An anonymous reader shares an excerpt from a report written by Andrew Cunningham via Ars Technica: Apple is working on new desktop Macs, including a ground-up redesign of the tiny-but-controversial 2013 Mac Pro. We're also due for some new iMacs, which Apple says will include some features that will make less-demanding pro users happy. But we don't know when they're coming, and the Mac Pro in particular is going to take at least a year to get here. Apple's reassurances are nice, but it's a small comfort to anyone who wants high-end processing power in a Mac right now. Apple hasn't put out a new desktop since it refreshed the iMacs in October of 2015, and the older, slower components in these computers keeps Apple out of new high-end fields like VR. This is a problem for people who prefer or need macOS, since Apple's operating system is only really designed to work on Apple's hardware. But for the truly adventurous and desperate, there's another place to turn: fake Macs built with standard PC components, popularly known as "Hackintoshes." They've been around for a long time, but the state of Apple's desktop lineup is making them feel newly relevant these days. So we spoke with people who currently rely on Hackintoshes to see how the computers are being used -- and what they'd like to see from Apple.

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The Chinese government is recruiting 20,000 people to create an online encyclopedia that will be the country's own, China-centric version of Wikipedia, or as one official put it, like "a Great Wall of culture." From a report: Known as the "Chinese Encyclopedia," the country's national encyclopedia will go online for the first time in 2018, and the government has employed tens of thousands of scholars from universities and research institutes who will contribute articles in more than 100 disciplines. The end result will be a knowledge base with more than 300,000 entries, each of which will be about 1,000 words long. "The Chinese Encyclopaedia is not a book, but a Great Wall of culture," Yang Muzhi, the editor-in-chief of the project and the chairman of the Book and Periodicals Distribution Association of China, said. He added that China was under pressure from the international community to produce an encyclopedia that will "guide and lead the public and society."

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I spent the weekend making a bunch of progress on the compiler. It has two pieces: a tokenizer, which I created by rewriting the original C code (langscan.c) in Swift, and a parser.

The parser in OrigFrontier was generated by MacYacc, which is similar to Yacc, which is similar to Bison, which is on my Mac. The thing about the parser is that it’s C code, and the rest of the app is Swift.

How do you bridge the two worlds? Easy answer: with Objective-C, which is a superset of C and which plays nicely (enough) with Swift.

So I renamed langparser.y — the rules file that the parser generator uses — to langparser.ym so that Xcode would know to treat the generated parser source as Objective-C. I edited it slightly, not to change the grammar rules but to change how nodes are created (as return values rather than via inout).

I also made my CodeTreeNode class, written in Swift, an Objective-C class so that it would be visible to my Objective-C code.

And then, finally, I started a build…

…and then it stopped with an error because the parser places my CodeTreeNode in a C union, which isn’t allowed in ARC.

Crushed.

* * *

I think I have three options:

1. Go down the rabbit hole of figuring out how to get the parser to work with ARC.
2. Go with the flow: have the parser generate nodes that are, as in OrigFrontier, C structs. The last compilation step would be Objective-C code that translates that tree of C structs into a tree of CodeTreeNode objects, and then disposes the C-struct-node-tree.
3. Write the parser by hand, in Swift.

My thinking:

I could waste a ton of time on #1, and bending tools in that way can be pretty frustrating work when they refuse to bend.

With #2 I’d feel a bit weird about the redundancy: building a tree and then building a copy of that tree with a different type of object.

My heart tells me #3 is the answer. After all, I’ve already done the tokenizer. How hard would it be to parse those tokens into a code tree? I could skip C and Objective-C altogether and stay in Swift. And it would be so fun. (Because that’s precisely the style of weirdo I am.)

* * *

But the real answer is #2. Writing a parser by hand would take way longer than I think. Given enough tests, it shouldn’t be a huge source of bugs, but still.

The thing about #2 is that yes, it’s redundant, it’s doing more work than it needs to, ideally — but my bet is that it would still be so fast that you wouldn’t be able to tell the difference. Computers are so good at this kind of thing. It’s not like reading files or networking; it’s just in-memory traversal and creating/releasing things.

You remember in Indiana Jones that guy with the twirling swords, and Indy gives that look and then just shoots him? The second option is the Indiana Jones solution.

Ankara is calling on Washington to stop supporting Kurdish forces inside Syria.

Ankara is calling on Washington to stop supporting Kurdish forces inside Syria.

Leading US-based rights group says nerve agent attacks are part of a "clear pattern" that could amount to war crimes.

Leading US-based rights group says nerve agent attacks are part of a "clear pattern" that could amount to war crimes.

An anonymous reader shares a report from marketing research firm eMarketer: Thanks to multitasking, US adults' average daily time spent with major media will slightly exceed 12 hours this year, according to eMarketer's latest report. But while our reports early in the decade told a story of robust gains -- with increases in digital usage more than compensating for declines in time spent with nondigital media -- growth has been petering out. Of course, media multitasking is what has made so much usage possible. That is how the figure for time spent can add up to 12 hours a day.

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multiple website content management framework

multiple website content management framework