cold fjord writes with this report from The Telegraph: "The original members of Monty Python will reunite more than 30 years after the comedy troupe last worked together. John Cleese, Terry Gilliam, Terry Jones, Eric Idle and Michael Palin will officially announce their reformation at a London press conference on Thursday. The five surviving members have reportedly been in months of secret talks about getting the Flying Circus back on the road. The reunion comes after several failed attempts to reform by the group. However, according to The Sun, the surviving members realised 'it was now or never,' and had decided to embark upon 'a fully-fledged reunion.'" Related stories include this commentary, one take on the best of Python and this negative reaction, too.

An anonymous reader points out The Register's report that Wi-Fi security expert Cédric 'Sid' Blancher has died as the result of a skydiving accident. "Among other things, the 37-year-old Blancher was a sought-after speaker on WiFi security, and in 2005 published a Python-based WiFi traffic injection tool called Wifitap. In 2006, while working for the EADS Corporate Research centre, he also put together a paper on how to exploit Skype to act as a botnet." Some of Blancher's skydiving videos are posted to Vimeo; clearly, it's something he was passionate about.

jfruh writes "Most day-to-day programmers have only a general idea of how compilers transform human-readable code into the machine language that actually powers computers. In an attempt to streamline applications, many compilers actually remove code that it perceives to be undefined or unstable — and, as a research group at MIT has found, in doing so can make applications less secure. The good news is the researchers have developed a model and a static checker for identifying unstable code. Their checker is called STACK, and it currently works for checking C/C++ code. The idea is that it will warn programmers about unstable code in their applications, so they can fix it, rather than have the compiler simply leave it out. They also hope it will encourage compiler writers to rethink how they can optimize code in more secure ways. STACK was run against a number of systems written in C/C++ and it found 160 new bugs in the systems tested, including the Linux kernel (32 bugs found), Mozilla (3), Postgres (9) and Python (5). They also found that, of the 8,575 packages in the Debian Wheezy archive that contained C/C++ code, STACK detected at least one instance of unstable code in 3,471 of them, which, as the researchers write (PDF), 'suggests that unstable code is a widespread problem.'"

An anonymous reader writes "Investment firm Knight Capital made headlines in 2012 for losing over $400 million on the New York Stock Exchange because of problems with their algorithmic trading software. Now, the owner of a Python programming blog noticed the release of a detailed SEC report into exactly what went wrong (PDF). It shows how a botched update rollout combined with useless or nonexistent process guidelines cost the company over $172,000 a second for over 45 minutes. From the report: 'When Knight used the Power Peg code previously, as child orders were executed, a cumulative quantity function counted the number of shares of the parent order that had been executed. This feature instructed the code to stop routing child orders after the parent order had been filled completely. In 2003, Knight ceased using the Power Peg functionality. In 2005, Knight moved the tracking of cumulative shares function in the Power Peg code to an earlier point in the SMARS code sequence. Knight did not retest the Power Peg code after moving the cumulative quantity function to determine whether Power Peg would still function correctly if called. ... During the deployment of the new code, however, one of Knight's technicians did not copy the new code to one of the eight SMARS computer servers. Knight did not have a second technician review this deployment and no one at Knight realized that the Power Peg code had not been removed from the eighth server, nor the new RLP code added. Knight had no written procedures that required such a review.'"

angry tapir writes "Mining small details from Facebook has become even easier with Graph Search, the site's new search engine that returns personalized results from natural-language queries. Graph Search granularly mines Facebook's vast user data: where people have visited, what they like and if they share those same preferences with their friends. 'FBStalker' is a Python script debuted at the Hack in the Box security conference in Kuala Lumpur. In its current form, FBStalker runs in the Chrome browser on OS X, entering queries into Facebook's Graph Search and pulling data. Even if a person's profile is locked down to strangers, their friends' open profiles can be examined, giving an indication, for example, who the person may be close with. FBStalker uses Graph Search to find photos in which two people are tagged in, comments on profiles and more."

ananyo writes "An offshoot of Mozilla is aiming to discover whether a review process could improve the quality of researcher-built software that is used in myriad fields today, ranging from ecology and biology to social science. In an experiment being run by the Mozilla Science Lab, software engineers have reviewed selected pieces of code from published papers in computational biology. The reviewers looked at snippets of code up to 200 lines long that were included in the papers and written in widely used programming languages, such as R, Python and Perl. The Mozilla engineers have discussed their findings with the papers’ authors, who can now choose what, if anything, to do with the markups — including whether to permit disclosure of the results. But some researchers say that having software reviewers looking over their shoulder might backfire. 'One worry I have is that, with reviews like this, scientists will be even more discouraged from publishing their code,' says biostatistician Roger Peng at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. 'We need to get more code out there, not improve how it looks.'"

theodp writes "Nate West has a nice essay on the importance of whimsy in learning to program. "It wasn't until I was writing Ruby that I found learning to program to be fun," recalls West. "What's funny is it really doesn't take much effort to be more enjoyable than the C++ examples from earlier...just getting to write gets.chomp and puts over cout > made all the difference. Ruby examples kept me engaged just long enough that I could find Why's Poignant Guide to Ruby." So, does the future of introductory computer programming books and MOOCs lie in professional, business-like presentations, or does a less-polished production with some genuine goofy enthusiasm help the programming medicine go down?"

angry tapir writes "Much of the urban vistas of Man of Steel, Cars 2 and the horrible remake of Total Recall were not modelled by hand. Instead they relied on a product called CityEngine, which is more typically associated with local government bodies' urban planning and urban design. The software procedurally generates cities using scripts written in a Python-like language. The next version of CityEngine, coming out next month, will incorporate an SDK so third-party developers can use parameter-defined procedural generation of urban environments in their own applications. CityEngine's product manager talks about the upcoming version, how it's being used at the moment, and plans to incorporate augmented reality in it."

cold fjord sends news that a study by Coverity has found open-source Python code to contain a lower defect density than any other language. "The 2012 Scan Report found an average defect density of .69 for open source software projects that leverage the Coverity Scan service, as compared to the accepted industry standard defect density for good quality software of 1.0. Python's defect density of .005 significantly surpasses this standard, and introduces a new level of quality for open source software. To date, the Coverity Scan service has analyzed nearly 400,000 lines of Python code and identified 996 new defects — 860 of which have been fixed by the Python community."

rjmarvin writes "Two developers were able to successfully reverse-engineer Dropbox to intercept SSL traffic, bypass two-factor authentication and create open-source clients. They presented their paper, 'Looking inside the (Drop) box' (PDF) at USENIX 2013, explaining step-by-step how they were able to succeed where others failed in reverse-engineering a heavily obfuscated application written in Python. They also claimed the generic techniques they used could be applied to reverse-engineer other Frozen python applications: OpenStack, NASA, and a host of Google apps, just to name a few..."

Last week you had a chance to ask Guido van Rossum, Python's BDFL (Benevolent Dictator For Life), about all things Python and his move to Dropbox. Guido wasted no time answering your questions and you'll find his responses below.

Guido van Rossum is best known as the creator of Python, and he remains the BDFL (Benevolent Dictator For Life) in the community. The recipient of many awards for his work, and author of numerous books, he left Google in December and started working for Dropbox early this year. A lot has happened in the 12 years since we talked to Guido and he's agreed to answer your questions. As usual, ask as many as you'd like, but please, one question per post.

mikejuk writes "Is it possible that we have been wasting our time typing programs. Could voice recognition, with a little help from an invented spoken language, be the solution we didn't know we needed? About two years ago Tavis Rudd, developed a bad case of RSI caused by typing lots of code using Emacs. It was so severe that he couldn't code. As he puts it: 'Desperate, I tried voice recognition'. The Dragon Naturally Speaking system used by Rudd supported standard language quite well, but it wasn't adapted to program editing commands. The solution was to use a Python speech extension, DragonFly, to program custom commands. OK, so far so good, but ... the commands weren't quite what you might have expected. Instead of English words for commands he used short vocalizations — you have to hear it to believe it. Now programming sounds like a conversation with R2D2. The advantage is that it is faster and the recognition is easier — it also sounds very cool and very techie. it is claimed that the system is faster than typing. So much so that it is still in use after the RSI cleared up."

jrepin writes "The KDE community has released version 4.11 of Software Compilation, which is dedicated to the memory of Atul 'toolz' Chitnis, a great Free and Open Source Software champion from India. This version of Plasma Workspaces will be supported for at least two years, and delivers further improvements to basic functionality with a smoother taskbar, smarter battery widget and improved sound mixer. The introduction of KScreen brings intelligent multi-monitor handling. KWin window manager incorporates first experimental support for Wayland. This release marks massive improvements in the Kontact PIM suite, giving much better performance and many new features, like scam detection and scheduling e-mail sending. Kate text editor improves the productivity of Python and Javascript developers with new plugins, Dolphin file manager became faster, and the educational applications bring various new features. The Nepomuk semantic storage and search engine received substantial performance improvements." The performance enhancements to nepomuk (KDE's semantic desktop engine) are particularly welcome. This release of the Plasma desktop also marks the end of Plasma version one; primary development focus will now switch to updating KDE for Qt 5. There should still be more updates to KDE 4, however. Also released recently by the KDE team was the first RC of Plasma Media Center 1.1.

Ingy döt Net (yes, that's his name) likes to bridge gaps in the software world. People get religious about their favorite programming languages, he says, but in the end, no matter the language, the methodology or the underlying OS, all programming is about telling computers what to do -- from "add these numbers" to complex text manipulation. Ingy compares a new app or module in the world of Free and Open Source as a gift that the creator has given to others; if that gift can be simultaneously bestowed on users of Perl, Python, and Ruby at the same time, its worth is amplified. So he proposes (and provides a growing set of tools) to make programming language irrelevant, by the sly means of encouraging people to write software using whatever their favorite tools are, but with a leaning toward using only language features which are broadly available to *other* programming languages as well. He's adopted the term Acmeism to describe this approach; Acmeists who follow his lead strive to create software that is broadly re-useable and adaptable, rather than tied only to a single platform.

Travis Goodspeed has authored a blog post detailing his method of tracking low-earth-orbit satellites. Starting with an old Felcom 82B dish made for use on maritime vessels, he added motors to move it around and a webcam-based homemade calibration system. "For handling the radio input and controlling the motors, I have a BeagleBone wired into a USB hub. These are all mounted on the trunk of the assembly inside of the radome, sending data back to a server indoors. ... In order to operate the dish, I wanted both a flashy GUI and concise scripting, but scripting was the higher priority. Toward that end, I constructed the software as a series of daemons that communicate through a PostgreSQL database on a server inside the house. For example, I can run SELECT * FROM sats WHERE el>0 to select the names and positions of all currently tracked satellites that are above the horizon. To begin tracking the International Space Station if it is in view, I run UPDATE target SET name='ISS';. For predicting satellite locations, I wrote a quick daemon using PyEphem that fetches satellite catalog data from CelesTrak. These positions are held in a database, with duplicates filtered out and positions constantly updated. PyEphem is sophisticated enough to predict in any number of formats, so it's easy to track many of the brighter stars as well as planets and deep-space probes, such as Voyagers 1 and 2."

New submitter LFSim writes "It's not the Turing test just yet, but in one more domain, AI is becoming increasingly competitive with humans. This time around, it's in interplanetary trajectory optimization. From the European Space Agency comes the news that researchers from its Advanced Concepts Team have recently won the Gold 'Humies' award for their use of Evolutionary Algorithms to design a spacecraft's trajectory for exploring the Galilean moons of Jupiter (Io, Europa, Ganymede and Callisto). The problem addressed in the awarded article (PDF) was put forward by NASA/JPL in the latest edition of the Global Trajectory Optimization Competition. The team from ESA was able to automatically evolve a solution that outperforms all the entries submitted to the competition by human experts from across the world. Interestingly, as noted in the presentation to the award's jury (PDF), the team conducted their work on top of open-source tools (PaGMO / PyGMO and PyKEP)."

super_rancid writes "In a 7,000 word interview with Raspberry Pi's founder posted on TuxRadar.com, Eben Upton talks about the challenges of managing such a successful project, what may be in the Raspberry Pi mark 2, and why he wishes he'd backed the Parallela Kickstarter." On interesting answer: "We were thinking of booting into Python or booting into Scratch. For younger kids, boot into Scratch. Have an environment where it’s Linux underneath, boots into Scratch and hold down a key at a particular point during boot and it doesn’t boot into Scratch it just drops into the prompt. So you can play with Scratch for six months, once you’re happy with Scratch you turn over the page and 'Hold down F1 during boot,' and it’s like 'Oh look - it’s a PC!' So I think that’s something we’d really like to do."

An anonymous reader writes "Drew Crawford has a good write up of the current state of JavaScript in mobile development, and why the lack of explicit memory handling (and a design philosophy that ignores memory issues) leads to massive garbage collection overhead, which prevents HTML5/JS from being deployed for anything besides light duty mobile web development. Quoting: 'Here’s the point: memory management is hard on mobile. iOS has formed a culture around doing most things manually and trying to make the compiler do some of the easy parts. Android has formed a culture around improving a garbage collector that they try very hard not to use in practice. But either way, everybody spends a lot of time thinking about memory management when they write mobile applications. There’s just no substitute for thinking about memory. Like, a lot. When JavaScript people or Ruby people or Python people hear "garbage collector," they understand it to mean "silver bullet garbage collector." They mean "garbage collector that frees me from thinking about managing memory." But there’s no silver bullet on mobile devices. Everybody thinks about memory on mobile, whether they have a garbage collector or not. The only way to get "silver bullet" memory management is the same way we do it on the desktop–by having 10x more memory than your program really needs.'"

An anonymous reader writes "Following up on an experiment from December, Michael Hansen has recorded video of programmers of varying skill levels as the read and evaluate short programs written in Python. An eye tracker checks 300 times per second to show what they look at as they mentally digest the script. You can see some interesting differences between experts and beginners: 'First, Eric's eye movements are precise and directed from the beginning. He quickly finds the first print statement and jumps back to comprehend the between function. The novice, on the other hand, spends time skimming the whole program first before tackling the first print. This is in line with expectations, of course, but it's cool to see it come out in the data. Another thing that stands out is the pronounced effect of learning in both videos. As Eric pointed out, it appears that he "compiled" the between function in his head, since his second encounter with it doesn't require a lengthy stop back at the definition. The novice received an inline version of the same program, where the functions were not present. Nevertheless, we can see a sharp transition in reading style around 1:30 when the pattern has been recognized.'"