Text will always be a major format for data and it will never be well-organized. According to Phil Karlton’s famous joke, the two hard problems in computing are naming things, cache invalidation, and off-by-one errors. A third problem could be “formatting things”. Most textual data has irregularities in the formatting that make it a pain to process. And much of the work in text processing goes into dealing with formatting issues. These are just the sad facts.
For the past ~3 years, we here on the Komodo Dev team have been gradually creating a new SDK for customizing and developing Komodo. As part of this process, we have also migrated legacy code into the new SDK to make it easier to access.
This is a pretty exciting time to be a developer on the Komodo team as there is so much room for growth. If we need a new feature or ready access to some legacy code, we can often create a new SDK to fill that need.
The pursuit of speed is one of the few constants in computing, and it is driven by two things: ever-increasing amounts of data, and limited hardware resources. Today in the era of Big Data and the Internet of Things we are getting pinched in both directions. Fortunately we are getting much better at distributed and parallel computing, but the need for raw speed at the algorithmic level is never going to go away. If we can make our algorithms inherently faster we will get more out of our expensive hardware, and that is always going to be a good thing.
It seems like every time you turn around these days, there’s a new programming language trying to be the new cool kid on the block. From Rust to Swift to Go, they’re all clamouring for your attention, but what’s wrong with what you already know and love?
ActiveState is super excited to announce we're open sourcing TEAcup/TEApot: one of Tcl's key community package repository systems. Until now, ActiveState has been internally maintaining and providing TEAcup and TEApot. Now, by open-sourcing these important pieces of the Tcl eco-system, everyone will benefit from peer-review, community collaboration and can tailor them to best suit the Tcl community.
Since its release in 2015 by the Google Brain team, TensorFlow has been a driving force in conversations centered on artificial intelligence, machine learning, and predictive analytics. With its flexible architecture, TensorFlow provides numerical computation capacity with incredible parallelism that is appealing to both small and large businesses.
Ever since it was introduced back in Komodo 3, CodeIntel (short for "Code Intelligence") has been one of Komodo's best features. With the rise of interpreted languages like Perl, Python, and Ruby, being able to obtain useful code completions for dynamic objects is crucial. Also, having the ability to show function arguments as you type, being able to jump to symbol definitions with the click of a mouse, and being able to view the overall structure of your code at a glance are all extremely useful tools for developers that CodeIntel has provided over the years.
If you’re a Java developer like me, chances are you’ve heard rumblings of a trendy new language that came out of Google: Go.
And if, like me, you’re always looking for ways to code faster and better, you may be asking yourself whether any of your existing applications are good candidates to move to Go. While not every Java application should be ported to Go, in many cases, Go is a more productive development framework than Java. There is, therefore, a great deal of value in understanding what Go can do; where it builds on the strengths offered by Java, and where it differs.