shift but as of right now, for a little while to come, this book takes the most realistic approach. That feels very fuzzy, but I have no idea how long it will be until Python 3 truly is the dominant version and Python 2 is truly put to bed.

If I had to guess how Beazley's Python Essential Reference has held in there over the years, the key would be that there is a lot of what a developer needs and very little of what she doesn't need. There is a twenty-four page tutorial introduction, but this is not a guide on how to program or how to use Python for beginners. An experienced programmer could probably use this reference to shift to Python as a new language, but someone completely new to writing code would probably not want to start here. A quick look at the table of contents shows that an explanation of the language itself is covered in under 200 pages. Extending and embedding Python also get their own section, but close to 400 pages is given to the Python library.

An inevitable question is what one will gain with this reference over the online documentation. A good example to see how things vary is to look at chapter nineteen, Operating System Services and the online documentation for Generic Operating System Services. The online documentation is very thorough, and covers each piece of the library starting with os and io, building from there. While every facet is documented much of it is rather brief. For example section 16.2.3. Raw File I/O is a very straightforward listing of the very low level functionality available via io.FileIO. In contrast, looking at the 3.1.1 Docs for Raw IO shows that parameters for FileIO changed with that version. Looking to the documentation for 2.7a1 Raw File I/O shows that these changes are being back-ported to Python 2.

In Python Essential Reference none of this hunting down changes and checking to see if they are coming to 2 are necessary. Beazley shows them in his documentation. This is the strength of his choice on how to handle these types of situations. On top of that, Beazley provides more than the online documents by including four paragraphs of additional information on Raw I/O and when its use is appropriate. This added content is probably available googling around for it, but then I have to take the time to check dates on posts to see if things are still current and in general just hope that things are accurate. I have never read a technical book that was completely error free, and there are probably at the very least some typos in Python Essential Reference, though I haven't caught any of them on my read through or use of the book yet. But the important thing is that I don't expect the book to be perfect, rather I value it for being a known quantity. I am aware of just when the material was compiled, who put it together and I have it all in one place.errno symbols is not exhaustive and oddly enough is not ordered alphabetically. Beazley provides two lists for errno symbols. They are provided in alphabetical order, have a description and are grouped as POSIX error codes and Windows error codes. A quick glance at these tables in a skimming of the book might lead one to believe that this is just a simple quick grab from already available sources, but that isn't the case. There is real value added even here.

The index is solid. It would seem that one should be able to take this for granted with a technical reference but I've seen some sad exceptions. Between the thorough index and the detailed table of contents I've never had to spend more than a few seconds looking for what I need. This is the result of those tools as well as the fact that this is not an exhaustive reference. After initially reading through the book for this review, I've taken some time just to use it day to day, as I doubt many will be reading it from front to back. I don't use Python professionally. I'm purely a hobbyist when it comes to programming, but I've found that if I want to get the most out of the time I do have to play with personal projects, I want this book close. I'm not cranking out code that fast to begin with and so I need all the help I can get. I've found that Beazley seems to have hit that sweet spot where he gives enough information to get me where I need to be without bogging down in too many details or the things that I just don't need to know. I imagine this proper balance of information is due to Beazley's extensive experience with Python and that of Noah Gift the technical editor for the book.

I've mentioned repeatedly that I approve of how the shift between Python 2 and 3 has been handled. Beazley hasn't completely integrated everything and left some of the unique new features of 3 out in the cold. There is an appendix that deals specifically with Python 3. It is short but does have some value. New features, common pitfalls for those making the move from 2 to 3 and how to run both at the same time in a single environment are covered. This is helpful and keeps my desk a little neater, though I think if I were going to be spending extensive time working with Python 3 then I would probably want to have another reference on hand.

If you are a week-end hacker like me, or someone that is writing Python on the clock, I think that this compact reference is very useful. I don't have any trouble running across huge technical books that do come in handy for any project that requires something heavy. I also see a lot of little books that seem to be quickly produced summaries of what is already out there, spending most of their short content on fluff. Every so often though, someone hits that sweet spot of concise usefulness. Beazley did this with Python Essential Reference and this new edition continues that history in strong fashion.

You can purchase Python Essential Reference 4th Ed. from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

lkcl writes "Two independent projects, Skulpt and Pyjamas, are working to bring Python to the web browser (and the JavaScript command-line) the hard way: as JavaScript. Skulpt already has a cool Python prompt demo on its homepage; Pyjamas has a gwtcanvas demo port and a GChart 2.6 demo port. Using the 64-bit version of Google v8 and PyV8, Pyjamas has just recently and successfully run its Python regression tests, converted to JavaScript, at the command-line. (Note: don't try any of the above SVG demos with FF2 or IE6; they will suck.)"

stoolpigeon writes "Hitting middle age has been an interesting time. I catch myself thinking about how well kids have it today and sounding a lot like my father. One difference is while my dad was happy to teach me about sports or cars, we never spent any time knocking out code together. I think he did realize that home computers were important and I will always be grateful for the Commodore Vic-20 he brought home one day. It was a substantial purchase for our household. I spent many days copying lines of basic from magazines and saving the results to cassette tapes. In my home today we have a considerably better situation, computing wise. There are usually a couple laptops running as well as the desktop machine upstairs. My kids take for granted what I found to be amazing and new. Still, that's all pretty normal and I'd like to give them an opportunity to go deeper if they are so inclined, just like we give them opportunities to explore other skills and pursuits. With that in mind I brought a copy of Hello World! home a few weeks ago, and the response from my oldest has been surprisingly enthusiastic." Keep reading for the rest of JR's review. Hello World! Computer Programming for Kids and Other Beginners author Warren and Carter Sande pages 430 publisher Manning rating 9/10 reviewer JR Peck ISBN 978-1933988498 summary Computer programming for kids and other beginners. Warren Sande wanted to teach his son Carter about programming but had difficulty finding what he thought was a suitable book to guide the process. At the encouragement of Warren's wife, he and Carter decided to write their own while Carter learned to code. Warren chose Python as the language they would work in and then the two together outlined the book and created the sample applications. As the book moves into more complex territory the sample applications are the kind kids like best. They are games. As soon as my daughter saw that she would get to make her own computer games she immediately asked me if we could start working through the book together. When it has been a while since we've had a chance to crack it open, she reminds me by asking when we will get back to it. I would say that on her end it has been a complete success. It has been a great time for us as father and daughter and educational for us both.

Language choice can be quite a hot topic amongst us geeks. In the preface Warren defends his choice of Python with a bullet list I'll summarize here.

• Python was created from the start to be easy to learn.
• Python is free.
• Python is open source software.
• Python is not just a 'toy' language.
• Python is multi-platform.
• Warren likes Python and thinks others will like it too.

I think the list is pretty solid. The only one I think may not be directly applicable to the case it hand is the FOSS angle. Warren explains that being open means that more can be done with the software and that there is a large set of corresponding code out there freely available. A case could be made that this is also true of more closed languages. The one thing I think that could make this important is if the teacher of the material is interested in not just teaching the technical side of programming but is also interested in communicating the philosophical values of freedom. In light of the amount of closed source software and ignorance in regards to FOSS options I've seen in the public school system where I live, I think this may be more important than some think.

The rest of the reasons though I think make Python an incredibly solid choice, and above all else is the simplicity. My daughter has been able to have fun typing code into IDLE without having to get hung up with a complicated environment. The syntax is clean and simple, there is no compiling, it's very easy to just jump in and start making things happen. I think this is important, the younger the student. I was concerned that nine might be just a touch too young for this undertaking. The book itself does not make any recommendations concerning age. The more I've thought about it, the more I agree with that choice. Children vary so greatly and any number chosen would be rather arbitrary. My nine your old has done well so far, but she is already quite a book worm and leans towards more academic pursuits. An older child may struggle and there may be some that are even younger that would be fine with the material in Hello World! So rather than focus on age I think a parent needs to come at this from a perspective of ability, proclivity and experience.

In the ability area, a child is going to know how to read, work with a mouse, and type things via the keyboard. Of course the mouse is optional strictly speaking but most will probably want to use it. Some math skill would be good as well as the ability to understand the use of variables. The book tackles the necessary material in a kid friendly way but it is not dumbed down. In fact the learning potential here is huge, as one may imagine. The book is formatted with lots of visuals and fly-outs that give information on how computers operate and how programming languages deal with information processing. My daughter and I have already had interesting discussions on subjects like integers and floats. An example that draws a sine wave lead to a great teachable moment about amplitude and wave length. Then there is the constant need for approaching problem solving in a structured manner using logic. I think that taking on programming brings a wide number of benefits.

One of the features, is a little caricature of Carter that is placed throughout the book with observations that the real Carter made as he learned with his dad. These are things that a real kid noticed, and so they are likely to stand out to a child working through this book. For instance in the chapter on "Print Formatting and Strings" Carter says, "I thought the % sign was used for the modulus operator!" The book explains that Python uses context to choose how the % sign is used. There are other little cartoon characters that appear throughout the book drawing attention to important points that need to be remembered. Learning is reinforced through quizzes at the end of the chapters. The chapters are not too long but I've found that my daughter and I have to break them into sections because of her typing speed. I've been tempted at times to move things along by typing for her but I know that she will not get the same benefit from the exercise if we do it that way. I will also let errors slide by at times to allow her the opportunity to look at error messages and find the problems.

As I mentioned the book is billed as being for kids and "other beginners." I'm going to say that the primary focus is rightly on kids, and probably kids who are in grade school or maybe junior high. This is not to say that the examples and information wouldn't be great for anyone brand new to programming. There are even some nuggets for someone who has written some code but is new to Python. I am going to guess though that the average high school student will not be as taken with the cartoons and puns. I'd have loved to have written my own lunar lander game at that age though, so maybe I'm selling this short, or maybe it would be something a teen would be happy to work on away from the eyes of others, so as not to appear childish. (I may take heat for this but even as a teenage geek I was immensely worried about the perceptions of my peer group.) I think an adult that was serious about learning to program, even if they had no prior experience, would do better with heavier material. All that said, I think for children they've really hit the sweet spot and as much as marketers would like it to be so, no book can be everything to everyone.

Things start simple with print statements and loops that took me back to good old days of watching messages scroll endlessly by on display computers at Sears when I was a kid. The move towards games starts even then with text and quickly moves on to leveraging Pygame for games that utilize graphics. I think this is important as it keeps things entertaining while teaching important concepts at the same time. I have to say it is quite a bit fun to sit with my child discussing nested loops and decision trees. By the end of the book examples will have included a simple virtual pet, a downhill skiing game and a lunar lander simulation.

I've discussed a child's ability a bit but I think the last two things I mentioned must be taken into account as well. They are proclivity and experience. I've let my daughter drive the time we spend working on this. Just like the parents who project their sports dreams on their kids, I think there is a possibility to do the same with my love for all things digital. It may even be easier to do so as I view the ability to do some amount of programming to be an important life skill. The thing is I don't want to push her too hard and have her back away from it completely. This fits in with the experience part. We take it as it goes, and if things stop being fun, we will back off. I don't do this with her core disciplines from school like reading and math, but for something that is extra right now I'm not going to push. It would transition from being a joy to being work. That brings up a last and unexpected benefit from Hello World! I'm rediscovering a lot of the fun and excitement that drew me into this industry in the first place.

You can purchase Hello World! from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

aceydacey writes "Sometimes a picture is worth a thousand words. Beginning Python Visualization: Creating Visual Transformation Scripts, published in February 2009 by Apress, shows how Python and its related tools can be used to easily and effectively turn raw data into visual representations that communicate effectively. The author is Shai Vaingast, a professional engineer and engineering manager who needed to train scientists and engineers to do this kind of programming work. He was looking for a tutorial and reference work, and unable to find a suitable text, wound up writing his first book. He writes in the easy and clear style of someone comfortable and engaged with the subject matter." Keep reading for the rest of aceydacey's review. Beginning Python Visualization: Crafting Visual Transformation Scripts author Shai Vaingast pages 363 publisher Apress rating 9/10 reviewer aceydacey ISBN 1430218436 summary learn how to process, organize, and visualize data from various sources using the Python language The book uses several very specific examples that illustrate general principles.

The first example is using GPS data. By using Python one can extract data from GPS receivers and enter it into the computer and manipulate it to do what one wants including creating graphs and charts. In this section he shows how to use CSV, comma separated values, as a most useful file format. He shows show to extract data from real world GPS devices and import it via serial ports and the PySerial module. It would be easy for the reader to duplicate and extend this project.

The heart of the book is coverage of useful examples utilizing MatPlotLib, NumPy and SciPy. These related tools are easy to use and fully integrated with Python. MatPlotLib is for plotting data and graphs, including interactive graphs and image files. NumPy is a powerful math library comparable to commercial tools like MatLab, and SciPy extends NumPy to for the sciences. Examples are numerous and include signal analysis using Fourier transforms.

There is also a section on Image Processing using PIL, the Python Imaging Library. This is used for relatively simple image cropping and sizing and also for bit by bit image processing. Interpolation and curve fitting are also well covered. For anyone wanting an introduction to graphical analysis of statistical data, this would be an excellent resource.

The author is obviously a professional in this field. He has a knack for good organizational style and a pragmatic approach to the work. In the book he says "Most of the time, research is organized chaos. The emphasis, however, should be on organized, not chaos." A real value I got from the book is a better understanding of data files, format, and organization as well as methods and guidelines for selecting file formats and storing and organizing data to enable fast and efficient data processing. It is obvious that this book was written by a practicing engineer.

The theme of the book is that Python can be an all purpose environment for data manipulation and visualization, using nothing but free and open source tools that are easily integrated and scriptable without using multiple programming languages. The book should be an invaluable tool for scientists and engineers but it is also easily accessible to anyone interested in math and data analysis. There is no need for an advanced math background. While, as a matter of full disclosure, I have undergraduate degrees in Math and Physics, I feel the book should be easily accessible to anyone with a solid high school math background who is seriously interested in the subject. The book contains a short introductory tutorial on the basics of Python so anyone familiar with programming in any language should be fine.

The book is an easy read from front to back, and I am sure it will also be a good reference resource for the future. The writing style is very clear and unforced and I found surprisingly few errors. While the Python world has a surplus of introductory and general books, books covering this kind of specific domain are especially welcome, and we could use more on other topics by competent authors.

At 363 pages the book is a surprisingly fast read. Its methodology is to use specific, short code examples to make all the key points. Most of the code samples are well selected, short and written in clear, concise Python. This is not the kind of book that overwhelms you with massive amounts of code. Either the book was well edited or else it was written by an exceptionally lucid thinker, or both.

So, if you want to learn how to process, organize, and visualize data from various sources using the Python language, I recommend this book to you. I have also posted a podcast of an interview with the author at Python411

You can purchase Beginning Python Visualization: Crafting Visual Transformation Scripts from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.

mithro writes "As everyone should already know, Google is running the Summer of Code again this year. For those who don't know, GSoC is where Google funds student's to participate in Open Source projects and has been running for 5 years, bringing together over 2600 students and 2500 mentors from nearly 100 countries worldwide. Google has just announced the projects which will be mentor organizations this year. It includes a great list of Open Source projects from a wide range of different genres, include content management systems, compilers, many programming languages and even a bunch of games!"

licorna writes "The 3.0 version of Python (also known as Python3k and Python3000) just got released few hours ago. It's the first ever intentionally backwards-incompatible Python release."

Robert writes "Along with many other techies, I share an interest in the world of finance (bubble-era stock options pulled me in). Unfortunately, as someone with a strong preference for GNU/Linux as my operating system of choice, I have found that software in this area seems quite sparse. For awhile I have made do with Python, R, Gnumeric, Gnucash and a telephone, along with some small utilities I have written myself. What I would like to know is: what FOSS software do you use for financial analysis, trading, system development, and testing in a Un*x environment? Are there programs you would like to see written or ported? Do any brokerages, data providers, or other services provide good support for we the few? And finally, what commercial entities do you know of that are using FOSS software in their operation?"

Coryoth writes "Design by Contract, writing pre- and post-conditions on functions, seemed like straightforward common sense to me. Such conditions, in the form of executable code, not only provide more exacting API documentation, but also provide a test harness. Having easy to write unit tests, that are automatically integrated into the inheritance hierarchy in OO languages, 'just made sense'. However, despite being available (to varying degrees of completeness) for many languages other than Eiffel, including Java, C++, Perl, Python, Ruby, Ada, and even Haskell and Ocaml, the concept has never gained significant traction, particularly in comparison to unit testing frameworks (which DbC complements nicely), and hype like 'Extreme Programming'. So why did Design by Contract fail to take off?"

dominator writes "It's been nearly 20 months since the last major release of the Python programming language, and version 2.5 is probably the most significant new release of Python since 2.2. The latest release includes a variety of additions to the standard library, language extensions, and performance optimizations. This is a final release, and should be suitable for production use. Read the release announcement, the highlights, what's new, and download it."

dominator writes "It's been nearly 20 months since the last major release of the Python programming language, and version 2.5 is probably the most significant new release of Python since 2.2. The latest release includes a variety of additions to the standard library, language extensions, and performance optimizations. This is a final release, and should be suitable for production use. Read the release announcement, the highlights, what's new, and download it."

dominator writes "It's been nearly 20 months since the last major release of the Python programming language, and version 2.5 is probably the most significant new release of Python since 2.2. The latest release includes a variety of additions to the standard library, language extensions, and performance optimizations. This is a final release, and should be suitable for production use. Read the release announcement, the highlights, what's new, and download it."

dominator writes "It's been nearly 20 months since the last major release of the Python programming language, and version 2.5 is probably the most significant new release of Python since 2.2. The latest release includes a variety of additions to the standard library, language extensions, and performance optimizations. This is a final release, and should be suitable for production use. Read the release announcement, the highlights, what's new, and download it."